US20130082010A1 - Tank dewatering sensing and valve control method and apparatus - Google Patents

Tank dewatering sensing and valve control method and apparatus Download PDF

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Publication number
US20130082010A1
US20130082010A1 US13/628,305 US201213628305A US2013082010A1 US 20130082010 A1 US20130082010 A1 US 20130082010A1 US 201213628305 A US201213628305 A US 201213628305A US 2013082010 A1 US2013082010 A1 US 2013082010A1
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Prior art keywords
pipe
water
crude oil
valve
conductivity
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US13/628,305
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Inventor
Khalid Abdulaziz Al-Mulhim
Salem Mohammed Al-Qahtani
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Saudi Arabian Oil Co
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Saudi Arabian Oil Co
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Priority to US13/628,305 priority Critical patent/US20130082010A1/en
Publication of US20130082010A1 publication Critical patent/US20130082010A1/en
Assigned to SAUDI ARABIAN OIL COMPANY reassignment SAUDI ARABIAN OIL COMPANY ASSIGNMENT OF ASSIGNORS INTEREST (SEE DOCUMENT FOR DETAILS). Assignors: AL-MULHIM, KHALID ABDULAZIZ, AL-QAHTANI, SALEM MOHAMMED
Priority to US15/957,094 priority patent/US10344221B2/en
Abandoned legal-status Critical Current

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    • CCHEMISTRY; METALLURGY
    • C10PETROLEUM, GAS OR COKE INDUSTRIES; TECHNICAL GASES CONTAINING CARBON MONOXIDE; FUELS; LUBRICANTS; PEAT
    • C10GCRACKING HYDROCARBON OILS; PRODUCTION OF LIQUID HYDROCARBON MIXTURES, e.g. BY DESTRUCTIVE HYDROGENATION, OLIGOMERISATION, POLYMERISATION; RECOVERY OF HYDROCARBON OILS FROM OIL-SHALE, OIL-SAND, OR GASES; REFINING MIXTURES MAINLY CONSISTING OF HYDROCARBONS; REFORMING OF NAPHTHA; MINERAL WAXES
    • C10G33/00Dewatering or demulsification of hydrocarbon oils
    • C10G33/08Controlling or regulating
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B01PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01DSEPARATION
    • B01D17/00Separation of liquids, not provided for elsewhere, e.g. by thermal diffusion
    • B01D17/02Separation of non-miscible liquids
    • B01D17/0208Separation of non-miscible liquids by sedimentation
    • BPERFORMING OPERATIONS; TRANSPORTING
    • B01PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01DSEPARATION
    • B01D17/00Separation of liquids, not provided for elsewhere, e.g. by thermal diffusion
    • B01D17/12Auxiliary equipment particularly adapted for use with liquid-separating apparatus, e.g. control circuits
    • EFIXED CONSTRUCTIONS
    • E21EARTH OR ROCK DRILLING; MINING
    • E21BEARTH OR ROCK DRILLING; OBTAINING OIL, GAS, WATER, SOLUBLE OR MELTABLE MATERIALS OR A SLURRY OF MINERALS FROM WELLS
    • E21B43/00Methods or apparatus for obtaining oil, gas, water, soluble or meltable materials or a slurry of minerals from wells
    • E21B43/34Arrangements for separating materials produced by the well

Definitions

  • the present invention relates generally to dewatering a bulk-storage tank and, in particular, to a method and apparatus for detecting water-to-crude oil transition in a pipe.
  • Unrefined crude oil stored in a bulk-storage tank has a percentage of water entrained within the oil. Such crude oil is typically pumped into a bulk-storage tank prior to shipment.
  • the capacity of bulk-storage tanks vary, but may be one-hundred (100) million barrels (i.e., 15.9 giga-litres).
  • the water and oil stored in a tank separate naturally, with the water collecting at the bottom of the tank beneath the oil.
  • the separated water and the crude oil within the tank are very distinct except for a “black water” or “rag” interface layer.
  • the black water interface layer is an emulsion of mixed oil and water.
  • the crude oil stored in a bulk-storage tank Prior to transferring the crude oil to a bulk carrier for shipment, the crude oil stored in a bulk-storage tank requires dewatering (i.e., removing the water from the tank).
  • dewatering i.e., removing the water from the tank.
  • the oil within a bulk-storage tank is dewatered by manually opening an outlet valve at the base of the bulk-storage tank and allowing any contained liquid to run through a pipe to a containment area.
  • the liquid running through the pipe is initially water.
  • An operator periodically checks the liquid, using a siphon point, to see if the liquid is water or oil.
  • the siphon point may be in the form of a domestic tap attached to the pipe.
  • the operator closes the outlet valve on the bulk-storage tank to stop the flow of liquid.
  • a conventional definition of “transition from water to crude oil” is when a ratio of water to crude oil in the liquid reaches 20:80 (i.e., 20% water: 80% crude oil).
  • the remaining liquid in the tank, which is primarily crude oil, may then be transferred by a separate pipe to a transport system such as a shipping delivery system.
  • oil is sent to the containment area where the oil is trapped in a mixture of oil and waste-water.
  • the oil may be recovered from the waste-water using conventional water processing methods. However, recovering the oil from the containment area is an expensive exercise.
  • the dewatering of a bulk-storage tank as described above often takes place in open air in extreme environmental conditions such as heat, wind, sand storms, and rain.
  • the reliability and accuracy of such a dewatering method is subject to the diligence of the operators.
  • the decision point for closure of the outlet valve at the transition of the liquid from water to oil is a subjective judgement and open to vary from one operator to another.
  • An ILDT comprises a tuning fork which is immersed within a pipe in the liquid being measured.
  • the tuning fork is excited into oscillation by a piezoelectric device (not shown) internally secured at the root of one tine.
  • the frequency of the vibration of the tuning fork is detected by a second piezoelectric device secured in the root of the other tine of the tuning fork.
  • the tuning fork is maintained at its natural resonant frequency, as modified by the surrounding liquid, by an amplifier circuit which may be located in an electronic housing.
  • This frequency of vibration is a function of the overall mass of the tine element and the density of the liquid in contact with the tine element. As the density of the liquid changes, the overall vibrating mass changes together with the resonant frequency. By measuring the resonant frequency the density of the liquid can be determined.
  • a density sensor may be in the form of a tube densitometer. A tube densitometer works in a similar manner to the ILDT discussed above.
  • the density measurements determined using such density sensors may be used to determine if the transition between water and oil has occurred.
  • Tables 3 and 4 of Appendix C show the density of water and crude oil.
  • density sensors such as those discussed above are not suitable for use with any liquid of unpredictable or erosive nature which can damage the tines causing erratic results. Further, such density sensors require complicated fitting within a pipe in order to perform the sampling. Still further such density sensors are prone to fouling when sampling particularly viscous liquids such as crude oil.
  • the present application discloses arrangements which seek to address the prior art problems by measuring one or more properties of liquid flowing within a pipe in order to detect water to oil transition.
  • One object of the present invention is to provide a method of detecting water to oil transition of liquid flowing in a pipe, said method comprising the steps of:
  • Another object further to the above comprises the step of determining whether the liquid is flowing in a laminar or turbulent manner depending on the comparison.
  • Another object further to the above comprises the step of determining electrical conductivity of the liquid.
  • Another object further to the above comprises the step of measuring vibrations in the pipe caused by turbulence of fluid flow in the pipe.
  • Another object further the above comprises the steps of opening a valve to allow outflow of water from a storage tank, and later closing said valve in order to stop the liquid flowing out of the tank if the transition from water to oil has occurred at the predetermined point.
  • Another object is to provide an apparatus for detecting water to oil transition of liquid flowing in a pipe, said apparatus comprising:
  • measuring means for measuring the sound pressure level produced by the liquid flowing at a predetermined point within the pipe
  • a processor for comparing the measured sound pressure level to a predetermined threshold value stored in a computer readable memory, and for detecting if the liquid flowing in the pipe at the predetermined point has transitioned from water to crude oil based on a result of the comparison.
  • Another object is to provide a computer readable storage medium, having a program recorded thereon, where the program is configured to make a computer execute a procedure to detect water to oil transition of liquid flowing in a pipe, said apparatus comprising:
  • Another object is to provide a method of detecting water to oil transition of liquid flowing in a pipe, said method comprising the steps of:
  • Another object further to the above method comprises the step of determining whether the liquid is flowing in a laminar or turbulent manner depending on the comparison.
  • Another object further to the above method comprises the step of determining sound pressure level of the liquid.
  • Another object further to the above method comprises steps of opening a valve to allow outflow of water from a storage tank, and later closing said valve in order to stop the liquid flowing out of the tank if the transition from water to oil has occurred at the predetermined point.
  • Another object is to provide an apparatus for detecting water to oil transition of liquid flowing in a pipe, said apparatus comprising:
  • measuring means for measuring electrical conductivity of the liquid flowing at a predetermined point within the pipe
  • a processor for comparing the measured conductivity to a predetermined threshold value stored in a computer readable memory, and for detecting if the liquid flowing in the pipe at the predetermined point has transitioned from water to crude oil based on a result of the comparison.
  • Another object is to provide a computer readable storage medium, having a program recorded thereon, where the program is configured to make a computer execute a procedure to detect water to oil transition of liquid flowing in a pipe, said apparatus comprising:
  • Another object is to provide a method of detecting water to oil transition of liquid flowing in a pipe, said method comprising the steps of:
  • FIG. 1 shows a system for dewatering crude oil stored in a bulk-storage tank
  • FIG. 2A is a schematic block diagram of an electronic device of the system of FIG. 1 ;
  • FIG. 2B is a schematic block diagram of a computer system used in the system of FIG. 1 ;
  • FIG. 3 is a flow diagram showing a method of dewatering the bulk-storage tank of FIG. 1 ;
  • FIG. 4 is a flow diagram showing a method of detecting water to crude oil transition in a pipe of the system of FIG. 1 ;
  • FIG. 5 is a flow diagram showing another method of detecting water to crude oil transition in a pipe of the system of FIG. 1 ;
  • FIG. 6 shows a fast Fourier transform (FFT) waterfall trace simulating the flow of water through the pipe of the system of FIG. 1 ;
  • FFT fast Fourier transform
  • FIG. 7 shows a fast Fourier transform (FFT) waterfall trace simulating the flow of crude oil through the pipe of the system of FIG. 1 ;
  • FFT fast Fourier transform
  • FIG. 8 shows an alternative system for dewatering the bulk-storage tank of FIG. 1 ;
  • FIG. 9 is a graph showing sound pressure level (SPL) versus time, in accordance with a dewatering example
  • FIG. 10 is a graph showing sound pressure level (SPL) versus time, in accordance with a dewatering example.
  • FIG. 11 is a graph showing conductivity versus time, in accordance with a dewatering example.
  • Appendix A is a table showing kinematic viscosity of water and crude oil
  • Appendix B is a table showing conductivity information for water and crude oil
  • Appendix C is a table showing density information for water and crude oil.
  • FIG. 1 shows a system 100 for dewatering a bulk-storage tank 101 .
  • the system 100 comprises two motorised valves 102 and 103 .
  • the valve 102 controls flow of liquid through a pipe 104 connecting the base of the tank 101 to a containment system 105 .
  • the valve 103 controls flow of liquid through another pipe 106 connecting the base of the tank 101 to a shipping (or transport) system 107 .
  • a measuring means in the form of an acoustic sensor array 109 is fixed at a predetermined point to the outside of the pipe 104 .
  • the acoustic sensor array 109 comprises two sensors (not shown) that output a voltage (e.g., 0-10 Volts) according to average sound pressure level (SPL) detected by the sensors of the acoustic sensor array 109 .
  • SPL average sound pressure level
  • Another measuring means in the form of a conductivity sensor 108 , is fixed at a further predetermined point to the outside of the pipe 104 .
  • the conductivity sensor 108 is an inductive, non-contact type sensor that outputs a current (0-20 mA) according to the average conductivity level detected.
  • system 100 is described as comprising both the acoustic sensor array 109 and the conductivity sensor 108 , in other implementations the system 100 may comprise one of either the acoustic sensor array 109 or the conductivity sensor 108 .
  • the system 100 is controlled by an electronic device 151 which is electrically connected to the valves 102 , 103 .
  • the device 151 is also connected to the conductivity sensor 108 and the acoustic sensor array 109 as seen in FIGS. 1 and 2A .
  • the device 151 may be a programmable logic controller (PLC). Such a PLC may be electrically connected to the conductivity sensor 108 and the acoustic sensor array 109 , via corresponding controllers for processing signals from the corresponding sensor 108 and array 109 .
  • PLC programmable logic controller
  • the system 100 uses the acoustic sensor array 109 to measure liquid turbulence inside the pipe 104 in order to detect water to crude oil transition.
  • the system 100 uses the conductivity sensor 108 to measure the conductivity of the liquid inside the pipe 104 in order to detect water to crude oil transition. Accordingly, the conductivity sensor 108 and/or the acoustic sensor array 109 provide a non-invasive method of detecting the transition of water to crude oil in the pipe 104 .
  • the device 151 is also connected to a computer system 200 (or computer), via a local computer network 222 (known as a Local Area Network (LAN)).
  • LAN Local Area Network
  • the computer system is seen in detail in FIG. 2B .
  • the computer system 200 allows an operator to activate or de-activate dewatering remotely using one or more controls displayed on a graphical user interface (GUI) represented on a display 214 of the computer system 200 , as will be described below.
  • GUI graphical user interface
  • the computer system 200 communicates directly with the device 151 which controls the valves 102 and 103 .
  • the system 100 increases the consistency of detecting the transition of water to crude oil in the pipe 104 and removes the dependence of such detection on a human operator.
  • the system 100 reduces demand on the containment system 105 to deal with oil overspill due to late termination of dewatering.
  • the system 100 allows dewatering to be performed remotely from the bulk-storage tank 101 , using the computer system 200 , by providing an alert when a specified ratio of water to crude oil (e.g., 20:80) has been reached in the pipe 104 .
  • the device 151 comprises an embedded controller 152 . Accordingly, the device 151 may be referred to as an “embedded device.”
  • the controller 152 comprises a processing unit (or processor) 155 which is bi-directionally coupled to an internal storage module 159 .
  • the storage module 159 may be formed from non-volatile semiconductor read only memory (ROM) and semiconductor random access memory (RAM).
  • the RAM may be volatile, non-volatile or a combination of volatile and non-volatile memory.
  • the embedded device 151 may comprise an indication means 165 in form of a liquid crystal display (LCD) panel and/or light emitting diodes (LEDs) or the like.
  • the embedded device 151 also comprises user input devices 153 which are typically formed by a keypad or like controls.
  • the embedded device 151 also comprises a portable memory interface 156 which is coupled to the processor 155 via a connection 119 .
  • the portable memory interface 156 allows a complementary portable memory device 175 to be coupled to the embedded device 151 .
  • the portable memory device 175 may act as a source or destination of data or to supplement the internal storage module 159 . Examples of such interfaces which permit coupling with portable memory devices such as Universal Serial Bus (USB) RAM, Secure Digital (SD) cards, Personal Computer Memory Card International Association (PCMIA) cards, optical disks and magnetic disks.
  • USB Universal Serial Bus
  • SD Secure Digital
  • PCMIA Personal Computer Memory Card International Association
  • the embedded device 151 also comprises a communications interface 158 to permit coupling of the embedded device 151 to the local computer network 222 via a connection 223 .
  • the connection 223 may be wired or wireless, such as radio frequency or optical.
  • An example of a wired connection includes USB.
  • an example of wireless connection includes BluetoothTM type local interconnection, WiFi (e.g., the IEEE802 family, Infrared Data Association (IrDa)) and the like.
  • the embedded device 151 also includes an input/output (I/O) interface 160 for communicating with the conductivity sensor 108 and the acoustic sensor array 109 , as seen in FIG. 2A .
  • the embedded device 151 also communicates with the valves 102 and 103 via the I/O interface 160 .
  • the methods described below may be implemented using the embedded controller 152 wherein the processes of FIGS. 3 to 10 , to be described, may be implemented as one or more software application programs 133 executable within the embedded controller 152 .
  • the embedded device 151 effects an advantageous apparatus for implementing the described methods.
  • the steps of the described methods are effected by instructions in the software 133 that are carried out within the controller 152 .
  • the software instructions may be formed as one or more code modules, each for performing one or more particular tasks.
  • the software 133 is generally loaded into the controller 152 from a computer readable medium, and is then typically stored in the internal storage module 159 , as illustrated in FIG. 2A , after which the software 133 can be executed by the processor 155 .
  • the application program 133 is typically pre-installed and stored in the ROM by a manufacturer prior to distribution of the embedded device 151 .
  • the software 133 may be supplied to the user encoded on one or more CD-ROM (not shown) and read via the portable memory interface 156 prior to storage in the internal storage module 159 or in the portable memory 175 .
  • the software 133 may be read by the processor 155 from the network 222 or loaded into the controller 152 or the portable storage medium 175 from other computer readable media.
  • Computer readable storage media refers to any storage medium that participates in providing instructions and/or data to the controller 152 for execution and/or processing. Examples of such storage media include floppy disks, magnetic tape, CD-ROM, a hard disk drive, a ROM or integrated circuit, USB memory, a magneto-optical disk, flash memory, or a computer readable card such as a PCMCIA card and the like, whether or not such devices are internal or external of the device 151 .
  • Examples of computer readable transmission media that may also participate in the provision of software, application programs, instructions and/or data to the device 151 include radio or infra-red transmission channels as well as a network connection to another computer or networked device, and the Internet or Intranets including e-mail transmissions and information recorded on Websites and the like.
  • a computer readable medium having such software or computer program recorded on it is a computer program product.
  • the computer system 200 is formed by a computer module 201 , input devices such as a keyboard 202 and a mouse pointer device 203 , and output devices including a printer 215 , a display device 214 and loudspeakers 217 .
  • An external Modulator-Demodulator (Modem) transceiver device 216 may be used by the computer module 201 for communicating to and from a computer network 220 via a connection 221 .
  • the network 220 may be a wide-area network (WAN), such as the Internet or a private WAN.
  • the modem 216 may be a traditional “dial-up” modem.
  • the modem 216 may be a broadband modem.
  • a wireless modem may also be used for wireless connection to the network 220 .
  • the computer module 201 typically includes at least one processor unit 205 , and a memory unit 206 for example formed from semiconductor random access memory (RAM) and read only memory (ROM).
  • the module 201 also includes an number of input/output (I/O) interfaces including an audio-video interface 207 that couples to the video display 214 and loudspeakers 217 , an I/O interface 213 for the keyboard 202 and mouse 203 and optionally a joystick (not illustrated), and an interface 208 for the external modem 216 and printer 215 .
  • the modem 216 may be incorporated within the computer module 201 , for example within the interface 208 .
  • the computer module 201 also has a local network interface 211 which, via a connection 225 , permits coupling of the computer system 200 to the local computer network 222 .
  • the interface 211 may be formed by an EthernetTM circuit card, a wireless BluetoothTM or an IEEE 802.11 wireless arrangement.
  • the interfaces 208 and 213 may afford both serial and parallel connectivity, the former typically being implemented according to the Universal Serial Bus (USB) standards and having corresponding USB connectors (not illustrated).
  • Storage devices 209 are provided and typically include a hard disk drive (HDD) 210 .
  • HDD hard disk drive
  • Other devices such as a floppy disk drive and a magnetic tape drive (not illustrated) may also be used.
  • An optical disk drive 212 is typically provided to act as a non-volatile source of data.
  • Portable memory devices, such optical disks (eg: CD-ROM, DVD), USB-RAM, and floppy disks for example may then be used as appropriate sources of data to the system 200 .
  • the memory 206 and the HDD 210 may be referred to as a “computer readable memory”.
  • the components 205 to 213 of the computer module 201 typically communicate via an interconnected bus 204 and in a manner which results in a conventional mode of operation of the computer system 200 known to those in the relevant art.
  • Examples of computers on which the described arrangements can be practised include IBM-PC's and compatibles, Sun Sparcstations, Apple MacTM or alike computer systems evolved therefrom.
  • One or more steps of the methods described below may be implemented within the computer system 200 , wherein one or more steps of the processes of FIGS. 3 to 6 may be implemented as software, such as one or more software application programs 233 executable within the computer system 200 .
  • one or more of the steps of the described methods may be effected by instructions in the software 233 that are carried out within the computer system 200 .
  • the instructions may be formed as one or more code modules, each for performing one or more particular tasks.
  • the software 233 executable within the computer system 200 may implement and manage the graphical user interface (GUI) displayed on the display 214 . As described above, one or more controls displayed on the GUI allow an operator to activate or de-activate dewatering remotely.
  • GUI graphical user interface
  • the software 233 resident on the computer system 200 and implementing GUI may be stored in a computer readable medium, including the storage devices described above, for example. Such software may be loaded into the computer system 200 from the computer readable medium, and then be executed by the computer system 200 .
  • the use of a computer program product in the computer system 200 preferably effects an advantageous apparatus for implementing one or more steps of the described methods.
  • GUI graphical user interface
  • the controlling commands and/or input may allow the operator to activate and de-activate dewatering remotely using the controls displayed on the GUI represented on the display 214 , FIG. 2B .
  • the GUI preferably also provides an indication of the status of the system 100 (e.g., “valve open” or “valve closed”) to indicate whether the valves 102 and 103 are open or closed, FIG. 1 .
  • the GUI may also display diagnostic information indicating problems with the system 100 .
  • the method 300 may be implemented as one or more code modules of the software 133 resident on the internal storage 159 of the embedded device 151 and being controlled in its execution by the processor 155 .
  • the method 300 begins at step 301 where the processor 155 performs the step of transmitting a first signal to the motorised valve 102 to open the valve 102 allowing liquid to flow out of the tank 101 through the pipe 104 . Liquid flows from the tank 101 through the open valve 102 and the pipe 104 to the containment system 105 .
  • the first signal may be generated by the embedded device 151 in response to a signal received from computer system 200 .
  • the signal received from the computer system 200 may be generated based on operator manipulation of the keyboard 202 and the mouse 203 to operate one or more controls of the GUI displayed on the display device 214 .
  • the software 233 may generate and send the first signal to the device 151 via the network 222 .
  • the processor 155 performs the step of detecting if the liquid flowing in the pipe 104 at a predetermined point in the pipe has transitioned from water to crude oil.
  • the processor 155 may detect whether the liquid flowing in the pipe 104 has transitioned from water to crude oil by measuring at least one property of the liquid flowing at the predetermined point within the pipe 104 . The measured property may be compared to a predetermined threshold value. Based on a result of the comparison, the processor 155 may detect if the liquid flowing in the pipe has transitioned from water to crude oil.
  • the processor 155 may determine if the flow of liquid within the pipe 104 is “laminar” or “turbulent” at the predetermined point, at any particular point in time, based on a measurement of sound pressure level (SPL) produced by the liquid flowing within the pipe 104 . Accordingly, the property measured at step 303 is sound pressure level (SPL) produced by the liquid flowing within the pipe 104 .
  • the determination of sound pressure level may be made using the acoustic sensor array 109 positioned at the predetermined point of the pipe 104 .
  • a method 400 of detecting water to crude oil transition in the pipe 104 using the acoustic sensor array 109 as may be executed at step 303 , will be described in detail below with reference to FIG. 4 .
  • the processor 155 may detect whether the flow of liquid in the pipe 104 has transitioned from water to crude oil by determining the conductivity of the liquid using the conductivity sensor 108 . Accordingly, the property measured at step 303 is conductivity of the liquid.
  • a method 500 of detecting water to crude oil transition in the pipe 104 using the conductivity sensor 108 as may be executed at step 303 , will be described in detail below with reference to FIG. 5 .
  • the processor 155 may detect whether the flow of liquid in the pipe 104 has transitioned from water to crude oil by monitoring vibration within the pipe 104 using an accelerometer, as will be described below. Accordingly, in this instance, the property measured at step 303 is vibration caused by the liquid flowing in the pipe 104 .
  • the method 300 continues at the next step 304 , where if the flow of liquid in the pipe 104 at the predetermined point has transitioned from water to crude oil (i.e., the transition has occurred), then the method 300 proceeds to step 305 . Otherwise, the method 300 returns to step 303 .
  • the processor 155 performs the step of transmitting a signal to the motorised valve 102 , via the I/O interface 160 , to close the valve 102 in order to stop the liquid flowing out of the tank 101 in the pipe 104 .
  • the closing of the valve 102 may be indicated to the operator via the GUI displayed on the display device 214 , in response to a further signal received by the processor 205 from the processor 155 .
  • Laminar flowing water is deterministic. Information about future behaviour of laminar flowing water is completely determined by specification of flow at an earlier time. For faster or larger scale water flowing from the tap (e.g., with the tap fully open), the flow pattern of water continuously changes. Although, average motion of the faster flowing water is in one direction within the flow there are irregularities everywhere within the flowing water.
  • Laminar flow of liquid occurs for low speeds, small diameters, low densities and high viscosities.
  • Turbulent flow of liquids occurs for the opposite conditions (i.e., high speeds, large diameters, high densities and low viscosities).
  • Viscosity is a measurable property of a liquid. Some other examples of measurable properties of liquids are conductivity, density and temperature. Other examples of a measurable property of a liquid are sound pressure level (SPL) and vibration, both produced by the liquid flowing within a pipe.
  • SPL sound pressure level
  • kinematic viscosity (units cSt or m 2 s ⁇ 1 ) of a liquid refers to the viscosity of the liquid divided by the density of the liquid.
  • Equation (1) a value known as the Reynolds number, Re, quantifies the relative importance of inertial forces to viscous forces for a given liquid and given flow conditions.
  • the Reynolds number for a liquid may be determined in accordance with Equation (1) below:
  • V represents speed of the liquid in meters per second (ms ⁇ 1 ) flowing through an orifice (e.g., inner diameter of a pipe) of diameter d in meters (m);
  • represents absolute dynamic fluid viscosity in Newton seconds per meter squared (Nsm ⁇ 2 );
  • V represents kinetic fluid viscosity in meters squared per second (m 2 s ⁇ 1 );
  • represents density of the liquid in kilograms per meter cubed (kg m ⁇ 3 ).
  • the Reynolds number Re is small. In this instance, the flow of the liquid will be laminar. Increasing the diameter, d, or the speed, V, or decreasing the viscosity, will increase the Reynolds number, Re.
  • the kinematic viscosity of water at 54.4° C. is approximately 0.55 cSt or 550 ⁇ 10 ⁇ 3 m 2 s ⁇ 1 .
  • the kinematic viscosity of crude oil at 54.44° C. is approximately 3.5 cSt. If the pipe diameter is one (1) cm, the speed, V, at which the Reynolds number, Re, is two-thousand (2000), is 0.2 ms ⁇ 1 (0.72 kmh-1) which is a relatively slow speed. Water undergoes transition to turbulence at low speeds.
  • a threshold Reynolds number, Re of approximately two-thousand-three-hundred (2300) in a pipe (e.g., the pipe 104 )
  • the precise value of the threshold Reynolds number depends on whether any small disturbances are present. If the inner surface of the pipe is very smooth and there are no disturbances to the velocity, higher values of the Reynolds number, Re, can be obtained with the flow still in a laminar state. However, if the Reynolds number, Re, is less than two-thousand-three-hundred (2300), then the flow of the liquid will be laminar even if the liquid is disturbed. Further, if the pipe has a different cross-sectional geometry (e.g., square), or the flow of liquid is over a turbine blade, then the transition from laminar to turbulent flow will occur at different Reynolds number values, Re.
  • the kinematic viscosity of crude oil and water is substantially different, as seen in Appendix A.
  • the difference between the laminar flow of crude oil and the turbulent flow of water in the pipe 104 may be detected using acoustic means in the form of the acoustic sensor array 109 attached to the pipe 104 . Any sounds and vibrations in the pipe 104 , caused by turbulence of the liquid, indicate that the liquid flowing through the pipe 104 is water.
  • relative silence and stillness within the pipe 104 when liquid is flowing through the pipe 104 , indicates the laminar flow of crude oil within the pipe 104 .
  • FIG. 6 shows a fast Fourier transform (FFT) waterfall trace 600 simulating the flow of water through the pipe 104 .
  • the trace 600 comprises a vertical axis showing sound pressure level (SPL) in decibels (dB).
  • SPL sound pressure level
  • dB decibels
  • the horizontal axis of the trace 600 shows frequency in Hertz (Hz).
  • Hz Hertz
  • the spectrum of the trace 600 is chaotic and resembles white noise.
  • the role off of the recorded signals below 100 Hz This role off is an artifact of the recording equipment used to generate the trace 600 and would unlikely be present in a typical implementation of the system 100 .
  • FIG. 7 shows a fast Fourier transform (FFT) waterfall trace 700 simulating the flow of crude oil through the pipe 104 .
  • the trace 700 comprises a vertical axis showing sound pressure level (SPL) in dB.
  • the horizontal axis shows frequency in Hz.
  • the amplitude of signal above 100 Hz, as highlighted by oval 701 is small compared to the trace 600 .
  • the overall difference in SPL between the trace 600 and the trace 700 is approximately fifty (50) dB.
  • the flow of crude oil within the pipe 104 may be distinguished from the flow of water within the pipe 104 by measuring the SPL using the acoustic sensor array 109 and comparing the measured level of SPL to a first predetermined threshold value.
  • Determination of the first predetermined threshold value will be described in detail below and may be stored in the memory 206 or on the hard disk drive 210 .
  • the area of the trace 700 highlighted by a circle 702 in the trace 700 is a combination of environmental noise and artifact of the equipment used to generate the trace 700 .
  • the method 400 of detecting water to crude oil transition in the pipe 104 using the acoustic sensor array 109 will now be described in detail below with reference to FIG. 5 .
  • the acoustic sensor array 109 is fixed at a predetermined point to the outside of the pipe 104 .
  • the method 400 may be implemented as one or more code modules of the software 133 resident on the storage module 159 of the embedded device 151 and being controlled in its execution by the processor 155 .
  • the method 400 will be described by way of example with reference to FIG. 9 which shows a graph 900 representing sound pressure level (SPL) versus time for a typical dewatering scenario.
  • the method 400 detects water to crude oil transition based on a baseline ambient SPL within the pipe 104 .
  • the processor 155 of the embedded device 151 may be configured to pole the acoustic sensor array 109 periodically (e.g., every second) to determine an SPL reading.
  • the software 133 Prior to commencement of dewatering at step 301 (i.e., prior to time t 0 in the graph 900 ), the software 133 (under execution of the processor 155 ) determines the baseline ambient SPL by determining output of the acoustic sensor array 109 at that time.
  • the determined ambient SPL may be stored in the RAM of the storage module 159 as a two dimensional (2D) data object.
  • the method 400 begins at step 401 , where the processor 155 determines the sound pressure level (SPL) measured in the pipe 104 at a current time.
  • SPL sound pressure level
  • dewatering of the tank 101 commences at time t 0 with the opening of the motorised valve 102 , as at step 301 of the method 300 .
  • the opening of the valve 102 represents a step stimulus to the system 100 as the SPL measured in the pipe 104 begins to rise.
  • the rising SPL will typically plateau, as at point A of the graph 900 .
  • the plateau represents turbulent flow of liquid within the pipe 104 and will last for a period from time t 0 to t 1 at which time transition from water to crude oil commences.
  • the plateau occurring at point A may be referred to as the “turbulent plateau”.
  • the period from time t 0 to t 1 will be as long as the discharge of water continues in the pipe 104 . Accordingly, in the initial execution of the method 400 , the SPL measured in the pipe 104 at step 401 will be a value between the ambient SPL and the SPL level at the turbulent plateau of the graph 900 .
  • the current value of SPL in the pipe 104 may be read by the processor 155 at step 401 from the RAM of the internal storage module 159 .
  • the processor 155 may be configured to pole the acoustic sensor array 109 at the current time (i.e., real time capture) to determine the SPL reading.
  • the processor 155 may be configured to record (i.e., capture and store) the signal (representing SPL) from the acoustic sensor array 109 for a predetermined period (e.g., sixty seconds).
  • the processor 155 may also process the signal from the acoustic sensor 109 using cross correlation and FFT analysis and compare the determined values of SPL against previously learned (and stored) values.
  • the processor 155 may be configured to implement a learning algorithm so that the system 100 may self adapt over a period of time to each new installation of the system 100 , as the frequency response of no two mechanical systems is exactly identical.
  • the system 100 may be configured to vary weightings associated with the acoustic sensor 109 and the conductivity sensor 108 .
  • the transition from water to oil commences, resulting in a knee (as at point B) on the graph 900 .
  • the rag interface layer separating the water and oil in the tank will be discharged typically resulting in a variable but reducing level of turbulence (i.e., reducing SPL) until time t 2 .
  • the majority of liquid flowing in the pipe 104 will be crude oil and the turbulence measured in the pipe 104 (i.e., represented by measured SPL) will plateau at a lower level. This lower level plateau represents laminar flow of liquid in the pipe 104 and may be referred to as the “termination plateau”.
  • point C on the graph 900 represents the point at which the valve 102 is closed, as at step 305 of the method 300 , in order to stop the liquid flowing out of the tank 101 into the pipe 104 .
  • Point C may be referred to as the “termination point”.
  • the difference between the baseline ambient SPL and SPL level at the turbulent plateau will typically be around 40 dB. However, this difference may vary significantly depending on the implementation of the system 100 and the liquid flowing in the pipe 104 .
  • the difference between the SPL level at the turbulent plateau and the SPL level at the termination plateau will typically be between 30 dB and 40 dB. Accordingly, the SPL level at the termination plateau will be close to the baseline ambient SPL.
  • the first predetermined threshold used for detecting if the liquid flowing in the pipe 104 has transitioned from water to crude oil may be set to 10 dB above the ambient baseline level. Again, the difference between the SPL level at the turbulent plateau and the SPL level at the termination plateau may vary significantly depending on the implementation of the system 100 and the liquid flowing in the pipe 104 .
  • the first predetermined threshold may be determined by the processor 155 prior to commencement of the method 300 and stored in the internal storage module 159 .
  • Steps 401 and 403 may occur many times between time t 0 and time t 2 on the graph 900 .
  • the processor 155 determines that the transition from water to crude oil has occurred.
  • the processor 155 may set a flag, for example, configured within the internal storage module 159 in order to indicate that the transition has occurred. Accordingly, at step 303 , the processor 155 may detect whether the flow of liquid in the pipe 104 has transitioned from water to crude oil by determining the state of the flag.
  • the SPL value determined at step 401 may represent an average (or Mean) SPL value dynamically determined by the processor 155 for a moving window of readings (e.g., 10 successive readings).
  • the reason for using an average SPL value is to discount random noise and smooth the determined SPL data.
  • the processor 155 may also be configured to determine a running standard deviation of the average SPL values.
  • FIG. 10 is a graph 1000 showing SPL values against time in accordance with one example.
  • the graph 1000 is similar to the graph 900 .
  • trace 1001 plots raw SPL values
  • trace 1002 plots average (or mean) SPL values
  • trace 1003 plots the standard deviation of the windowed average SPL values.
  • Point B (occurring at time t 1 ) on the graph 1000 substantially corresponds to point B (i.e., the knee) on the graph 900 .
  • Point B on the graph 1000 may initially be determined by the processor 155 from a variation in standard deviation data (as represented by trace 1003 ) greater than three times the running average standard deviation (as represented by trace 1002 ). This three times factor may be refined as part of the learning algorithm.
  • Point C (i.e., the point at which the termination plateau begins at time t 2 ) on the graph 1000 corresponds to point C on the graph 900 .
  • point C may be determined and refined by the processor 155 , as at step 405 , based on decline in standard deviation (as represented by trace 1003 ) to 50% of the maximum value of standard deviation variation subsequent to point B. As seen in FIG. 10 , point C corresponds to the point on trace 1003 where the variation in standard deviation has dropped to 50% of its maximum value subsequent to point B.
  • the determination at step 405 of whether the transition from water to crude oil has occurred may be made by determining when the variation in standard deviation has dropped to 50% of its maximum value subsequent to point B.
  • step 403 of the method 400 may be described as a determination by the processor 155 of whether an “SPL Function” is at the threshold.
  • SPL Function refers to each of a measured SPL value as described above; an average (or Mean) SPL value dynamically determined for a moving window of readings (e.g., 10 successive readings); and a running standard deviation of the average SPL values.
  • the processor 155 may also be configured to implement a learning algorithm so that the system 100 may self adapt over a period of time to each new installation of the system 100 .
  • the following system variables may be recorded into a history file stored within the internal storage module 159 to allow reinforced learning to take place, relative to time t 0 :
  • the methods described above introduce a minimal amount of lag into the system 100 .
  • the learning algorithm may account for this lag by applying weightings to the determined SPL values to ensure that point B occurs as close as possible to the actual beginning of the transition from water to crude oil.
  • standard deviation is a measure of the variability or dispersion of a population, a data set, or a probability distribution. A low standard deviation indicates that the data points tend to be very close to the same value (the mean), while high standard deviation indicates that the data are “spread out” over a large range of values.
  • the standard deviation of a discrete random variable is the root-mean-square (RMS) deviation of its values from the mean.
  • RMS root-mean-square
  • the standard deviation a of the variable X may be determined by finding the mean, x , of the values x 1 . . . x N , determining the deviation (x i . . . x ) from the mean for each value x i . determining the squares of these deviations, determining variance ⁇ 2 representing the mean of the squared deviations, and determining the square root of the variance.
  • the standard deviation ⁇ of the variable X may be determined in accordance with Equation 2 as follows:
  • the learning algorithm may be based on comparison of the SPL data values in the history file stored within the internal storage module 159 .
  • the learning algorithm may be parameterised using the mean SPL values from previous dewatering processes, with SPL values beyond the mean by more than two standard deviations being ignored.
  • the operator may be notified by way of the GUI displayed on the display device 214 , that the dewatering currently underway is atypical, where the actual determined SPL values are above the mean by more than two standard deviations.
  • the learning algorithm may also compare data determined using the acoustic sensor array 109 to equivalent data determined using the conductivity sensor 108 , in order to correct the determination of points B and C on the graph 1000 .
  • Electrical conductivity is measured in Siemens per metre (Sm-1). As seen in Appendix B, water has a conductivity ranging from pure water at 5.5 ⁇ 10 ⁇ 6 ⁇ m ⁇ 1 to sea water with a conductivity of 5 ⁇ m ⁇ 1 . Depending on contamination levels, crude oil exhibits conductivity tending towards that of pure water. In particular, depending on source of the crude oil, the conductivity ranges from between 35 ⁇ 10 ⁇ 6 ⁇ m ⁇ 1 to 110 ⁇ 10 ⁇ 6 ⁇ m ⁇ 1 . Accordingly, crude oil may be distinguished from contaminated water passing through a non-contact conductivity sensor such as the conductivity sensor 108 .
  • the method 500 of detecting water to crude oil transition in the pipe 104 , using the conductivity sensor 108 , as may be executed at step 303 , will now be described in detail with reference to FIG. 5 .
  • the conductivity sensor 108 is positioned at a predetermined point within the pipe 104 .
  • the method 500 may be implemented as one or more code modules of the software 133 resident in the storage module 159 of the embedded device 151 and being controlled in its execution by the processor 155 .
  • the method 500 will be described by way of example with reference to FIG. 11 which shows a graph 1100 representing conductivity Siemens per metre (Sm-1) versus time for a typical dewatering scenario.
  • the method 500 detects water to crude oil transition based on a baseline ambient conductivity value within the pipe 104 .
  • the processor 155 of the embedded device 151 may be configured to pole the conductivity sensor 108 periodically (e.g., every second) to determine a conductivity reading.
  • the software 133 Prior to commencement of dewatering at step 301 (i.e., prior to time t 0 in the graph 1100 ), the software 133 (under execution of the processor 155 ) determines a baseline ambient conductivity value by determining a current output of the conductivity sensor 108 .
  • the determination of the baseline ambient conductivity value allows for any plaque on the sensor 108 from any previous dewatering processes.
  • the determined ambient conductivity value may be stored in the RAM of the storage module 159 as a two dimensional (2D) data object.
  • the method 500 begins at step 501 , where the processor 155 determines conductivity of the liquid in the pipe 104 at a current time.
  • dewatering of the tank 101 commences at time t 0 with the opening of the motorised valve 102 , as at step 301 of the method 300 .
  • the opening of the valve 102 represents a step stimulus to the system 100 as the conductivity value measured in the pipe 104 begins to rise.
  • the rising conductivity will typically plateau, as at point A of the graph 1100 .
  • the plateau represents turbulent flow of liquid within the pipe 104 and will last for a period from time t 0 to t 1 at which time transition from water to crude oil commences. Again, the plateau occurring at point A of the graph 1100 may be referred to as the “turbulent plateau”.
  • the period from time t 0 to t 1 will be as long as the discharge of water continues in the pipe 104 .
  • the conductivity values measured in the pipe 104 at step 501 will be a value between the baseline ambient conductivity value and the conductivity value at the turbulent plateau on the graph 1100 .
  • the conductivity reading may be stored in RAM of the internal storage module 159 .
  • the current value of conductivity may be read by the processor 155 from the RAM of the internal storage module 159 .
  • the processor 155 may be configured to pole the conductivity sensor 108 at the current time to determine the conductivity reading.
  • the processor 155 may be configured to record the signal (representing conductivity value) from the conductivity sensor 108 for a predetermined period (e.g., sixty seconds).
  • the transition from water to oil commences, resulting in a knee (at point B) on the graph 1100 .
  • the rag interface layer separating the water and oil in the tank 101 will be discharged typically resulting in a variable but reducing level of conductivity (i.e., reducing Sm-1) until time t 2 .
  • the majority of liquid flowing in the pipe 104 will be crude oil and the conductivity measured in the pipe 104 will plateau at a lower level.
  • This lower level plateau represents laminar flow of liquid in the pipe 104 and, again, may be referred to as the “termination plateau” similar to the graph 900 .
  • point C on the graph 1100 represents the point at which the valve 102 is closed, as at step 305 of the method 300 , in order to stop the liquid flowing out of the tank 101 in the pipe 104 .
  • the difference between the baseline ambient conductivity value and the conductivity value at the turbulent plateau will typically range from 1 Sm ⁇ 1 to 5 Sm ⁇ 1 . However, this difference may vary significantly depending on the implementation of the system 100 and the liquid flowing in the pipe 104 .
  • the conductivity of crude oil relative to water may be approximated to zero.
  • the system 100 may be configured so that the termination point (i.e., point C on the graph 1100 ) is reached when mean conductivity of the liquid in the pipe 104 drops to 20% of the difference between the baseline ambient conductivity value and the conductivity value at the turbulent plateau of the graph 1100 (i.e., 0.2 Sm ⁇ 1 to 1 Sm ⁇ 1 ).
  • the difference between the conductivity value at the turbulent plateau and the conductivity value at the termination plateau will typically range between 0.8 Sm ⁇ 1 to 4 Sm ⁇ 1 .
  • the conductivity value at the termination plateau will be close to the baseline ambient conductivity value.
  • a second predetermined threshold used for detecting if the liquid flowing in the pipe 104 has transitioned from water to crude oil may be set to 20% above the ambient baseline conductivity value. Again, the difference between the conductivity value at the turbulent plateau and the conductivity value at the termination plateau may vary significantly depending on the implementation of the system 100 and the liquid flowing in the pipe 104 . In one implementation of the system 100 , the second predetermined threshold may be set to 0.01 Sm ⁇ 1 .
  • step 503 if the processor 155 determines that the conductivity of the liquid at the current time is less than or equal to the second predetermined threshold value, indicating that the liquid flowing within the pipe 104 is oil, then the method 500 proceeds to step 505 . Otherwise, the method 500 returns to step 501 .
  • Steps 501 and 503 may occur many times between time t 0 and time t 2 on the graph 1100 .
  • the second predetermined threshold value may be stored in the internal storage module 159 of the device 151 .
  • the processor 205 determines that the transition from water to crude oil has occurred. Again, the processor 205 may set a further flag described above, for example, configured within the memory 206 in order to indicate that the transition has occurred. Accordingly, at step 303 , the processor 205 may detect whether the flow of liquid in the pipe 104 has transitioned from water to crude oil by determining the state of the further flag.
  • the system 100 may be configured so that the conductivity of the liquid must be less than or equal to the second predetermined threshold value for a predetermined period (e.g., sixty seconds), before the method 500 proceeds to step 505 and the processor 155 determines that the water has transitioned to crude oil.
  • a predetermined period e.g., sixty seconds
  • the processor 155 may also be configured to implement a learning algorithm so that the system 100 may self adapt over a period of time to each new installation of the system 100 .
  • the following system variables may be recorded into a history file stored within the internal storage 159 to allow reinforced learning to take place, relative to time t 0 :
  • the learning algorithm may be based on comparison of the conductivity values in a history file stored within the internal storage module 159 .
  • the learning algorithm may be parameterised using the mean values from previous dewatering processes, with conductivity values beyond the mean by more than two standard deviations being ignored.
  • the operator may be notified by way of the GUI displayed on the display device 214 , that the dewatering currently underway is atypical, where the actual determined conductivity values above the mean by more than two standard deviations are ignored.
  • the learning algorithm may also compare conductivity data values determined using the conductivity sensor 108 to equivalent data determined using the acoustic sensor array 109 , in order to correct the determination of points B and C on the graph 1100 .
  • valve 105 may be opened to send the crude oil to the transport system 107 .
  • the methods 300 , 400 and 500 described above may alternatively be implemented in dedicated hardware such as one or more integrated circuits performing the functions or sub functions of FIGS. 3 to 5 .
  • dedicated hardware may include graphic processors, digital signal processors, or one or more microprocessors and associated memories.
  • both of the methods 400 and 500 may be performed at step 303 .
  • the transition from water to crude oil may be determined to have occurred only when both of the sensors 108 and 109 provide a result indicating that the transition has occurred (i.e., when the measured SPL is less than the first predetermined threshold value and the measured conductivity is less than the second predetermined threshold value).
  • weightings may be applied to each of the sensors 108 and 109 .
  • the acoustic sensor array 109 may be given a higher weighting than the conductivity sensor 108 .
  • the processor 205 may still determine that the transition has occurred on the basis that the sensor array 109 has a higher weighting.
  • the processor 205 may be configured to adjust the weightings associated with each of the sensors 108 and 109 , based on results produced by the system 100 . For example, upon the sensors 108 and 109 being installed and trials being conducted on the system 100 , one of the sensors 108 and 109 may be given a higher weighting if that sensor is found to produce more accurate and reliable results in indicating that the transition has occurred. After a predetermined period of time (e.g., one or more days or weeks) the weightings associated with the sensors 108 and 109 may be adjusted based on results at that time.
  • a predetermined period of time e.g., one or more days or weeks
  • the acoustic sensor array 109 is preferably configured to permanently bolt to the pipe 104 at a predetermined point of the pipe 104 .
  • the acoustic sensor array 109 may be bolted to a fitting connected to the pipe 104 .
  • Any suitable acoustic sensor may be used for the acoustic sensor array 109 in the system 100 .
  • the acoustic sensor 109 is a SitransTM AS100 manufactured by Siemens AG.
  • the SitransTM AS100 requires a controller to process signals from the acoustic sensor array 109 .
  • the controller is a SitransTM AS100+CU02 manufactured by Siemens AG.
  • Such a controller is electrically configured between the acoustic sensor array 109 and the electronic device 151 .
  • the conductivity sensor 108 is preferably configured to overcome fouling and be resistant to moderate temperatures, chemical exposure and physical wear.
  • the conductivity sensor 108 preferably has a large bore to allow solids to pass through the sensor 108 without plugging, to allow the sensor to be used for applications containing high levels of suspended solids.
  • the conductivity sensor 108 is preferably configured to measure accurately over a large range of Scm ⁇ 1 .
  • the conductivity sensor 108 may be formed of an exceptionally strong and hard material (e.g., chemically resistant polyetheretherketone (PEEK)). Any suitable conductivity sensor may be used for the sensor 108 in the system 100 .
  • the conductivity sensor 108 is a RosemountTM Analytical Model 226 large bore “toroidal” conductivity sensor.
  • the RosemountTM Analytical Model 226 requires a controller to process signals from the conductivity sensor 108 .
  • the controller is a RosemountTM Analytical Model 54eC.
  • Such a controller is electrically connected between the conductivity sensor 108 and the electronic device 151 .
  • the Model 226 conductivity sensor is very resistant to fouling effects.
  • the Model 226 uses an inductive method of measuring conductivity.
  • the Model 226 has a large 47 mm bore to allow solids to pass through the sensor without plugging.
  • the Model 226 is preferably configured to work at temperatures to 120° C. and measure accurately over the range of 50 ⁇ Scm ⁇ 1 to 1,000 mScm ⁇ 1 .
  • the conductivity sensor 108 is a FoxboroTM Model 875EC, Intelligent Electrochemical Analyser for Electrodes Conductivity Measurement sensor.
  • the conductivity sensor 108 is a FoxboroTM Model 871EC-LB, Electrodes Conductivity Sensor—Large Bore, PEEK, High Sensitivity.
  • valves 102 and 103 , the acoustic sensor array 109 and the conductivity sensor 108 may be connected directly to the local computer network 222 , as seen in FIG. 8 .
  • the methods described above may be implemented using the processor 205 .
  • the processes of FIGS. 3 to 7 may be implemented as one or more software application programs resident within the hard disk drive 210 and being controlled in their execution by the processor 205 .
  • the steps of the described methods may be effected by instructions in the software that are carried out within the computer module 201 .
  • the ratio of crude oil to water in the liquid at different times should preferably be displayed on the GUI.
  • the ratio of crude oil to water may be determined by the processor 155 based on SPL and/or conductivity measurements.
  • the system 100 may be calibrated so that predetermined SPL and/or conductivity measurements indicate certain water to crude oil ratios of the liquid.
  • the system 100 may also be configured so that the predetermined SPL and conductivity thresholds may be adjusted by an operator using the computer module 201 .
  • the system 100 should preferably be fail-safe such that in the event of a failure the valves 102 and 105 should move to a closed position.
  • a measuring means in the form of an accelerometer may be fixed to the pipe 104 in a similar manner to the acoustic sensor 109 and the conductivity sensor 108 .
  • the accelerometer may be used in place of the acoustic sensor array 109 and/or the conductivity sensor 108 or together with the array 109 and the sensor 108 .
  • Such an accelerometer may be adapted to the lower end of the frequency spectrum in order to measure vibration at a predetermined point of the pipe 104 . In this connection, when water is flowing in the pipe 104 , the measured vibration will be relatively higher than when crude oil is flowing in the pipe 104 .
  • a change in the level of vibration at the predetermined point of the pipe 104 may therefore be used to detect the water to crude oil transition of the liquid in a similar manner to the methods 400 and 500 . Similar to the methods 400 and 500 described above, the measured vibration may be compared to a predetermined threshold level of vibration.
  • the methods 300 , 400 and 500 , and the system 100 have been described above with reference to crude oil.
  • the described methods may have applications with other liquids and substances including petroleum products.
  • Such petroleum products include unfinished oils, liquefied petroleum gases, pentanes plus, aviation gasoline, motor gasoline, naphtha-type jet fuel, kerosene-type jet fuel, kerosene, distillate fuel oil, residual fuel oil, petrochemical feedstocks, special naphthas, lubricants, waxes, petroleum coke, asphalt, road oil and still gas.
  • the acoustic sensor array 109 to accurately differentiate between water and other water-insoluble liquid, the kinetic viscosity of this other liquid needs to be greater than water.
  • the word “comprising” means “including principally but not necessarily solely” or “having” or “including”, and not “consisting only of”. Variations of the word “comprising”, such as “comprise” and “comprises” have correspondingly varied meanings.
  • ⁇ t ⁇ 15 ⁇ exp ⁇ [ - a 15 ⁇ ⁇ t ⁇ ( 1 + 0.8 ⁇ ⁇ a 15 ⁇ ⁇ t ) ]
  • ⁇ : ⁇ t the ⁇ ⁇ product ⁇ ⁇ density ⁇ ⁇ at ⁇ ⁇ t ⁇ ⁇ ° ⁇ ⁇ C .
  • ⁇ ⁇ 15 the ⁇ ⁇ product ⁇ ⁇ density ⁇ ⁇ at ⁇ ⁇ 1 ⁇ ⁇ 5 ⁇ ⁇ ° ⁇ ⁇ C .
  • ⁇ ⁇ t t ⁇ ⁇ ° ⁇ ⁇ C . - ⁇ 15 ⁇ ⁇ ° ⁇ ⁇ C .
  • K0 and K1 are defined in accordance with Table 4 as follows: Density Range Product (kg/m ⁇ circumflex over ( ) ⁇ 3) K 0 K 1 Crude Oil 771-981 613.97226 0.00000 Gasolines 654-779 346.42278 0.43884 Kerosenes 779-839 594.54180 0.00000 Fuel Oils 839-1075 186.96960 0.48618

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Cited By (10)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20120017998A1 (en) * 2010-07-22 2012-01-26 Saudi Arabian Oil Company Sound-Velocity Dewatering System
CN104291031A (zh) * 2014-09-24 2015-01-21 广州天禾自动化实业有限公司 一种用于虹吸式油罐的呼吸式自动脱水回油系统及方法
US20170009564A1 (en) * 2014-01-30 2017-01-12 Total Sa System for treatment of a mixture from a production well
US20170115147A1 (en) * 2014-10-01 2017-04-27 Finetek Co., Ltd. Method for sensing conductivity and flow rate of a liquid in a tube
CN106841323A (zh) * 2016-12-22 2017-06-13 中海油能源发展股份有限公司 一种高乳化油水混合体系差异组份分质分类方法
WO2017197209A1 (en) * 2016-05-11 2017-11-16 General Electric Company System and method for fluid interface identification
US10030498B2 (en) 2014-12-23 2018-07-24 Fccl Partnership Method and system for adjusting the position of an oil-water interface layer
US20190192996A1 (en) * 2016-05-10 2019-06-27 Rocco Slop Ab Method and system for purification of oil
WO2020035624A1 (en) * 2018-08-17 2020-02-20 Leonardo Mw Limited A gas-liquid separator
CN116374431A (zh) * 2023-04-25 2023-07-04 广东石油化工学院 一种用于大型储油罐的油品排水装置及方法

Families Citing this family (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP6676364B2 (ja) * 2015-12-18 2020-04-08 株式会社テイエルブイ 蒸気インジェクション装置
CN110499184B (zh) * 2018-05-18 2021-07-06 中石化广州工程有限公司 一种液化烃罐脱水装置
CN112940775B (zh) * 2021-02-20 2021-08-17 东北石油大学 一种优化脉冲电场原油脱水参数的方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3849285A (en) * 1972-09-15 1974-11-19 Combustion Eng Electric control system
WO1992019350A1 (en) * 1991-05-02 1992-11-12 Conoco Specialty Products Inc. Hydrocylones for oil spill cleanup
US5259250A (en) * 1990-05-14 1993-11-09 Atlantic Richfield Company Multi-phase fluid flow mesurement
US5741978A (en) * 1994-11-09 1998-04-21 Gudmundsson; Jon Steinar Method for determination of flow rate in a fluid
US6218948B1 (en) * 1998-08-17 2001-04-17 Alfred Dana Bilge sentry

Family Cites Families (4)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3253711A (en) * 1962-12-31 1966-05-31 Pfaudler Permutit Inc Fluid separation
US4573346A (en) * 1983-07-18 1986-03-04 Nusonics, Inc. Method of measuring the composition of an oil and water mixture
JPH059347Y2 (ja) * 1987-02-13 1993-03-08
JP5036792B2 (ja) * 2009-11-19 2012-09-26 中国電力株式会社 制御方法及び制御システム

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US3849285A (en) * 1972-09-15 1974-11-19 Combustion Eng Electric control system
US5259250A (en) * 1990-05-14 1993-11-09 Atlantic Richfield Company Multi-phase fluid flow mesurement
WO1992019350A1 (en) * 1991-05-02 1992-11-12 Conoco Specialty Products Inc. Hydrocylones for oil spill cleanup
US5741978A (en) * 1994-11-09 1998-04-21 Gudmundsson; Jon Steinar Method for determination of flow rate in a fluid
US6218948B1 (en) * 1998-08-17 2001-04-17 Alfred Dana Bilge sentry

Cited By (13)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US9086354B2 (en) * 2010-07-22 2015-07-21 Saudi Arabian Oil Company Sound-velocity dewatering system
US20120017998A1 (en) * 2010-07-22 2012-01-26 Saudi Arabian Oil Company Sound-Velocity Dewatering System
US20170009564A1 (en) * 2014-01-30 2017-01-12 Total Sa System for treatment of a mixture from a production well
US10900340B2 (en) * 2014-01-30 2021-01-26 Total Sa System for treatment of a mixture from a production well
CN104291031A (zh) * 2014-09-24 2015-01-21 广州天禾自动化实业有限公司 一种用于虹吸式油罐的呼吸式自动脱水回油系统及方法
US20170115147A1 (en) * 2014-10-01 2017-04-27 Finetek Co., Ltd. Method for sensing conductivity and flow rate of a liquid in a tube
US10030498B2 (en) 2014-12-23 2018-07-24 Fccl Partnership Method and system for adjusting the position of an oil-water interface layer
US20190192996A1 (en) * 2016-05-10 2019-06-27 Rocco Slop Ab Method and system for purification of oil
WO2017197209A1 (en) * 2016-05-11 2017-11-16 General Electric Company System and method for fluid interface identification
CN106841323A (zh) * 2016-12-22 2017-06-13 中海油能源发展股份有限公司 一种高乳化油水混合体系差异组份分质分类方法
WO2020035624A1 (en) * 2018-08-17 2020-02-20 Leonardo Mw Limited A gas-liquid separator
US11953270B2 (en) 2018-08-17 2024-04-09 Leonardo UK Ltd Gas-liquid separator
CN116374431A (zh) * 2023-04-25 2023-07-04 广东石油化工学院 一种用于大型储油罐的油品排水装置及方法

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