MX2008009775A - Methods, systems, and computer-readable media for fast updating of oil and gas field production models with physical and proxy simulators - Google Patents

Abstract

Methods, systems, and computer readable media are provided for fast updating of oil and gas field production optimization using physical and proxy simulators. A base model (30) of a reservoir (100), well (100), or a pipeline network (100) is established in one or more physical simulators (26). A decision management system (24) is used to define uncertain parameters for matching with observed data (114). A proxy model is used to fit the uncertain parameters to outputs of the physical simulators (26), determine sensitivities of the uncertain parameters, and compute correlations between the uncertain parameters and output data from the physical simulators (26). Parameters for which the sensitivities are below a threshold are eliminated. The decision management system (24) validates parameters which are output from the proxy model in the simulators (26). The validated parameters are used to make production decisions.

Description

METHODS, SYSTEMS AND MEANS SUSCEPTIBLE TO BE READ BY COMPUTER FOR THE QUICK UPDATE OF MODELS OF EXTRACTION OF PETROLIFER AND GAS PLACES WITH PHYSICAL SIMULATORS AND PROXY FIELD OF THE INVENTION The present invention relates to the optimization of the extraction of oil and gas fields. More particularly, the present invention relates to the use of physical and proxy simulators that improve mining decisions related to oil and gas fields.

BACKGROUND OF THE INVENTION The deposit and extraction engineers who have the task with the model or management of large oil fields containing hundreds of wells are faced with the reality of being able to only evaluate and physically manage a few individual wells per day. . The management or management of the individual well could include tests to measure the speed of oil, gas and water that comes out of an individual well (below the surface) with respect to a test period. Other tests may include tests that measure the pressure above and below the surface as well as the REF. 195307 fluid flow on the surface. As a result of the time needed to manage individual wells in an oilfield, the extraction in large oilfields is handled through the periodic measurement (for example every few months) of the fluids in the collection points joined with multiple wells in a oil field and later, distributing the measurements of the collection points back to the individual wells. The data collected from the periodic measurements are analyzed and used to make extraction decisions that include the optimization of future extraction. However, the data collected could be several months old when they are analyzed and, therefore, they would not be useful in the management of decisions in real time. In addition to the aforementioned time constraints, multiple analysis tools could be used that make it difficult to interpret a consistent analysis of a large reservoir. These tools could be multiple simulators based on physical devices or analytical equations that represent the flow and processing of oil, gas and water. In order to improve efficiency in the management of an oilfield, sensors have been installed in oilfields in recent years to continuously monitor temperatures, fluid velocities and pressures. As a result, extraction engineers have much more data to analyze than those that were generated from previous methods of periodic measurement. However, the increase in data makes it difficult for extraction engineers to react to data in time in order to respond to detected problems and to make extraction decisions in real time. For example, current methods allow the real-time detection of excess water in the fluids produced by a well, although they do not allow the engineer to respond quickly to this data in order to change the valve settings in order to reduce the amount of water based on the detection of excess water. The additional developments in recent years have led to the use of computer models that optimize the handling and extraction of the oil field. In particular, software models have been developed for deposits, wells and system performance as a whole with the purpose of managing and optimizing extraction. The common models used include deposit simulation, well nodal analysis and physical models or based on physical network simulation devices. Currently, the use of models based on physical devices to handle extraction is problematic due to the length of time that models take to execute them. further, models based on physical devices have to be "tuned" with the extraction data measured from the reservoir (pressures, flow rates, temperatures, etc.) to optimize extraction. Tuning or synchronization is achieved through a process of "history comparison" which is a complex process, time consuming and often does not originate unique extraction models. For example, the history comparison process could take many months for a specialist deposit or extraction engineer. In addition, the current history comparison algorithms and workflows for assisted or automatic history comparison are complex and annoying. In particular, in order to take into account the many possible parameters in a deposit system that could make extraction predictions, many tests of one or more simulators based on physical devices would need to be executed, which is not practical in the industry. With respect to these and other considerations is that the present invention has been made.

SUMMARY OF THE INVENTION Illustrative embodiments of the present invention address these problems and others by providing rapid updating of oil and gas field extraction models using physical and proxy simulators. An illustrative embodiment includes a method that establishes a base model of a physical system in one or more simulators based on physical devices. The physical system could include a deposit, a well, a network of pipelines and a processing system. One or more of the simulators look like the flow of fluids in the reservoir, the well, the pipeline network and the processing system. The method also includes the use of a decision management system that defines the uncertain parameters of the physical system for comparison with the observed data. Uncertain parameters could include parameters of permeability, fault transmission, pore volume and outer well layer. The method also includes defining the marginal limits and the distribution of uncertainty for each one that the uncertain parameters of the physical system through an experimental design process, automatically executing one or more of the simulators with respect to a set of parameters of design to generate a series of outputs, the set of design parameters includes the uncertain parameters and the outputs that represent the extraction predictions, the collection of the characterization data in a relationship database, the characterization data that they comprise values associated with the set of design parameters and the values associated with the outputs of one or more of the simulators, the adjustment of the relationship data comprising a series of inputs, the inputs include the values associated with the set of parameters of design, with the outputs of one or more simulators that use a proxy model or a system of equations for the physical system. The proxy model could be a neural network and is used to calculate the derivatives with respect to the design parameters in order to determine the sensitivities and calculate the correlations between the design parameters and the outputs of one or more of the simulators. The method also includes the elimination of the design parameters of the proxy model for which the sensitivities are below a threshold, using an optimizer with the proxy model that determines the value intervals of the design parameter, for the design parameters that were not eliminated from the proxy model, for which the outputs of the proxy model are compared with the observed data, the design parameters that were not eliminated are then designated as selected parameters, placing the selected parameters and their proxy model intervals in the decision management system, executing the decision management system as a global optimizer that validates the selected parameters in one or more of the simulators, and using the selected parameters that are validated from one or more of the simulators for extraction decisions. Other illustrative embodiments of the invention could also be implemented in a computer system or as an article of manufacture such as a computer program product or as computer-readable media. The computer program product could be a computer storage medium capable of being read by a computer system and which encodes a computer program of instructions for the execution of a computer process. The computer program product could also be a propagated signal on a carrier capable of being read by a computer system and which encodes a computer program of instructions for the execution of the computer process. These and several other features, as well as advantages, which characterize the present invention, will be apparent from the reading of the following detailed description and the review of the associated figures.

BRIEF DESCRIPTION OF THE FIGURES Figure 1 is a simplified block diagram of an operating environment that could be used in accordance with the illustrative embodiments of the present invention; Figure 2 is a simplified block diagram illustrating a computer system in the operating environment of Figure 1, which could be used to perform various illustrative embodiments of the present invention; and Figure 3 is a flow diagram showing an illustrative routine that rapidly updates petroleum and gas field extraction models with physical and proxy simulators, according to an illustrative embodiment of the present invention.

DETAILED DESCRIPTION OF THE INVENTION The illustrative embodiments of the present invention provide for the rapid updating of petroleum and gas field extraction models using physical simulators and proxy simulators. Next, with reference to the figures, in which the same numbers represent the same elements, various aspects of the present invention will be described. In particular, it is intended that Figure 1 and the corresponding discussion provide a brief and general description of the suitable operating environment in which the embodiments of the invention could be implemented. The embodiments of the present invention could be employed, generally, in the operating environment 100 as shown in Figure 1. The operating environment 100 includes the oil field surface facilities 102 and the well flow and flow devices. sub-surface 104. Oilfield surface facilities 102 could include any of a number of facilities that are normally used in the extraction of oil and gas fields. These facilities could include, without limitation, drilling equipment, anti-eruption shutters, slurry pumps and the like. Well flow and sub-surface flow devices could include, without limitation, deposits, wells and pipeline networks (and their associated hardware). It should be understood that as discussed in the following description and the appended claims, the production or extraction could include drilling and exploration of oil fields and gas fields. The surface facilities 102 and the well flow and sub-surface devices 104 are in communication with the field sensors 106, the remote terminal units 108 and the field or reservoir controllers 110, in a manner known to those skilled in the art. experts in the art. Field sensors 106 measure various surface and sub-surface properties of an oilfield (ie, deposits, wells and pipeline networks) including, but not limited to, oil, gas and water extraction rates, injection of water, adjustments of the head of pumping pipe and pressures of the node, adjustments of valve in the levels of deposit, zone and well. In one embodiment of the invention, the field sensors 106 have the ability to take continuous measurements in a petroleum field and to communicate data in real time to the remote terminal units 108. It should be appreciated by those skilled in the art that the environment Operation 100 could include "smart reservoir" technology, which allows the measurement of data on the surface, as well as, below the surface in the wells by themselves. Smart deposits also allow the measurement of individual zones and deposits in an oil field. The reservoir controllers 110 receive the measured data from the field sensors 106 and allow reservoir monitoring of the measured data. The remote terminal units 108 receive the measurement data from the field sensors 106 and communicate the measurement data to one or more Supervisory Control and Data Acquisition ("SCADA") systems 112. As is known to those skilled in the art. The technique, SCADA are computer systems that collect and analyze data in real time. The SCADA 112 communicate the received measurement data to a real-time history database 114. The real-time history database 114 is in communication with an integrated engineering and extraction drilling database 116 that has the ability to have access to the measurement data. The integrated extraction engineering and extraction database 116 is in communication with a dynamic evaluation model computer system 2. In the various illustrative embodiments of the invention, the computer system 2 executes several program modules for the update rapid extraction of oil and gas fields using physical simulators and proxy simulators. In general, program modules include routines, programs, components, data structures, and other types of structures that perform particular tasks or that implement particular types of abstract data. The program modules include a decision management system ("DMS") application 24 and a real-time optimization program module 28. Computer system 2 also includes additional program modules that will be explained later in the description of Figure 2. It will be appreciated that communications between field sensors 106, remote terminal units 108, reservoir controllers 110, SCADA 112, databases 114 and 116 and computer system 2 could be activated. using communication links through a local area or wide area network in a manner known to those skilled in the art. As will be discussed in more detail below with respect to Figures 2-3, computer system 2 uses the DMS application 24 in conjunction with physical or physical device-based simulators and a proxy model (such as a proxy simulator) for updating of oil and gas field extraction models used in an oil or gas field. The core functionality of the DMS application 24 is described in detail in copending U.S. Patent Application 2004/02200790, entitled "Method and System for Scenario and Case Management Decision," which is incorporated herein by reference. The real-time optimization program module 28 uses the aforementioned proxy model to determine the parameter value ranges for the outputs that compare the real-time observed data that are measured by the field sensors 106. Next, with reference to Figure 2, an illustrative computer architecture for the computer system 2 that is used in the different embodiments of the invention will be described. The computer architecture shown in Figure 2 illustrates a conventional desktop computer or portable laptop computer, which includes a central processing unit 5 ("CPU"), a system memory 7, which includes a memory of random access 9 ("RAM") and a read-only memory ("ROM") 11, and a system bus 12 that connects the memory to the CPU 5. A basic input / output system that contains the basic routines that help to the transfer of information between elements within the computer, such as during startup, is stored in ROM 11. Computer system 2 also includes a large capacity storage device 14 that stores operating system 16, the DMS application 24, a simulator based on physical devices 26, a module of real-time optimization 28, models based on physical devices 30 and other program modules 32. These modules will be described in greater detail later. It should be understood that the computer system 2 for practicing the embodiments of the invention could also be representative of other computer system configurations., which include portable devices, multi-processor systems, consumer electronic devices based on microprocessors or programmable, minicomputers, central computers, and the like. The embodiments of the invention could also be practiced in distributed computing environments where tasks are performed through remote processing devices that are linked through a communications network. In a distributed computing environment, the program modules could be located in storage devices, both local memory and remote memory. The large capacity storage device 14 is connected to the CPU 5 through a large capacity storage controller (not shown) connected to the bus 12. The large capacity storage device 14 and its associated means can be computer readings provide non-volatile storage for the computer system 2. Although the description of the computer readable media contained herein refers to a large capacity storage device, such as a hard disk drive or a CD-ROM drive, it should be appreciated by those skilled in the art that the means capable of being read by computer can be any type of available means that can be accessed through the computer system 2. By way of example and not as limitation, the means capable of being read by computer could comprise means of computer storage prays and media. Computer storage media includes volatile and non-volatile, removable and non-removable media that are implemented in any method or technology for the storage of information such as instructions capable of being read by computer, data structures, program modules or other data. Computer storage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM, flash memory or other solid state memory technology, CD-ROM, digital versatile discs ("DVD"), or other storage devices optical, magnetic cassettes, magnetic tapes, magnetic disk storage devices or other magnetic storage devices, or any other means that can be used to store the desired information and that can be accessed by the computer system 2. According to several embodiments of the invention, the computer system 2 could operate in a network interconnection environment using logical connections with computers, databases and other remote devices through the network 18. The computer system 2 could be connected to the network 18 through a network interface unit 20 connected to the bus 12. The connections that could be made through the unit network interface 20 could include local area network ("LAN") or wide area network ("WAN") connections. Network LAN and WAN interconnection environments are common places in offices, large company computer networks, internal networks and the Internet. It should be appreciated that the network interface unit 20 could also be used to connect with other types of networks and remote computer systems. The computer system 2 could also include an input / output controller 22 for the reception and input processing of a number of other devices, including a keyboard, a mouse, an electronic light pen (not shown in Figure 2) . Similarly, the input / output controller 22 could provide output to a display screen, printer or other type of output device. As mentioned briefly above, a number of program modules could be stored in the large capacity storage device 14 of the computer system 2, which includes the operating system 16 suitable for controlling the operation of the personal computer interconnected in a network. The large capacity storage device 14 and RAM 9 could also store one or more program modules. In one embodiment, the DMS application 24 is used in conjunction with one or more simulators based on physical devices 26, a real-time optimization module 28 and the physical device-based models 30 that optimize extraction control parameters for use in real time in an oil or gas field. As is known to those skilled in the art, simulators based on physical devices use equations representing physical fluid and chemical fluid conversion devices. Examples of simulators based on physical devices include, without limitation, tank simulators, pipeline flow simulators and process simulators (eg, separation simulators). In particular, the DMS application 24 could be used to define the parameter sets in a model based on physical devices or a physical model that are unknown and that could be regulated so that the simulator based on physical devices 26 could compare the data in real time that are currently observed in an oil or gas field. As discussed previously in the explanation of Figure 1, the real-time data could be measurement data received by field sensors 106 through continuous monitoring. The simulator based on physical devices 26 is operative to create models based on physical devices that represent the operation of physical systems such as deposits, wells and networks of oil and gas pipelines. For example, models based on physical devices 30 could be used to pretend the flow of fluids in a reservoir, a well or an oil pipeline network taking into account several characteristics such as the deposit area, the number of wells, the trajectory of the well, the pumping pipe radii of the well, the size of the well pumping pipe, the length of the pumping pipe, the geometry of the pumping pipe, the temperature gradient and the types of fluids that are received in the simulator based in physical devices. The simulator based on physical devices 26, during the creation of a model, could also receive estimated or uncertain inputs, such as reservoir reservations. Next with reference to Figure 3, a demonstration routine 300 will be described illustrating a process for the rapid updating of oil and gas field extraction models using a physical simulator and a proxy simulator. When reading the discussion of the illustrative routines presented in this document, it should be appreciated that the logical operations of the various embodiments of the present invention are implemented (1) as a sequence of the implemented computer stages or program modules that are executed in a computer system and / or (2) as machine logic circuits or circuit modules interconnected within the computer system. The implementation is a matter of choice according to the performance requirements of the computer system implementing the invention. Accordingly, the logic operations illustrated in Figure 3, and the embodiment of the illustrative embodiments of the present invention described herein are variously referred to as operations, structural devices, stages or modules. It will be recognized by a person skilled in the art that these operations, structural devices, stages and modules could be implemented in software, in firmware, in a digital logic of special use and any combination thereof without deviating from the spirit and scope of this invention as indicated within the claims appended thereto. The illustrative routine 300 starts in the operation 305, wherein the DMS application 24 executed by the CPU 5, instructs the simulator based on physical devices 26 to establish a "base" model of a physical system. It should be understood that a "base" model could be a physical representation or based on physical (software) devices of a reservoir, a well, a pipeline network or a processing system (such as a separation processing system) in an oil or gas field based on the characteristic data such as the deposit area, the number of wells, the trajectory of the well, the radius of the pumping pipe of the well, the size of the pumping pipe of the well, the length of the pumping piping, the geometry of the pumping piping, the temperature gradient and the types of fluids that are received in the base simulator of physical devices. The physical device base simulator 26, during the creation of a "base" model, could also receive estimated or uncertain inputs, such as deposit reservations. It should be understood that one or more base simulators of physical devices 26 could be used in the embodiments of the invention. Then, routine 300 continues from operation 305 to operation 310, where application D S 24 automatically defines uncertain parameters (ie, unknown parameters) with respect to the base model. For example, uncertain parameters could include, without limitation, the permeability through the deposit area, the outer layer of the net-to-gross well, the transmission of failure, the vertical-to-horizontal permeability ratio and the wait in cement ("WOC"). Once the uncertain parameters are defined, routine 300 then continues from operation 310 to operation 315, where the DMS application 24 defines the marginal limits for uncertain parameters. In particular, the DMS application 24 could use an experimental design process to define the marginal limits for each uncertain parameter that include end levels (for example, a maximum, an intermediate point or a minimum) of the values for each uncertain parameter. The DMS 24 application could also calculate an uncertainty distribution for each uncertain parameter. Those skilled in the art will appreciate that the distribution of uncertainty could be determined through the application of one or more probability density functions. In one modality, the experimental design process used by the DMS 24 application could be the well-known experimental design processes of the Orthogonal, Factorial or Box-Behnken series. Then, routine 300 continues from operation 315 operation 320, where DMS application 24 automatically executes the physical device base simulator 26 with respect to the set of uncertain parameters as defined by the marginal limits and the distribution of uncertainty determined in step 315. It should be understood that, from this point forward, these parameters will be referred to herein as "design" parameters. In the execution of the design parameter set, the physical device base simulator 26 generates a series of outputs that could be used to perform a number of extraction predictions. For example, the physical device-based simulator 26 could generate outputs related to fluid flow in a reservoir including without limitation, pressures, hydrocarbon flow rates, water flow rates and temperatures that are based on a range of values of permeability defined by the DMS application 24.

Next, routine 300 continues from operation 320 to operation 325, where the DMS application 24 collects the characterization data in a relationship database, such as the integrated drilling and extraction engineering database 116. Characterization data could include value ranges associated with the design parameters as determined in operation 315 (ie, the design parameter data), as well as the physical device base simulator outputs 26. Then, routine 300 continues from step 325 to step 330, where the DMS application 24 uses a regression equation for setting or adjusting the design parameter data (i.e., the relationship data of the inputs) in the outputs of the physical device base simulator 26 using a proxy model. As used in the above description and the appended claims, a proxy model is a mathematical equation used as a proxy for models based on physical devices produced by the simulator based on physical devices 26. Those skilled in the art will appreciate that in the In various embodiments of the invention, the proxy model could be a neural network, a polynomial expansion, a support vector machine, or an intelligent agent. An illustrative proxy model that could be employed in an embodiment of the invention is given by the following equation: i) It should be understood that according to one embodiment of the invention, a proxy model could be used to filter the internet traffic with a local area network simultaneously, of multiple simulators based on physical devices that foresee the flow and chemistry with respect to to time Next, the routine 300 continues from operation 330 to operation 335, where the DMS application 24 uses the proxy model to determine the sensitivities for the design parameters. As defined herein, the term "sensitivity" is a derivative of a base simulator output of physical devices 26 with respect to a design parameter within the proxy model. For example, the sensitivity could be that derived from the extraction of petroleum from hydrocarbons with respect to the permeability in the deposit. In a modality, the derivative of each output with respect to each design parameter could be calculated in the proxy model equation (shown previously). Then, routine 300 continues from operation 335 to operation 340, where the DMS application 24 uses the proxy model to calculate the correlations between the design parameters and the outputs of the physical device base simulator 26. Next, the routine 300 continues from step 340 to step 345, where the DMS application 24 removes the design parameters of the proxy model for which the sensitivities are below a threshold. In particular, according to one embodiment of the invention, the DMS application 24 could eliminate a design parameter when the sensitivity or a derivative for this design parameter, as set by the proxy model, is determined to be close to a zero value. In this way, it will be appreciated that one or more of the uncertain parameters (ie, the permeability through the reservoir area, the outer layer of the net-to-gross well, the transmission of fault, the vertical permeability ratio- a-horizontal and OC) that were discussed earlier in operation 310, could be eliminated because they are not important or because they have minimal impact. It should be understood that non-deleted or unimportant parameters are selected for optimization (i.e., the selected parameters) as will be discussed in greater detail in step 350. Then, routine 300 continues from step 345 to step 350, in where the DMS application 24 uses the real-time optimization module 28 with the proxy model to determine the value ranges for the selected parameters (i.e., the non-eliminated parameters) set in operation 345. In particular, the optimization module in real time 28 generates an unadjusted function that represents a square difference between the outputs of the proxy model and the real-time observed data that is retrieved from the field sensors 106 and that are stored in databases 114 and 116. illimitable illustrative functions for a well that could be used in the various embodiments of the invention are given by or the following equations: Obj =? w,? w, («/» < /, /) - WJ (/, /)) 2 where w ± = weight for well i, Wi = weight for time t, sim (i, t) = the simulated or normalized value for well i at time t, and his (i, t) = the historical or normalized value for well i at time t. It should be understood that the optimized value ranges that are determined by the real-time optimization module 28 are values for which the mismatched function is small (ie, almost zero). Furthermore, it should be understood that the selected parameters and the optimized value ranges are representative of a proxy model that could be executed and validated in a base simulator of physical devices 26, as will be described in more detail below.

Then, routine 300 continues from step 350 to step 355, wherein the real-time optimization module 28 places the selected parameters (determined in operation 345) and the optimized value intervals (determined in operation 350) return to the DMS application 24, which then executes the base simulator of physical devices 26 to validate the parameters selected in operation 360. It should be understood that all of the operations discussed above with respect to the DMS application 24 are automatic operations in the computer system 2. Next, routine 300 continues from operation 360 to operation 365, where the validated parameters could then be used to make extraction decisions. Then, routine 300 ends. Based on the foregoing, it should be appreciated that the various embodiments of the invention include methods, systems and means capable of being read by computer for the rapid updating of oil and gas field extraction models using a physical simulator and a proxy simulator. . A simulator based on physical devices in a dynamic evaluation model computer system is used to extend the range of possibilities for unknown parameters that are uncertain. A decision management application that runs on a computer system is used to build a proxy model that simulates a physical system (that is, a reservoir, a well, or a pipeline network). It will be appreciated that the simulation performed through the proxy model is almost instantaneous, and in this way, it is faster than traditional simulators based on physical devices that are slow and difficult to update. As a result of the proxy model, models based on physical devices are updated faster and more frequently and the design process undertaken by warehouse engineers is facilitated in this way. Although the present invention has been described in connection with various illustrative embodiments, those of ordinary skill in the art will understand that many modifications thereto can be made within the scope of the claims that follow. Accordingly, it is not intended that the scope of the invention be limited in any way by the foregoing description, but instead be determined in its entirety with reference to the claims that follow. It is noted that in relation to this date the best method known by the applicant to carry out the aforementioned invention, is that which is clear from the present description of the invention.

Claims (21)

1. CLAIMS Having described the invention as above, the content of the following claims is claimed as property: 1. A method for the rapid updating of petroleum and gas extraction models using a physical simulator and a proxy simulator, characterized in that it comprises : establish a base model of a physical system at least in a physical device base simulator, where the physical system includes at least one of a deposit, a well, a network of pipelines and a processing system, and where at least one simulator looks like the flow of fluids in at least one of the tank, a well, a network of pipelines and a processing system; define the marginal limits that include end levels and a distribution of uncertainty for each of the plurality of uncertain parameters of the physical system through an experimental design process, where the uncertain parameters as defined by the marginal limits and the distribution of uncertainty are constituted by a set of design parameters; adjust the data that includes a series of inputs, the inputs comprise the values associated with the set of design parameters, in outputs of at least one simulator that uses a proxy model, where the proxy model is a proxy for at least one simulator, at least one simulator includes at least one of the following: a tank simulator, an oil pipeline network simulator, a process simulator and a well simulator; and using an optimizer with the proxy model to determine the design parameter value ranges for which the outputs of the proxy model are compared with the observed data. The method according to claim 1, further characterized in that it comprises: using the proxy model to calculate the derivatives with respect to the design parameters of the physical system to determine the sensitivities; use the proxy model to calculate the correlations between the design parameters and the outputs of at least one simulator; classify the design parameters from the proxy model; and use the selected parameters that are validated from at least one simulator for extraction decisions. 3. The method according to claim 2, further characterized in that it comprises: using a decision management system that defines a plurality of control parameters of the physical system for comparison with the observed data; automatically execute at least one simulator with respect to the set of design parameters to generate a series of outputs, the outputs represent extraction predictions; and collecting the characterization data in a relationship database, the characterization data includes values associated with the set of design parameters and the values associated with the outputs of at least one simulator. 4. The method according to claim 3, further characterized by comprising: placing the design parameters for which the sensitivities are not below the threshold and their proxy model intervals in the decision management system, the parameters of design for which the sensitivities are not below the threshold are the selected parameters; and executing the decision management system as a global optimizer to validate the selected parameters in at least one simulator. The method according to claim 1, characterized in that the establishment of a base model of a physical system at least in a base simulator of physical devices comprises the creation of a representation of data of the physical system, wherein the representation The data includes the physical characteristics of at least one of the deposit, the well, the pipeline network and the processing system including the dimensions of the deposit, the number of wells in the reservoir, the trajectory of the well, the size of the pumping piping in the well, the geometry of the pumping piping, the temperature gradient, the types of fluids and the estimated values of data from other parameters associated with the physical system. 6. The method according to claim 1, characterized in that the definition of the marginal limits that include end levels and an uncertainty distribution for each of the plurality of uncertain parameters of the physical system through an experimental design process comprises Define the marginal limits that include end levels and the uncertainty distribution of the parameters of permeability, transmission of failure, pore volume and inner layer of well, using at least one of the experimental design processes of Orthogonal, Factorial and Box-Behnken. The method according to claim 1, characterized in that the use of the proxy model to calculate the derivatives with respect to the design parameters in order to establish the sensitivities comprises determining a derivative of an output of at least one simulator with respect to to one of the series of entries. 8. The method according to claim 1, further characterized in that it comprises removing the design parameters of the proxy model that are determined by the user because they have a minimal impact on the physical system. The method according to claim 1, characterized in that the use of an optimizer with the proxy model to determine the design parameter value ranges comprises the use of the optimizer with at least one of the following: a neural network, a polynomial expansion, a support vector machine and an intelligence agent. 10. A system for the rapid updating of oil and gas field extraction models using a physical simulator and a proxy simulator, characterized in that it comprises: a memory that stores an executable program code; and a processor, functionally connected to the memory, the processor is sensitive to instructions that can be executed by computer that are contained in the program code and is operative to: establish a base model of a physical system at least in a physical device base simulator, where the physical system includes at least one of a reservoir, a well, a pipeline network and a processing system, and where at least one simulator appears to be at least fluid flow in one of the deposit, a well, a network of pipelines and a processing system; define the marginal limits that include end levels and a distribution of uncertainty for each of the plurality of uncertain parameters of the physical system through an experimental design process, where the uncertain parameters as defined by the marginal limits and the distribution of uncertainty are constituted by a set of design parameters; adjust the data that includes a series of inputs, the inputs comprise the values associated with the set of design parameters, in outputs of at least one simulator that uses a proxy model, where the proxy model is a proxy for at least one simulator, at least one simulator includes at least one of the following: a tank simulator, an oil pipeline network simulator, a process simulator and a well simulator; and using an optimizer with the neural network to determine the design parameter value ranges for which the outputs of the proxy model are compared with the observed data. 11. The system in accordance with the claim 10, further characterized in that the processor is operative to: use the proxy model to calculate the derivatives with respect to the design parameters of the physical system to determine the sensitivities; use the proxy model to calculate the correlations between the design parameters and the outputs of at least one simulator; classify the design parameters from the proxy model; and use the selected parameters that are validated from at least one simulator for extraction decisions. 12. The system in accordance with the claim 11, further characterized in that the processor is operative to: use a decision management system that defines a plurality of control parameters of the physical system for comparison with the observed data; automatically execute at least one simulator with respect to the set of design parameters to generate a series of outputs, the outputs represent extraction predictions; and collecting the characterization data in a relationship database, the characterization data includes values associated with the set of design parameters and the values associated with the outputs of at least one simulator. 13. The system in accordance with the claim 12, further characterized in that the processor is operative to: place the design parameters for which the sensitivities are not below the threshold and their proxy model intervals in the decision management system, the design parameters for which the Sensibilities not found below the threshold are the selected parameters; and executing the decision management system as a global optimizer to validate the selected parameters in at least one simulator. 14. The system according to claim 10, characterized in that the establishment of a base model of a physical system at least in a basic simulator of physical devices comprises the creation of a data representation of the physical system, wherein the Data representation includes the physical characteristics of at least one of the reservoir, the well, the pipeline network and the processing system including the dimensions of the reservoir, the number of wells in the reservoir, the path of the well, the size of the pipeline pumping of the well, the geometry of the pumping pipe, the temperature gradient, the types of fluids and the estimated data values of other parameters associated with the physical system. 15. The system in accordance with the claim 10, characterized in that the definition of the marginal limits that include end levels and an uncertainty distribution for each of the plurality of uncertain parameters of the physical system through an experimental design process comprises defining the marginal limits that includes extreme levels. and the uncertainty distribution of the parameters of permeability, transmission of failure, pore volume and inner layer of the well, using at least one of the experimental design processes of the Orthogonal, Factorial and Box-Behnken series. 16. The system according to claim 10, characterized in that the use of the proxy model to calculate the derivatives with respect to the design parameters in order to establish the sensitivities comprises determining a derivative of an output of at least one simulator with respect to to one of the series of entries. 17. The system according to claim 10, further characterized in that it comprises removing the design parameters of the proxy model that are determined by the user because they have a minimal impact on the physical system. 18. The system according to claim 10, characterized in that the use of an optimizer with the proxy model to determine the design parameter value ranges comprises the use of the optimizer with at least one of the following: a neural network, a polynomial expansion, a support vector machine and an intelligence agent. 19. A computer-readable medium containing instructions that can be executed by computer, which, when executed on a computer, perform a method for the rapid updating of oil and gas extraction models using a physical simulator and a proxy simulator, characterized in that the method comprises: establishing a basic model of a physical system at least in a basic simulator of physical devices, where the physical system includes at least one of a deposit, a well, a pipeline network and a processing system, and wherein at least one simulator appears to flow fluid in at least one of the reservoir, a well, a pipeline network and a processing system; define the marginal limits that include end levels and a distribution of uncertainty for each of the plurality of uncertain parameters of the physical system through an experimental design process, where the uncertain parameters as defined by the marginal limits and the distribution of uncertainty are constituted by a set of design parameters; adjust the data that includes a series of inputs, the inputs comprise the values associated with the set of design parameters, in outputs of at least one simulator that uses a proxy model, where the proxy model is a proxy for at least one simulator, at least one simulator includes at least one of the following: a tank simulator, an oil pipeline network simulator, a process simulator and a well simulator; and using an optimizer with the proxy model to determine the design parameter value ranges for which the outputs of the proxy model are compared with the observed data. 20. The computer-readable medium according to claim 18, further characterized in that it comprises: using the proxy model to calculate the derivatives with respect to the design parameters of the physical system to determine the sensitivities; use the proxy model to calculate the correlations between the design parameters and the outputs of at least one simulator; classify the design parameters from the proxy model; and use the selected parameters that are validated from at least one simulator for extraction decisions; using a decision management system that defines a plurality of control parameters of the physical system for comparison with the observed data; automatically execute at least one simulator with respect to the set of design parameters to generate a series of outputs, the outputs represent extraction predictions; and collecting the characterization data in a relationship database, the characterization data includes values associated with the set of design parameters and the values associated with the outputs of at least one simulator. 21. The medium capable of being read by computer according to claim 20, further characterized because it comprises: placing the design parameters for which the sensitivities are not below the threshold and their proxy model intervals in the administration system of decision, the design parameters for which the sensitivities are not below the threshold are the selected parameters; and executing the decision management system as a global optimizer to validate the selected parameters in at least one simulator.