Method, apparatus, electronic device, and storage medium for constructing a permeability model

Abstract

Embodiments of the present invention disclose a method, apparatus, electronic device, and storage medium for constructing a permeability model. The method includes: analyzing core data of a complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; based on the elastic parameters in the reservoir change information, constructing a porosity model of the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir, and constructing a permeability model of the complex carbonate reservoir based on the porosity model-optimized logging interpretation porosity curve. By adopting the solution of the present application, to improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion, for the construction of the permeability model of the carbonate reservoir, it not only meets the accuracy requirements of the permeability model at the core and logging scales, but also avoids using non-elastic parameters, and through seismic inversion of reservoir-sensitive elastic parameters, it enables the prediction of the spatial distribution characteristics of the permeability of the complex carbonate reservoir through seismic inversion to have a petrophysical basis.

Description

Technical Field

[0001] The embodiments of the present invention relate to the technical field of oil and gas reservoir exploitation, and in particular, to a method, device, electronic device and storage medium for constructing a permeability model. Background Art

[0002] Currently, the methods for constructing permeability models mainly focus on log interpretation. First, porosity is interpreted based on lithology identification, and then permeability curves are calculated using different porosity-permeability relationships for different lithofacies.

[0003] For conventional reservoirs with relatively simple pore structures, there is a good linear relationship between the elastic parameter wave impedance and porosity, and there is also a good linear relationship between porosity and permeability. Therefore, the reservoir permeability attribute volume can be obtained through simple conversion of the wave impedance data based on seismic inversion.

[0004] However, for complex carbonate reservoirs, the factors affecting permeability are very complex. The complexity of their microscopic pore characteristics and mineral structure characteristics is much higher than that of conventional sandstone reservoirs. Even the porosity-permeability relationships of different lithofacies in the same formation vary greatly, showing characteristics such as the same porosity but large differences in permeability, resulting in insufficient accuracy of the permeability model constructed by conventional methods. Summary of the Invention

[0005] In the embodiments of the present invention, a method, device, electronic device and storage medium for constructing a permeability model are provided to construct a permeability model for complex carbonate reservoirs and improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion.

[0006] In a first aspect, the embodiments of the present invention provide a method for constructing a permeability model, and the construction method includes:

[0007] Analyze the core data of the complex carbonate reservoir to determine the change information of the reservoir in the complex carbonate reservoir; the change information of the reservoir includes the change rules among elastic parameters, porosity, and permeability;

[0008] Based on the elastic parameters in the change information of the reservoir, construct a porosity model of the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir;

[0009] Construct a permeability model of the complex carbonate reservoir based on the log interpretation porosity curve optimized by the porosity model.

[0010] In a second aspect, the embodiments of the present invention also provide a device for constructing a permeability model, and the device includes:

[0011] A core data analysis module, which is used to analyze the core data of complex carbonate reservoirs and determine the reservoir change information of complex carbonate reservoirs; the reservoir change information includes the variation laws among elastic parameters, porosity and permeability;

[0012] A porosity model construction module, which is used to construct a porosity model of complex carbonate reservoirs based on the elastic parameters in the reservoir change information and according to the shale content information of complex carbonate reservoirs;

[0013] A permeability model construction module, which is used to construct a permeability model of complex carbonate reservoirs based on the well logging interpreted porosity curve optimized by the porosity model.

[0014] Thirdly, an electronic device is further provided in an embodiment of the present invention, including:

[0015] One or more processing devices;

[0016] A storage device, which is used to store one or more programs;

[0017] When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the method for constructing the permeability model provided in any embodiment of the present invention.

[0018] Fourthly, a computer-readable storage medium is further provided in an embodiment of the present invention, on which a computer program is stored, and when the program is executed by a processing device, the method for constructing the permeability model provided in any embodiment of the present invention is implemented.

[0019] A method for constructing a permeability model is provided in an embodiment of the present invention. The core data of complex carbonate reservoirs is analyzed to determine the reservoir change information of complex carbonate reservoirs. The reservoir change information includes the variation laws among elastic parameters, porosity and permeability. On this basis, a porosity model of complex carbonate reservoirs is constructed based on the elastic parameters in the reservoir change information and according to the shale content information of complex carbonate reservoirs. Furthermore, a permeability model of complex carbonate reservoirs is constructed based on the well logging interpreted porosity curve optimized by the porosity model. By adopting the solution of the present application, in order to improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion, for the construction of the permeability model of complex carbonate reservoirs, it not only meets the accuracy requirements of the permeability model at the core and well logging scales, but also avoids using non-elastic parameters. Through seismic inversion of elastic parameters sensitive to reservoirs, it enables the prediction of the spatial distribution characteristics of the permeability of complex carbonate reservoirs through seismic inversion to have a petrophysical basis.

[0020] The above summary of the invention is only an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, it can be implemented according to the content of the specification. And in order to make the above and other purposes, features and advantages of the present invention more obvious and understandable, the following specifically describes the embodiments of the present invention. Description of the Drawings

[0021] Other features, objects, and advantages of the present invention will become more apparent by reading the following detailed description of non-limiting embodiments with reference to the accompanying drawings. The drawings are only for the purpose of showing the preferred embodiments and are not considered as limiting the present invention. Moreover, throughout the drawings, the same reference numerals are used to represent the same components. In the drawings:

[0022] Figure 1 is a flowchart of a method for constructing a permeability model provided in an embodiment of the present invention;

[0023] Figure 2a is a schematic diagram of different lithofacies reservoirs provided in an embodiment of the present invention;

[0024] Figure 2b is a schematic diagram of the subdivision of different lithofacies reservoirs according to density and resistivity provided in an embodiment of the present invention;

[0025] Figure 2c is a schematic diagram of establishing three sets of porosity-permeability models based on three lithofacies in conventional logging interpretation provided in an embodiment of the present invention;

[0026] Figure 3a is an analysis diagram of measured porosity versus density and longitudinal wave velocity provided in an embodiment of the present invention;

[0027] Figure 3b is an analysis diagram of measured porosity versus permeability provided in an embodiment of the present invention;

[0028] Figure 4 is a flowchart of another method for constructing a permeability model provided in an embodiment of the present invention;

[0029] Figure 5 is a comparison diagram of new interpretation results and conventional technical results provided in an embodiment of the present invention;

[0030] Figure 6 is a comparison diagram of the permeability and lithology division of the new interpretation and the conventional technical results provided in an embodiment of the present invention;

[0031] Figure 7 is a structural block diagram of a device for constructing a permeability model provided in an embodiment of the present invention;

[0032] Figure 8 is a schematic diagram of the structure of an electronic device provided in an embodiment of the present invention. Detailed implementation manners

[0033] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It can be understood that the specific embodiments described herein are only used to explain the present invention, rather than limiting the present invention. Additionally, it should be noted that for the sake of description, only parts related to the present invention rather than all structures are shown in the accompanying drawings.

[0034] Before discussing the exemplary embodiments in more detail, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowcharts describe the operations (or steps) as sequential processes, many of the operations (or steps) can be implemented in parallel, concurrently, or simultaneously. In addition, the order of the operations can be rearranged. The process can be terminated when its operations are completed, but it can also have additional steps not included in the drawings. The process can correspond to a method, function, procedure, subroutine, subprogram, and so on.

[0035] The construction method, device, electronic device, and storage medium of the permeability model provided in the present application will be elaborated in detail below through the following various embodiments and their alternative solutions.

[0036] Figure 1 is a flowchart of a construction method of a permeability model provided in an embodiment of the present invention. The embodiment of the present invention is applicable to the construction of a permeability model for a complex carbonate reservoir, especially in the case where the permeability interpretation of a carbonate reservoir with rapid lithofacies change and strong heterogeneity can be optimized. This method can be executed by a construction device of the permeability model, and the device can be implemented in a software and / or hardware manner and integrated on any electronic device with network communication functions. As Figure 1 shown, the construction method of the permeability model provided in the embodiment of the present application may include the following steps:

[0037] S110. Analyze the core data of the complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation laws among elastic parameters, porosity, and permeability.

[0038] Based on the vertical resolution ability of well logging data and the horizontal resolution ability of seismic data, carrying out well-seismic joint reservoir inversion prediction to describe the spatial variation characteristics of the lithology and physical properties of the oil and gas reservoir is an important means for reservoir research in oil and gas exploration and development.

[0039] Figure 2aWell A is on the left and Well B is on the right in the middle. The reservoir section of ZJ10A is a reef facies, and the reservoir section of ZJ10B is a shoal facies. According to the cross-plot analysis of logging density and resistivity, the complex carbonate reservoir section can be divided into three different types of carbonates, namely ZJ10A conventional normal reef limestone, ZJ10A special reef limestone, and ZJ10B shoal limestone. Figure 2b In the middle, ZJ10A is further divided into conventional normal reef limestone (rhombus points) and special reef limestone (rectangular points) according to density and resistivity. Refer to Figure 2c. According to the conventional interpretation method, the permeability interpretation of the three different lithofacies reservoirs corresponds to three models. Due to the rapid change of lithofacies and strong heterogeneity, the permeability model will switch frequently in the whole carbonate reservoir section, affecting the vertical stability of the interpretation results. At the same time, the parameters of the interpretation model involve resistivity inelastic parameters, and the resistivity volume cannot be obtained by seismic inversion, making it difficult to establish a three-dimensional lithofacies body, and thus impossible to judge which model to apply to predict the spatial variation of permeability.

[0040] To improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion, for the construction of the permeability model of complex carbonate reservoirs, data analysis can be carried out on the core data of complex carbonate reservoirs to obtain the variation law between the elastic parameters, porosity and permeability of complex carbonate reservoirs. In this way, not only the accuracy requirements of the permeability model are met at the core and logging scales, but also the use of inelastic parameters is avoided. By seismic inversion of reservoir-sensitive elastic parameters, it becomes possible to generalize the permeability model in three-dimensional space.

[0041] Optionally, core tests can be carried out based on the core data of complex carbonate reservoirs and comprehensive data analysis can be carried out. The actual test data of core samples are shown in Table 1. Through core test analysis, it can be determined that there is a good correlation between the longitudinal wave velocity, density and porosity, and there is a quasi-proportional relationship between porosity and permeability, but it is slightly scattered in the range of 15%-20% porosity, and it is considered to be related to the shale content. For details, refer to Figure 3a and Figure 3b .

[0042] Table 1 Actual test data table of core samples

[0043]

[0044] S120. Based on the elastic parameters in the reservoir change information of the rock, a porosity model of complex carbonate reservoirs is constructed according to the shale content information of complex carbonate reservoirs.

[0045] Considering that seismic inversion can only obtain the elastic parameters of underground media, in order to obtain physical parameters such as porosity and permeability, it is necessary to establish the conversion relationship between elastic parameters, porosity and permeability, so as to achieve the purpose of obtaining the spatial distribution characteristics of permeability based on the elastic parameters sensitive to the seismic inversion reservoir. In the process of constructing the permeability model, elastic parameters are mainly used as the basis, so that the prediction of the spatial distribution characteristics of permeability of complex carbonate reservoirs through seismic inversion has a rock physics basis.

[0046] Conventional permeability models are constructed to meet the single well matching rate, mostly using non-elastic parameters such as resistivity, while seismic inversion cannot obtain non-elastic parameters such as resistivity. This application uses elastic parameters to construct the model, which increases the multi-solution of predicting the spatial distribution characteristics of reservoir permeability using elastic parameters of seismic inversion. This application scheme is based on elastic parameters, combined with mud content correction, etc. to establish a new porosity interpretation model, optimize the interpretation scheme, and improve the accuracy. It can minimize the problem that the density and porosity of pure carbonate rocks are theoretically well correlated using density curves, but once there is a well expansion, the density is most affected, and it is difficult to ensure that the density is corrected to the actual formation response, affecting the calculation accuracy of porosity.

[0047] S130. Based on the porosity model optimized well logging interpretation porosity curve, a permeability model of complex carbonate reservoirs is constructed.

[0048] According to the method for constructing a permeability model provided in an embodiment of the present invention, in order to improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion, the construction of a permeability model for a complex carbonate reservoir not only meets the accuracy requirements of the permeability model at the core and logging scales, but also avoids the use of non-elastic parameters. Through seismic inversion of reservoir-sensitive elastic parameters, the prediction of the spatial distribution characteristics of the permeability of complex carbonate reservoirs through seismic inversion has a rock physics basis. Starting from core analysis and combined with logging data, a variety of elastic parameters that are sensitive to permeability changes are found, and then a new method for converting between multiple elasticities and permeability is constructed.

[0049] Figure 4 is a flow chart of another method for constructing a permeability model provided in an embodiment of the present invention. The embodiment of the present invention further optimizes the above embodiment on the basis of the above embodiment. The embodiment of the present invention can be combined with various optional solutions in one or more of the above embodiments. Figure 4 As shown, the method for constructing the permeability model provided in the embodiment of the present application may include the following steps:

[0050] S410, analyzing core data of complex carbonate reservoirs to determine reservoir change information of the complex carbonate reservoirs; the reservoir change information includes change rules among elastic parameters, porosity and permeability.

[0051] S420. Analyze the rock porosity of a complex carbonate reservoir and construct a rock pore morphology factor for the complex carbonate reservoir; wherein, the rock pore morphology factor is used to characterize the shale content of the complex carbonate reservoir.

[0052] In an alternative embodiment of the present implementation, analyzing the rock porosity of a complex carbonate reservoir and constructing a rock pore morphology factor for the complex carbonate reservoir may include the following steps:

[0053] Step A1. Use acoustic logging to analyze the rock porosity of a complex carbonate reservoir to obtain an acoustic porosity.

[0054] Step A2. Use density logging to analyze the rock porosity of a complex carbonate reservoir to obtain a density porosity.

[0055] Step A3. Conduct a porosity difference analysis based on the acoustic porosity and density porosity of the complex carbonate reservoir to obtain the pore morphology factor of the complex carbonate reservoir.

[0056] Both acoustic logging and density logging can calculate the rock porosity. The difference between them mainly reflects the rock pore morphology. Therefore, a pore morphology factor can be constructed to characterize these differences. The specific formula is as follows:

[0057] PORDT = (DT - 49) / (189 - 49)

[0058] PORDEN = (DEN - 2.71) / (1.0 - 2.71)

[0059] PDD = PORDT - PORDEN

[0060] Wherein, PORTDT is the acoustic porosity, DT is the acoustic travel time of logging; PORDEN is the density porosity, DEN is the logging density; PDD is the pore morphology factor, and the specific constants can be pre-configured and analyzed based on the complex carbonate reservoir.

[0061] Acoustic logging emits acoustic waves at the transmitter end. The acoustic waves will fluctuate and propagate along the wellbore and within a certain radial range from the wellbore to the formation interior, and finally reach the receiver end. The propagation of compressional waves is affected by many factors such as formation lithology, porosity, pore structure, fluid properties, compaction, and cementation. The rock porosity can be calculated using the acoustic travel time. At the same time, the acoustic wave propagation always follows the fastest path and is most sensitive to the rock structure and pore structure.

[0062] Density logging uses a gamma-ray source of medium intensity, with the emitted gamma-ray energy less than 1.02 MeV (mega-electron volts). After the gamma rays enter the formation, they collide with the electrons in the atoms, transferring part of their energy to the electrons, causing the electrons to be emitted in a certain direction, and the gamma rays that have lost part of their energy are emitted in another direction. This is the Compton effect. The Compton effect mainly depends on the number of photoelectrons in the rock per unit volume. Therefore, density measurement is a volume measurement, reflecting the average rock density within a unit sphere around the instrument receiver. It can be used for the calculation of pure mineral porosity, and the obtained porosity curve is independent of the pore structure, morphology, and cementation of the rock.

[0063] S430: Based on the elastic parameters in the rock reservoir change information, and according to the rock pore morphology factor of the complex carbonate rock reservoir, a porosity model of the complex carbonate rock reservoir is constructed through multiple linear regression.

[0064] Optionally, the elastic parameters include parameters for characterizing the rock physical properties. The elastic parameters include the longitudinal wave impedance constructed from the product of the longitudinal wave velocity and density. The longitudinal wave impedance in the elastic parameters is the product of the longitudinal wave velocity and density, which is the most commonly used and easiest property to invert in seismic reservoir prediction. Therefore, the wave impedance can be used as the main curve for porosity research. Considering the influence of shale content at the same time, a porosity model is established through multiple linear regression as follows:

[0065] PORAI = (AI - 15000) / (4300 - 15000)*0.4 - Vcl*0.25

[0066] Among them, PORAI is the porosity calculated using the longitudinal wave impedance, AI is the longitudinal wave impedance, and Vcl is the shale content interpreted by logging. See Figure 5 , the third column includes the newly interpreted porosity using the newly built porosity model and the porosity interpreted based on logging density. The circled dots in the third column are the core analysis porosity. It is not difficult to see that the overall newly interpreted porosity fits better with the core analysis porosity.

[0067] Compared with the conventional logging interpretation that often uses various parameter combinations, especially including resistivity and inelastic parameters, to consider the coincidence rate on a single well, but the seismic inversion cannot obtain the inelastic parameter solution, the permeability model construction method proposed in this application applies elastic parameters, enabling the permeability interpretation to have a clear rock physical basis, which is beneficial to guiding the spatial promotion of the permeability interpretation model through seismic inversion and achieving the purpose of comprehensive evaluation of the permeability of complex carbonate rock reservoirs.

[0068] S440: Based on the porosity curve of the logging interpretation optimized by the porosity model, a permeability model of the complex carbonate rock reservoir is constructed.

[0069] In an alternative solution of this embodiment, a permeability model of a complex carbonate reservoir is constructed based on a porosity curve optimized by a porosity model, which may include the following steps B1 - B2:

[0070] Step B1: Perform well logging interpretation through the porosity model to obtain an optimized well logging interpreted porosity curve.

[0071] Step B2: Use the porosity optimized by well logging interpretation and the correction of the pore morphology factor to construct a unified permeability model for the entire complex carbonate reservoir.

[0072] After constructing the pore morphology factor, use the porosity optimized by well logging interpretation and the correction of this pore morphology factor to establish a unified permeability model for the entire carbonate formation, as follows:

[0073] PERMAI = 10^(-2.9 + 20 * PORAI * (1 - PDD * 5))

[0074] Among them, PERMAI is the permeability obtained by correcting with the optimized porosity and pore factor, PDD is the pore morphology factor, and PORAI is the porosity calculated using the P-wave impedance. Through the optimized well logging interpreted porosity curve and the correction of the pore morphology factor, this application establishes a unified set of permeability models. Compared with the multiple sets of permeability models that often use segmentation or lithofacies in conventional well logging interpretation, it greatly simplifies the permeability interpretation scheme, not only reducing the interpretation difficulty but also improving the interpretation accuracy.

[0075] The permeability interpreted by applying the present invention is as shown in the fifth column. It can be seen that the corrected curve is the permeability calculated by the unified model corrected with the pore morphology factor, the conventional curve is the permeability calculated by the three sets of models used in the conventional method, and the circle points are the core test permeabilities. From the comparison, the newly interpreted permeability is in good agreement with the core analysis results. The new lithology and the original lithology divided by the permeability cut-off value of 1.5 mD (millidarcy) are generally basically similar, but locally more refined, as Figure 5 shown in the comparison diagram of the permeability and lithology division interpreted by this application and the conventional technical results (Well A on the left, Well B on the right). Figure 6

[0076] According to the method for constructing a permeability model provided in the embodiments of the present invention, to improve the accuracy of predicting the spatial distribution of reservoir physical properties based on seismic inversion, for the construction of a permeability model of a complex carbonate reservoir, it not only meets the accuracy requirements of the permeability model at the core and well logging scales, but also avoids using inelastic parameters. By seismic inversion of elastic parameters sensitive to the reservoir, it enables the prediction of the spatial distribution characteristics of the permeability of a complex carbonate reservoir through seismic inversion to have a petrophysical basis.

[0077] ​Figure 7 It is a structural block diagram of a device for constructing a permeability model provided in an embodiment of the present invention. The embodiment of the present invention is applicable to the construction of a permeability model for a complex carbonate reservoir, especially in the case where the permeability interpretation of a carbonate reservoir with rapid lithofacies changes and strong heterogeneity can be optimized. The device can be implemented in software and / or hardware and integrated on any electronic device with network communication functions. As Figure 1 shown, the device for constructing a permeability model provided in an embodiment of the present application may include the following: a core data analysis module 710, a porosity model construction module 720, and a permeability model construction module 730. Among them:

[0078] The core data analysis module 710 is used to analyze the core data of the complex carbonate reservoir and determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation law between elastic parameters, porosity, and permeability;

[0079] The porosity model construction module 720 is used to construct a porosity model of the complex carbonate reservoir based on the elastic parameters in the reservoir change information and according to the shale content information of the complex carbonate reservoir;

[0080] The permeability model construction module 730 is used to construct a permeability model of the complex carbonate reservoir based on the porosity curve of the well logging interpretation optimized by the porosity model.

[0081] On the basis of the above embodiment, optionally, the elastic parameters include parameters for characterizing rock physical properties, and the elastic parameters include the longitudinal wave impedance constructed by the product of the longitudinal wave velocity and density.

[0082] On the basis of the above embodiment, optionally, constructing a porosity model of the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir includes:

[0083] Performing rock porosity analysis on the complex carbonate reservoir to construct a rock pore morphology factor of the complex carbonate reservoir; the rock pore morphology factor is used to characterize the shale content of the complex carbonate reservoir;

[0084] Constructing a porosity model of the complex carbonate reservoir through multiple linear regression based on the rock pore morphology factor of the complex carbonate reservoir.

[0085] On the basis of the above embodiment, optionally, performing rock porosity analysis on the complex carbonate reservoir to construct a rock pore morphology factor of the complex carbonate reservoir includes:

[0086] Performing rock porosity analysis on the complex carbonate reservoir by using acoustic well logging to obtain acoustic porosity;

[0087] Rock porosity analysis of complex carbonate reservoirs is carried out using density logging to obtain density porosity;

[0088] Porosity difference analysis is carried out based on the acoustic porosity and density porosity of the complex carbonate reservoir to obtain the pore shape factor of the complex carbonate reservoir.

[0089] Optionally, on the basis of the above embodiments, before carrying out rock porosity analysis of the complex carbonate reservoir and constructing the rock pore shape factor of the complex carbonate reservoir, it further includes:

[0090] Carry out rock physics analysis on the complex carbonate reservoir based on the geological data and actual drilling data of the complex carbonate reservoir;

[0091] Based on the results of the rock physics analysis, determine the acoustic wave and density sensitive to shale content to use acoustic logging and density logging for rock porosity analysis.

[0092] Optionally, on the basis of the above embodiments, constructing a permeability model of a complex carbonate reservoir according to the porosity curve of the well logging interpretation optimized by the porosity model includes:

[0093] Carry out well logging interpretation through the porosity model to obtain an optimized well logging interpretation porosity curve;

[0094] Utilize the porosity after the well logging interpretation is optimized and the correction of the pore shape factor to construct a unified permeability model for the entire complex carbonate reservoir.

[0095] The device for constructing the permeability model provided in the embodiments of the present invention can execute the method for constructing the permeability model provided in any of the above embodiments of the present invention, and has the corresponding functions and beneficial effects for executing the method for constructing the permeability model. For the detailed process, refer to the relevant operations of the method for constructing the permeability model in the foregoing embodiments.

[0096] Figure 8 It is a schematic structural diagram of an electronic device provided in an embodiment of the present invention. As Figure 8 shown in the structure, the electronic device provided in the embodiment of the present invention includes: one or more processors 810 and a storage device 820; the processors 810 in the electronic device can be one or more, Figure 8 taking one processor 810 as an example; the storage device 820 is used to store one or more programs; the one or more programs are executed by the one or more processors 810, so that the one or more processors 810 implement the method for constructing the permeability model as described in any one of the embodiments of the present invention.

[0097] The electronic device may further include: an input device 830 and an output device 840.

[0098] The processor 810, storage device 820, input device 830, and output device 840 in the electronic device may be connected via a bus or other means. Figure 8 Take the connection via the bus as an example.

[0099] The storage device 820 in the electronic device, as a computer-readable storage medium, can be used to store one or more programs. The programs can be software programs, computer-executable programs, and modules, such as the program instructions / modules corresponding to the method for constructing a permeability model provided in the embodiments of the present invention. The processor 810 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the storage device 820, that is, implements the method for constructing a permeability model in the above method embodiments.

[0100] The storage device 820 may include a program storage area and a data storage area. Among them, the program storage area can store an operating system and application programs required for at least one function; the data storage area can store data created according to the use of the electronic device, etc. In addition, the storage device 820 may include a high-speed random access memory, and may also include a non-volatile memory, such as at least one magnetic disk storage device, a flash memory device, or other non-volatile solid-state storage devices. In some instances, the storage device 820 may further include a memory remotely set relative to the processor 810, and these remote memories can be connected to the device through a network. Examples of the above network include but are not limited to the Internet, enterprise intranet, local area network, mobile communication network, and their combinations.

[0101] The input device 830 can be used to receive input digital or character information, and generate key signal inputs related to the user settings and function controls of the electronic device. The output device 840 may include a display device such as a display screen.

[0102] And when one or more programs included in the above electronic device are executed by the one or more processors 810, the programs perform the following operations:

[0103] Analyze the core data of the complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation laws among elastic parameters, porosity, and permeability;

[0104] Based on the elastic parameters in the reservoir change information, construct a porosity model of the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir;

[0105] Construct a permeability model of the complex carbonate reservoir based on the well logging interpreted porosity curve optimized according to the porosity model.

[0106] Of course, those skilled in the art can understand that when one or more programs included in the above electronic device are executed by the one or more processors 810, the programs can also perform the relevant operations in the method for constructing the permeability model provided in any embodiment of the present invention.

[0107] An embodiment of the present invention provides a computer-readable medium, on which a computer program is stored, and when the program is executed by a processor, it is used to execute a method for constructing a permeability model, and the method includes:

[0108] Analyze the core data of a complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation laws among elastic parameters, porosity, and permeability;

[0109] Based on the elastic parameters in the reservoir change information, construct a porosity model of the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir;

[0110] Construct a permeability model of the complex carbonate reservoir according to the well logging interpreted porosity curve optimized by the porosity model.

[0111] The computer storage medium of the embodiment of the present invention can adopt any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable CD-ROM, an optical storage device, a magnetic storage device, or any suitable combination of the above. The computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or in combination with an instruction execution system, apparatus, or device.

[0112] A computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries computer-readable program code. Such a propagated data signal may take many forms, including but not limited to: electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium may also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device.

[0113] The program code contained on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, optical fiber cable, radio frequency (RF), and the like, or any suitable combination of the foregoing.

[0114] The computer program code for performing the operations of the present invention may be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code may execute entirely on the user's computer, partially on the user's computer, execute as a stand-alone software package, execute partially on the user's computer and partially on a remote computer, or execute entirely on a remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (e.g., through the Internet using an Internet service provider).

[0115] In the description of this specification, the description of reference terms such as "one embodiment", "some embodiments", "example", "specific example", or "some examples" means that the specific features, structures, materials, or characteristics described in connection with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representations of the above terms do not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials, or characteristics described may be combined in any one or more embodiments or examples in a suitable manner.

[0116] Note that the above is only the preferred embodiment of the present invention and the technical principles applied. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, re-adjustments and substitutions can be made by those skilled in the art without departing from the protection scope of the present invention. Therefore, although the present invention has been described in more detail through the above embodiments, the present invention is not limited to the above embodiments. Without departing from the concept of the present invention, more other equivalent embodiments can be included, and the scope of the present invention is determined by the scope of the appended claims.

Claims

1. A method for constructing a permeability model, characterized in that, The method includes: Analyzing the core data of the complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation laws among elastic parameters, porosity, and permeability; Based on the elastic parameters in the reservoir change information, constructing a porosity model for the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir; Constructing a permeability model for the complex carbonate reservoir based on the well logging interpreted porosity curve optimized by the porosity model; Among them, constructing a porosity model for the complex carbonate reservoir according to the shale content information of the complex carbonate reservoir includes: Conducting rock porosity analysis on the complex carbonate reservoir to construct a rock pore morphology factor for the complex carbonate reservoir; the rock pore morphology factor is used to characterize the shale content of the complex carbonate reservoir; Based on the rock pore morphology factor of the complex carbonate reservoir, constructing a porosity model for the complex carbonate reservoir through multiple linear regression; Among them, conducting rock porosity analysis on the complex carbonate reservoir to construct a rock pore morphology factor for the complex carbonate reservoir includes: Using acoustic logging to conduct rock porosity analysis on the complex carbonate reservoir to obtain acoustic porosity; Using density logging to conduct rock porosity analysis on the complex carbonate reservoir to obtain density porosity; Conducting porosity difference analysis based on the acoustic porosity and density porosity of the complex carbonate reservoir to obtain the pore morphology factor of the complex carbonate reservoir; Among them, constructing a permeability model for the complex carbonate reservoir based on the well logging interpreted porosity curve optimized by the porosity model includes: Conducting well logging interpretation through the porosity model to obtain an optimized well logging interpreted porosity curve; Using the porosity after well logging interpretation optimization and the correction of the pore morphology factor to construct a unified permeability model for the entire complex carbonate reservoir.

2. The method according to claim 1, characterized in that, The elastic parameters include parameters for characterizing rock physical properties, and the elastic parameters include the longitudinal wave impedance constructed by the product of the longitudinal wave velocity and density.

3. The method according to claim 1, characterized in that, Before conducting rock porosity analysis on the complex carbonate reservoir to construct a rock pore morphology factor for the complex carbonate reservoir, it further includes: Based on the geological data and actual drilling data of the complex carbonate reservoir, conducting rock physics analysis on the complex carbonate reservoir; According to the results of the rock physics analysis, determining the acoustic wave and density sensitive to the shale content for conducting rock porosity analysis using acoustic logging and density logging.

4. An apparatus for constructing a permeability model, characterized in that The device includes: A core data analysis module for analyzing the core data of the complex carbonate reservoir to determine the reservoir change information of the complex carbonate reservoir; the reservoir change information includes the variation laws among elastic parameters, porosity, and permeability; A porosity model construction module for constructing a porosity model for the complex carbonate reservoir based on the elastic parameters in the reservoir change information according to the shale content information of the complex carbonate reservoir; A permeability model construction module for constructing a permeability model for the complex carbonate reservoir based on the well logging interpreted porosity curve optimized by the porosity model; Among them, the permeability model construction module is used to: analyze the rock porosity of complex carbonate reservoirs, and construct the rock pore morphology factor of complex carbonate reservoirs; the rock pore morphology factor is used to characterize the shale content of complex carbonate reservoirs; based on the rock pore morphology factor of complex carbonate reservoirs, construct the porosity model of complex carbonate reservoirs through multiple linear regression. Among them, analyzing the rock porosity of complex carbonate reservoirs and constructing the rock pore morphology factor of complex carbonate reservoirs includes: using acoustic logging to analyze the rock porosity of complex carbonate reservoirs to obtain acoustic porosity; using density logging to analyze the rock porosity of complex carbonate reservoirs to obtain density porosity; based on the acoustic porosity and density porosity of the complex carbonate reservoir, perform porosity difference analysis to obtain the pore morphology factor of the complex carbonate reservoir. Among them, constructing the permeability model of complex carbonate reservoirs based on the logging interpretation porosity curve optimized by the porosity model includes: performing logging interpretation through the porosity model to obtain an optimized logging interpretation porosity curve; using the porosity after optimized logging interpretation and the correction of the pore morphology factor to construct a unified permeability model for the entire complex carbonate reservoir.

5. The device according to claim 4, characterized in that The elastic parameters include parameters for characterizing rock physical properties, and the elastic parameters include the longitudinal wave impedance constructed by the product of the longitudinal wave velocity and density.

6. An electronic device, characterized in that, Including: One or more processing devices; A storage device for storing one or more programs; When the one or more programs are executed by the one or more processing devices, the one or more processing devices implement the method for constructing the permeability model according to any one of claims 1-3.

7. A computer-readable medium having a computer program stored thereon, characterized in that, When the program is executed by the processing device, it implements the method for constructing the permeability model according to any one of claims 1-3.

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