Well-to-well formation rock mechanics parameter prediction method and device, electronic equipment, storage medium and program product

Abstract

Embodiments of the present application disclose a method and device for predicting interwell formation rock mechanics parameters, electronic equipment, storage medium and program product. The method can comprise: for each well in a plurality of wells in a study area, obtaining well logging rock mechanics parameters of the well according to well logging data of the well; obtaining a plurality of seismic rock mechanics parameters of the study area according to seismic data of the study area; taking each well logging rock mechanics parameter as input data and taking each seismic rock mechanics parameter as a constraint condition, and predicting interwell formation rock mechanics parameters of the plurality of wells. The technical scheme of the embodiments of the present application can take into account the plane prediction accuracy and the longitudinal prediction accuracy.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of gas reservoir engineering, and in particular to a method, device, electronic device, storage medium and program product for predicting inter-well formation rock mechanical parameters. Background Technology

[0002] During the gas reservoir development phase, accurate prediction of inter-well formation rock mechanical parameters is necessary to meet the requirements of refined engineering design. Currently, prediction is mainly based on seismic inversion methods and stochastic simulation methods.

[0003] In the process of realizing this invention, the inventors discovered the following technical problem in the prior art: it is impossible to balance the accuracy of planar prediction and the accuracy of longitudinal prediction, which urgently needs to be solved. Summary of the Invention

[0004] This invention provides a method, device, electronic equipment, storage medium, and program product for predicting inter-well formation rock mechanical parameters, solving the problem of not being able to simultaneously achieve both planar and vertical prediction accuracy.

[0005] According to one aspect of the present invention, a method for predicting inter-well formation rock mechanical parameters is provided, which may include:

[0006] For each of the multiple wells in the study area, the logging rock mechanics parameters of the well are obtained based on the well logging data;

[0007] Based on the seismic data of the study area, multiple seismic rock mechanics parameters of the study area were obtained;

[0008] Using the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic well as constraints, the inter-well formation rock mechanics parameters of multiple wells are predicted.

[0009] According to another aspect of the present invention, a device for predicting inter-well formation rock mechanical parameters is provided, which may include:

[0010] The well logging rock mechanics parameter acquisition module is used to obtain the well logging rock mechanics parameters of each well in multiple wells in the study area based on the well logging data.

[0011] The earthquake rock mechanics parameter acquisition module is used to obtain multiple earthquake rock mechanics parameters of the study area based on the earthquake data of the study area;

[0012] The inter-well formation rock mechanics parameter prediction module is used to predict the inter-well formation rock mechanics parameters of multiple wells using the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic well as constraints.

[0013] According to another aspect of the present invention, an electronic device is provided, which may include:

[0014] At least one processor; and

[0015] A memory that is communicatively connected to at least one processor; wherein,

[0016] The memory stores a computer program that can be executed by at least one processor, such that when the at least one processor executes the program, it implements the method for predicting inter-well formation rock mechanical parameters provided in any embodiment of the present invention.

[0017] According to another aspect of the present invention, a computer-readable storage medium is provided having computer instructions stored thereon, the computer instructions being configured to cause a processor to execute and implement the method for predicting inter-well formation rock mechanical parameters provided in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer program product is provided, on which a computer program is stored, which, when executed by a processor, implements the method for predicting inter-well formation rock mechanical parameters provided in any embodiment of the present invention.

[0019] The technical solution of this invention addresses multiple wells within a study area. For each well, based on its logging data, well logging rock mechanics parameters are obtained. The application of these parameters helps ensure vertical prediction accuracy. Based on seismic data of the study area, multiple seismic rock mechanics parameters are obtained. The application of these parameters helps ensure horizontal prediction accuracy. Furthermore, using each well logging rock mechanics parameter as input data and each seismic rock mechanics parameter as constraint conditions, the inter-well formation rock mechanics parameters of the multiple wells are predicted. This technical solution combines well logging data and seismic data—specifically, utilizing single-well logging data vertically to ensure vertical prediction accuracy—and uses seismic data for horizontal constraints to reduce horizontal uncertainty and ensure horizontal prediction accuracy. In other words, the two work together to achieve a balance between horizontal and vertical prediction accuracy.

[0020] It should be understood that the description in this section is not intended to identify key or important features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a method for predicting inter-well formation rock mechanical parameters according to an embodiment of the present invention;

[0023] Figure 2 This is a flowchart of another method for predicting inter-well formation rock mechanical parameters according to an embodiment of the present invention;

[0024] Figure 3 This is a schematic diagram of the correlation relationship in another method for predicting inter-well formation rock mechanical parameters provided by an embodiment of the present invention;

[0025] Figure 4 This is a flowchart of another method for predicting inter-well formation rock mechanical parameters according to an embodiment of the present invention;

[0026] Figure 5 This is a structural block diagram of a device for predicting inter-well formation rock mechanical parameters according to an embodiment of the present invention;

[0027] Figure 6 This is a schematic diagram of the structure of an electronic device for implementing the method for predicting inter-well formation rock mechanical parameters according to embodiments of the present invention. Detailed Implementation

[0028] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0029] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. The same applies to "target," "original," etc., and will not be repeated here. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0030] Before introducing the embodiments of the present invention, the implementation process of the prediction scheme for inter-well formation rock mechanical parameters and the reasons for the inability to simultaneously achieve both planar and vertical prediction accuracy will be explained by way of example, so as to better understand how the prediction scheme for inter-well formation rock mechanical parameters proposed in the embodiments of the present invention can simultaneously achieve both planar and vertical prediction accuracy.

[0031] For example, seismic inversion methods are used to predict inter-well rock mechanical parameters. Specifically, based on pre-stack seismic data, rock mechanical parameter calculation formulas are applied to invert and obtain the distribution characteristics of rock mechanical parameters across the entire area. It should be noted that because the vertical distance between two data points in the seismic data is approximately 20 meters, the vertical resolution of the inter-well rock mechanical parameters predicted using this seismic inversion method is relatively low. That is, although good planar prediction accuracy can be achieved, the vertical prediction accuracy is poor.

[0032] For another example, stochastic simulation methods can be used to predict inter-well formation rock mechanical parameters. Specifically, the rock mechanical parameters calculated from the logging data of a single well can be used as input data, and a stochastic simulation algorithm can be employed to predict the distribution characteristics of inter-well formation rock mechanical parameters. It should be noted that although the vertical distance between two data points in the logging data is about 0.125 meters, thus achieving good vertical prediction accuracy, the horizontal distance between the two wells is several hundred meters. This results in significant uncertainty in horizontal prediction when using this stochastic simulation method for horizontal prediction, i.e., poor horizontal prediction accuracy.

[0033] It is clear that neither seismic inversion methods nor stochastic simulation methods can simultaneously achieve both horizontal and vertical prediction accuracy. To address this, this invention combines seismic data and well logging data to predict inter-well formation rock mechanical parameters, thus achieving a balance between horizontal and vertical prediction accuracy.

[0034] This will be explained in detail next.

[0035] Figure 1 This is a flowchart illustrating a method for predicting inter-well formation rock mechanical parameters according to an embodiment of the present invention. This embodiment is applicable to predicting inter-well formation rock mechanical parameters, which may include shear modulus, bulk modulus, Young's modulus, or Poisson's ratio, etc. This method can be executed by the inter-well formation rock mechanical parameter prediction device provided in this embodiment of the invention. This device can be implemented in software and / or hardware, and can be integrated into an electronic device, which may be various user terminals or servers.

[0036] See Figure 1 The method of this invention specifically includes the following steps:

[0037] S110. For each well in the study area, obtain the well logging rock mechanics parameters based on the well logging data.

[0038] In this study area, multiple wells are set up. This step is used to process each of these multiple wells separately, that is, to process a single well.

[0039] Taking any single well as an example, the well logging data of that single well is obtained. In this embodiment of the invention, optionally, the well logging data can be represented by well logging curves or other methods. Then, the rock mechanical parameters of the single well are obtained based on the well logging data. In this embodiment of the invention, optionally, the rock mechanical parameters can be shear modulus, bulk modulus, Young's modulus, or Poisson's ratio, etc.; further optionally, the rock mechanical parameters can be dynamic rock mechanical parameters or static rock mechanical parameters, etc.; all of the above are related to the actual situation and are not specifically limited here. It should be noted that the above rock mechanical parameters are obtained based on well logging data. Therefore, in order to distinguish them from the rock mechanical parameters obtained based on seismic data described in step (S120) below, the rock mechanical parameters obtained in this step can be called well logging rock mechanical parameters, while the rock mechanical parameters obtained in the following steps can be called seismic rock mechanical parameters.

[0040] This step allows us to obtain the logging rock mechanics parameters for each individual well in the study area.

[0041] S120. Based on the seismic data of the study area, multiple seismic rock mechanics parameters of the study area are obtained.

[0042] The process involves acquiring seismic data for the study area, then performing inversion based on this seismic data to obtain multiple rock mechanics parameters for the study area. These multiple rock mechanics parameters can cover multiple wells and the spaces between them.

[0043] S130. Using the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic well as constraints, predict the inter-well formation rock mechanics parameters of multiple wells.

[0044] In the process of predicting the rock mechanics parameters of the formation between multiple wells, the obtained rock mechanics parameters of each well logging are used as input data to ensure the accuracy of vertical prediction, and the obtained seismic rock mechanics parameters are used as constraints to ensure the accuracy of horizontal prediction. Based on this, random simulation is performed to predict the rock mechanics parameters of the formation between wells.

[0045] The technical solution of this invention addresses multiple wells within a study area. For each well, based on its logging data, well logging rock mechanics parameters are obtained. The application of these parameters helps ensure vertical prediction accuracy. Based on seismic data of the study area, multiple seismic rock mechanics parameters are obtained. The application of these parameters helps ensure horizontal prediction accuracy. Furthermore, using each well logging rock mechanics parameter as input data and each seismic rock mechanics parameter as constraint conditions, the inter-well formation rock mechanics parameters of the multiple wells are predicted. This technical solution combines well logging data and seismic data—specifically, utilizing single-well logging data vertically to ensure vertical prediction accuracy—and uses seismic data for horizontal constraints to reduce horizontal uncertainty and ensure horizontal prediction accuracy. In other words, the two work together to achieve a balance between horizontal and vertical prediction accuracy.

[0046] An optional technical solution, using each seismic rock mechanics parameter as a constraint, predicts the inter-well formation rock mechanics parameters of multiple wells, which may include: using each seismic rock mechanics parameter as a co-kriging constraint, and using a sequential Gaussian indicator simulation algorithm to simulate the inter-well formation rock mechanics parameters of multiple wells.

[0047] The above technical solution further reduces planar uncertainty by using each seismic rock mechanics parameter as a co-kriging constraint and employing a sequential Gaussian indicator simulation algorithm to simulate the inter-well formation rock mechanics parameters, thereby further ensuring the accuracy of planar prediction.

[0048] Another optional technical solution is to obtain the well logging rock mechanics parameters based on the well logging data, which may include: obtaining the P-wave velocity and S-wave velocity of the well based on the well logging data; and obtaining the well logging rock mechanics parameters based on the P-wave velocity and S-wave velocity.

[0049] Specifically, for any single well, the P-wave velocity and S-wave velocity of that well can be obtained based on the well logging data. Optionally, in this technical solution, the P-wave velocity can be represented by formation density and formation P-wave transit time, and the S-wave velocity can be represented by formation density and formation S-wave transit time.

[0050] Furthermore, based on the P-wave velocity and S-wave velocity, the logging rock mechanics parameters of this single well can be obtained.

[0051] For example, this section takes the calculation of dynamic logging rock mechanics parameters as an example, where the logging rock mechanics parameter is the dynamic Poisson's ratio ν. d In this case, it can be calculated using the following formula:

[0052]

[0053] Where, Δt S Δt represents the shear wave transit time in the formation, in μs / ft. p This represents the P-wave time difference of the formation, in μs / ft;

[0054] The rock mechanics parameter in this well logging is the dynamic Young's modulus E. d In the case of (unit GPa), it can be calculated using the following formula:

[0055]

[0056] Where, ρ b This indicates the density of the formation, expressed in g / cm³. 3 ;

[0057] The rock mechanics parameter in this well logging is the dynamic shear modulus G. d In the case of (unit GPa), it can be calculated using the following formula:

[0058]

[0059] The rock mechanics parameter in this well logging is the dynamic bulk modulus K. d In the case of (unit GPa), it can be calculated using the following formula:

[0060]

[0061] The above technical solution utilizes the P-wave velocity and S-wave velocity of a single well to achieve accurate calculation of the logging rock mechanics parameters of that single well.

[0062] Figure 2This is a flowchart of another method for predicting inter-well formation rock mechanical parameters provided in this embodiment of the invention. This embodiment is an optimization based on the above-mentioned technical solutions. In this embodiment, optionally, multiple seismic rock mechanical parameters of the study area are obtained based on the seismic data of the study area, including: obtaining multiple study area wave impedances based on the seismic data of the study area, and for each well, determining the well wave impedance of the corresponding well among the multiple study area wave impedances; establishing a correlation relationship based on the logging rock mechanical parameters and well wave impedances corresponding to each well, and obtaining the seismic rock mechanical parameters corresponding to each study area wave impedance based on the correlation relationship, so as to obtain multiple seismic rock mechanical parameters of the study area. The explanations of terms that are the same as or corresponding to those in the above embodiments are not repeated here.

[0063] See Figure 2 The method in this embodiment may specifically include the following steps:

[0064] S210. For each well in the study area, obtain the well logging rock mechanics parameters based on the well logging data.

[0065] S220. Based on the seismic data of the study area, obtain multiple study area wave impedances for the study area, and for each well, determine the well wave impedance of the corresponding well among the multiple study area wave impedances.

[0066] Based on seismic data, multiple wave impedances of the study area can be obtained. Furthermore, these multiple wave impedances can be extracted to individual wells to obtain the well wave impedance of each well. For example, taking wells A and B as examples, the wave impedances of the multiple study areas are extracted to well A to obtain the well wave impedance at well point A, and the wave impedances of the multiple study areas are extracted to well B to obtain the well wave impedance at well point B.

[0067] S230. Based on the logging rock mechanics parameters and well wave impedance corresponding to each well, establish a correlation relationship, and based on the correlation relationship, obtain the seismic rock mechanics parameters corresponding to the wave impedance of each study area, so as to obtain multiple seismic rock mechanics parameters of the study area.

[0068] After the two steps described above, each well has its own logging rock mechanics parameters and well wave impedance. Based on this, correlation analysis can be performed on these corresponding logging rock mechanics parameters and well wave impedance to establish correlation relationships. For example, Figure 3 This demonstrates a certain correlation, which can be expressed by the following formula:

[0069] Well wave impedance = a × logging rock mechanics parameters + b;

[0070] Where a and b are both correlation coefficients.

[0071] Furthermore, for each study area's wave impedance, the wave impedance of that study area can be substituted into the correlation relationship to obtain the seismic rock mechanics parameters corresponding to the wave impedance of that study area. These seismic rock mechanics parameters can be understood as rock mechanics parameters calculated based on seismic data, which have good planar prediction accuracy.

[0072] S240. Using the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic well as constraints, predict the inter-well formation rock mechanics parameters of multiple wells.

[0073] The technical solution of this invention calculates the seismic rock mechanics parameters in the study area, especially the seismic rock mechanics parameters between wells, by using the wave impedance obtained from seismic data as a basis. This further reduces the plane uncertainty and thus further ensures the accuracy of plane prediction.

[0074] An optional technical solution involves obtaining multiple wave impedances of the study area based on seismic data of the study area, including: performing inversion based on the seismic data of the study area to obtain the rock density and seismic wave propagation velocity corresponding to multiple locations within the study area; and obtaining multiple wave impedances of the study area based on the corresponding rock density and seismic wave propagation velocity.

[0075] Specifically, seismic data from the study area can be used for inversion to obtain the rock density and seismic wave propagation velocity corresponding to multiple locations within the study area. Furthermore, for each location, the wave impedance of the study area at that location can be obtained based on the rock density and seismic wave propagation velocity. For example, the wave impedance of the study area can be obtained using the following formula: Wave impedance of the study area = Rock density × Seismic wave propagation velocity.

[0076] The above technical solution utilizes rock density and seismic wave propagation velocity to achieve accurate calculation of wave impedance in the study area.

[0077] Figure 4 This is a flowchart illustrating another method for predicting inter-well formation rock mechanical parameters provided by an embodiment of the present invention. This embodiment is an optimization based on the above-described technical solutions. Explanations of terms that are the same as or corresponding to those in the above embodiments will not be repeated here.

[0078] See Figure 4 The method in this embodiment may specifically include the following steps:

[0079] S310. For each well in the study area, based on the well logging data, obtain the P-wave velocity and S-wave velocity of the well, and based on the P-wave velocity and S-wave velocity, obtain the well logging rock mechanics parameters of the well.

[0080] S320. Based on the seismic data of the study area, the wave impedance of multiple study areas is obtained.

[0081] S330. For each well, determine the well wave impedance of the corresponding well in multiple study areas, and establish a correlation relationship based on the logging rock mechanics parameters and well wave impedance of each well.

[0082] S340. Based on the correlation, the seismic rock mechanics parameters corresponding to the wave impedance of each study area are obtained, so as to obtain multiple seismic rock mechanics parameters of the study area.

[0083] S350. Using the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic rock mechanics as co-kriging constraints, the sequential Gaussian indicator simulation algorithm is used to simulate the inter-well formation rock mechanics parameters of multiple wells.

[0084] For example, the Luzhou block has well-developed micro-structures, a well-developed fault system, and complex geostress. The rock mechanical parameters of this Luzhou block were predicted using embodiments of the present invention. The prediction study shows that the rock mechanical parameters of single wells have a high degree of matching, the continuity of rock mechanical parameters between wells is good, and the prediction results are consistent with the interpretation of single-well logging and the wave impedance distribution characteristics of formations between wells, demonstrating high accuracy.

[0085] The technical solutions of the embodiments of the present invention have at least the following advantages:

[0086] 1) Taking advantage of the good horizontal continuity and high vertical resolution of seismic data, the correlation between well logging rock mechanical parameters and well wave impedance is established. Using well logging rock mechanical parameters as input data (i.e., hard data) and wave impedance as the inter-well formation trend constraint, the sequential Gaussian indicator simulation algorithm is used to predict the distribution characteristics of inter-well formation rock mechanical parameters. This improves the inter-well horizontal and vertical prediction resolution and significantly improves the prediction accuracy. This helps to provide support for calculating the maximum horizontal principal stress, minimum horizontal principal stress and rock fracture pressure, and provides a basis for fracturing scheme design and optimization.

[0087] 2) The distribution characteristics of the rock mechanical parameters of the inter-well formation predicted above are consistent with the previous geological understanding, the distribution has a high degree of consistency with the actual geological conditions, and the prediction results have high credibility.

[0088] 3) The rock mechanical parameter property model established based on the above prediction method can be directly imported into numerical modeling software for fracturing scheme simulation, providing a basis for optimizing fracturing scheme parameters.

[0089] 4) The data acquisition method is simple, the calculation steps are convenient, and the method is highly reproducible. It can be used to calculate rock mechanical parameters in other oil and gas fields, and has a wide range of applications.

[0090] Figure 5 This is a structural block diagram of an inter-well formation rock mechanical parameter prediction device provided in an embodiment of the present invention. This device is used to execute the inter-well formation rock mechanical parameter prediction method provided in any of the above embodiments. This device and the inter-well formation rock mechanical parameter prediction methods of the above embodiments belong to the same inventive concept. Details not described in detail in the embodiments of the inter-well formation rock mechanical parameter prediction device can be found in the embodiments of the above-described inter-well formation rock mechanical parameter prediction methods. See also... Figure 5 The device may specifically include: a well logging rock mechanics parameter acquisition module 410, a seismic rock mechanics parameter acquisition module 420, and an inter-well formation rock mechanics parameter prediction module 430.

[0091] Among them, the well logging rock mechanics parameter acquisition module 410 is used to obtain the well logging rock mechanics parameters of each well in the study area based on the well logging data.

[0092] The seismic rock mechanics parameter acquisition module 420 is used to obtain multiple seismic rock mechanics parameters of the study area based on the seismic data of the study area;

[0093] The inter-well formation rock mechanics parameter prediction module 430 is used to predict the inter-well formation rock mechanics parameters of multiple wells by taking the rock mechanics parameters of each well logging as input data and the rock mechanics parameters of each seismic well as constraints.

[0094] Optionally, the earthquake rock mechanics parameter acquisition module 420 may include:

[0095] The well wave impedance determination unit is used to obtain multiple study area wave impedances based on the seismic data of the study area, and for each well, determine the well wave impedance of the corresponding well among the multiple study area wave impedances.

[0096] The seismic rock mechanics parameter unit can be used to establish a correlation relationship based on the well logging rock mechanics parameters and well wave impedance corresponding to each well, and based on the correlation relationship, obtain the seismic rock mechanics parameters corresponding to the wave impedance of each study area, so as to obtain multiple seismic rock mechanics parameters of the study area.

[0097] Based on this, the optional well-wave impedance determination unit may include:

[0098] The seismic wave propagation velocity is obtained as a sub-unit, which is used to invert the seismic data of the study area to obtain the rock density and seismic wave propagation velocity corresponding to multiple locations in the study area.

[0099] The wave impedance of the study area is obtained as a sub-unit, which can be used to obtain multiple wave impedances of the study area based on the corresponding rock density and seismic wave propagation velocity.

[0100] Optional, the inter-well formation rock mechanical parameter prediction module 430 can be used for:

[0101] Using the rock mechanics parameters from each well logging operation as input data and the rock mechanics parameters from each seismic operation as co-kriging constraints, the sequential Gaussian indicator simulation algorithm was used to simulate the inter-well formation rock mechanics parameters of multiple wells.

[0102] Optionally, the well logging rock mechanics parameter acquisition module 410 may include:

[0103] The shear wave velocity unit can be used to obtain the P-wave velocity and shear wave velocity of a well based on well logging data;

[0104] The well logging rock mechanics parameter acquisition unit is used to obtain the well logging rock mechanics parameters based on the P-wave velocity and S-wave velocity.

[0105] Optionally, based on any of the above devices, the logging rock mechanics parameters may include shear modulus, bulk modulus, Young's modulus, or Poisson's ratio.

[0106] The inter-well formation rock mechanics parameter prediction device provided in this invention, through a well logging rock mechanics parameter acquisition module, obtains the well logging rock mechanics parameters for each well in a study area based on its logging data. The application of these well logging rock mechanics parameters helps ensure vertical prediction accuracy. Through a seismic rock mechanics parameter acquisition module, multiple seismic rock mechanics parameters for the study area are obtained based on seismic data. The application of these seismic rock mechanics parameters helps ensure horizontal prediction accuracy. Furthermore, through an inter-well formation rock mechanics parameter prediction module, using each well logging rock mechanics parameter as input data and each seismic rock mechanics parameter as constraint conditions, the inter-well formation rock mechanics parameters for multiple wells are predicted. This device, by combining well logging data and seismic data—specifically, utilizing single-well well logging data vertically to ensure vertical prediction accuracy—and using seismic data for horizontal constraints to reduce horizontal uncertainty and ensure horizontal prediction accuracy, achieves a balance between horizontal and vertical prediction accuracy through their combined use.

[0107] The device for predicting inter-well formation rock mechanical parameters provided in this embodiment of the invention can execute the prediction method for inter-well formation rock mechanical parameters provided in any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.

[0108] It is worth noting that in the embodiments of the above-mentioned inter-well formation rock mechanical parameter prediction device, the various units and modules included are only divided according to functional logic, but are not limited to the above division, as long as the corresponding functions can be achieved; in addition, the specific names of each functional unit are only for easy differentiation and are not used to limit the scope of protection of the present invention.

[0109] Figure 6 A schematic diagram of an electronic device 10 that can be used to implement embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0110] like Figure 6 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded into the RAM 13 from storage unit 18. The RAM 13 can also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0111] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0112] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, central processing unit (CPU), graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, digital signal processors (DSPs), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as methods for predicting inter-well formation rock mechanical parameters.

[0113] In some embodiments, the method for predicting inter-well formation rock mechanical parameters can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the method for predicting inter-well formation rock mechanical parameters described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the method for predicting inter-well formation rock mechanical parameters by any other suitable means (e.g., by means of firmware).

[0114] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), payload-programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0115] Computer programs used to implement the methods of the present invention can be written in any combination of one or more programming languages. These computer programs can be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be implemented. The computer programs can be executed entirely on a machine, partially on a machine, as a standalone software package partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0116] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0117] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0118] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0119] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0120] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0121] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of predicting formation rock mechanical parameters between wells, characterized in that, include: For each of the multiple wells in the study area, the logging rock mechanics parameters of the well are obtained based on the logging data of the well. Based on the seismic data of the study area, multiple seismic rock mechanics parameters of the study area were obtained; Using the well logging rock mechanics parameters as input data and the seismic rock mechanics parameters as constraints, the inter-well formation rock mechanics parameters of the multiple wells are predicted.

2. The method of claim 1, wherein, Based on the seismic data of the study area, multiple seismic rock mechanics parameters of the study area are obtained, including: Based on the seismic data of the study area, multiple study area wave impedances of the study area are obtained, and for each well, the well wave impedance corresponding to the well among the multiple study area wave impedances is determined. Based on the logging rock mechanics parameters and well wave impedance corresponding to each well, a correlation relationship is established, and based on the correlation relationship, the seismic rock mechanics parameters corresponding to the wave impedance of each study area are obtained, so as to obtain multiple seismic rock mechanics parameters of the study area.

3. The method of claim 2, wherein, The method of obtaining multiple wave impedances of the study area based on seismic data of the study area includes: Based on the seismic data of the study area, the rock density and seismic wave propagation velocity corresponding to multiple locations within the study area were obtained by inversion. Based on the corresponding rock densities and seismic wave propagation velocities, the wave impedances of multiple study areas in the study region are obtained.

4. The method of claim 1, wherein, The method of predicting the inter-well formation rock mechanical parameters of multiple wells using the aforementioned seismic rock mechanical parameters as constraints includes: Using the aforementioned seismic rock mechanics parameters as co-kriging constraints, and employing a sequential Gaussian indicator simulation algorithm, the inter-well formation rock mechanics parameters of the multiple wells were simulated.

5. The method of claim 1, wherein, The process of obtaining the well logging rock mechanics parameters based on the well logging data includes: Based on the logging data of the well, the P-wave velocity and S-wave velocity of the well are obtained; Based on the longitudinal wave velocity and the transverse wave velocity, the logging rock mechanics parameters of the well are obtained.

6. The method according to any one of claims 1 to 5, characterized in that, The logging rock mechanics parameters include shear modulus, bulk modulus, Young's modulus, or Poisson's ratio.

7. An apparatus for predicting formation rock mechanical parameters between wells, characterized by, include: The well logging rock mechanics parameter acquisition module is used to obtain the well logging rock mechanics parameters of each well in a study area based on the well logging data. The earthquake rock mechanics parameter acquisition module is used to obtain multiple earthquake rock mechanics parameters of the study area based on the earthquake data of the study area; The inter-well formation rock mechanics parameter prediction module is used to predict the inter-well formation rock mechanics parameters of multiple wells by taking the well logging rock mechanics parameters as input data and the seismic rock mechanics parameters as constraints.

8. An electronic device, comprising: include: At least one processor; as well as A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor to cause the at least one processor to perform a method for predicting inter-well formation rock mechanical parameters as described in any one of claims 1-6.

9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that, when executed by a processor, implement the method for predicting inter-well formation rock mechanical parameters as described in any one of claims 1-6.

10. A computer program product, characterised in that, The computer program product includes a computer program that, when executed by a processor, implements the method for predicting inter-well formation rock mechanical parameters as described in any one of claims 1-6.

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