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  • 专利说明
  • 权利要求
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    • 专利摘要:
    Systems and methods of the present invention relate to reservoir simulation modeling using rock compaction tables derived from physical pore compressibility tests. The illustrative methods transform rock mechanics-based pore compressibility tests into compliant rock compaction tables for reservoir simulators using dimensionless conversion of pore pressure stress to thereby transfer geomechanical changes due to stress. confinement in expressions of geomechanical changes due to interstitial pressure.
    公开号:FR3073556A1
    申请号:FR1858075
    申请日:2018-09-09
    公开日:2019-05-17
    发明作者:Travis St.George Ramsay
    申请人:Landmark Graphics Corp；
    IPC主号:
    专利说明:

    CONVERSION OF ROCK MECHANICAL DATA OF A CONTAINMENT CONSTRAINT INTO INTERSTITIAL PRESSURE FOR TANK SIMULATORS
    FIELD OF THE INVENTION
    The present invention relates to reservoir simulation and, more specifically, the conversion of rock mechanics data obtained from pore compressibility tests into rock compacting tables for a reservoir simulator using dimensionless conversion of the stress to pore pressure.
    CONTEXT
    In the oil and gas industry, the most widely accepted phases of work to carry out production-induced compaction studies are probably to perform a coupled reservoir and geomechanical simulation which takes into account the mechanics of fluids and solids and move. However, such methods are generally more costly and time-consuming due to the use of disparate simulators or a single multi-physical simulator. As a result, practitioners often deny the effects of coupled geomechanics in their modeling at the expense of their ability to accurately predict the response of their asset to production. Alternatively, practitioners use the incorporation of pore volume and pressure transmissibility multipliers in reservoir simulation studies using rock compaction tables, as a pseudo-representation of structural changes in underground passages caused by production. However, this approach does not capture all of the physics from the interaction of structural and hydrodynamic phenomena that occur as a result of production from the reservoir.
    BRIEF DESCRIPTION OF THE DRAWINGS
    Figure 1 is a flow diagram of a generalized method for simulating a reservoir, according to certain illustrative embodiments of the present invention.
    FIG. 2 is a flow diagram of a detailed method intended to simulate a reservoir, according to an illustrative embodiment of the present description.
    FIG. 3A is an illustrative graph representing the changes in porosity as a function of the confinement stress for a certain number of rock samples.
    Figure 3B is an illustrative graph showing the changes in permeability as a function of the confining stress for a number of rock samples.
    2017-IPM-101196-U1-EN
    FIG. 3C is an illustrative plot of the pore volume multiplier calculated as a function of the pore pressure.
    Figure 3D is an illustrative plot of the permeability multiplier calculated as a function of pore pressure.
    FIG. 4A is a plot representing the ratio of dry rock / bulk mineral module calculated for the mechanical data of the original rocks and modeled according to the present invention, providing validation of the illustrative methods.
    Figure 5 is a block diagram illustrating an example of a computer system in which embodiments of the present invention can be implemented.
    DESCRIPTION OF ILLUSTRATIVE EMBODIMENTS
    Illustrative embodiments and related methods of the present invention are described below, to the extent that they could be used in systems and methods for deriving rock compaction tables from physical core compressibility tests for use in a tank simulation. For the sake of clarity, all the characteristics of an implementation or of a real process are not described in this description. It will of course be understood that in the development of any real embodiment of this type, many implementation-specific decisions must be made to achieve the specific objectives of the engineers, such as compliance with system constraints and to the company, which will vary from one implementation to another. Furthermore, it will be understood that such a development effort could be complex and tedious, but would nevertheless constitute a routine undertaking for those skilled in the art having the advantage of this invention. Other aspects and advantages of the various embodiments and related methods of this invention will become apparent from the following description and drawings.
    As described herein, illustrative systems and methods of this specification relate to reservoir simulation models using rock compaction tables derived from physical core compressibility tests. Illustrative processes transform pore compressibility tests based on rock mechanics into conformal rock compaction tables for reservoir simulators using dimensionless conversion of stress to pore pressure (“DSPC”) to thereby transfer geomechanical changes due to a confinement constraint in expressions of geomechanical changes due to pore pressure. The hypothesis underlying the development of the model transform of the effects of a confinement constraint (namely
    2017-IPM-101196-U1-FR a constraint surrounding the rock on all sides) in those of an interstitial pressure (i.e. a pressure of fluid towards the outside inside pores of the rock due, for example , to the injection of fluid), is a completely linear elastic response of porous media, so that the variations of the pore space due to a confinement stress are proportional to the changes of the pore space due to a pressure interstitial.
    In a generalized process of the present description, the rock mechanics data are obtained from one or more pore compressibility tests. The rock mechanics data are expressed as a function of the confinement stress. The rock mechanics data are then converted from a confinement stress function to a pore pressure function using the DSPC. Rock compaction tables are generated using the mechanics data of the converted rocks. The rock compaction tables are entered into a reservoir simulator in order to run a reservoir simulation model, which can be used to assess and / or predict various asset operations. Consequently, the reservoir model simulates changes in the mechanical data of the converted rocks generated as a function of the confinement stress as expressions of the changes in the reservoir simulation due to pore pressure.
    Illustrative embodiments and related methods of the present invention are described below with reference to Figures 1 to 5 to the extent that they could be employed, for example, in a computer system for reservoir simulation and analysis of data. An illustrative tank simulator is the Nexus® Suite tank simulation platform, commercially available from Landmark Graphies Corp. from Houston, TX. Other characteristics and advantages of the embodiments described will be or will become obvious to those skilled in the art on examining the figures and the detailed description below. It is understood that all of these additional features and advantages are included in the scope of the described embodiments. In addition, the figures illustrated are only illustrative and are not intended to assert or imply any limitation with respect to the environment, architecture, design or process in which different embodiments can be implemented. artwork.
    Figure 1 is a flow diagram of a generalized method for simulating a reservoir, according to certain illustrative embodiments of the present invention. In block 102 of method 100, the rock mechanics data performed on nuclei are obtained by a computer system and expressed as a function of the confinement constraint. Rock mechanics data can be obtained in various ways, such as carrying out a pore volume compressibility test as a function of the confinement stress. In the
    2017-IPM-101196-U1-FR test, the confining stress of a core is increased, then the porosity and permeability are measured at a given confining stress. At block 104, the computer system converts rock mechanics data from expressions of confinement stress into expressions of pore pressure. As described in more detail below, the reservoir models provided here take data from rock mechanics performed on nuclei, which are measured at different confinement constraints, and define an appropriate transform to model the corresponding property multipliers as a function pore pressure. In block 106, the computer system generates one or more rock compacting tables, which are then included in a reservoir simulation model in block 108. Subsequently, the generated reservoir model can be used to simulate and / or perform asset operations on reservoirs, such as predicting well production or assessing production mechanisms.
    Illustrative reservoir simulation models assume constant pore space rigidity, and model validation can be performed by evaluating whether the modeled property multipliers, created as a function of pore pressure, converge in the same family of relationship ratios. interstitial space / mineral mass modulus. Small differences in association between measured and modeled data indicate a very high level of model accuracy, while larger differences indicate poor quality of the model. As such, the models can be validated.
    In view of the generalized method above, a more detailed description of the present invention will be provided with reference to Figure 2, which is a flow diagram of method 200 according to an illustrative embodiment of the present invention. At block 202, rock mechanics data is collected from pore compressibility test data. The rock mechanics data include porosity and / or permeability data (also called here "property data") as a function of the confinement stress. Figure 3A is an illustrative graph showing the porosity changes as a function of the confinement stress for a number of rock samples. Figure 3B is an illustrative graph showing the changes in permeability as a function of the confining stress for a number of rock samples. The data in the two figures 3 A and 3 B were obtained from compressibility tests of rock mechanics.
    In block 204, the measured property data of block 202 are analyzed as a function of the confinement constraint. Here, the computer system guarantees that the property data (porosity or permeability, for example) are represented as a fraction and not as a percentage. The associations between property data and the constraint of
    2017-IPM-101196-U1-FR containment are also determined. Linear elasticity is assumed, so there must be a linear association between the rock mechanical property data and the confining stress, but there may be different degrees of correlation, as shown in Figures 3A and 3B.
    At block 206, the computer system performs the DSPC on the confinement constraint data of block 202. At this moment, the computer system normalizes the maximum confinement constraint value to the unit (ie at 1) and all the others. confinement stress values to a value less than unity. The confining stress values can then be called the normalized pressure response. In block 208, the computer system normalizes the property data measured as a function of the confinement stress of block 202 to its respective porosity / permeability of maximum amplitude in the pore compressibility test. In this way, the maximum normalized porosity / permeability becomes unity and the porosity / permeability measured at the maximum confinement stress becomes a value less than unity. The standardized porosity / permeability represents the respective “property multiplier”. The property multiplier is the scaling parameter which, multiplied by the reference property value of the unit, leads to a dimensional description of the desired property for a specific confinement constraint.
    At block 210, the computer system mathematically projects the normalized stress response of block 206 so that it is dimensioned symmetrically above the unit. The explanatory variable (i.e., the x-axis variable) is not considered to be converted from the confining constraint to pore pressure. As it is symmetrically dimensioned above the unit, the minimum pore pressure is equal to the unit and the maximum pore pressure is 2. This can be called a symmetric normalized pressure response.
    In block 212, the computer system plots the symmetric normalized pressure response of block 210 as a function of the normalized porosity / permeability of block 208. Thereafter, the equation of the trend curve describing the association between the predictor (pressure interstitial) and the normalized pressure response variable (porosity / permeability) is calculated. The trendline equation can be calculated, for example, in a spreadsheet using endpoints in the plot to calculate a slope and then derive the intercept, as humans would understand. of the trade benefiting from this invention.
    At block 214, the computer system reverses the range of the normalized pressure response of block 212 so that it is in ascending order. The computer system then resizes the pore pressure range so that the value
    2017-IPM-101196-U1-FR maximum is equal to one. In some illustrative methods, the computer system can do this by subtracting the normalized pressure from the maximum pressure value of 2 from block 212.
    In block 216, the computer system develops a resizing model of the property multiplier (porosity / permeability multiplier) from block 208 using the trend curve of block 212. To achieve this in certain illustrative embodiments, the substitution in the inverse normalized pressure trend curve for block 214 is used to calculate the property multiplier. In this way, a function based on the tendency of the property multiplier as a function of the inverse normalized pressure is obtained. This newly resized property multiplier is then plotted as a function of the inverse normalized pressure of block 214.
    Then, at block 218, the computer system resizes the normalized pressure resized from block 214 to dimensional pressure. Here, in order to maintain the correct sizing of the property multiplier and the normalized pressure, the computer system sizes the slope of the trend curve of block 216 according to the difference in minimum and maximum dimensional pressures. Subsequently, the computer system plots the property multiplier as a function of the dimensional pore pressure. At block 220, the system performs a reservoir simulation using the dimensional pressure model. Figure 3C is an illustrative plot of the pore volume multiplier, or porosity, calculated as a function of pore pressure. Figure 3D is an illustrative plot of the permeability multiplier calculated as a function of pore pressure. Figures 3C and 3D are also known as rock compaction tables / curves.
    The computer system can then generate the rock compacting tables, which are tables characterized as being dimensional property multipliers (for example, pore volume, porosity or permeability) as a function of pore pressure, unlike the original confinement stress used in the rock mechanics test. The rock compaction tables can be used by the computer system to execute a reservoir simulation model which integrates a structural and hydrodynamic interaction resulting from the production of hydrocarbons, for example via a user computer station , from a cluster or cloud computer network. The reservoir model can be used to analyze or predict well production for a given well, or to assess the mechanisms governing the production of a planned or operational well.
    2017-IPM-101196-U1-EN
    As mentioned earlier, in some illustrative methods, the generated reservoir model can be validated by evaluating whether the modeled property multipliers, created as a function of pore pressure, converge in the same family of pore space modulus / mass ratio. mineral. FIG. 4A is a plot of this validation, representing the ratio of dry rock module / mineral mass calculated for the original rock mechanics data and modeled. Note that FIG. 4A only shows the porosity and the ratio of dry rock modulus / mineral mass. It is noted that the ratio of dry rock modulus / mineral mass calculated for the rock mechanics laboratory data is calculated as a function of the confinement stress (orig) and the property multipliers of modeled rocks (mod) are calculated in function of pore pressure. Constant lines of the pore space modulus / mineral mass ratio are provided to confirm that the modeled properties coincide with the original laboratory data. Small differences in association between measured and modeled data indicate a higher level of model accuracy, while large differences indicate poor quality of the model. As illustrated in Figure 4A, the small differences between the original rock mechanics laboratory data and the modeled pore pressure data emphasize the accuracy of the model generated using the illustrative methods provided herein.
    In one or more illustrative embodiments, a visual representation of various tank patterns and models can be displayed to a user through a GUI graphical interface of a tank simulation application executable on the computing device of the tank. 'user. Such a computing device can be implemented with any type of device comprising one or more processors, user input (for example a mouse, a QWERTY keyboard, a touch screen, a graphic tablet or a microphone), a screen and a communication infrastructure capable of receiving and transmitting data via a network. An example of such a computing device will be described in more detail below with reference to FIG. 5.
    FIG. 5 is a block diagram illustrating an example of a computer system 500 in which embodiments of the present invention can be implemented. For example, the methods 100 or 200 of FIGS. 1 and 2, as described above, can be implemented using the system 500. The system 500 can be a computer, a telephone, a PDA or any other type of electronic device. This electronic device includes different types of computer readable media and interfaces for various other types of computer readable media. As shown in Figure 5, the system 500 includes a permanent storage device 502, a system memory 504, a device interface
    2017-IPM-101196-U1-FR output 506, a system communication bus 508, a read-only memory (“ROM”) 510, one or more processing units 512, an input device interface 514 and an interface for network 516.
    The bus 508 collectively represents any system, peripheral, and chipset bus which communicatively connect the numerous internal devices of the system 500. For example, the bus 508 communicatively connects the processing unit or units 512, the ROM 710, the system memory 504 and the permanent storage device 502. From these different memory units, the processing unit or units 512 retrieve the instructions to be executed and the data to be processed in order to execute the methods of the present invention. The processing unit (s) can be a single processor or a multicore processor in different implementations.
    The ROM 510 stores static data and instructions which are necessary for the processing unit or units 512 and other modules of the system 500. The permanent storage device 502, on the other hand, is a storage memory device. read-write type. This device is a non-volatile memory unit that stores instructions and data, even when the system 500 is turned off. Certain implementations of the present invention use a mass storage device (such as a magnetic or optical disc and its corresponding disc drive) as a permanent storage device 502.
    Other implementations use a removable storage device (such as a floppy disk, a flash drive, and its corresponding disk drive) as a permanent storage device 502. Like the permanent storage device 502, the system memory 504 is a memory device of the read-write type. However, unlike the storage device 502, the system memory 504 is a volatile read-write type memory, such as a random access memory. System memory 504 stores some of the instructions and data that the processor needs during execution. In certain implementations, the methods of the present invention are stored in the system memory 504, the permanent storage device 502 and / or the ROM 510. From these different memory units, the processing unit or units 512 recover the instructions to be executed and the data to be processed in order to execute the processes of certain implementations.
    Bus 508 also connects to the input and output device interfaces 514 and 506. The input device interface 514 allows the user to communicate information and select commands for the system 500. The devices Input devices used with the input device interface 514 include, for example, alphanumeric, QWERTY or T9 keyboards, microphones, and pointing devices (also called "cursor control devices"). 506 output device interfaces
    2017-IPM-101196-U1-FR allow, for example, the display of images generated by the 500 system. The output devices used with the output device interface 506 include, for example, printers and displays, such as cathode ray tubes ("TRC") or liquid crystal displays ("LCD"). Some implementations include devices, such as a touch screen, which function as both input and output devices. It should be noted that embodiments of the present invention can be implemented using a computer comprising any of various types of input and output devices to allow interaction with a user. This interaction may include the feedback of information to or from the user in various forms of sensory feedback including, but not limited to, visual feedback, auditory feedback, or tactile feedback. In addition, user input can be received in any form including, but not limited to, acoustic, voice, or touch input. In addition, interaction with the user may include the transmission and reception of different types of information, for example in the form of documents, to and from the user via the interfaces described below. -above.
    Also, as shown in FIG. 5, the bus 508 also connects the system 500 to a public or private network (not shown) or to a combination of networks via a network interface 516. This network can include, for example, a local area network ("LAN"), such as an intranet, or a wide area network ("WAN"), such as Internet. Each or all of the components of the system 500 can be used in conjunction with the present invention.
    These functions described above can be implemented in digital electronic circuits, computer software, firmware or computer hardware. The techniques can be implemented using one or more computer program products. Programmable processors and computers can be included in, or grouped as, mobile devices. Logic processes and flows can be performed by one or more programmable processors and by one or more programmable logic circuits. Computing and general and special storage devices can be interconnected via communication networks.
    Some implementations include electronic components, such as microprocessors, storage and memory devices that store computer program instructions on machine-readable or computer-readable media (also called computer-readable storage media, readable media by machine, or machine-readable storage media). Some examples of these supports readable by
    2017-IPM-101196-U1-FR computer include RAM, ROM, read only compact discs ("CD-ROM"), writable compact discs ("CD-R"), rewritable compact discs ("CD-RW" ”), Versatile digital read-only discs (for example, DVD-ROM, double-layer DVD-ROM), a variety of recordable / rewritable DVDs (for example, DVD-RAM, DVD-RW, DVD + RW, etc.). ), flash memory (e.g. SD cards, mini-SD cards, micro-SD cards, etc.), magnetic and / or solid state hard disk drives, memory Blu-Ray® discs dead or recordable, very high density optical discs, all other optical or magnetic media, and flexible floppy disks. The computer-readable media can store a computer program executable by at least one processing unit and include sets of instructions for performing various operations. Examples of computer programs or computer codes include machine code, as produced by a compiler, and files comprising higher level code which are executed by a computer, electronic component, or a microprocessor using an interpreter.
    Although the above discussion mainly refers to a microprocessor or multicore processors that run the software, some implementations are performed by one or more integrated circuits, such as application-specific integrated circuits ("ASIC") or user programmable pre-broadcast matrices ("FPGA"). In some implementations, these integrated circuits execute instructions stored on the circuit itself. Consequently, the methods 100 or 200, as described above, can be implemented using the system 500 or any computer system comprising a processing circuit or a computer program product containing instructions stored thereon which, when they are executed by at least one processor, make the processor perform functions relating to these processes.
    As used in this description and all the claims of this application, the terms "computer", "server", "processor", and "memory" all mean electronic or other technological devices. These terms exclude individuals or groups of individuals. As used herein, the terms "computer readable media" and "computer readable media" generally refer to tangible, physical, non-transient electronic storage media that store information in a computer-readable format.
    Embodiments of the object described in this description can be implemented in a computer system which comprises a back-end component, for example a data server, or which comprises an intermediate component, for example an application server or which includes a front end, for example, a client computer
    2017-IPM-101196-U1-FR having a graphical user interface or a web browser through which a user can interact with an implementation of the object described in this description, or any combination of one or more of these back-end components , intermediate or frontal. The components of the system can be interconnected by any form or medium of digital data communication, for example a communication network. Examples of communication networks include a LAN and a WAN, an internetwork (for example the Internet), and peer-to-peer networks (for example peer-to-peer ad hoc networks).
    The computer system can include clients and servers. A client and a server are generally distant from each other and usually interact via a communication network. The client and server relationship derives from computer programs executed on the respective computers and which have a client-server relationship with each other. In some embodiments, a server transmits data (for example, a web page) to a client device (for example, for the purpose of displaying data to a user and receiving user input from an interacting user with the client device). Data generated at the client device (for example a result of user interaction) can be received from the client device on the server.
    It is understood that any specific order or hierarchy of steps in the methods described is an illustration of examples of approach. Depending on the design preferences, it is understood that the specific order or hierarchy of steps in the processes can be rearranged, or that all of the illustrated steps can be carried out. Some of the steps can be done simultaneously. For example, in some cases multitasking and parallel processing may be advantageous. Furthermore, the separation of different components of the system in the embodiments described above should not be understood as indicating that this separation is necessary in all embodiments, and it should be understood that the components and systems of programs described can generally be integrated together into a single software product or grouped into several software products.
    Accordingly, the illustrative embodiments described herein provide improved reservoir simulation models generated using rock compaction tables which express changes in the geomechanical processes of the reservoirs due to pore pressure. This is advantageous because the pore pressure is modeled in the tank simulator; the confinement constraint is not. If the porosity / pore volume / permeability are not expressed as a function of pore pressure, it will be impossible to model their changes in the reservoir simulator. The present invention has a number of other advantages. It provides: a
    2017-IPM-101196-U1-FR reproducible method for calculating variations in rock property as a function of pore pressure data data measured as a function of the confinement stress; an intrinsic consideration of the property of rocks during the construction of rock compacting tables for modeling the compressibility of pore volume in reservoir simulations; it promotes: the existing capacity for modeling rock compaction as a function of pore pressure in Nexus®; the ability to identify the 4D anomalies attributed (such as the stress arc) to changes in properties of saturated rocks using reservoir simulation in the absence of a coupled geomechanical model; and it increases accuracy while maintaining a simplified approach to modeling rock compaction in a reservoir simulation model. In addition, the cost of acquiring additional rock mechanical test data based on pore pressure is canceled for the end user and the time required to acquire the rock mechanical data is short, the present invention can therefore be easily integrated into existing work phases without significant load for end users.
    Embodiments and methods of the present invention described herein also relate to any one or more of the following paragraphs:
    1. Reservoir simulation method implemented by computer, consisting in obtaining rock mechanics data from a pore compressibility test, the rock mechanics data being expressed as a function of a confinement constraint; converting the rock mechanics data from a function of the confining stress to a function of the pore pressure using a dimensionless conversion of the stress into pore pressure ("DSPC"); generating one or more rock compacting tables using the mechanical data of the converted rocks; and inputting data from the rock compaction table into a reservoir simulator to thereby generate a reservoir model, in which the reservoir model can be used to assess well production.
    2. Process implemented by computer as defined in paragraph 1, in which the porosity or permeability data as a function of the confinement stress are obtained from the rock mechanics data.
    3. Computer-implemented method as defined in paragraphs 1 or 2, in which the reservoir model simulates changes in the mechanical data of the converted rocks generated as a function of the confinement stress as expressions of changes in the simulation of reservoir due to pore pressure.
    4. Computer-implemented method as defined in any one of paragraphs 1 to 3, wherein the conversion of rock mechanics data to
    2017-IPM-101196-U1-EN function of pore pressure includes determining a supposed linear association which is supposed to exist between the rock mechanics data and the confinement stress, the rock mechanics data being composed of data porosity or permeability; representing rock mechanics data as a fraction; using DSPC, normalizing rock mechanics data so that a maximum containment stress value is 1 and all other containment stress values are less than 1, in which the values of containment stress represent a normalized stress response; the use of DSPC, normalization of rock mechanics data so that a maximum value of porosity and permeability is equal to 1 and a value of porosity and permeability for a value of maximum confinement stress is less than 1, in which the normalized porosity and permeability values represent porosity and permeability multipliers; projecting the normalized stress response to be symmetrical above 1, thereby converting the confining stress into pore pressure, wherein the pore pressure values represent a normalized pressure response; plotting the symmetric normalized pressure response as a function of the normalized porosity and permeability values, and calculating a trend curve equation describing an association between the symmetric normalized pressure response and the porosity and standardized permeability; resizing a range of the symmetric normalized pressure response so that the maximum pore pressure value is 1; the use of the trend curve, the generation of a resizing model of the porosity and permeability multipliers; resizing the resized range of the symmetric normalized pressure response to dimensionless pore pressure using the DSPC; and plotting the resized porosity and permeability multipliers according to dimensionless pore pressure, thus representing compaction tables that can be included in the execution of a reservoir model to associate the pore pressure changes with the multipliers that model the porosity or permeability of an underground system.
    5. A computer-implemented method as defined in any one of paragraphs 1 to 4, in which the reservoir model is used to predict the production of wells or to assess the mechanisms governing production.
    6. A tank simulation system, the system comprising a non-transient memory storing rock mechanics data; and one or more hardware processors coupled to the non-transient memory and configured to execute instructions for the system to perform operations including: obtaining mechanical data from the
    2017-IPM-101196-U1-EN rocks from a pore compressibility test, the rock mechanics data being expressed as a function of a confinement constraint; converting rock mechanics data from a confinement stress function to a pore pressure function using a dimensionless conversion of the stress to pore pressure (“DSPC”); the generation of one or more rock compacting tables using the mechanical data of the converted rocks; and inputting the data from the rock compaction table into a reservoir simulator to thereby generate a reservoir model, in which the reservoir model can be used to perform well drilling operations.
    7. System as defined in paragraph 6, in which the porosity or permeability data as a function of the confinement stress are obtained from the rock mechanics data.
    8. System as defined in paragraphs 6 or 7, in which the reservoir model simulates changes in the mechanical data of the converted rocks generated as a function of the confinement stress as expressions of the changes in the reservoir simulation due to pressure interstitial.
    9. A system as defined in any one of paragraphs 6 to 8, in which the conversion of rock mechanics data to pore pressure includes determining an assumed linear association which is believed to exist between the data rock mechanics and confinement stress, the rock mechanics data being composed of porosity or permeability data; representing rock mechanics data as a fraction; using a DSPC, normalizing rock mechanics data so that a maximum containment stress value is 1 and all other containment stress values are less than 1, in which the values containment stress represent a normalized stress response; the use of a DSPC, the normalization of rock mechanics data so that a maximum value of porosity and permeability is equal to 1 and a value of porosity and permeability for a value of maximum confinement stress is lower at 1, in which the normalized porosity and permeability values represent porosity and permeability multipliers; projecting the normalized stress response to be symmetrical above 1, thereby converting the confining stress into pore pressure, wherein the pore pressure values represent a normalized pressure response; plotting the symmetric normalized pressure response as a function of the normalized porosity and permeability values, and calculating a trend curve equation describing an association between the symmetric normalized pressure response and the porosity and permeability
    2017-IPM-101196-U1-FR standardized; resizing a range of the symmetric normalized pressure response so that the maximum pore pressure value is 1; the use of the trend curve, the generation of a resizing model of the porosity and permeability multipliers; resizing the resized range of the symmetric normalized pressure response to dimensionless pore pressure using a DSPC; and plotting the resized porosity and permeability multipliers according to dimensionless pore pressure, thus representing compaction tables that can be included in the execution of a reservoir model to associate the pore pressure changes with the multipliers that model the porosity or permeability of an underground system.
    10. A system as defined in any one of paragraphs 6 to 9, in which the reservoir model is used to predict the production of wells or to assess the mechanisms governing production.
    In addition, the illustrative methods described herein can be implemented by a system comprising a processing circuit or a non-transient computer readable medium comprising instructions which, when executed by at least one processor, cause the processor any of the methods described here.
    Although various embodiments and methods have been shown and described, the present invention is not limited to such embodiments and methods and will be understood to include all modifications and variations which would be obvious to those skilled in the art. Therefore, it should be understood that this invention is not intended to be limited to the particular forms described. On the contrary, the intention is to cover all the modifications, all the equivalents and all the alternatives coming within the spirit and the field of application of the invention as defined by the appended claims.
    权利要求:
    Claims (11)
    [1" id="c-fr-0001]
    1. Method of reservoir simulation implemented by computer, comprising:
    obtaining rock mechanics data from a pore compressibility test, the rock mechanics data being expressed as a function of a confinement constraint;
    converting rock mechanics data from a confinement stress function to a pore pressure function using a dimensionless conversion of the stress to pore pressure (“DSPC”);
    generation of one or more rock compacting tables using the converted rock mechanics data; and inputting the data from the rock compaction table into a reservoir simulator to thereby generate a reservoir model, in which the reservoir model can be used to assess well production.
    [2" id="c-fr-0002]
    2. Process implemented by computer according to claim 1, in which the porosity or permeability data as a function of the confinement stress are obtained from the rock mechanics data.
    [3" id="c-fr-0003]
    The computer implemented method of claim 2, wherein the reservoir model simulates changes in the mechanical data of the converted rocks generated as a function of the confinement stress as expressions of changes in the reservoir simulation due to the pore pressure.
    [4" id="c-fr-0004]
    4. A computer-implemented method according to any one of claims 1 to 3, in which the conversion of the rock mechanics data into a function of the pore pressure comprises:
    determining a supposed linear association which is supposed to exist between the rock mechanics data and the confinement stress, the rock mechanics data being composed of porosity or permeability data;
    representing rock mechanics data as a fraction;
    using DSPC, normalizing rock mechanics data so that a maximum containment stress value is 1 and all other containment stress values are less than 1, in which the values of containment stress represent a normalized stress response;
    2017-IPM-101196-U1-EN the use of DSPC, normalization of rock mechanics data so that a maximum value of porosity and permeability is equal to 1 and a value of porosity and permeability for a maximum confinement stress value is less than 1, in which the normalized porosity and permeability values represent porosity and permeability multipliers;
    projecting the normalized stress response to be symmetrical above 1, thereby converting the confining stress into pore pressure, wherein the pore pressure values represent a normalized pressure response;
    plotting the symmetric normalized pressure response as a function of the normalized porosity and permeability values, and calculating a trend curve equation describing an association between the symmetric normalized pressure response and the porosity and standardized permeability;
    resizing a range of the symmetric normalized pressure response so that the maximum pore pressure value is 1;
    the use of the trend curve, the generation of a resizing model of the porosity and permeability multipliers;
    resizing the resized range of the symmetric normalized pressure response to dimensionless pore pressure using the DSPC; and plotting the resized porosity and permeability multipliers according to dimensionless pore pressure, thus representing compaction tables that can be included in the execution of a reservoir model to associate the pore pressure changes with the multipliers that model the porosity or permeability of an underground system.
    [5" id="c-fr-0005]
    The computer-implemented method of any of claims 1 to 4, wherein the reservoir model is used to predict the production of wells or to assess the mechanisms governing production.
    [6" id="c-fr-0006]
    6. Tank simulation system, the system comprising:
    a non-transient memory storing rock mechanics data; and one or more hardware processors coupled to the non-transient memory and configured to execute instructions for the system to perform operations comprising:
    2017-IPM-101196-U1-FR obtaining rock mechanics data from a pore compressibility test, the rock mechanics data being expressed as a function of a confinement constraint;
    converting rock mechanics data from a confinement stress function to a pore pressure function using a dimensionless conversion of the stress to pore pressure (“DSPC”);
    the generation of one or more rock compacting tables using the mechanical data of the converted rocks; and inputting the data from the rock compaction table into a reservoir simulator to thereby generate a reservoir model, in which the reservoir model can be used to perform well drilling operations.
    [7" id="c-fr-0007]
    7. The system as claimed in claim 6, in which the porosity or permeability data as a function of the confinement stress are obtained from the rock mechanics data.
    [8" id="c-fr-0008]
    The system of claim 7, wherein the reservoir model simulates changes in the mechanical data of the converted rocks generated as a function of the confinement stress as expressions of the changes in the reservoir simulation due to pore pressure.
    [9" id="c-fr-0009]
    9. System according to any one of claims 6 to 8, in which the conversion of the rock mechanics data as a function of the pore pressure comprises:
    determining a supposed linear association which is supposed to exist between the rock mechanics data and the confinement stress, the rock mechanics data being composed of porosity or permeability data;
    representing rock mechanics data as a fraction;
    using a DSPC, normalizing rock mechanics data so that a maximum containment stress value is 1 and all other containment stress values are less than 1, in which the values containment stress represent a normalized stress response;
    2017-IPM-101196-U1-EN the use of a DSPC, the normalization of rock mechanics data so that a maximum value of porosity and permeability is equal to 1 and a value of porosity and permeability for a maximum confinement stress value is less than 1, in which the normalized porosity and permeability values represent porosity and permeability multipliers;
    projecting the normalized stress response to be symmetrical above 1, thereby converting the confining stress into pore pressure, wherein the pore pressure values represent a normalized pressure response;
    plotting the symmetric normalized pressure response as a function of the normalized porosity and permeability values, and calculating a trend curve equation describing an association between the symmetric normalized pressure response and the porosity and standardized permeability;
    resizing a range of the symmetric normalized pressure response so that the maximum pore pressure value is 1;
    the use of the trend curve, the generation of a resizing model of the porosity and permeability multipliers;
    resizing the resized range of the symmetric normalized pressure response to dimensionless pore pressure using a DSPC; and plotting the resized porosity and permeability multipliers according to dimensionless pore pressure, thus representing compaction tables that can be included in the execution of a reservoir model to associate the pore pressure changes with the multipliers that model the porosity or permeability of an underground system.
    [10" id="c-fr-0010]
    The system of any of claims 6 to 9, wherein the reservoir model is used to predict the production of wells or to assess the mechanisms governing production.
    [11" id="c-fr-0011]
    11. A non-transient computer readable medium comprising instructions which, when executed by a processor, cause the processor to execute any one of the methods according to claims 1 to 5.
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    同族专利:
    公开号 | 公开日
    GB202005129D0|2020-05-20|
    NO20200451A1|2020-04-14|
    US20210405246A1|2021-12-30|
    GB2580833A|2020-07-29|
    WO2019098988A1|2019-05-23|
    CA3077300A1|2019-05-23|
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    法律状态:
    2019-09-26| PLFP| Fee payment|Year of fee payment: 2 |
    2020-05-08| PLSC| Publication of the preliminary search report|Effective date: 20200508 |
    2021-05-14| RX| Complete rejection|Effective date: 20210402 |
    优先权:
    申请号 | 申请日 | 专利标题
    PCT/US2017/061457|WO2019098988A1|2017-11-14|2017-11-14|Conversion of rock mechanics data from confining stress to pore pressure for reservoir simulators|
    IBWOUS2017061457|2017-11-14|
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