MXPA06010011A - Multi-phase coriolis flowmeter - Google Patents

Abstract

A flowmeter (200, 2100) is disclosed. The flowmeter includes a vibratable flowtube (215), and a driver (210) connected to the flowtube (215) that is operable to impart motion to the flowtube (215). A sensor (205) is connected to the flowtube (215) and is operable to sense the motion of the flowtube (215) and generate a sensor signal. A controller (104) is connected to receive the sensor signal. The controller (104) is operable to determine an individual flow rate of each phase within a multi-phase flow through the flowtube.

Description

ETRO FLOW TYPE CORIOLIS ULTIPHASE TECHNICAL FIELD This description refers to flow meters.

BACKGROUND OF THE INVENTION Flow meters provide information about materials that are being transferred through a conduit or flow tube. For example, mass flow meters provide an indication of the mass of material that is being transferred through the conduit. Similarly, density flowmeters or densimeters provide an indication of the density of the material flowing through the conduit. Mass flow meters can also provide an indication of the density of the material. For example, Coriolis mass flow meters are based on the Coriolis effect, in which the material that flows through a conduit is affected by the Coriolis force and, consequently, undergoes an acceleration. Many of the Coriolis mass flow meters induce a Coriolis force by sinusoidally oscillating a conduit about a pivot axis, which, the latter, is orthogonal to the length of the conduit. In this type of mass flow meters, the Coriolis reaction force experienced by the mass of the fluid in motion is transferred to the conduit by itself and manifests as a deviation or de-centering of the conduit in the vector direction of the Coriolis force in the rotation plane.

SUMMARY OF THE INVENTION According to a general aspect, a system includes a controller that can be operated to receive a sensor signal from a first sensor connected to a vibrating flow tube containing a three-phase fluid flow that includes a liquid first, a second liquid and a gas, the controller can also be operated to analyze the sensor signal to determine an apparent flow parameter of the fluid flow, a second sensor that can be operated to determine an apparent flow condition of the flow of fluid, and a module of corrections that can be operated to admit the apparent flow parameter and the apparent flow condition and determine a corrected flow parameter from them. The implementations may include one or more of the following characteristics. For example, in addition, the correction module can be operated to admit the apparent flow parameter and the apparent flow condition and determine a corrected flow condition therefrom. The apparent flow parameter may include an apparent bulk density of the fluid flow or an apparent gross mass flow rate of the fluid flow. The second sensor can include a liquid fraction meter that can be operated to determine a measurement of the liquid fraction that identifies a volumetric fraction of the first liquid with respect to the second liquid, or a hole fraction determination system that can be operated for determine a fraction of gas gaps (FHG) within the fluid flow. A system for determining the flow rate of components that can be operated to determine a flow rate of the first liquid within the fluid flow can be included. The system for determining the flow rate of the component in the controller, the corrections module, the second sensor, or a server computer in communication with the controller, the correction module or the second sensor can be implemented. A system for determining the flow rate of components that can be operated to determine a flow rate of the gas within the fluid flow can be included. The implementation of the corrections module may be associated with a processor of the controller, or with a processor of the second sensor. • A server computer can be in communication with the controller or with the second sensor, and can be operated to implement the corrections module. In the system, the second sensor can be operated to send a first value of the apparent flow condition to the controller for use in determining a first corrected flow parameter value, and the controller can be operated to send the first value of the apparent flow condition to the second sensor for the determination of a first value of the corrected flow condition, and the second sensor can be operated to send a second value of the corrected flow condition to the controller for use in determining the value of the corrected flow parameter. The corrections module can include a neural network that can be operated to support the apparent flow parameter and the apparent flow condition and send the corrected flow parameter and a corrected flow condition. The neural network can include a first correction model that is particular to the second sensor type and the flow condition, and that can be operated to send a corrected flow condition, and a second correction model that is particular to the type of the apparent flow parameter and that can be operated to send the corrected flow parameter, where the first correction model can be operated to correct the apparent flow condition based on the apparent flow condition and on the corrected flow parameter , and the second correction model can be operated to correct the apparent flow parameter based on the apparent flow parameter and the corrected flow condition. The controller can be operated to correct the apparent flow parameter based on a theoretical relationship between the apparent flow parameter and the corrected flow parameter. The controller can be operated to correct the apparent flow parameter based on an empirical relationship between the apparent flow parameter and the corrected flow parameter. The system may include a conduit connecting the second sensor and the vibrating flow tube, so that the fluid flows through the second sensor, the tubing and the vibrating flow tube. The first liquid, the second liquid and the gas may be intermixed with each other within the fluid flow during the determination of the flow condition made by the second sensor. According to another general aspect, an apparent gross density of a multiphase flow is determined through the flow tube, the multiphase flow includes a first liquid, a second liquid and a gas. The apparent gross mass flow rate of the multiphase flow is determined, and the first mass flow rate of the first liquid is determined, based on the apparent gross density and apparent gross mass flow rate. The implementations may include one or more of the following characteristics. For example, an apparent flow condition of the multiphase flow other than the gross apparent density, and the apparent gross mass flow can be determined, where the determination of the first mass flow rate of the first liquid involves the determination of the first mass flow rate based on the apparent condition of flow. In determining the first mass flow rate of the first liquid, a corrected flow condition can be determined, based on the apparent flow condition. In the determination of the corrected flow condition, a corrected gross density and a corrected gross mass flow can be determined. The determination of the apparent flow condition can include the determination of a measurement of the apparent liquid fraction of a volumetric fraction of the first liquid within the multiphase flow, and / or the determination of a fraction of apparent gas voids within the multiphase flow. The determination of the first mass flow rate of the first liquid may include the determination of a corrected gross density, based on the gross apparent density, and the determination of a corrected gross mass flow rate, based on the apparent mass flow rate. The determination of the corrected gross density and the determination of the gross mass flow rate can include the determination of a corrected flow condition, based on the apparent flow condition. According to another general aspect, a flowmeter includes a vibrating flow tube that contains a three phase flow that includes a first liquid, a second liquid and a gas, a controller connected to the tube. flow and that can be operated to impart movement to the flow tube, a sensor connected to the flow tube and which can be operated to detect the movement of the flow tube and to generate a sensor signal, and a controller connected to receive the signal of sensor and to determine a first flow of a first phase within the flow of three phases through the flow tube, based on the sensor signal. According to another general aspect, a method for improving the output signal of a flow meter includes the determination of an apparent gross density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid, a second liquid and A gas, the determination of an apparent gross mass flow rate of the multiphase flow, the determination of an apparent flow condition of the multiphase flow, and the correction of apparent bulk density or apparent mass flow rate, based on gross apparent density, apparent mass flow and apparent flow condition. According to another general aspect, a method for improving the output signal of a liquid fraction meter includes the determination of an apparent bulk density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid, a second liquid and a gas, the determination of an apparent gross mass flow rate of the multiphase flow, the determination of an apparent liquid fraction of the first liquid within the multiphase flow, and the correction of the apparent liquid fraction to obtain a corrected liquid fraction, based on in the apparent gross density, the apparent mass flow and the apparent liquid fraction. The implementations may include one or more of the following characteristics. For example, a fraction of gas gaps can be determined from the gas within the multiphase flow based on apparent gross density, apparent mass flow rate and corrected liquid fraction. According to another general aspect, a method for obtaining a measurement of the void fraction of a gas includes the determination of an apparent gross density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid , a second liquid and a gas, the determination of an apparent gross mass flow rate of the multiphase flow, the determination of an apparent gas gap fraction of the gas within the multiphase flow, and the correction of the apparent gas gap fraction to obtain a fraction of apparent gas gaps, based on gross apparent density, apparent mass flow rate and apparent gas gap fraction. The implementations may include one or more of the following characteristics. For example, a liquid fraction of the first liquid within the multiphase flow can be determined based on the apparent gross density, the apparent mass flow rate and the corrected gas gap fraction. According to another general aspect, a system includes a conduit having a fluid flow through itself, the fluid flow includes at least a first liquid component, a second liquid component and a gas component, a Vibrating flow tube in series with the conduit and having the flow of fluid through itself, a first sensor that can be operated to determine a first apparent property of fluid flow through the conduit, a second sensor connected to the tube of flow and that can be operated to detect the information of a movement of the flow tube, a controller connected to the flow tube and that can be operated to impart energy to the flow tube, a control and measurement system that can be operated to measure a second apparent property and a third apparent property of the fluid flow, and a correction system that can be operated to determine a corrected first property, a second corrected property and a corrected third property, based on the first apparent property, the second apparent property and the third apparent property. According to another general aspect, a system includes a controller that can be operated to determine a first apparent property of a fluid flow, in which a first liquid, a second liquid and a gas are intermixed, a meter that can be operated to measure a second apparent property of the fluid flow, and a correction module that can be operated to admit the first apparent property and produce a corrected first property, where the meter can be operated to admit the first corrected property and the second property corrected and produce a second corrected property. The details of one or more implementations are presented in the attached drawings and in the following description thereof. Other features will be apparent from the following description, drawings and claims.

DESCRIPTION OF THE DRAWINGS Figure 1A is an illustration of a Coriolis type flowmeter that employs a bent flow tube. Figure IB is an illustration of a Coriolis type flowmeter that uses a straight flow tube. Figure 2 is a block diagram of a Coriolis type flow meter. Figure 3 is a flow chart illustrating an operation of the Coriolis type flowmeter of Figure 2. Figure 4 is a flow chart illustrating techniques for determining liquid and gaseous flow rates for a two-phase flow. Figures 5A and 5B are graphs illustrating a percentage error in a measurement of the void fraction and the liquid fraction, respectively. Figure 6 is a graph illustrating a mass flow error as a function of the density decrease of a flow tube having a particular orientation and in a selected flow range. Figure 7 is a flow diagram illustrating techniques for correction of density measurements. Figure 8 is a table showing a relationship between an apparent decrease in density and an apparent mass flow rate of the biphasic flow. Figure 9 is a flow chart illustrating techniques for determining measurements of the void fraction. Figure 10 is a flow chart illustrating techniques for determining corrected mass flow measurements. Figure 11 is a table showing a relationship between an apparent mass flow rate and a corrected decrease in the density of the two-phase flow. Figures 12-14 are graphs illustrating examples of density corrections for various flow tubes. Figures 15-20 are graphs that illustrate examples of mass flow corrections for various flow tubes. Figure 21 is a block diagram of a flowmeter system. Figure 22 is a diagram of a first implementation of the system of Figure 21. Figure 23 is a block diagram of a second implementation of the system of Figure 21. Figure 24 is a block diagram of an implementation of the corrections (2108) of Figures 21-23. Figure 25 is a flow diagram illustrating a first operation of the flow meters of Figures 21-23.

Figure 26 is a flow diagram illustrating a first example of the techniques of Figure 25. Figure 27 is a flow diagram illustrating a second example of the techniques of Figure 25. Figure 28 is a flow chart which illustrates a third example of the techniques of Figure 25. Figure 29 is a flow chart illustrating techniques for determining component flows for a three-phase flow. Figure 30 is a flow chart illustrating more specific techniques for performing the determinations of Figure 29. Figures 31A-31D are graphs illustrating the correction of a two-phase liquid flow rate in a three-phase flow. Figure 32 is a graph showing an error in the mass flow as a function of mass flow for oil and water. Figure 33 is a graph showing an error in the fraction of gas voids as a function of the true void fraction of gas. Figure 34 is a graphic representation of a neural network model. Figure 35 is a graphical representation of units of the model of Figure 34.

Figures 36A, 36B and 37A-D illustrate the results of the two-phase flow data for which the model of Figures 34 and 35 is applied. Figures 38-68 are graphs that illustrate the test / modeling results of several implementations described above with respect to Figures 1-37, or related implementations.

DETAILED DESCRIPTION OF THE INVENTION The types of flow meters include digital flow meters. For example, U.S. Pat. 6,311,136, which is incorporated herein by reference, describes the use of a digital flow meter and related technology that includes signal processing and measurement techniques. This type of digital flowmeters can be very accurate in their measurements, with little or insignificant noise, and may be able to make viable a wide range of positive and negative gains in the electrical circuitry of the controller to drive the conduit. These digital flow meters are, therefore, advantageous in a wide range of configurations. For example, U.S. Pat. 6,505,519, assigned in a joint manner, which is incorporated as reference to this description, describes the use of a wide range of gain, and / or the use of negative gain, to avoid reducing the flow rate and to apply with more precise control of the flow tube, even during difficult conditions, such as, for example, a two-phase flow (for example, a flow containing a mixture of liquid and gas). Although digital flow meters are discussed in more detail below with respect to Figures 1 and 2, for example, it should be understood that analogous flow meters also exist. Although these analog flow meters may be prone to typical deficiencies of the analog electrical systems, for example, poor accuracy and very noisy measurements with respect to those of the digital flowmeters, they may also be comparable to the various techniques and implementations discussed in this description. Accordingly, in the following discussion, the term "flow meter" or "meter" is used to refer to any type of device and / or system in which a Coriolis flow meter system employs various control systems and related elements to measure a Mass flow, density and / or other parameter of one or more materials that move through a flow tube or other conduit. Figure IA is an illustration of a digital flow meter employing a bent flow tube (102). Specifically, the bent flow tube (102) can be used to measure one or more physical characteristics of, for example, a fluid (in motion), as mentioned above. In Figure IA, the digital transmitter (104) exchanges sensor signals and driver signals with the bent flow tube (102) to detect an oscillation of the bent flow tube (102) and, consequently, to drive the oscillation of the bent flow tube (102). By quickly and accurately determining the sensor signals and exciter signals, the digital transmitter (104), as referred to above, provides fast and accurate operation of the bent flow tube (102). Examples of the digital transmitter (104) are provided by being employed with a bent flow tube in, for example, U.S. Pat. 6,311,136, assigned in a joint manner. Figure IB is an illustration of a digital flow meter employing a straight flow tube (106). More specifically, in Figure IB, the straight-flow tube (106) interacts with the digital transmitter (104). This type of straight flow tubes functions, in general terms, in a manner similar to the bent flow tube (102), and has several advantages / disadvantages with respect to the bent flow tube (102). For example, the straight flow tube (106) may be easier (as a whole) to fill and empty than the bent flow tube (102), which is simply due to the geometry of its construction. In operation, the bent flow tube (102) can be operated at a frequency of, for example, 50-110 Hz, while the straight flow tube (106) can be operated at a frequency of, for example, 300- 1,000 Hz. The bent flow tube (102) represents flow tubes having various diameters, and can be operated in a multiplicity of orientations, such as, for example, in a horizontal or vertical orientation. Referring to Figure 2, it is a digital mass flow meter (200) including the digital transmitter (104), one or more motion sensors (205), one or more controllers (210), a flow tube (215). ) (which may also be referred to as a conduit, and which may represent the bent flow tube (102), the straight flow tube (106) or some type of flow tube), and a temperature sensor (220). The digital transmitter (104) can be implemented using one or more of, for example, a processor, a Digital Signal Processor (DSP), a field programmable gate array (FPGA, Field Programmable Gate Array), an ASIC (Application Specific Integrated Circuit), other programmable logic or gate arrangements, or programmable logic with a processor core. It should be understood that, as described in the patent 6, 311, 136, analog-to-analog converters may be included associated with the operation of the controllers (210), while analog-to-digital converters may be used to convert the sensor signals from the sensors (205) for use in the digital transmitter (104). The digital transmitter (104) generates a measurement of, for example, density and / or mass flow of a material flowing through the flow tube (215), based on at least the signals received from the motion sensors ( 205). The digital transmitter (104) also controls the controllers (210) to induce movement in the flow tube (215). The motion sensors (205) detect this movement. The density measurements of the material flowing through the flow tube are related to, for example, the frequency of flow tube movement (215) which is induced in the flow tube (215) by means of a driving force supplied by the controllers (210), and / or by the temperature of the flow tube (215). Similarly, the mass flow through the flow tube (215) is related to the phase and frequency of the movement of the flow tube (215), as well as to the temperature of the flow tube (215). The temperature in the flow tube (215), which is measured using the temperature sensor (220), affects certain properties of the flow tube, such as, for example, its stiffness and dimensions. The digital transmitter (104) can compensate for these effects of temperature. Also in Figure 2, a pressure sensor (225) is in communication with the transmitter (104), and connected to the flow tube (215) so that it can be operated in order to detect a pressure of a flowing material through the flow tube (215). It should be understood that both the pressure of the fluid entering the flow tube (215) and the pressure drop through relevant points in the flow tube can be indicators of certain flow conditions. Also, while external temperature sensors can be used to measure fluid temperature, these sensors can be used in addition to an internal flowmeter sensor designed to measure a representative temperature for flow tube calibrations. As well, some flow tubes employ multiple temperature sensors for the purpose of correcting measurements of a temperature differential effect between the process fluid and the environment (eg, a sheath temperature of a flow tube housing). As discussed in more detail below, a potential use of internal fluid pressure and temperature measurements is to calculate the actual densities of a liquid or gas in a two-phase flow, based on the predefined formulas.

The term "liquid fraction meter" (230) refers to a device for measuring a volumetric fraction of liquid, e.g., water, when a liquid in the flow tube (215) includes water and another fluid, such as, for example, petroleum. Of course, if such a measurement is preferred or if the liquid does not include water, such a meter, or similar meters, can be used to measure the volume fraction of a fluid in addition to water. In the above description, it is assumed that the liquid measured is, in general terms, water for the purposes of example, so that the liquid fraction meter (230) is generally referred to as an aqueous fraction meter (230). ), or as a water cut meter (230). A gap fraction sensor (235) measures a percentage of a material in the flow tube (215) which is in gaseous form. For example, water flowing through the flow tube (215) may contain air, perhaps in the form of bubbles. This condition, in which the material flowing through the flow tube (215) contains more than one material is referred to, in general terms, as "two-phase flow". In particular, the term "biphasic flow" can refer to a liquid or a gas; however, the term "biphasic flow" can also refer to other combinations of materials, such as two liquids (eg, oil and water).

There are several techniques, represented, in general terms, in Figure 2 by the hole fraction sensor (235), to measure the fraction of gas voids in a two-phase flow of liquid and gas. For example, there are several sensors and meters that could be inserted into the flow to determine a fraction of gas voids. As another example, a Venturi tube (ie, a tube with a restricted throat that determines fluid pressures and velocities by measuring pressure differentials generated in the throat as a fluid passes through the tube) can be employed, based on the fact that gas, in general terms, moves with a higher speed than the liquid (s) through the restriction, in order to determine a pressure gradient and thereby allow the determination of the fraction of gas voids. Measurements of gas bubble fractions can also be obtained by using equipment that is totally external to the flow tube. For example, sonar measurements can be taken to determine the fraction of gas holes. As a specific example of this type of sonar-based systems, the SONARtrac ™ gas gap fraction monitoring system produced by CiDRA Corporation of Wallingford, Connecticut can be employed. In this description, a quantity of gas in a flowing fluid, measured with the hole fraction sensor or determined in some other way, is referred to as a void fraction or a is defined as a = volume of gas / 'total volume = volume of gas / (volume of liquid + volume of gas). Accordingly, an amount, referred to herein as the liquid fraction, is defined as 1-a. In many applications where mass flow measurements are required, the void fraction of the flow can be as high as 20, 30, 40% or greater. However, even in very small bubble fractions of 0.5%, the fundamental theory behind the Coriolis type flowmeter becomes less applicable. Furthermore, a presence of gas in the fluid flow can also affect both the actual value and a measured value of a fluid flow density, which usually causes the density measurement to be, and be read, lower than if the fluid flow contained only the liquid component. That is, it must be understood that the puquido density of a liquid that flows by itself through a flow tube will be greater than the real density of a two-phase flow containing the liquid and a gas, since the density of the Gas (for example, air) will, in general, be lower than the density of the liquid (eg, water) in the two-phase flow. In other words, when gas is added to a liquid flow, which previously contained only the liquid, a reduction in density occurs. Beyond this physical phenomenon, a meter type Coriolis measuring a two-phase flow containing gas can produce a density reading that is a clear measurement of the gross density of the biphasic flow. (for example, water and air combined). This pure potato measurement will be, in general terms, different (lower) of the true gross density of the biphasic flow. For example, for a situation in which only the liquid component is present, the resonant frequency used by the flow meter can be corrected, but, due to the relative movement of the gas in the fluid flow, which serves to mask an inertia of the tube. flow (that is, it causes an amount of inertia that is less than would be expected for a flow only in the liquid state), the density measurement may be low. It should be understood that many conventional flow meters of the prior art were indifferent to this problem, since most Coriolis meters have faults to operate continuously (for example, stagnate measurements or produce inaccurate measurements) even in the most high fraction of holes. In the U.S. patent No. 6,505,519, which is incorporated as a reference to this description, described that this type of potato variation can be characterized (ie, a reading of the indicated gross density of a biphasic flow produced by a Coriolis type flowmeter) to pVeradera (ie, a true gross density of biphasic flow) by a variety of techniques. As a result, you can correct a measured mass to obtain a ratio of the actual gross density, which is at least approximately equal to the true. In a somewhat similar way, a gross mass flowrate indicated CMaparent (ie, a mass flow rate). of all the biphasic flow) measured with a Coriolis type flowmeter can be different from a predictable or characterizable quantity coming from a real mass flow True CM- It must be understood that the corrections techniques for the corrected gross mass flow CMV can be different than the techniques to correct the density. For example, in U.S. Pat. No. 6,505,519 Several techniques were discussed to correct a measured CMaparente in order to obtain a real CM (or, at least, a CM corrected). • Detailed examples of detailed techniques to correct both Paparente and CMaparente are discussed in more detail below. , speaking in general terms with respect to Figure 2, the digital transmitter is shown including a density correction system (240), which has access to a database for density correction (245) and a correction system of the Mass flow (250), which has access to a database for mass flow correction (255). As discussed in more detail below, the database (245) and (255) may contain, for example, correction algorithms that have been elaborated in a theoretical manner or obtained empirically, and / or tables of corrections that provide values of corrected density or mass flow for a certain group of input parameters. The databases (245) and (255) also store a variety of other types of information that may be useful when performing density or mass flow corrections. For example, the database for density correction can store different densities that correspond to particular liquids (for example, water or oil). In addition, in Figure 2, the void fraction determination / correction system (260) can be operated to determine a void fraction of a two-phase flow containing a liquid and a gas. In one implementation, for example, the determination / correction system of the hole fraction (260) can determine a real hole fraction from the corrected density Corrected- In another implementation, the determination / correction system of the fraction of holes (260) can produce a measurement of the apparent or indicated gap fraction obtained with the hole fraction sensor (235), and can correct this measurement based on an error characterization similar to the density and mass flow techniques mentioned above. In another implementation, the gap fraction sensor (235) can be operated to directly measure a fraction of real holes aeraA in which case the hole fraction determination / correction system (260) simply produces this measurement. Once the factors of P corrected, CM corrected and "corrected, - and perhaps in conjunction with other known or discovered quantities, a flow component mass flow determination system (265) operates to simultaneously determine a mass flow rate for the liquid phase component and a mass flow rate for the gas phase component. That is, the transmitter (104) can be operated to determine the individual mass flow rates CM? Iquid and CMgas of the flow components, as opposed to only determining the gross flow of CM biphase total or combined flow. Although, as mentioned just before, these measurements can be determined and / or simultaneously produced, they can also be determined separately or independently from each other. Once the flow rates of CM? IqUio and CMgas components have been determined in the manner described, in general terms, lines above, these initial determinations can be improved with a process that is based on the surface velocities of the flow components, velocities , speed of sliding between the components and / or in an identified flow regime of the flow. In this way, improved values of the flow rates CMiiquio Y CMgas can be obtained, or they can be obtained with the passage of time as those flow rates change. In this document the surface velocities are identified as those speeds that would exist if the same mass flow of a given phase had traveled as a single phase through the flow tube (215). A surface velocity determination / correction system (270) for, for example, determining an apparent or corrected surface velocity of a gas or liquid in the two-phase flow. The term "sliding velocities" refers to a condition in which the gas and liquid phases in a two-phase flow have different average velocities. That is, an average velocity of a VP gas is different from an average velocity of a lipophilic VPii. Thus, the S phase slip can be defined as: S = VPgas / VPiiqUido. A flow regime is a term that refers to a characterization of the manner in which the two phases flow through the flow tube (215) with respect to each other and / or with respect to the flow tube (215), and it can be expressed, at least partially, in terms of barely determined surface velocities. For example, a flow regime is known as the "bubble regime", in which gas is trapped as bubbles within a liquid. As another example, the "slow fluidization regime (slug)" refers to a series of liquid "plugs" or "fluid slugs" separated by relatively large gas pockets. For example, in vertical flow, the gas in a slow fluidisation flow (slug) regime can occupy almost a complete cross-sectional area of the flow tube (215), such that the resulting flow alternates between the composition rich in liquid and rich in gas. It is known that other flow regimes exist and that they have certain defined characteristics, among which are included the annular flow regime, the dispersed flow regime and the foamy flow regime and others. It is known that the existence of a particular flow regime is influenced by a variety of factors, including a fraction of gas voids in the fluid flow, an orientation of the flow tube (215) (e.g. vertical or horizontal), a diameter of the flow tube (215), the materials included within the two-phase flow and the speeds (and relative speeds) of the materials within the two-phase flow. Depending on these and other factors, a fluid flow can transit between different flow regimes in a given period of time. The flow displacement information can be determined, at least in part, from knowledge of the flow regime. For example, in the bubble flow regime, which assumes that the bubbles are evenly distributed, there may be little relative movement between the phases. Where the bubbles conglomerate and combine to form a less uniform distribution of the gas phase, some slippage may occur between the phases, with the gas tending to cut through the liquid phase. In Figure 2, a flow rate determination system (275) is included that has access to a database (280) on flow rate maps. In this way, information of an existing flow regime, including the phase slip information, can be obtained, stored and accessed to be used to simultaneously determine the mass flow rates of the liquid and gas within a two-phase flow. In Figure 2, it should be understood that the various components of the digital transmitter (104) are in communication with each other, although, for reasons of clarity, communication links are not explicitly illustrated. Furthermore, it should be understood that in Figure 2 the conventional components of the digital transmitter (104) are not illustrated, but it is assumed that they exist in their interior, or that they are accessible to the digital transmitter (104). For example, the digital transmitter (104), as a rule, will include mass flow and density (gross) measurement systems, as well as electrical circuitry systems for actuating the controller (210). Figure 3 is a flow diagram (300) illustrating an operation of the Coriolis type flowmeter (200) of Figure 2. Specifically, Figure 3 illustrates techniques by means of which the flow meter (200) of Figure 2 it can be operated to simultaneously determine the flow rates of liquid and gas CMiiquid and CMgas for a two-phase flow. In Figure 3, it is determined that a gas / liquid biphasic flow exists in the flow tube (215) (302). This can be done, for example, by an operator during the configuration of the mass flowmeter / hydrometer for gas / liquid flow. As another example, ase can make this determination automatically using a Coriolis-type meter function to detect whether a gas-liquid two-phase flow condition exists. In the latter case, these techniques were described in greater detail in, for example, U.S. Pat. No. 6,311,136 and in U.S. Pat. No. 6,505,519, which were incorporated as reference in the above. Once the biphasic flow is established, a corrected gross density pCorregxda (304) is established with the density correction system (240), using the database for the density correction (245) of the transmitter (104). That is to say, a corrected density is corrected to obtain the pCorregida "The techniques for making this correction are discussed in more detail later. Once the Pcorregida / - is determined, the corrected corrected gas hole fraction (306) can be determined with the hole fraction determination / correction system (260). In addition, corrected gross mass flowrate CM corrected (308) is determined with the mass flow correction system (250). As with the density, techniques are discussed below to obtain the corrected hole fraction corrected and the corrected mass flow MCorregido • In Figure 3, it should be understood from the flow diagram (300) that the determination of pCorrected, "• corrected and CM corrected can happen in a variety of sequences. For example, in one implementation, the corrected corrected hole fraction is determined based on the previously calculated corrected density pcorrected / - after which the corrected mass flow rate CM is corrected based on the corrected- In another implementation, the occorregida and pcorregida independently one of Other, and / or can be calculated the corrected and CM corrected independently of each other. Once the Pcorregida corrected density, corrected corrected and corrected mass flow fraction CM corrected, is known, then the mass flow rates of the gas and liquid components (310) are determined with the flow component mass flow determination system ( 265). The techniques for determining the liquid / gas flow rates will be discussed in more detail with reference to Figure 4. Once determined, the flow rates of the gas / liquid component (312) can be obtained or displayed for the flowmeter operator to make use of. from them. In this way, the operator is provided, perhaps simultaneously, with information on the mass liquid flow rate and the mass flow of CM gas from a two-phase flow. In some examples, this determination may be sufficient (314), in which case the emission of the liquid / gas component flows completes the process flow. However, in other implementations, the determination of the flow rates of individual components can be improved by factoring information from, for example, the surface velocities of the gas / liquid components, the flow rate or the flow regimes and the phase slip. , if any, between the components. In particular, the surface velocities of gas and liquid, VSgas and Siiqui0 are determined in the following manner. The superficial velocity of the gas VSgas is defined as: Sgas = CMgas / (pgas * At) Ec. 1 Where the quantity At represents an area of the cross section of the flow tube (215), which can be taken at a point where a fraction of flow gaps is measured. Similarly, the liquid liquid surface velocity is defined as: VSiíqUi o = CMiiquido / (Piquido * AT) Ec. 2 As shown in Equations 1 and 2, the determination of viral vectors in this context is based on the previous determination of CMgas and CMiiquid. From the previous description and Figure 3, it should be understood that CMgas and CMiqUido represent corrected or true mass flows, CMc ° ™ and, since these factors are calculated on the basis of Pverdedera, «true and CMver adero- As a result, The surface velocities VSgas and SiiqUido represent corrected values? sc °% lda and VS¡? ^ £ da. In addition, the pgas and liquid density values are used, as determined above, to know the densities of the liquid and gas in question, which may be stored in the database for density correction (245). As discussed in more detail above with respect to the techniques for calculating corrected density pcorregida, the pgas and liquid density values can be known as a function of the existing temperature and pressure, detected as the temperature sensor does ( 220) and the pressure sensor (225). Using the surface speeds and other known and calculated factors, some may be stored in the flow rate map database (280), a relevant flow rate and / or a phase slip (318) can be determined with the flow rate determination system (275). Once the surface velocities, the flow rate and the phase slip are known, other corrections can be made to the corrected gross density perda era, corrected gross flow CM corrected and / or fraction of holes corrected aCorrected. In this way, as illustrated in Figure 3, the CMgas and CMiiquid0 component flows can be determined. The flow regime or regimes in the gas / liquid two-phase flow can be described by following contour lines in a graph plotting the surface velocity of the liquid versus the surface velocity of the gas. As described above, an improvement can be obtained for the determination of Pcorregida, "corrected and / or CMC corrected to, first, establishing an approximate value of the gas and liquid flows, and then applying a more detailed model for the flow regime identified. For example, in the relatively low FHG and relatively high flow there is a flow regime in which the fluid with gas behaves as a homogeneous fluid with few or no errors in density and mass flow. This can be detected as a homogeneous flow that does not require corrections, simply using the observation of gain, which shows little or no increase in such a configuration, despite a significant decrease in observed density. Figure 4 is a flow diagram (400) illustrating techniques for the determination of gas and liquid flows C iiquid0 and CMgas for a biphasic flow. That is, the flow diagram (400), in general terms, represents an example of the techniques for determining gas and liquid flow rates (310), as described above with respect to Figure 3. In the Figure 4, the determination of the gas and liquid flow rates (310) starts with the entry of the data of mass flow factors, corrected density and hole fraction Pcorregida, "corrected and CM corrected (402). In a first instance, (404), the flow rates of the liquid and gas (406) are determined using the Ees. 3 and 4. Mgas = "corrected (Pgas / Pverdadera) AMCOrregido) liiC. orCM? ÍQUi o = (1 - «corrected) (Pliquido / Pcorregida) (Mcorregido) tC. 4 The Ees. 3 and 4 assume that there is no slip velocity (ie, phase slip) between the gaseous and liquid phases (ie, the average gas phase velocity, VPgas, and the average velocity of the 'liquid phase, v "). Piiquid, they are equal.) This assumption is consistent with the fact that, in the first instance, the surface velocities and the flow regimes (and consequently, the phase slip) have not been determined. (404), a determination is made, perhaps by means of the flow rate determination system (275), with respect to whether there is a phase slip (408) .If 'it is not, then Eqs. Once again, the process is completed (406) or the process is completed If there is a phase slip (408), previously defined as S = VPgas / VPiiquid0, the terms CMgas and CMüquicjo are calculated using the cross sectional area of the flow tube (215), At, the same form a as also it was used in the calculation of the superficial speeds in the Ees. 1 and 2 (410). Using the definition of slip S just given, CMg s = pgas ("correctedAt) (VPgas) = Pgas (" correctedA) (S) (Piiquitjo) EC. 5 CMiiquicjo = Pliquido ((1"« corrected) At) (PiigUido) Eq. 6 Since CM corrected = CMgas + CM? Iquido, the Ees can be solved. 5 and 6 for VP? Iquid0 to obtain Eq. 7: LIQUID - CM true / (A (Pgas «corrected 'Pliquido (« corrected /)) Ec. 7 As a result, the flow rates of the liquid and gas (406) are determined using the E's. 8 and 9: ZO CMiíqjojo = L Pliquido (I - «corrected) / (Pgas« corrected + Pliquido (I - "Corrected") J L CMcorreg doJ EC.o Mgas = Mcorregi o - iqui or EC. Y As described above, gas trapped in liquid forms a two-phase flow. Measurements of such a biphasic flow with a Coriolis type flowmeter produces parameters indicated as "corrected" and CMaparene for the density, the hole fraction and the mass flow, respectively, of the biphasic flow. Due to the nature of the two-phase flow in relation to an operation of the Coriolis type flowmeter, these indicated values are corrected by a determinable factor. As a result, the indicated parameters can be corrected to obtain real parameters corrected, "corrected" and "corrected CMC - A SU, S? they can use the corrected values, real, to simultaneously determine individual flow rates of the two components (gas and liquid). Figures 5A and 5B are graphs illustrating a percentage error in a measurement of the void fraction and the liquid fraction, respectively. In Figure 5A, the percentage error is an error of the percentage of density that is dependent on various design and operational parameters, and that, in general terms, refers to the deviation of the apparent density (indicated) from the density true combined that could be expected obtained from the percentage (%) of the gas in the liquid. The true liquid fraction versus the indicated liquid fraction is illustrated in Figure 5B. Figure 5B shows the results, for the relevant design of the flow meter, of various flow rates and tube sizes. In more general terms, the functional relationship can be more complex and dependent on both the flow rates and the tube sizes. In Figure 5B, a simple polynomial fit that can be used to correct the apparent liquid fraction is shown. Other graphing techniques can be employed; for example, the true hole fraction can be plotted against the indicated hole fraction. For example, Figure 6 is a graph illustrating a mass flow error as a function of a decrease in density for a flow tube having a particular orientation and in a selected flow range. Figure 7 is a flow chart (700) illustrating techniques for correcting density measurements (304 in Figure 3). In Figure 7, the process starts with the input of the type of flow tube (215) that is being used (702), which may include, for example, whether the flow tube (215) is straight or bent, as well as other relevant factors, such as, for example, a size or orientation of the flow tube (215). Next, the still density of the liquid liquid (704) is determined. This amount may be useful in the following calculations, or to ensure that other factors that may influence the measurement of potato density, such as, for example, are not misinterpreted as effects of the hole fraction. In one implementation, the user can enter the liquid liquid density directly, along with a density dependency of the density. In another implementation, known fluids (and their temperature dependencies) can be stored in the database for density correction (245), in which case the user can enter a fluid by name. In yet another implementation, the flowmeter (200) can determine the liquid density during a single phase time, liquid flow, and store this value for future use. A mass flowrate indicated CMaparente is read from the Coriolis type meter (706), and then a potato apparent density of the Coriolis meter (708) is read. Next, the density correction system (240) applies a theoretical algorithm (710) or a tabular empirical correction (712) to determine the true truth density of the gas / liquid mixture. Then you can enter the true quantity as the corrected density (714). An algorithmic density correction (710) can be determined based on the knowledge that, if there was no effect of the biphasic flow from the normal operation of a Coriolis meter when it is used to measure density, the indicated density would decrease an amount derived from the equation describing the hole fraction, in which it was described in terms of volumetric flow and which is now repeated in terms of density as Eq. 10: «(%) = [(Paparente ~ Pliquido) / (Pgas ~ 'Pliquid)] * 100 Ec. 10 This can be useful to define a quantity "decrease in density", or? P, as shown in Eq. 11: (%) X ((Pliquido ~ Pgas) / Pliquido) / 100 Ec.ll Note that Eq. 11 shows the amount? p being positive; however, this amount could be shown as a negative decrease simply by multiplying the right side of the equation by -1, with which we obtain Ec. 12:? p = (Paparente "" Pliquido) / piiquido = «(% ) X ((Pgas ~~ Pliquido) / Pliquido / 100 Ec.12 The quantity pgas can be small compared to püquio, in which case Eq. 12 to Eq. 13 can be simplified: ? p = (pliquido - Paparente) = Cl (%) / 100 EC. 13 As discussed extensively in the foregoing, density measurements with a Coriolis-type meter, or with any vibrating density meter, are generally below those reported with the meter, and require correction. Therefore, under the biphasic flow, EEs can be used. 12 or 13 of biphasic flow to, consequently, define the following two quantities: a decrease in the corrected and true density,? Pverdadera, and a decrease in the indicated or apparent density,? Paparente-Using Eq. 13 as an example, this produces the Ees. 14 and 15:? P verdadera = (Pliquido "Pverdadera) = 0C (%) / 100 Eq. 14? Paparente = (Pliquido ~ Paparente) = 0C (%) / 100 Eq. 15 Can you derive or empirically determine a relationship between? Pverdaera and Paparente and apparent mass flowrate, CMaparente, as well as other parameters, such as gain in momentum, temperature, phase regime, etc. Can you express this relationship as? Perdadera = f (CMaparente, paparente, gain in the impulse, the balance of the sensor, temperature, regime of the phase and / or other factors). As a result, one can derive, in general terms, the relationship, at least check, for each flow tube in each configuration. For a flow tube model, known and referred to in this description as the Foxboro / Invensys CFS10 flow tube, it has been empirically determined that for some conditions the above functional relationship can be simplified so that they are only a function of? paparente and in the manner shown in Eq. 16: M i V ^ true = S ai P apparent) Ec? ß 1 = 0 To force the condition of both sides of Eq. 16 to be zero when there is no decrease in apparent density, the relation produces Eq. 17: M i V P true =? «I (Apparent P) Ec? ^; = 1 M usually depends on the complexity of the empirical relationship, but in many cases it can be as small as the number 2 (quadratic) or 3 (cubic). Once the descent of the true density is determined, then working again with the previous equations is simple to derive the true density of the Pverdadera mixture, as well as the liquid and gaseous fractions (holes) (the last mentioned is discussed with more detail with respect to Figure 9). A tabular correction for density (712) can be used when, for example, a functional relationship is too complex or inconvenient to implement. In these cases, you can use knowledge of the quantities? Paparente and? CMaparente to determine? Pverdadera using a table that has the form of the table (800) of Figure 8. The table (800) can be, for example, a tabular query table that can be stored, for example, in the database (245), or in another memory, for use in a multiplicity of applications of the table. In addition, the table can be established during an initiation procedure, to be stored in the database (245) for an individual application of the table. It should be understood that one or both of the algorithmic or tabular forms can be extended in order to include multiple dimensions, such as gain, temperature, balance or flow regime. You can also expand the algorithmic or tabular correction in order to include other superficial adjustment techniques, such as Neural Net functions, radical base functions, Wavelet analysis or principle of analysis by component. As a result, it should be understood that these extensions can be implemented in the context of Figure 3 during the methodology described in this document. For example, during a first instance, density can be determined in the manner described above. Then, during a second instance, when a flow regime has been identified, the density can be further corrected using the flow rate information. Figure 9 is a flow chart (900) illustrating the techniques for determining hole fraction measurements (306 in Figure 3). In Figure 9, the process starts with data entry using the density determination system (240) of the liquid and gross (corrected) densities determined above, Liquid and Pverdadera (902). Then, a gas density is determined, pgas (904). As with the liquid density piíquio, there are several techniques for the determination of pgas. For example, one can simply assume that pgas is the density of the air, usually at a known pressure, or it can be a known real density of the particular gas in question. As another example, this known density pgas can be one of the - previous factors (ie, a known density of the air or specific gas) at an actual or calculated pressure, in the manner as detected by the pressure sensor (225), and / or at an actual or known temperature, in the manner as detected by the temperature sensor (220). The temperature and pressure can be monitored using external equipment, as shown in Figure 2, between what is included, the temperature sensor (220) and / or the pressure sensor (225). In addition, it can be known that the gas has specific characteristics with respect to the factors, among which are, pressure, temperature or comprehensibility. These characteristics can be entered together with a gas identification, and can be used for the determination of the actual density of the gas pgas. As with the liquid (s), multiple gases can be stored in the memory, perhaps together with the characteristics just described. , so that a user can access the density characteristics of a particular gas by selecting the name of the gas from a list. Once the known factors are known, Pgas and True, then it should be clear from Eq. 10 that the hole fraction "true" can be easily determined (906). Then, if necessary, the liquid fraction (908) can be determined simply by calculating l-a True-Although the previous discussion presents techniques for determining the true hole fraction based on density, it must be understood that it can be determine the hole fraction with other techniques. For example, a hole fraction indicated with the Coriolis type flowmeter can be determined directly, perhaps in combination with other hole fraction determination systems (represented by the hole fraction sensor (235) of Figure 2) , and then can be corrected based on the empirical or derivative equations to obtain "true". In other implementations, these external systems for determining the hole fraction can be used to provide a direct measurement of "True • Figure 10 is a flow diagram (1000) illustrating techniques for determining mass flow measurements (308 in Figure 3). In Figure 10, the mass flow correction system (250), first, inputs data from the previously corrected data loss (1002), and then produces an apparent mass flow measured true CM (1004). The mass flow correction system (250) applies a tabular (1006) or algorithmic (1008) correction to determine the true true CM mass flow rate of the gas / liquid mixture. The true CM quantity can then be sent as the corrected mass flow rate (1010). When applying the tabular correction for mass flow (1006), it may be useful to know the quantities? True and? True to determine the true CM using a table that has the form of table (1100) of Figure 11.

The table (1100), as in the case of the table (800) can be, for example, a tabular query table that can be stored, for example, in the database (245) or in another memory, to be used in multiple applications of the table. In addition, the table can be established during an initiation procedure, to be stored in the database (245) for an individual application of the table. The normalized values CMn? Rm_aparente and CMnorm_verdadero can be used instead of the real values shown above, in order to cover more than a Coriolis type flow tube of a certain size. Also, the entries may be in correction terms, when the correction is defined by Eq. 18: ? CM = True CM ~ CMaparient Eq. 18 It must be understood that the values in Eq. 18 represent real or normalized values. In an algorithmic methodology, as with density, the correction of the mass flow can be implemented by means of a theoretical or empirical functional relation that is understood that, in general terms, it is of the form? CM = f (CMaparente, fraction of holes , gain in momentum, sensor balance, temperature, phase regime and / or other factors).

For some cases, the function can be simplified to a polynomial, such as the polynomial shown in Eq. 19: M N. . . . ACM = ?? afij. { p erdadera). { CMiorm apparent) Ec? 9 -O 0 For some set of conditions, the functional relationship can be a combination of a polynomial and exponential, as shown in Eq. 20: ACM = a.de ^ 2 + a? + a + a ^ + a6d2 + a7d + 8m2 + a9m Ec. 2 o In equation 20, d =? True, and m = f (CMaparente) In one implementation, m can be replaced in Eq. 20 with the apparent surface velocity of the Siiquid liquid which is given as described above with Eq. 2 as Siqqid = CMiiquid / (Pliquid * At). In this case, Puuido and the cross section of the flow tube are known or entered factors, and can be corrected in real time for the temperature using, for example, the included temperature measurement device (220) of the digital transmitter / controller (104). It should be understood that, as with the density corrections discussed above, one or both of the algorithmic or tabular forms can be extended in order to include multiple dimensions, such as gain, temperature, balance, or flow regime. You can also expand the algorithmic or tabular correction in order to include other superficial adjustment techniques, such as Neural Net functions, radical base functions, Wavelet analysis or principle of analysis by component. As a result, it should be understood that these extensions can be implemented in the context of Figure 3 during the methodology described in this document. For example, during a first instance, the mass flow can be determined in the manner described above. Then, during a second instance, when a flow regime has been identified, the mass flow rate can be further corrected by using the flow rate information. All of the above functional relationships for mass flow can be restored using the fraction of gas (a) and liquid fraction (100-a) instead of the decrease in density, as shown in table (1100) of Figure 11. Also, Although the above described methods depend on the knowledge of the descent of the corrected density? pverdadera, it must be understood that other techniques can be used to correct an indicated mass flow. For example, in U.S. Pat. No. 6,505,519, incorporated herein by reference, several techniques for correcting mass flow measurements were described. Figures 12 to 14 are graphs illustrating examples of density corrections for various flow tubes. In particular, the examples are based on data obtained from three vertical flow tubes for water, the flow tubes have a diameter of 1.27 cm (1/2"), 1.9 cm (3/4") and 2.54 cm ( 1' ') . More specifically, data of the diameter of 1.27 cm (1/2") were taken with a flow rate of 0.15 kg / s and a flow rate of 0.30 kg / s; data of the diameter of 1.9 cm (3/4") were taken with a flow rate of 0.50 kg / s and a flow rate of 1.00 kg / s; and the data of the diameter of 2.54 cm were taken (1 '') with a flow rate of 0.50 kg / s, a flow rate of 0.90 kg / s and a flow rate of 1.20 kg / s. Figure 12 illustrates an error, ie, of the apparent density of the fluid and gas mixture (two-phase flow) versus the true decrease in the density of. the fluid mixture and gas,? pverdadera.

A Ap =, 10 ?? 0 • - líq -uido r true E r, c. 2 ~ 1 r liquid ed = 100 • Paparente - True Ec. 22 r where, as above, pliquio is the density of the liquid without gas, P verdadera is the true density of the liquid and gas mixture, and paparente is the apparent or indicated density of the liquid mixture and gas. In Figures 12 to 14, the correction is carried out in terms of the apparent decrease in the density of the mixture,? Paparente, as shown in Eq. 23: ^ apparent = ^ '' ^ ° "" * Ec. 23 Pliquido In Figures 12 to 14, when the data is adjusted, the apparent and true decrease in the density of the mixture were normalized to values between 0 and 1 when divided by 100, where this standardization is designed to ensure the numerical stability of the optimization algorithm. In other words, the apparent and true normalized decreases in the density of the mixture are apparent and true normalized decreases in the density of the mixture defined as a ratio, rather than as a percentage, of the liquid liquid density, as It is shown in Eq. 24: A normalized r "apparent -r,?? Paparente - -,?? &C.? '* 100 The model formula, based on Eq. 17, provides Eq. 25: A -.normalized _ (i ^ normalized ¥. _ (\ -.normalized \, I \ normalized r? G ^ true = «1 Paparente f + a2 Paparente) +« 3 Paparente) Ec.25 In this case, the coefficients are a? = - 0.51097664273685, a2 = l .26939674868129 and a3 = 0.24072693119420. Figures 13A and 13B illustrate the model with experimental data and residual errors, as shown. Figures 14A and 14B provide the same information, but with each flow plotted separately. To summarize, the correction is made in the decrease of the density in the transmitter (104) when calculating the decrease in the apparent density, using the value of the apparent apparent first density and the liquid density of the liquid. normalizes the value of the apparent decrease in density to obtain? ^ "° = - ^^, in such a way, as explained in the above, the decrease in density is calculated as a proportion instead of as a percentage. The density correction model (s) can then be applied to obtain the corrected normalized decrease in the density of the mixture Ap "° ™ aaJrz ° C. Finally, this value is denormalized to obtain the corrected decrease in the density Apverdadera = 100 • Apaparente Of course, the final calculation is not necessary if the corrected decrease in the density of the mixture is defined as a proportion instead of as a percentage of the true value Figures 15 to 20 are graphs illustrating examples of mass flow corrections for various flow tubes In particular, the examples are based on data obtained from three vertical flow tubes for water, the flow tubes have a diameter of 1.27 cm (1/2") , 1.9 cm (3/4 '') and 2.54 cm (11) More specifically, data of the diameter of 1.27 cm (1/2") were taken with a flow rate of 0.15 kg / s and a flow rate of 0.30. kg / s, the data of the diameter of 1.9 cm (3 / 4 '') with a flow rate of 0.50 kg / s and a flow rate of 1.00 kg / s; and data of the diameter of 2.54 cm (1") were taken with 18 flow rates between 0.30 kg / s and 3.0 kf / s, with a maximum decrease in density of approximately 30%. Figures 15A and 15B illustrate errors in the apparent mass flow for the data used to adjust the model against the corrected decrease in the density of the mixture? True and true normalized surface velocity of the fluid; that is, the apparent mass flow error curves per flow line, together with an error scatter plot in the apparent mass flow versus the corrected decrease in the true density and true normalized surface velocity of the fluid vm, as shown in Eq. 26: v vm - - - ', v v = i Le.26 Vmax Pliquido' ^ T where mv is the true mass flow of the fluid, that is, the value of the mass flow independently measured, Fluid is the liquid density, At is the cross sectional area of the flow tube, vmax is the maximum value for the superficial velocities of the fluid (at this point considered 12 m / s), so - that vm. it provides the ratio of the true surface velocities of the fluid from the entire range of the flow tube (215). In these examples, both the decrease in the density of the mixture and the fluid surface velocity between 0 and 1 are normalized before adjusting the model, with the purpose of ensuring numerical stability in the optimization algorithm of the model. Figure 16 illustrates errors in the apparent mass flow versus the corrected decrease in the density of the mixture and the normalized apparent surface velocity of the fluid, with safety dimensions for the correction mode. That is, Figure 16 provides the scatter diagram of the apparent mass flow errors versus the corrected decrease in density and, this time, the normalized apparent surface velocity of the fluid v tn vn = =, where m is the apparent mass flow of the v ma.xv ma.x • ro A fluid (ie, as the digital transmitter (104) measures it). The overlapping boundaries in the graph define the security region for the model, that is, the region for which the model is expected to provide accuracy similar to the accuracy for the adjusted data. Using this nomenclature, the error in the apparent mass flow is The model formula for this situation is shown as Eq. 27: e "= axddcn - ea > dd < "+" A + a < * + a¡v "+ a6ddc2n + a7ddcn + 8v" 2 + 9v "Ec. 27 d m - mt e "= Eq. 28 100 m, where, in the Ees. 27 and 28, ddcn is the normalized corrected decrease in the density of the mixture, and vn is the normalized apparent surface velocity of the liquid. In this case, the coefficients are: a? = - 4.78998578570465, a2 = 4.20395000016874, a3 = -5.93683498873342, a4 = 12.03484566235777, a5 = ~ 7.70049487145105, a6 = 0.69537907794202, a7 = -0.52153213037389, a8 = 0.36423791515369 and a9 = -0.16674339233364. Figure 17 illustrates a scatter diagram for model residuals, along with the model formula and coefficients; that is, it shows the residuals of the model against the corrected decrease in the density of the mixture and the true normalized velocity of the fluid. Figures 18A-18D and Figures 19A-19D provide the model residual errors for the entire data set used to fit the model and the actual data alone, respectively. Finally, Figures 20A and 20B illustrate the model plane by interpolating and extrapolating outside the secure fit area. From Figures 16, 20A and 20B, the apparent mass flow (liquid surface velocity) and the decrease in density densities for the model should be included. To summarize, in this example, the mass flow correction in the transmitter (104) is calculated by calculating an apparent decrease in density, correcting it using the method (s) described above, and normalizing the resulting value by dividing it by 100 (or when using the corrected normalized descent obtained in density from the model for density). Then, a normalized surface velocity of the fluid vn is calculated, and the model is applied to obtain an estimate of the error in the normalized mass flow in, where this value provides the apparent mass flow error as a proportion of the true mass flow. The value obtained can be denormalized by multiplying it by 100, with which the error in the mass flow is obtained as a percentage of the true mass flow. Finally, the apparent mass flow can be corrected with the error in the de-normalized mass flow »J" «. + 1 As will be appreciated, the above description has a wide range of applications to improve the accuracy of measurement and correction of a meter type Coriolis during two-phase flow conditions. In particular, the techniques described above are particularly useful in measurement applications where the mass flow of the liquid phase and the mass flow of the gas phase must be measured and / or corrected at a high level of accuracy. An illustrative application is the measurement of the mass flow of the liquid phase and the measurement of the gas phase in gas and oil production environments. The above discussion was given in the context of the digital flowmeter of Figure 2. However, it should be understood that any vibrating or oscillating, analogue or digital hydrometer or flowmeter capable of measuring multiphase flow including a gaseous phase can be employed. of a certain percentage. That is, some flow meters are only capable of measuring process fluids that include a gaseous phase when that gas is limited to a small percentage of the overall process fluid, such as less than 5%. Other flow meters, for example, the digital flowmeter (s) mentioned above, are capable of operating even when the fraction of holes in the gas reaches 40% or more. Many of the equations and calculations presented above were described in terms of density, mass flow and / or hole fraction. However, it must be understood that the same or similar results can be achieved by using variations of these parameters. For example, instead of the mass flow, a volumetric flow can be employed. Also, instead of the hole fraction, the liquid phase can be used. The above discussion provided examples of measuring the mass flow rates of components in a biphasic flow. You can also use flow meters to measure even more mixed flows. For example, the term "biphasic" or "mixed biphasic flow" refers to a situation in which two types of liquids are mixed with a gas. For example, a flowing mixture of oil and water may contain air (or another gas), thereby forming a "three-phase flow", where the terminology refers to three components of the flow, and does not imply that, in general terms, a solid is included in the flow. Figure 21 is a block diagram of a flow meter system (2100). The flow meter system (2100) can be used, for example, to determine the mass flow rates of individual components within a three-phase flow, a gas flow traveling through a pipe in an oil extraction facility, over a period of time. of certain time. You can also use 'the flow meter system (2100) to obtain very accurate measurements with the digital transmitter (104), such as density measurements or measurements of mass flow rates. The system (2100) can also be used, for example, to obtain an improved measurement with an external sensor, such as the liquid fraction meter (230) or the hole fraction sensor. (235), in relation to measurements that must be obtained using only the external sensor (s). In Figure 21, the digital transmitter (104) includes a gap fraction determination system (2102), a density determination system (2104) and a mass flow determination system (2106) (in addition to a variety of components that are not shown for reasons of clarity, for example, a driving signal generator or a multiphase detection system, or any of the components illustrated or discussed with respect to Figure 2). That is, as it should be understood from the above description, systems (2102), (2104) and (2106) can be employed to measure the corresponding parameters of a fluid flow within the flow (215). In addition, as also explained in the foregoing, to the extent that the fluid flow contains mixed liquids and / or gas, the output signals of the measurements made by the systems (2102), (2104) and (2106) represent, in general terms, unrefined or apparent values for the corresponding parameters, which can finally be corrected with a corrections system (2108). For example, an apparent mass flow rate of a three-phase flow within the flow tube (215) can be sent as a signal to the correction system (2108) for correction using a mass flow correction module (2112), while a density Apparent of the three-phase flow within the flow tube (215) can be sent as a signal to the correction system (2108) for correction using a density correction system (2118). Similarly, a measurement or determination of an apparent void fraction within the fluid flow can be corrected by using the density correction module (2114), while a measurement or determination of an apparent liquid fraction can be corrected (for example). example, a water cut from a meter (230) using a water cut correction module (2116) As described in more detail below, the various correction modules (2112-2118) can work in together, and / or with other components, in order to obtain their respective corrected values Once obtained, the corrected values, as for example, mass flow, density, water cut or hole fraction (or some combination of these) can be sent as a signal to a server computer (2110) for the determination of individual mass flow rates of three components of the three-phase flow, using a system for determining mass flow of components (2120). As a result, and as mentioned above, individual mass flows and / or quantities of each of the three components can be determined. More specifically, an example of the system (2100) includes three general elements used to obtain corresponding measurement values and / or mass flow rates of individual components: The transmitter (104), one more of the individual external sensors generically identified with the number reference (2122), and one or more elements of the correction system (2108). Of course, many combinations, variations and implementations of these elements can be used, the various examples of which are discussed in more detail below. For example, in some implementations, the digital transmitter (104) may not include the gap fraction determination system (2102). In some cases, the void fraction determination system (2102) may be included with, or associated with, the liquid fraction meter (230), or it may be unnecessary depending on the type or configuration of the void fraction sensor. (235). In this type of case, as necessary, the hole fraction can be determined from the output signals of the correction modules (212), (2116) and / or (2118). In addition, although Figure 21 shows the external sensors (2122) in communication with the digital transmitter (104) and with the flow tube (215), it should be understood that the external sensors (2122) can obtain their respective measurements in a diversity of different ways. For example, examples of the temperature sensor (220), the pressure sensor (225) and the hole fraction meter (230) are described below, with respect to, for example, Figure 2. In addition, the sensor liquid fraction (235) can be in series with the flow tube (215) with respect to a primary tube for transporting the three-phase fluid flow, it can maintain separate communication with the transmitter (104), the correction system (2108) and / or the server computer (2110) In Figure 21, the correction system (2108) is shown separately from the digital transmitter (104) and the server computer (2110). In some implementations, however, the correction system (2108) may be placed within the digital transmitter (104), the server computer (2110), or may be associated with one or more external sensors (2122). In still other implementations, portions of the correction system (2108) may be included within the sections of the system (2100). For example, density and mass flow rate corrections can be made in the digital transmitter (104), while water cuts can be made in the gap fraction meter (230). In some implementations, the correction system (2108) may include all modules (2112-2118) (as shown), or in some subset thereof, or may include other modules, not specifically illustrated in the Figure 21 (for example, a correction module to correct a density of the two-phase component within the three-phase flow, such as, for example, the oil / water mixture in an oil / water / gas flow). In addition, some or all of these correction modules can be integrated with each other. For example, the mass flow and density corrections can be incorporated into a module, while the water cut correction module (2116) can be separated. Along the same lines, it should be understood that the system for determining mass flow of components (2120) can be placed in a variety of places within the system (2100). For example, the component mass flow determination system (2120) may be placed within the correction system (2108) or it may be placed within the digital transmitter (104). A number of examples of the above and many other implementations are described in more detail below, as well as examples of specific techniques for obtaining flow measurements and mass flows of individual corrected components. However, in general, it should be understood that the system (2100) and other implementations thereof allow all or substantially all of the three-phase fluid flow to flow continuously through the flow tube (215) and through an associated tube. and another conduit for transporting the three-phase flow material. As a result, mass flow determinations of individual components are not required separately from the three-phase fluid flow in separate flows containing one or more constituent components. For example, when the three-phase flow contains oil, water and gas, it is not necessary to separate the gas from the oil / water liquid combination in order to make measurements (for example, the mass flow rate) in the oil portion of the resulting oil flow. /liquid. Therefore, reliable measurements of a quantity of oil produced, for example, can be carried out easily, quickly, cheaply and reliably., in an oil production facility. Figure 22 is a diagram of a first implementation of the system (2100) of Figure 2. In Figure 22, the liquid fraction meter (230) is illustrated as a water cut meter that is in series with the digital transmitter (104) with respect to the three-phase fluid flow through the tube (2202). More detailed examples of the use of measurements from the water cut-off meter (230) in the determination of flow measurements are given below. Also in Figure 22, a static mixer-tester (2204) is illustrated which serves to homogenize the three-phase flow. The mixer-tester (2204) can also be used for other measurements. For example, the mixer-tester (2204) can be used to validate measurements of the water cutter (230) or other measurements. In one implementation, the mixer-tester (2204) may be used to siphon a portion of the three-phase oil / water / gas flow for evaporation of the gas from this flow, for independent confirmation of the formation of water within the resulting biphasic composition. In somewhat similar way, a pressure transmitter (2206) may be employed in various post-processing techniques to validate or confirm measurements of the system. Figure 23 is a block diagram of a second implementation of the system of Figure 21. In Figure 23, the liquid fraction meter (230) is illustrated as a microwave water cut-off meter (230a) and / or a water cut meter (230b) infrared. Also illustrated is an energy supply (2302) for supplying power to the system. It should be understood that the flow tube (215) of Figure 23 contains, for example, the bent flow tube (102) of Figure IA, although, of course, the straight flow tube (106) can also be employed. of Figure IB or some other flow tube. In addition, in Figure 23, the sensors are illustrated (230a), (230b) and / or (2206) in bidirectional communication with the transmitter (104), including a standard 4-20 mA control signal. In the meantime, the transmitter (104) is in communication with the server computer (2110) via the Modbus RS485 connection. Also, as mentioned in the above, Figure 23 illustrates various possible locations for the correction system (2108). For example, as shown, the correction system (2108) can be located in, or associated with, a processor associated with the server computer (2110), or with the digital transmitter (104) and / or the meter. water cut (230a) (and / or other external sensor (230b)). Figure 24 is a block diagram of an implementation of the correction system (2108) of Figures 21-23. In Figure 24, and as it should be appreciated from the previous description of Figure 21, the correction system (2108) receives, from the transmitter (104), measurements, such as, for example, an apparent measurement (or gross) of a liquid fraction (eg, water cut) of the three-phase flux, together with an apparent gross mass flow rate and an apparent gross density. The correction system (2108) in this example includes a water cut error model (2402) and a Coriolis error model (2404). • Models (2402) and (2404), as shown, allow the calculations of the corresponding corrected measurements, or the estimate of the corresponding true measurements, of the water cut, mass flow and density. In other words, as it should be evident from the above discussion of biphasic fluid flows, flow parameters and known configurations of model (2402) and (2404) can be corrected, so that subsequently the measured flow parameters can be corrected with modeling results by means of, for example, interpolation. For example, as discussed in more detail below, models (2402) and (2404) can be implemented to provide polynomial adjustments of measured (apparent) flow parameters. In other examples, models (2402) and (2404) can represent neural network correction models to correct water cuts and mass flow / density. In the example of Figure 24, where the available measurement includes an apparent water cut, then the resulting corrected measurements allow the calculation of the additional gas gap fraction parameter. Conversely, if a fraction of apparent gas gaps were available, instead of an apparent water cutoff measurement, then the correction system can produce a corrected hole fraction measurement (thus allowing the subsequent estimation of a real water cut). In any case, or in similar cases, the corrections system (2108) can send the corrected measurements as a signal to the component mass flow determination system (2120) for the calculation of mass flows of individual components. Figure 24 illustrates an example in which the output signals of each model (2402) and (2404) are fed back to each other, in order to obtain sequentially better results, before obtaining the final value for the corrected water cut , mass flow (gross) and density (gross) and, therefore, calculate flows of individual components. In other words, for example, it is assumed that the initial determination of an apparent water cut can be dependent on, and vary with, an amount of gas within the three-phase fluid flow (i.e., the gas gap fraction). However, an exact value of the gas gap fraction may not be, in general terms, available until after an estimate of the true water cut measurement has been determined. Therefore, as illustrated, by feeding the values of a first determination of a water cutoff value corrected from the water cut error model (2402) back to the Coriolis error model (2404), a corrected estimate of the mass flow, density and fraction of gas holes corrected can be obtained, and, later, feedback in the water cut error model. This process may continue, for example, until a desired level of accuracy is reached, or until a certain amount of time has elapsed. In Figure 24, the models (2402) and (2404) can be orthogonal to each other, so that one can be replaced without affecting the operation of the other. For example, if a new water cut meter is used (eg, meter 230a instead of meter 230b of Figure 23), then a corresponding water cut error model can be substituted in a similar way, while you can continue to use the Coriolis error model. In other implementations, and, for example, where it is assumed that a specific water-cut meter, Coriolis-type meter and the configuration thereof are unalterable with respect to each other, then it may be possible to construct a single error model that produces the three measurements of water cut, mass flow, and density, and produce corrected values for the three (along with, possibly, a fraction of corrected gas holes). In this implementation, it may not be necessary to feed back the sequential results in the error model in order to obtain the three corrected values (or four or more). Figure 25 is a flow diagram (2500) illustrating a first operation of the flow meter of Figures 21-23. More particularly, Figure 25 represents a high-level description of many different techniques and combinations of techniques, specific examples of some of them (along with other examples) are presented in more detail below. - In Figure 25, the existence of a three-phase flow is determined and apparent measurements (2502) are obtained. For example, the transmitter (104) can obtain an apparent bulk density and an apparent mass flow rate, the liquid fraction meter (230) can obtain an apparent water cut measurement. As shown in Figure 21, these measurements can then be sent to the corrections system (2108). In this way, a corrected water cut (2504), a corrected gross density (2506), corrected gross mass flow (2508) and a fraction of corrected gas voids (2510) can be obtained. As illustrated, there are many variations for obtaining these corrected measurements. For example, the corrected mass flow rate can be determined based on apparent measurements, such as the apparent mass flow rate, or can be determined based on these factors together with an already corrected density and / or a measurement of the fraction of gas hollows Similar comments apply, for example, to techniques for obtaining corrected density measurements and / or fraction of gas voids. Also, it should be understood that other factors and parameters can be used in the calculation of corrected values that are not necessarily shown in Figure 25, such as temperature, pressure, liquid and gaseous densities of the flow components or other parameters , known or measured. Furthermore, as mentioned above, a certain correction can be obtained multiple times, with subsequent corrections based on intermediate corrections of other parameters. For example, a first measurement of the corrected water cut can be obtained, and then it can be revised based on a later determination of the hole fraction, to obtain a second measurement of the corrected water cut. Once some or all of these corrected parameters are obtained, mass flow rates of individual components can be obtained for one or more of the first liquid component, second liquid component and the gas component (2512). Then, these output signals, and / or the corrected values of themselves, can be displayed or some other way displayed (2514). Figure 26 is a flow chart (2600) illustrating a first example of the techniques of Figure 25. In particular, in Figures 21-25, the correction action can be associated with the action of determining a water cut measurement, using the water cut meter (230). Accordingly, in Figure 26, the existence of a three-phase flow having a first liquid, a second liquid and a gas is assumed, and the process begins with the determination of an apparent water cut measurement (2602). Then, the density of the mixture of the two liquids (2604) is determined. Based on this knowledge, the fraction of gas holes apparent Paparente (2606) is determined. Then, in one implementation, the process (2600) continues with a determination of the corrected values of, for example, gross density and gross mass flow rate (2608). Once these values are known, a correction of the gas hole fraction "corrected" (2610) can be made, which produces a new revised determination of the gas hole fraction (2606). In this way, a correction of the initial water cut measurement (2612) can be made, in order to take into account an effect of the gas within the three-phase flow in the initial measurement of water cut (2602), and in consequently obtain a better water cut measurement. Then, the improved water cut measurement can be used to determine and better the liquid density measurement (2604), which, in turn, can be used to determine a corrected and improved measurement of the gas gap fraction (2606). ). As a result, even more corrected measurements of gross density and gross mass flow rate (2608) can be obtained. The process (2600), or variations thereof, may be continued until satisfactory results have been determined for the corrected values of gross density, gross mass flow rate, water cut and / or fraction of gas voids. Then, individual mass flows can be determined for the three components (eg, oil, water and gas) of multiphase flow. Following are specific equations and a discussion for the implementation of the example processes (2500) and (2600), as well as for later examples. In this context, specific examples of how and why selected parameters are used are also provided. For example, water cut in a two-phase flow is defined as the volumetric fraction of water in the biphasic mixture (eg, oil-water), when there is no gas. Under this condition, the water cut is given by the following Eq. 29: F-? i Pliquido P oil r, ~ Q Pa P oil where Piquido is the density of the oil-water mixture, petroleum and pa are the densities of pure oil and pure water, respectively. Of course, the liquid petroleum and water components are just examples, and other liquids can be used. In general terms, in the case of only a two-phase oil-water flow, where there is no gas, the Coriolis type flowmeter can measure the density (gross) of the mixture, liquid, and the mass flow of the mixture, CM. The water cut of the mixture is then calculated based on Eq. 29. This technique is described in greater detail in, for example, U.S. Pat. No. 5,029,482 assigned to Chevron Research Company, and may be useful in obtaining the water cut from the density measurement using the Coriolis type flow meter. The volumetric flow of the liquid mixture (oil-water) can be derived using Eq. 30: C ^ M liquid ^ V and liquid Ec.30 Pliquido Therefore, the two independent measurements of the gross density (mixture) and the mass flow using the Coriolis type flowmeter provide sufficient information to satisfy the mathematical adjustment requirement where two components are present in the combined current. In the Ees. 29 and 30, however, can not be applied directly when in an intermixed stream of three distinct phases (i.e., oil, water and gas), i.e., a three-phase flow, as discussed above with respect to Figures 21- 25, since the Coriolis type flowmeter can measure the density and mass flow of the mixture of the two liquids and the gas. In the three-phase case of, for example, oil-water-gas flow, a third component is introduced whose benefits from a third independent source of information to satisfy the mathematical adjustment for the three-phase flow. In the implementations described above, the independent information is provided by another device installed in line with the Coriolis type flowmeter, which meets the same three-phase mixture, that is, the water cut meter (230). The water cut meter (230), as described above with respect to Figures 21-25, can be of any possible technology including microwave technology, capacitance, capacitance-inductance, nuclear magnetic resonance, infrared and infrared. close, and can be implemented using a combination of these types of water cut meters. Also within the scope of the present invention is the use of other types of water cutting meters (or, more generally, liquid fraction meters). The transmitter (104), as described above, can be used to provide an apparent bulk density, as well as an apparent gross mass flow rate, CMaparent- Meanwhile, in this example, the cut-off meter can be used. water (230) to obtain an apparent water cut measurement CAaparente. The density of the oil-water liquid portion only mixes it three-phase, therefore, it can be derived from the water cut information as shown in the Ec *! 31, where, as in the above, the liquid densities of the components are known or can be obtained, for example, according to the techniques also described in the foregoing.

Puquido = \ ^ ~ Aaparente ¡PpETR¿LB0 + Aaparente pa Ec. 31 The fraction of gas voids, a, as mentioned above, is defined as the volumetric fraction occupied by the gas phase in the three-phase mixture. A definition of a in terms of apparent and uncorrected values is given below and is repeated at this point as Eq. 32: Paparente P liquid r. I aaparente ~~ -C, C- - ^ P Piquid gas The density of the gas phase in the previous Eq. 32 can be calculated based on an independent measurement of process pressure and temperature. For example, the pressure can be measured with the pressure transmitter (225), while the temperature is measured either independently using a temperature transmitter or obtained from the temperature of the Coriolis type flowmeter, for example, the temperature sensor (220). ), such as the Resistance Temperature Detector (RTD). The application of, for example, algorithms of the American Gas Association (AGA, American Gas Association), incorporated in the transmitter (104), can then be employed to provide the density of the gas phase. In Eq. 32, and as already described with respect to Figure 26, the density of the calculated liquid phase (2604) and the fraction of gas holes based on the water cut information are approximations, since The measurement of water cut by itself is affected by the presence of gas, which until now was unknown. As shown in Figure 26, a solution technique can therefore be employed to converge to the correct density of the liquid phase and to the fraction of gas voids. Specifically, after the application of the mass flow and gross density corrections, an updated gas hole fraction (2610, 2606) is obtained. This value of the updated gas hole fraction is then applied to the water cut reading to correct the effect of the presence of gas (2612, 2602). For each specific water cutting device, the relationship between the water cut and the effect of the gas hole fraction can be known, as shown in Eq. 33: Aaparent = J \ (apparent X 'Paparente> Maparente, OtrOS.}. C. 00 That is, the apparent water cut measurement can be a function of many different parameters, so that a corrected water cut measurement CACOrrefied can be, in general terms, a function of the same parameters, corrected values of these parameters and / or the same water cut measurement. With the reading of the updated water cut, the process is repeated, starting with Eq. 31, until the appropriate convergence criteria have been met. Then, in the process temperature can be reported the mass flow (gross) of the three-phase mixture, density and fraction of gas holes corrected. Then the individual volumetric flow of each phase / component is calculated and corrected to the standard temperature using, for example, the equations of the American Petroleum Institute (API) for crude oil and for produced water, and the algorithms of the AGA for gas produced. These features can be incorporated into the transmitter (104). For example, in one implementation, the water cut meter (230) can be operated to feed its measurement and information signal directly into a communications port either analogue or digital (input / output) of the transmitter (104). In another implementation, the water cut meter is capable of communicating with the transmitter (104) in a bidirectional communications mode. As part of this implementation, the water cut meter is capable of feeding its information and measured signal directly into the communication port of the transmitter (104) as described. The transmitter (104) may also be able to send signals and information to the water cut meter (230). Figure 27 is a flow chart (2700) illustrating a second example of the techniques of Figure 25.

In Figure 27, as in Figure 26, the process (2700) starts with a determination of an apparent water cut measurement (2702). Then, the water cut measurement can be used to determine a density of the total liquid component (eg, a density of a combined portion of oil and water of the three-phase flow), guizá using Eq. 31 (2704). An apparent bulk density of the multiphase flow or a decrease in bulk density can be determined as described above (2706), and a fraction of apparent gas voids can be determined, either independent of, or based on, apparent gross density (2708). Similarly, then an apparent mass flow rate of the total liquid component (2710) can be calculated, using some or all of the previously calculated parameters. At this point, the first values for the corrected gross density and the corrected gross mass flow rate (2712) can be determined. Then, the values for a corrected gas gap fraction (2714), a corrected total liquid component mass flow rate (2716) and a revised or corrected water cut measurement (2718) can be determined. With the measurement of the revised water cut-off and with other parameters, a measurement of the gas gap fraction reviewed can be obtained. Then, as shown, additional corrections can be made to gross mass flow rates and gross density, and this process can be repeated until an adequate level of correction is reached. And, as described in the above with respect to Figures 25 and 26, information of the corrected gross mass flow rate, corrected gross density, corrected water cut and / or measurements of the corrected gas gap fraction can be obtained. Also, although not explicitly illustrated in Figure 27, the mass flow rates for the three individual components of the multiphase flow can be obtained. Figure 28 is a flow chart (2800) illustrating a third example of the techniques of Figure 25. The process of Figure 28 starts, as in the process (2700), with the determinations of the water cutoff measurements, total gross density, and gross apparent density (2702, 2704, 2706). Then, an apparent gross mass flow rate is determined (2802). Based on this information, corrected values of gross density and gross mass flow (2804) can be determined. Then, the density of the gas can be determined as, for example, a function of pressure and temperature (2806). Accordingly, a fraction of gas voids can be determined (2808) and corrected (2810). Using the corrected gas gap fraction, a revised water cut measurement (2812) can be determined, and can be used to calculate an improved liquid density, and the process is repeated until a satisfactory result is achieved. As with Figure 26, and in combination with the discussion thereof, specific examples, equations and techniques for implementing the processes of Figures 27 and 28 are presented below. Of course, other techniques may be employed. The water cut meter (230) or other instrument, as described above, provides a measurement of the volumetric ratio of water to raw liquid in the liquid phase, as shown in Eq. 34 (2702), where the water cut-off value CA initially represents a value of the apparent water cut (ie, calculated on the basis of apparent values of the mass flow or density) that can be improved or corrected as the processes continue, as already described: CMn QA = "= - Ec 34 Va + OilCell CM ^ + CMpelr? ¡O Pa P petroleum Accordingly, the flowmeter is able to use the water cut measurement to calculate the phase-specific density, as shown in Eq. 31 (2704) From this, the flowmeter is able to determine the apparent decrease in density caused by the presence of gas, as discussed above with respect to, for example, the standardized Eq. , which is reproduced at this point for convenience: Paparente liquid rp or apparent = 100 liquid and, as described above, apply a correction algorithm, according to the orientation of the meter, to apply a cubic form of Eq. 17, also reproduced at this point for convenience: M ^ V ^ P true = S «/ P apparent) ^ .17 í = l and determine a corrected density of mixture using Eq. 35: P verdadera = V ~ ^ -P erdadera) P liquid C. 35 which can be used to calculate a "best estimate" of the gas hole fraction defined by the previous Eq. 32. Other techniques to be used with the processes of Figures 25-28 from the above discussion on similar calculations in the context of, for example, two-phase flow (e.g., liquid and gas). In particular, it should be understood that some or all of the equations used in a biphasic configuration can be applied with respect to a three-phase flow, since a three-phase flow of, for example, oil, water and gas, can be considered a two-phase flow. of gas with a mixture of oil / water. Other techniques for using the systems of Figures 21-24 with respect to the data relating to implementations and specific uses thereof are described below. Figure 29 is a flowchart (2900) illustrating techniques for determining component flows for a three-phase flow. That is, Figure 29 corresponds to a more detailed view of the component flows, as shown in Figure 25 (2512). In Figure 29, the parameters of corrected gross mass flow rate, corrected gross density and fraction of corrected gas voids (and / or corrected water cut) are entered (2902). Then, a corrected liquid flow rate (2904) is determined, that is, a flow rate of the mixture of the two liquids (e.g., oil and water) in the three-phase flow. Then, a mass flow rate of a first liquid component (e.g., water) (2906) is determined, followed by a determination of a mass flow rate of the second liquid component (e.g., petroleum) (2908). Finally, the density, fraction of gas voids and / or water cut-off value corrected can be used to determine a mass flow rate of the gas component of the three-phase flow (2910). Figure 30 is a flow diagram (3000) illustrating examples of more specific techniques for performing the determinations of Figure 29. In Figure 30, it should be understood that the corrected mass flow rates of the liquid and its components are determined independently of the density measurements and fraction of gas holes corrected. Specifically, a fraction of apparent gas voids (3002) is determined, using the above Eq. 32. Then, the apparent mass flow rate of the gas (3004) is determined, using Eq. 36: C gas Piquid liquid Paparente ^ M agpaasrente = a "" apparent CM gas a.parente CMaparente Ec.36 apparent Pigue liquid Pipante Then, the apparent superficial velocity of the gas (3006) is determined. Apparent surface velocity of the gas can be calculated by the volumetric flow rate of the liquid divided between the cross-sectional area of the flow tube At, as demonstrated above, and reproduced at this point, Eq. 1: VSgas = CMgas / (pgas * t> Ec. 1 Then, an apparent flow rate of the liquid (3008) can be determined. The apparent flow rate of the liquid can be derived from the apparent gross mass flow rate and the apparent gas void fraction, using Eq. 37: -i -i liquid '-' • '"apparent Eq. 37 Then, the apparent surface velocity of the liquid (3010) can be determined. To find the apparent surface velocity of the liquid, the volumetric flow rate of the liquid can be divided between the cross-sectional area of the At-flow tube, as demonstrated above and now reproduced in Eq. 2: VSiiqUi o = CMiiquido / (pliquido * At) Ec. 2 Then, an error index of the mass flow measurement of the liquid (3012) is determined. This error can be defined in the apparent mass flow rate of the liquid as a fraction of the true mass flow of the liquid, as shown in Eq. 38: rrsr (CM «. - Ec.38 This error of the fractional liquid flow of the liquid can be estimated as a function of the apparent surface fluxes of the liquid and apparent superficial gas flows (normalized) using a polynomial expression shown in Eq. 39, where the term eff error is shown indicating a Corrected error for the mass flow of the liquid: a ..a In 'gn V I, ma • x V v gmax 0 ° -n, a 0aX¿ + a? > XaYYaY «, n.,« 2, n? } a, n ,, »2,? a p Q ei -aiVgn -e + Cl6Vgn + Cí Vgn + CÍSVgn + a9Vln EC. OV In Eq. 39, due to the size of the expression (s), the following notation is used: vfn refers to the normalized apparent flow of the liquid (replacing "1" with "g" in the subscript for the corresponding gas parameter), where the normalization is based on, for example, one or several possible maximum flows, as indicated by vi max and Vg max. The corrected fluid mass flow measurement (3014) can be determined, using the Ees. 38 and 39, expressed at this point as Eq. 40 C- -LMyl cltoqrmredg ° ido Ec. 40 Then, the component and water cut densities (3016) can be determined, or it can be obtained using the techniques described above, it can be used to determine a correct oil flow rate and a correct water flow rate (3018). Then, using the corrected gross density and the corrected gas hole fraction (3020), the corrected gas flow can be determined (3022). For example, the mass flow rates of water and oil can be calculated using the E's. 41 and 42: Eq. 41 Eq. 42 Then, using the density of the corrected mixture (or fraction of holes of corrected gas), the mass flow rate of the gas can be determined using the Ees. 43 and 44: liquid gas corrected r "corrected liquid CM clioqruriedgoido Ec. 44 Pcorregida Pcorregida Pgas It should be understood that, based on the single-phase densities and their variation with temperature, it is possible to convert the mass fluxes into volumetric fluxes at a reference temperature. In some cases, there may be uncertainty in the polynomial adjustment to the error curves, where the effect of this uncertainty on the corrected mass flow is given by Eq. 45: f-t-rp T? ? - Eq. 45 helps explain why some data may exhibit serious errors when using correction algorithms outside of a tested region. For example, if the error calculated at a given flow rate is - 70%, but the true error is -75%, then the model error is only 5%, but the error in the corrected mass flow is: -0-7 + 0.75 1- 0.75 This calculation can also be used in 2-phase flow modeling results as described in the lines above, to consider the residual error resulting in the modeling. In one implementation, the least squares adjustment of the model can be modified in order to minimize the resulting mass flow error instead of the model error. In addition, speaking in general terms, it is expected that a flow tube exhibits small mass flow errors, so that if you anticipate that a flow tube will correct serious errors, then the modeling of the error (and therefore the experimental data) becomes relatively more important. Accordingly, as described above with respect to Figure 30, apparent surface velocities are employed to carry out mass flow corrections, in order to differentiate the correction of the gross density from the correction of the mass flow of the liquid. Figures 31A-31D are graphs illustrating the correction of a mass flow rate of a two-phase liquid in a three-phase flow. Figures 31A-31D show the predicted errors of mass flow of the liquid when the three-phase flow correction algorithm is applied to data obtained from four oil + water + gas tests using vertical orientations. Figures 31A-31D show that the basic correction curve operates within 5% for all but for the highest gas flows, which are outside the range of data used for modeling. Figure 32 is a graph showing a mass flow error as a function of the mass flow rate for oil and water. Figure 33 is a graph showing a gas gap fraction error as a function of the true gas gap fraction. Figures 32 and 33 illustrate the errors in the estimation of the three fractions of mass flow by means of the implementation of spreadsheet of the previous algorithms. It should be noted that the actual determination of the gas mass flow can be affected by the uncertainty in the density of the mixture and by a relative difference in the density between the liquid phase and the gas phase. Also, it should be understood that the polynomial for density correction discussed above may be more or less applicable depending on, for example, the orientation of the flow tube. As a result, for example, horizontal flow can produce a lower error than vertical flow, or vice versa. In the methodology described above, the use of superficial velocities of the liquid and gas can enable the correction algorithms to include knowledge of the multiphase flow regimes found, which can lead to better correction algorithms. The results on practical data indicate that the polynomial correction curves can benefit from being designed based on data that cover the expected flow ranges, and of being "cached" to avoid spurious results when exposed to data outside the known range. Although the implementations discussed in the above make use of an external water-cut meter or some similar technique, other implementations based on the external hole fraction sensor / meter (235) and / or others may be employed. input parameters. Additionally, as mentioned above, other devices may be used, such as those designed to determine an "oil cut", instead of a water cut. Also, if oil and water in a mixture have perfectly separated densities, a sampling system can be used that takes a representative sample of the mixture, degasses it, and uses a Coriolis meter to determine the water cut. As described, in the case of a biphasic flow of a single liquid, knowledge of the densities of the liquid and gas in the operating temperature and pressure can be used with the corrected mass flow and density measurements in order to calculate each one of the mass flows of liquid and gas, and, consequently, the volumetric flow of liquid and gas. In the case of the three-phase flow, in addition, external measurements can be used to enable the estimation of the mass flow of the gas and the mass flow of each of the liquids. In the case of a mixture of water and liquid oil, the water cut of the mixture upstream of the Coriolis type meter can be measured, as explained and illustrated above. In one implementation, it can be assumed that the two liquids do not interact in such a way as to invalidate the assumption that the mixture of the two liquids behaves as a single liquid as far as the interaction with the gas phase is concerned. This assumption converts the three-phase flow into an extension of the biphasic flow of a single liquid, additional measurements are used to determine the density of the mixed liquid, and to differentiate the mass flows from the separated liquids, then the biphasic flow calculations are applied. As also discussed above, a Coriolis type meter will usually take low readings of the mixture density as well as the mass flow rate of a liquid / gas mixture. To compensate for errors in these raw measurements and to estimate the values of the measurement, a model for the error surfaces can be used to find a mapping between gross density and mass flow measurements, and the value of the errors of the raw measurement, for the measurements of both the mass flow and the density, that is, to perform a data adjustment. As already noted, both the density curve and the mass flow curve may depend on many factors, such as the size of the meter, the orientation of the meter (for example, horizontal vs. vertical) and a mass flow. nominal of the liquid. Accordingly, corrections can be developed for each size-and orientation of the individual meter. In other implementations, the offsets can be scaled according to meter size, and / or they can be adjusted according to the alignment of the meter with respect to others. For example, Figure 24 illustrates error models that can be implemented using neural networks. Figure 34 shows a particular form of the neural network model, the perceptron by MLP (multi layer layer perceptron), with only two levels of specific values (3412), (3414) and hidden sigmoid units (3408), has been shown to be able to approximate any function of continuous mapping to an arbitrary accuracy (as long as the number of hidden units is large enough), also called the property of universality. This is intuitively supported by the idea that any reasonable functional mapping with arbitrary accuracy can be approximated by a linear superposition (performed by the activation functions of the output units) of a sufficiently large number of nonlinear functions (represented by the functions of activation of the hidden units). Furthermore, it is a direct-feed network (that is, there are no internal loops in the data flow of the input signals to the output signals), its output signals are deterministic functions of the input signals, which makes to the global network equivalent to a non-linear functional multivariate mapping. For the design of a flexible compensation technique, for biphasic flow errors or three-phase flow in a Coriolis type meter, neural network models have at least the following advantageous characteristics. For example, these types of models provide the ability to derive a non-linear functional mapping from a representative and large enough database of relevant measurements, without prior knowledge of the fundamental physical model of the process. Such a feature can be particularly advantageous in the example of the two-phase / three-phase flow compensation. In addition, the development time for a workable solution to a particular problem can be significantly reduced compared to other data adjustment techniques, which may be based on professional expertise in the area. For example, in the particular case of a two-phase flow compensation, changing the size / orientation / type of the meter should completely change the shape of the surface of the raw measurements, and for a conventional data technique, this can imply a process of finding another way for functional mapping that does not guarantee finding a solution in a reasonable time. On the contrary, when using a neural network architecture, the orientation of the neural network can find the "best" (in the sense of the cost function chosen to control the orientation of the network) for the available data by adjusting its parameters internal during the orientation process. The following discussion provides the explanation of an example of a neural network, that is, an MLP model. Specifically, Figure 34 is a graphic representation of the MLP model. To model error surfaces of raw measurements for density and mass flow, as discussed above, a functional mapping can be obtained by means of Error Measurement = F (dd, m), dd being the apparent decrease in density of the mixture and m the apparent mass flow of the liquid. It should be noted that this notation is slightly different from the previous notation for the same parameters, that is,? P and CM, respectively. Therefore, Figure 34 illustrates a multi-layer perceptron (MLP) model with two input signals (dd (3402) and m (3404)) and one output signal (Error Measurement (3406)). In Figure 35 the behavior of each unit is graphically represented. An output signal and (3510) of a unit can be obtained by applying an activation function f (3502) to the weighted sums (3504) of the input signals x (3506) of the unit n, to thereby define a unit function (3508), as shown in Figure 35 and in Eq. 46: In general terms, an MLP is a direct-feed neural network architecture with various unit levels. The term direct power means that the data flows monotonically from the inputs to the outputs, without internal loops; this ensures that the function of the output signals is deterministic. In order to ensure universality property, the MLP, used for the error compensation of the biphasic flow measurement, can be a two-tier architecture with sigmoid activation functions for the hidden units (3308) and the activation function linear for the output unit (3410). In this case, sigmoid activation function can be given by sig (d) = -, while it can be represent the linear activation function as lin (a) = a. Then, an output signal from the MLP used as a function of the input signals can be written as in Eq. 47: Error Measuring • = nh i S output signal ^ r? *? 1 _j. e-V »? dd + w2 m That is, Eq. 47 represents a non-linear function in an apparent decrease in the density and mass flow of the mixture, with nh being the number of hidden units (3408). The network parameters we21trada of ent ^ d * 1 of saiida and nh can be determined during a process called network orientation, essentially, an optimization of the cost function. As stated in the above, to ensure the property of universality, it must be large enough (in fact it stipulates the degree of freedom of the model, hence its complexity). However, its value must be chosen appropriately; a value that is too small would lead to a poor adjustment of the orientation data, while a value that is too large would lead to poor generalization capabilities due to an excessive adjustment of the orientation data (the parallel in the adjustment field of conventional polynomial data is the degree of the polynomial). There are several methods to choose the number of hidden units (3408). One technique is to perform an exhaustive search for nh (within reasonable limits) and choose the value for which the best generalization is achieved. The following describes the general outline of an implementation of an orientation process. The available data for guidance are divided into three independent sets: the orientation set (used to iteratively change the values of the MLP weights to minimize the cost function); the validation set (used to stop early orientation to avoid over-adjustment of guidance data); and the test set (used to choose the number of hidden units). In one implementation, the orientation of the network starts with an initial set of the weights of the r "Oedj .Wo -_ (/.w.signal of input o, wsignal of, and t s", u, c_e_s_i • "va__mQe_nJt_Qe lIa- , s, -, change to minimize a predefined cost function, for example, the average square error In each of these changes, the output signals of the MLP can be evaluated corresponding to the data in the orientation set, and they update the values of the weights according to a specific "learning rule", as is known in the field of neural network design, in order to mini- mize the value of the cost function in the orientation set. evaluate the cost function in the validation set, and the orientation stops when this starts to increase, so that an appropriate compromise can be made between the adjustment of the orientation data and the generalization capabilities. the excessive adjustment of the orientation stage to the convergence stage in the orientation set. If there is enough data available, a hidden unit test set can be used to choose the architecture that provides the minimum cost function in the test set. In the case of mass flow compensation, for an FHG region, the accuracy of the compensation can be increased if this area is considered separated from the rest and if it is modeled accordingly. This type of methodologies suggest the use of a "set of models", also called "mix of experts", with experience in different areas, but related, to allow smooth exchange between models. An example of this type of assembly, one used to compensate gross mass flow errors for a 2.54 cm (1 inch) flow tube in vertical alignment, is: Model 1: 0-1.5 kg / s, 0-15 % FHG Model 2: 0-1.2 kg / s, 0-15% FHG ascending Model 3: 1.2 kg / s ascending, 0-15% FHG Model 4: 1.2 kg / s ascending, 10% Upward FHG You can also target a different model, called an "interference model", using the full range of flows and FHG. The interference network can be used to provide a rough idea about the true mass flow of the liquid. Using this estimate together with estimated true FHG (based on the density compensation model), you can select a specific expert model (or a combination of two expert models if the data are in the overlap region), and your compensation can be applied. Figures 36A, 36B and 37A-D illustrate the results of two-phase flow data collected for a 2.54 cm Coriolis (! ") Type flowmeter, horizontal as well as vertical alignment, with water and air. Fifty-five flow lines were used, with nominal flow that fluctuated between 0.35 kg / s and 3.0 kg / s in increments of 0.025 kg / s, with typical FHG increments of 0.5% and 1% FHG (depending on the flow value). nominal), giving a total of 3400 experimental points, for an average of 45 points per flow line. The corresponding surfaces for mass flow and gross density errors are presented in Figures 36A and 36B, respectively. Based on this data, compensation solutions can be derived and validated online for liquid mass flow and density errors as described above, using independent test data, as shown in Figures 37A-37D. The input signals of the model for the compensation technique are the normalized surface velocity of the liquid CM alplqauriednote = (with notation in which At represents a v I, ma .xv I, max cross-sectional area of the flow tube and , v, max the maximum surface velocity of the liquid, and CM "give a mass flow rate of the liquid) and the apparent decrease in the density of the mixture." The test data in this example includes thirteen flow lines, with nominal flows. that fluctuated between 0.6 kg / s and 3 kg / s, in increments of 0.25 kg / s, with increases in FHG of 2%, given a total of 266 experimental points, an average of 20 points per flow line. 68 are graphs illustrating test results and / or modeling of various implementations described above with respect to Figures 1-37, or of related implementations More specifically, Figures 38-68, unless stated otherwise, they are graphics that r They show the results of tests of three phases in which the fluids used were crude oil with API 35 ° gravity, simulated brine (that is, mixture of salt and water) with 2% by weight of NaCl and nitrogen. The tests were carried out at a pressure of approximately 10,207 atmospheres (150 psig) and temperature of 37,778 ° C (100 ° F). In the following description and figures, reference is made to the following test conditions: TestOOca - 4000 bpd TestingOca - 6000 bpd TestOdd - 3000 bpd TestOdd - 4000 bpd Test06ca - 6000 bpd Test06ca - 8000 bpd Test3ca - 3000 bpd Test3ca - 6000 bpd Test25ca - 3000 bpd Test25ca - 7000 bpd Test35ca - 3000 bpd Test35ca - 7000 bpd Test50ca - 3000 bpd TestSOca - 5000 bpd Test50ca - 7000 bpd Test50ca - 8000 bpd In this context, Figures 38A and 38B illustrate an error induced in the gas originated by the mass density and mass flow measurements, respectively, of the Coriolis type meter. Figure 39 illustrates the observed response of the water cut meter used in these tests. For this particular device, the presence of free gas reduces the water cut observed compared to the true value (for the mixture of oil and gas-free water), decreasing monotonically as the fraction of gas voids increases. The response can also be a function of the total mass flow and the intrinsic water cut of the liquid phase, among other factors. For a level of the fraction of gas gaps determined (FHG), the observed water cut, in general terms, decreases as the total mass flow and the intrinsic water cut increases. Parameters, such as fluid properties and flow rate, can also affect the response surface of the water cut. Figures 40A-40C illustrate residual errors for water cut, mass flow, and bulk density measurements, after a modeling based on the neural network has been completed, based on the data sets shown in Figures 38A , 38B and 39, with water cuts that fluctuated between 0 and 50%. Mass bulk flow errors mostly remain within 2% of the reading, gross density errors are mostly within 1% of the reading, and water cut errors are mostly within of 2% of the range of the full scale 0-100%. Figure 41 illustrates how these results are mapped into corresponding volumetric flow errors for oil and gas streams. Note that for gas and water volumes, a low absolute volumetric flow (for water in low water cuts, and gas in low FHG) can lead to large percentage errors as a proportion of the reading. As the flow of oil can be significant in these tests, the errors in percentage terms remain mostly within 5%. Figures 42-47, the error corrections of density and mass flow are based on the oil data described above, with a water cut of 6% and a cut-off value of reference water of 5.5%. Since the same graphs are also based on this data, the predictions of density and mass flow errors are relatively small, which is not necessarily relevant to the demonstration of how water cut accuracy affects volumetric measurements. The Coriolis principle and related techniques, as described in the foregoing, provide estimates for an overall mass density or flow of the mixed three-phase fluid. The knowledge of the true densities of the fluids and (perhaps estimated or corrected) the water cut, together with the biphasic flow error models, provides estimation of the mass flow only for fluids and the fraction of gas holes (FHG) . Therefore, in Figures 42-47, final calculations are illustrated, in which, determining the mass flow only for fluids and the water cut, the volumetric mass flow rates of the oil and gas components are obtained, while the FHG produces the volumetric flow of the gas. Accordingly, Figures 42-44 illustrate the calculations of volumetric flow rates of water, oil and gas, respectively, assuming that the water cut is perfectly known. Under this assumption, the volumetric errors of water and oil are consistently small, being mainly dependent on the residual modeling errors for the corrections of density and mass flow, which, under the conditions, are small. The volumetric flow of the gas can be sensitive to errors in the calculation of density at low FHG. For example, with a FHG of 2%, an absolute error of 1% in the estimate of FHG can lead to a 50% error in the estimated volumetric flow of the gas. This type of large relative errors, in general terms, may be associated with relatively low gas flows, and, consequently, may unlikely be significant in oil and gas applications, such as, for example, the examples described in this description. Figures 45-47 illustrate the same calculations when the estimate of the water cut is at an error by + 1% absolute. This is a reasonable margin of error, which allows a basic measurement accuracy, followed by corrections for the effects of biphasic flows or three-phase flows. More specifically, Figure 45 illustrates the volumetric error in water with an absolute error of + 1% in the water cut. The medium large error is approximately 16%. With a true water cut of only 6% of the total volume of the liquid, an absolute error of 1% in the estimate of the water cut can produce an overestimation of approximately 16% of the water volumetric flow. Figure 46 illustrates that the corresponding errors for the volumetric flow of oil are much smaller, which is manifested in the lower impact than the 1% error in the water cut has on the oil cut measurement of 94%. Finally, Figure 47 illustrates the impact of the water cutoff error on the gas volume measurement. Therefore, it can be observed that the errors in the gas flow are sensitive to errors in the water cut in a low FHG, where this influence can decrease with higher FHG. Figures 49-50 are graphs illustrating a reading correction from a water cut meter (ie, the Phase Dynamics water cut meter) for induced gas errors. The data in Figures 48-50 are based on the petroleum data described above, with nominal water cutoff values of 0.0, 5.5, 13.1, 24.8, 35.6, and 50.0%. Although an actual water cutoff output is usually determined to be zero, the raw frequency data and characteristic equations associated with water cut meter operations allow for large water cut readings that fall below 0% , as shown. In this context, the water cut meter has an error even in 0% of FHG, due to the presence of residual amounts of gas "transported below" from the processes, as mentioned below (in absolute units of water cut) with respect to the specified test results mentioned above: TestingOca - 4000 bpd: -0.52 TestingOca - 6000 bpd: -1.91 TestingOdca - 3000 bpd: -0.89 Testing06ca - 4000 bpd: -0.74 TestingOdca - 6000 bpd: -1.53 TestOdd - 8000 bpd: -2.78 Pruebal3ca - 3000 bpd: 1.17 Pruebal3ca - 6000 bpd: 0.87 Test25ca - 3000 bpd: 0.91 Test25ca - 7000 bpd: -0.56 Test35ca - 3000 bpd: 0.74 Test35ca - 7000 bpd: -0.35 Test50ca - 3000 bpd: 3.89 Test50ca - 5000 bpd: 2.64 Test50ca - 7000 bpd: 2.90 Test50ca - 8000 bpd: 2.31 In order to correct the gas induced errors, the water cut meter was considered without error in 0% FHG (as in Figure 1). In Figures 48 and 49, a neural network, along the lines described above, was constructed with input signals of: reading of the raw water cut, reading of the true mass flow, and with the fraction of gas holes true The output signals include the error in the water cut (in absolute units of water cut - in this case, percentages). Therefore, successive calculations between this neural network and the mass flow / density corrections, as described above, lead to a common global solution. With the data as described, you can correct the reading of the water cut meter from errors as large as -40% to mainly within an absolute error of 2 percent, as shown in Figure 48, which , as mentioned above with respect to Figures 42-47, may have an impact on the corrections of water and oil for the Coriolis type meter. Figure 48 seems to illustrate that the neural network model does not correct some lines correctly, but a detailed study of the lines in question shows that the model is a uniform least-squares approximation of the experimental behavior, while the error data of the real water are not linear (for examples, see Figure 49). As with errors in density and mass flow, higher density data (ie, more experimental points) may provide improvement in the quality of the fit, and may also allow a good assessment of the experimental noise level. Figures 50-54 are graphs illustrating a successive correction of mass flow of liquid and gas and using the water cut correction, as described in general terms above with respect to figure 27. In figures 50-54, the data are based on the oil data as described above, with a nominal value of the water cut of 5.5%, while the corrections of mass flow and density employed in this stage are based on oil data with a water cut Of 6%. The water cut correction model (ie, the neural network model) used at this point is the one described above with respect to Figures 48 and 49. Water cutoff errors were previously described and shown in gross with respect to Figure 39, which shows the error in the cut of raw water, - as described above, however, for the rest of the flow analyzes, the reading of the water cut is limited within the interval of 0 and 100%, with the values outside the range being forced to take the limit value. Figures 50A and 50B illustrate mass flow errors and bulk mix density, respectively. Figures 51A-51C illustrate gross errors for the mass flows of water, oil and gas, respectively. Figure 52 illustrates a convergence after two repetitions of Figure 27, with the water cut measurement corrected within 3%, the blend density mainly within 1%, and the mass flow mainly within 2%. Figures 53A-53C illustrate the water cutting behavior corrected during the process. Water correction accuracies are illustrated in Figures 54A-54C, oil and gas, respectively. At this point, the mass flow of oil is corrected within 3%. In Figures 54A-54C, the mass flow of water is more affected, with an error of 2-3% water cut that produces an error +/- 40% in the mass flow of water. The error in the gas is high at a low FHG, falling to within 3% for FHG above 15%. As with errors in density and mass flow, higher density data (ie, more experimental points) may generally allow for improvement in the quality of the fit, and may also allow a better assessment of the experimental noise level. Figures 55-63 are graphs illustrating a "three-dimensional" correction for the mass flow of liquid and density, which takes into account variations in the error caused by variations in the water cutoff measurement (s). This technique can be used to obtain acceptable errors over a wider range of water cuts (unlike the previous examples, in which the reported flow data are generally limited to approximately 6% water cut). Therefore, in order to consider this type of variations in mass flow and density errors that are caused by variations in the water cut measurement (s), Figures 55-63 illustrate the use of a true water cut reading as an additional input signal parameter, together with the apparent decrease in bulk density and apparent mass flow. The data are based on the oil data discussed above, but with nominal water cutoff values of 0, 5.5, 13.1, 24.8, 35.6, and 49%. The distribution of the flow lines by nominal water cut is as follows: 0% 4000 and 6000 bpd O • O * d "3000, 4000, 6000 and 8000 bpd 13.1% 3000 and 6000 bpd 24.8% 3000 and 7000- bpd 35.6% 3000 and 7000 bpd 49% 3000, 5000, 7000 and 8000 bpd Figures 55A and 55B illustrate mix density errors of the raw fluid and mass flow, respectively. Figures 56-61 illustrate mass flow errors of residual fluid mixture after the "6% water cut" model previously used is applied. It is evident that while some of the errors (especially for the same water cutoff data of 6%, Figure 57) are small, at higher levels of water cut residual errors increase. Similar trends are observed for residual density errors using water cut data of 6 as the model.

Improved models for mix density and mass flow errors were assimilated using the true water cutoff value as an additional input signal. The accuracy of the resulting corrections in the orientation data is presented in Figures 62 and 63. The residual errors are greater than for a model based on a single water cut (mass flow within 5% instead of 2%, density within 2% instead of 1%). However, the model covers a good range of water cut readings instead of a single value, and presents a potential improvement over the faulty errors in Figures 56-61. The errors described can be reduced by having more data points . For example, for most water cuts there were only two flow lines. The number of data points in the set may be insufficient to be able to identify outliers. With higher and better data quality, smaller errors in the mass flow and density may even be possible, even allowing a range of water cutoff values to be possible. Figures 64-68 are graphs illustrating results of entering the three-dimensional density and liquid mass flow correction of Figures 55-63 in the process described above with respect to Figures 50 and 54 and Figure 27. successive generations of water cut, you can show corrections of the density and mass flow, volumetric errors that original use of this model and the error model in the water cut. Therefore, Figures 64-68 illustrate results of successive water, liquid (s), and gas mass flow correction corrections using the mass flow and density corrections that take into account the variations caused by the cutoff. of water. The final results are calculations of volumetric flows of oil, water and gas, since they can be used by, for example, the oil or gas industry. These illustrated calculations represent a "complete" assembly, suitable for continuous applications in the oil industry. The data are based on oil data as described above, with nominal water cutoff values of 0.55, 13.1, 24.8, 35.6 and 49%. The corrections of water cut, density and mass flow used are based on a whole set of data determined for the water cut range from 0 to 50%. The water cut correction model employed is the same as the one discussed above with respect to Figures 42-49. As already stated, the procedure used is as described with respect to Figures 27 and 50-54, but the corrections of density and mass flow employed take into account the variations of the water cut. The density correction and mass flow models used are those discussed above with respect to Figures 55-63. Figure 39, above, illustrates the raw errors of the water cut meter and induced errors of raw gas. Figures 64A, 64B, 65A, 65B and 65C show the induced gas error of mass flow and density, and the gross error in water, oil and gas, respectively. With the available data it is possible to converge in successive calculations, with the corrected water cut measurement within 5%, the mixing density mainly within 2% and the mass flow mainly within 5%, as shown in Figure 66A-66C. The correction accuracies for water, oil and gas achieved after successive calculations are shown in Figures 67A-67C. The mass flow of oil is corrected mainly within 5%. The volumetric flow of water is more affected, with an error of 2-3% in the water cut that produces an error of +/- 40% in the volumetric flow of water. The gas error is high at a low FHG, as expected, down to mainly within 5% for FHG above 15%. Figure 68 illustrates an example of corrected water cutting behavior during the process (s). As with density and mass flow errors, higher density data (ie, more experimental points) may allow improvements in the quality of the adjustment, and may also enable a better assessment of the experimental noise level. A set of analysis tools and correction algorithms has been illustrated that, by determining appropriate data for oil, water and gas used in a specific application, can compensate for the gas induced errors in the water cut-off and meter type readings Coriolis, with which it obtains volumetric flow of gas, water and oil. As described above, a mass flow meter may be capable of being maintained in operation in the presence of a high percentage of gas in a measured flow, both with a single liquid and with a mixed liquid (i.e., in a two-phase flow or a three-phase flow). Therefore, estimates and / or apparent measurements of the density and mass flow of the liquid and gas mixture can be obtained. However, these estimates have errors that depend on several factors, including the fraction of gas voids and / or the true mass flow of liquid, which can be large enough to make the raw measurements useless. By using an additional measurement parameter, such as a water cut measurement or gas hole fraction, together with measurements of bulk density and apparent mass flow, corrected values can be obtained for all these parameters and for others. Furthermore, by iterating through these parameters and calculations with increasingly improved corrections, successively improved values can be obtained, such as, for example, the correction that converge on specific values. As described above, the techniques for making these corrections can be based on data adjustment techniques that seek to determine, for example, errors in a particular configuration or arrangement, so that these errors can be taken into account by measurements and future corrections. Thus, these techniques may be dependent on some degree of correlation between the arrangements / configurations in which the data is associated, and on the arrangements / configurations in which they finally apply these techniques. Techniques can be used relationships or other correction techniques that seek to characterize the fluid flow (s) in a more general sense, that is, using fluid flow equations that seek to describe a flow behavior as a physical aspect. For example, in this sense, the well-known Navier-Stokes equations can be used. Specifically, the three-dimensional unstable form of the Navier-Stokes equations describes how the velocity, pressure, temperature, and density of a fluid in motion are related. The equations are a set of associated differential equations and can be solved, in theory, for a given flow problem using calculation methods, or they can be solved analytically, perhaps using certain simplifications or adjustments that can be determined to help and be applied in a certain circumstance. These equations and related equations can be considered, for example, a property of convection (a physical process that happens in a gas flow in which some property is transported by the orderly movement of the flow) and / or a property of diffusion (a physical process that happens in a flow of gas in which it transports some property by means of the random movement of the molecules of the gas, and that can be related to the viscosity the gas). The turbulence and the generation of boundary layers are the result of diffusion in the flow. Using this type of equations and fluid flow characteristics, correction techniques can be obtained for many of the parameters and techniques, even for all, which were discussed in the foregoing. For example, this type of fluid flow equations can be used in the definition of a general correction model, which can be complemented with data fitting techniques, such as those described above or vice versa. A variety of implementations have been described. However, it will be understood that several modifications can be made. Accordingly, other implementations are within the scope of the following claims.

Claims (35)

1. CLAIMS: 1. A system comprising a controller that can be operated to receive a sensor signal from a first sensor connected to a vibrating flow tube containing a three-phase fluid flow that includes a first liquid, a second liquid and a gas, the controller can also be operated to analyze the sensor signal to determine an apparent flow parameter of the fluid flow; a second sensor that can be operated to determine an apparent flow condition of the fluid flow; and a correction module that can be operated to admit the apparent flow parameter and the apparent flow condition and determine a corrected flow parameter from them. The system according to claim 1, wherein the correction module can be further operated to admit the apparent flow parameter and the apparent flow condition, and to determine a corrected flow parameter. The system according to claim 1, wherein the apparent flow parameter includes an apparent bulk density of the fluid flow. The system according to claim 1, wherein the apparent flow parameter includes an apparent gross mass flow rate of the fluid flow. The system according to claim 1, wherein the second sensor 'includes a liquid fraction meter that can be operated to determine a liquid fraction measurement that identifies a volume fraction of the first liquid with respect to the second liquid. The system according to claim 1, wherein the second sensor includes a hole fraction determination system which can be operated to determine a fraction of gaps of the gas within the fluid flow. The system according to claim 1, further comprises a system for determining the flow rate of components that can be operated to determine a flow rate of the first liquid within the fluid flow. The system according to claim 7, wherein the system for determining the flow rate of components in the controller, the correction module, the second sensor, or in a server computer in communication with the controller, the correction module is implemented. or with the second sensor. 9. The system according to claim 1 further comprises a system for determining the flow rate of components that can be operated to determine a flow rate of the gas within the fluid flow. 10. The system according to claim 1, wherein the implementation of the corrections module is associated with a controller process. The system according to claim 1, wherein the implementation of the corrections module is associated with a process of the second sensor. The system according to claim 1, comprising a 'server computer which is in communication with the controller or with the second sensor and which can be operated to implement the corrections module. The system according to claim 1, wherein the second sensor can be operated to send a first value of the apparent flow condition to the controller for use in the determination of a first value of the corrected flow parameter; the controller can be operated to send the first value of the corrected flow parameter to the second sensor for the determination of a first value of the corrected flow condition; and the second sensor can be operated to send a second value of the corrected flow condition to the controller for use in determining the corrected value of the flow parameter. The system according to claim 1, wherein the correction module includes a neural network that can be operated to support the apparent flow parameter and the apparent flow condition and produce the corrected flow parameter and a corrected flow condition. The system according to claim 14, wherein the neural network includes a first correction model that is specific to a type of the second sensor and to a flow condition and that can be operated to produce a corrected flow condition; and a second correction model that is specific to a type of apparent flow parameter and that can be operated to produce the corrected flow parameter; where the first correction model can be operated to correct the apparent flow condition based on the apparent flow condition and the corrected flow parameter, and the second correction model can be operated to correct the apparent flow parameter based on in the apparent flow parameter and the corrected flow condition. The system according to claim 1, wherein the controller can be operated to correct the apparent flow parameter based on a theoretical relationship between the apparent flow parameter and the corrected flow parameter. The system according to claim 1, wherein the controller can be operated to correct the apparent flow parameter based on an empirical relationship between the apparent flow parameter and the corrected flow parameter. 18. The system according to claim 1, further comprising a conduit connecting the second sensor and the vibrating flow tube, so that the flow of fluid flows through the second sensor, the tube and the vibrating flow tube. The system according to claim 18, wherein the first liquid, the second liquid and the gas are intermixed with each other within the fluid flow during the determination of the flow condition by the second sensor. 20. A method comprising determining an apparent gross density of a multiphase flow through the flow tube, the multiphase flow includes a first liquid, a second liquid and a gas; determine an apparent gross mass flow rate of the multiphase flow; and determining a first mass flow rate of the first liquid, based on apparent gross density and gross apparent mass flow rate. The method according to claim 20 which comprises determining an apparent flow condition of the multiphase flow apart from the apparent bulk density and apparent gross mass flow rate, wherein the action of determining the first mass flow rate of the first liquid comprises the action of determining the first mass flow rate based on the apparent flow condition. 22. The method according to claim 21, wherein the action of determining the first mass flow rate of the first liquid comprises the action of determining a corrected flow condition, based on the apparent flow condition. 23. The method according to claim 22, wherein the action of determining the corrected flow condition comprises the action of determining a corrected gross density and a corrected gross mass flow rate. The method according to claim 21, wherein the action of determining the apparent flow condition comprises the action of determining an apparent liquid fraction measurement of a volumetric fraction of the first liquid within the multiphase flow. 25. The method according to claim 21, wherein the action of determining the apparent flow condition comprises the action of determining a fraction of apparent gas gaps of the gas within the multiphase flow. 26. The method according to claim 21, wherein the action of determining the first mass flow rate of the first liquid comprises determining a corrected gross density, based on the apparent gross density; and determine a corrected gross mass flow, based on apparent mass flow. 27. The method according to claim 26, wherein the action of determining the corrected gross density and the action of determining the gross mass flow comprises the action of determining a corrected flow condition, based on the apparent flow condition. 28. A flow meter comprising a vibrating flow tube containing a three-phase flow including a first liquid, a second liquid and a gas; an impeller connected to the flow tube and operable to impart movement to the flow tube; a sensor connected to the flow tube and that can be operated to detect the movement of the flow tube and to generate a sensor signal; and a controller connected to receive the sensor signal and to determine a first flow rate of a first phase within the three-phase flow through the flow tube, based on the sensor signal. 29. A method for improving an output signal of a flow meter; the method comprises determining an apparent gross density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid, a second liquid and a gas; determine an apparent gross mass flow rate of the multiphase flow; determine an apparent flow condition of the multiphase flow; and correct apparent gross density or apparent mass flow, based on gross apparent density, apparent mass flow and apparent flow condition. 30. A method for improving an output signal of a liquid fraction meter; the method comprises determining an apparent gross density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid, a second liquid and a gas; determine an apparent gross mass flow rate of the multiphase flow; determine an apparent liquid fraction of the first liquid within the multiphase flow; and correct the apparent liquid fraction to obtain a corrected liquid fraction, based on apparent gross density, apparent mass flow rate and apparent liquid fraction. 31. The method according to claim 30 comprising the action of determining a gas void fraction of the gas within the multiphase flow based on the apparent gross density, the apparent mass flow rate and the corrected liquid fraction. 32. A method to obtain a measurement of the fraction of gas voids; the method comprises determining an apparent gross density of a multiphase flow through a flow tube, the multiphase flow includes a first liquid, a second liquid and a gas; determine an apparent gross mass flow rate of the multiphase flow; determine a fraction of apparent gas gaps in the gas within the multiphase flow; and correcting the fraction of apparent gas voids to obtain a corrected gas void fraction, based on apparent gross density, apparent mass flow rate and apparent gas void fraction. 33. The method according to claim 32 comprising the action of determining a liquid fraction of the first liquid within the multiphase flow based on the apparent gross density, the apparent mass flow rate and the corrected gas void fraction. 34. A system comprising a conduit having a flow of fluid therethrough, the fluid flow includes at least a first liquid component, a second liquid component and a gas component; a tube of vibrating flow in series with the conduit and having the flow of fluid through itself; a first sensor that can be operated to determine a first apparent property of the fluid flow through the conduit; a second sensor connected to the flow tube and which can be operated to capture the information about a 'flow of the flow tube; a controller connected to the flow tube and operable to impart power to the flow tube; a control and measurement system that can be operated to measure a second apparent property and a third apparent property of the fluid flow; and a correction system that can be operated to determine a corrected first property, a corrected second property, and a corrected third property, based on the first apparent property, the second apparent property, and the third apparent property. 35. A system comprising a controller that can be operated to determine a first apparent property of a fluid flow in which a first liquid, second liquid and a gas are intermixed; a meter that can be operated to measure a second apparent property of the fluid flow; and a correction module that can be operated to admit a first apparent property and produce a corrected first property, wherein the meter can be operated to admit the first corrected property and the second apparent property and produce a second corrected property.