Reservoir fracture evolution stage and pore permeability parameter collaborative quantitative characterization method
By employing a seismic inversion method for mechanical parameters of fractured-vuggy reservoirs constrained by well logging geostress, combined with rock mechanics experiments, CT scans, and digital core modeling, the problem of rapidly and accurately determining reservoir porosity and permeability response in the absence of nuclear magnetic resonance and acoustic wave detection was solved, thus improving the accuracy of reservoir evaluation.
Patent Information
- Application Number
- CN202511248338.3
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2025-09-03
- Publication Date
- 2025-11-28
AI Technical Summary
In the absence of nuclear magnetic resonance and acoustic wave detection, it is difficult to quickly and accurately determine the porosity and permeability response of reservoir rocks, which affects the accuracy of reservoir evaluation.
A seismic inversion method for mechanical parameters of fractured-vuggy reservoirs based on well logging stress constraints was adopted. By combining rock mechanics experiments and CT scans with digital core modeling, the porosity and tortuosity of the rocks were determined. Combined with particle flow modeling, the macroscopic structural evolution of the reservoir was simulated, and the synergistic quantitative characterization of porosity and permeability parameters was achieved.
It enables rapid and accurate determination of the porosity and permeability response of rocks without nuclear magnetic resonance or acoustic wave detection, thus improving the accuracy and reliability of reservoir evaluation.
Smart Images
Figure CN121027177A_ABST
Abstract
Description
TECHNICAL FIELD
[0001] The present application relates to the field of oil and gas field exploration and development, and particularly relates to a method for quantitatively representing reservoir fracture evolution stage and porosity-permeability parameters. BACKGROUND
[0002] The porosity-permeability parameters refer to the response of the porosity and tortuosity of the reservoir rock to the change of external factors. The reservoir fracture evolution stage refers to the process that the internal structure and properties of the reservoir rock change in a series due to the comprehensive influence of multiple factors such as tectonic movement, sedimentation and diagenesis in the geological history. Therefore, it is of great significance to determine the porosity-permeability parameters and the fracture evolution stage for reservoir evaluation. The macroscopic tectonic evolution process of the research area includes the formation of folds, the development of faults and the evolution of tectonic deformation, and the micro-pore structure change is analyzed, and accordingly the influence relationship between the reservoir fracture evolution stage and the porosity, tortuosity and permeability is studied. Through the compression experiment, the stress-strain curve of the rock can be obtained, and then the generation and expansion law of the fracture can be analyzed. In addition, the digital core modeling technology can reconstruct the three-dimensional pore structure of the rock based on the CT scanning image, and provide technical support for the quantitative analysis of the porosity, tortuosity and other parameters. The digital core modeling technology is widely used in reservoir research, and can construct the micro-pore structure model of the rock through high-resolution CT scanning or image reconstruction algorithm. The particle flow modeling technology PFC can simulate the macroscopic tectonic evolution process of the fold thrust belt, and the accuracy of the model is verified by comparison with the geological exploration data. The technology can provide a macro background for studying the reservoir fracture evolution stage, and reveal the influence mechanism of the fracture development on the reservoir porosity-permeability performance by combining with the micro-pore structure change. The porosity and tortuosity are the key parameters for reservoir evaluation. Through the digital core modeling and numerical simulation, the influence of the fracture development on the porosity and tortuosity can be analyzed, and then the flow behavior of the fluid in the reservoir can be predicted. This micro-macro combined research method provides a new idea for the dynamic evaluation of the reservoir and the design of the development plan.
[0003] The pore-throat ratio determined in the above method is the change of the indirect physical pressure, which is converted through a certain mathematical relationship, and the accuracy is affected to a certain extent. SUMMARY To solve the above defects in the prior art, the purpose of the present application is to provide a method for quantitatively representing the reservoir fracture evolution stage and the porosity-permeability parameters, which can quickly and accurately obtain the porosity-permeability response of the rock without nuclear magnetic resonance and acoustic waves. The technical scheme of the present application is as follows: First step: rock sample screening, preparing two sets of samples A and B. Representative core samples were selected, ensuring they were intact, free from obvious cracks, damage, or impurities. They were processed to specific dimensions according to the experimental setup requirements, and the sample ends were machined using a grinder or lathe to ensure parallelism and uniform stress during the experiment. The processed samples were then divided into two sets, A and B, ensuring consistency in material composition, diagenetic strength, and sampling depth. Sets A and B were numbered. Ensuring consistency in material composition and diagenetic strength between the two sets involved analyzing the samples using whole-rock mineral analysis methods, comparing the mineral composition, grain size distribution, and microscopic characteristics of the two sets, and calculating diagenetic parameters to ensure consistency.
[0004] The second step is to conduct rock mechanics experiments on sample A to determine the rock stress-strain curve. Sample A is placed into the rock mechanics testing equipment, ensuring close contact between the sample and the loading plate of the equipment; the testing machine is preloaded, and the sample is checked for displacement or loosening during the loading process to ensure the stability of the test; pressure is applied to sample A at a constant loading rate, and the stress, strain data and fracture characteristics of the sample are recorded during the test. The characteristics of the stress-strain curve are analyzed to determine the Young's modulus, Poisson's ratio, and compressive strength of the rock. The specific steps for analyzing the characteristics of the stress-strain curve and determining the Young's modulus, Poisson's ratio, and compressive strength of the rock are as follows: Determine the elastic modulus and Poisson's ratio of the rock based on the stress-strain curve: (1) (2) In formula (1)-(2), E s , μ s —These represent the elastic modulus and Poisson's ratio of the rock, respectively; Δ σ —Axial stress increment; Δ ε 1 — Axial strain increment; Δ ε 2—Transverse strain increment; When calculating the elastic modulus and Poisson's ratio of rock, the elastic state segment of its stress-strain curve should be used; The maximum load was recorded by continuously loading the specimen until it fractured. P max Compressive strength through σ c = P max / A Calculation determined, where A This represents the cross-sectional area.
[0005] The third step is to determine the CT scan points of sample B based on the stress and strain curves. Based on the stress-strain curve of sample A, the critical fracture point is determined. The scanning position corresponding to the critical fracture point of sample A is marked on sample B to ensure that the scanning point can cover the rock's initiation point, propagation path and final fracture area.
[0006] The fourth step involves conducting rock mechanics experiments on sample B and performing CT scans at the corresponding scanning points. Mount sample B onto the rock mechanics testing machine and ensure that the scanning device can accurately align with the marked scanning points; while performing a compression test on sample B, perform a CT scan on the marked scanning points; apply pressure at the same loading rate and record the stress and strain data, as well as the CT scan images, in real time during the experiment; ensure that the resolution and contrast of the CT scan images meet the requirements.
[0007] Ensuring that the resolution and contrast of the CT scan images meet the requirements means that the images can clearly reflect the changes in the internal structure of the rock; recording stress and strain data during the experiment, as well as the CT scan images, to ensure the integrity and accuracy of the data; and preprocessing the CT scan images to remove noise and artifacts and extract the pore structure information of the rock.
[0008] The fifth step is digital core modeling, which calculates the porosity and tortuosity of the rock at different fracture stages; Two-dimensional images acquired from CT scans are processed, and image segmentation algorithms are used to extract pore structure information of the rock. Pores are classified and labeled to distinguish between pore, fracture, and matrix regions, ensuring the integrity of the pore structure. Three-dimensional images of the rock core are reconstructed using the two-dimensional images, and image reconstruction algorithms are employed to ensure that the reconstructed images accurately reflect the pore structure of the rock. The reconstructed three-dimensional images are verified by comparing them with the two-dimensional images to check the continuity and integrity of the pore structure. Based on the three-dimensional images, the porosity and tortuosity of the rock at different fracture stages are calculated. The variation patterns of porosity and tortuosity are analyzed to study the influence of fracture generation and propagation on the pore structure. A comparative analysis of porosity and tortuosity at different fracture stages is conducted to determine the influence mechanism of fractures on reservoir porosity and permeability.
[0009] The calculation of rock porosity and tortuosity at different fracture stages refers to the following: porosity here refers to total porosity, which macroscopically manifests as an increase in rock porosity, the propagation of cracks, the development of internal pores, and enhanced connectivity of the pore structure. Microcracks extend around carbonate minerals and may terminate at mechanically stable minerals. Tortuosity, the ratio of the actual fluid seepage path to its apparent seepage path, is an important parameter describing seepage in rough fracture structures. Its calculation formula is the ratio of the actual fluid seepage distance to the apparent fluid seepage distance; the larger the value, the worse the connectivity of the pore structure.
[0010] The sixth step uses granular flow modeling to determine the macroscopic structural evolution stages of the fold-thrust belt; The fold-thrust belt in the study area was modeled using the particle flow software PFC. Based on the geological and structural background of the study area, the initial conditions of the model were set, including the mechanical parameters of the rocks, boundary conditions and tectonic stress field, to simulate its macroscopic tectonic evolution process and determine the macroscopic tectonic evolution stage of the fold-thrust belt.
[0011] The simulation of the macroscopic tectonic evolution process defines the macroscopic tectonic evolution stages of the fold-thrust belt as including fold formation, fault development, and tectonic deformation evolution. The simulation results are compared with geological exploration data to verify the model's accuracy. Based on the simulation results, the macroscopic tectonic evolution stages of the fold-thrust belt are determined, and different evolution stages are divided, including the fold formation stage, fold evolution stage, fault development stage, and tectonic stability stage. The tectonic characteristics and deformation patterns of different evolution stages are analyzed to provide a macroscopic background for subsequent research.
[0012] The seventh step, based on the macroscopic structural evolution stages and combined with digital core modeling, examines the reservoir fracture evolution stages and porosity-permeability responses. By combining the strain magnitude at different tectonic locations in the study area, and using the rock porosity and tortuosity calculated in digital core modeling at different fracture stages, the reservoir fracture evolution stage and porosity-permeability response were determined.
[0013] The determination of reservoir fracture evolution stages and porosity-permeability response refers to: analyzing the strain magnitude at different evolution stages based on the geological and structural background and experimental data of the study area to determine the evolution stages of reservoir fracture; dividing the evolution stages of reservoir fracture by combining macroscopic structural evolution stages and microscopic pore structure changes; studying the response relationship between reservoir fracture evolution stages and parameters such as porosity and permeability by combining digital core modeling results and strain analysis; analyzing the influence mechanism of fracture generation and expansion on porosity and permeability to determine the variation law of porosity-permeability parameters in reservoirs at different structural locations; discussing the research results and comparing and verifying them with actual geological exploration data to ensure the accuracy and reliability of the results.
[0014] The patent includes an electronic device characterized by comprising: a memory and a processor; the memory is used to store program instructions; the processor is used to invoke the program instructions in the memory to execute the above-described method.
[0015] The patent includes a computer-readable storage medium, characterized in that a computer program is stored on the computer-readable storage medium; when the computer program is executed, it implements the above-mentioned method for co-characterizing reservoir fracture evolution stages and porosity-permeability parameters.
[0016] The patent also includes a computer program product, comprising a computer program, characterized in that, when the computer program is executed by a processor, it implements the aforementioned method for co-characterizing reservoir fracture evolution stages and porosity-permeability parameters. Attached Figure Description
[0017] Figure 1 This is a flowchart of a method for the coordinated quantitative characterization of reservoir fracture evolution stages and porosity-permeability parameters.
[0018] Figure 2 This is a diagram of experimental equipment for rock mechanics.
[0019] Figure 3 This is the stress-strain curve for sample A.
[0020] Figure 4 This is a CT scan image of sample B.
[0021] Figure 5 Image showing the results of the scanning model for sample B.
[0022] Figure 6 The result of digital core modeling for sample B.
[0023] Figure 7 This is a diagram illustrating the specific calculation process of tortuosity in digital rock cores.
[0024] Figure 8 This is a diagram showing the variation of total porosity and tortuosity during rock fracturing.
[0025] Figure 9 Figure showing the modeling results for PFC particle flow.
[0026] Figure 10 This is a diagram of the macroscopic structural evolution process after simulation.
[0027] Figure 11 This diagram shows the fracture evolution stage of underground rocks and its predicted permeability. Detailed Implementation
[0028] The specific embodiments of the present invention are described below with reference to the accompanying drawings: This invention patent uses the tight sandstone reservoir in the Bozi-Dabei area on the northern margin of the Tarim Basin in western China as an example to illustrate the specific implementation process of the invention. The Bozi-Dabei tight sandstone reservoir is located in the western part of the Kelasu tectonic belt in the northern part of the Kuqa Depression in the Tarim Basin. It is the first row of thrust belts in the southern Tianshan Mountains. The overall deformation of the Bozi-Dabei area is relatively gentle, and together with the Wensu Paleo-Uplift in the southwest, it controls the differences in the lateral deformation characteristics of the tectonic belt, forming multiple tectonic deformation modes and exhibiting forward-protruding deformation characteristics. The Bozi-Dabei gas field is difficult to exploit due to its deep burial and well-developed fractures in the tight sandstone reservoir. The contribution of fractures in different tectonic units to the reservoir is unclear. Therefore, a quantitative characterization method for the reservoir fracture evolution stage and porosity-permeability parameters is needed to optimize the distribution of high-quality reservoirs.
[0029] The first step is rock sample screening, preparing two sets of samples, A and B; Select representative core samples, ensuring that the samples are intact, without obvious cracks, damage or impurities. Process them to specific dimensions according to the experimental setup requirements, and use a grinder or lathe to process the sample end faces to keep them parallel, ensuring uniform stress during the experiment. Divide the processed samples into two sets, A and B, ensuring that the two sets of samples are consistent in material composition, diagenetic strength, and sampling depth, and number the two sets of samples.
[0030] The second step is to conduct rock mechanics experiments on sample A to determine the rock stress-strain curve. Sample A was placed into the rock mechanics experimental equipment. Figure 2 Ensure that the sample is in close contact with the loading plate of the rock mechanics experimental equipment; preload the experimental machine and check whether the sample has displacement or loosening during the loading process to ensure the stability of the experimental process; apply pressure to sample A at a constant loading rate, record the stress and strain data and fracture characteristics of the sample during the experiment, analyze the characteristics of the stress-strain curve, and determine the Young's modulus, Poisson's ratio, and compressive strength of the rock.
[0031] The third step is to determine the CT scan points of sample B based on the stress and strain curves. Based on the stress-strain curve of sample A ( Figure 3 To identify the critical fracture point, the scanning position corresponding to the critical fracture point of sample A is marked on sample B, ensuring that the scanning point can cover the rock's fracture initiation point, propagation path, and final fracture area.
[0032] The fourth step involves conducting rock mechanics experiments on sample B and performing CT scans at the corresponding scanning points. Sample B was mounted on a rock mechanics testing machine, ensuring the scanning equipment was accurately aligned with the marked scanning points. Simultaneously with the compression test of sample B, a CT scan was performed on the marked scanning points. Pressure was applied at the same loading rate, and stress and strain data, as well as CT scan images, were recorded in real time during the experiment. Figure 4 Ensure that the resolution and contrast of the CT scan images meet the requirements.
[0033] The fifth step is digital core modeling, which calculates the porosity and tortuosity of the rock at different fracture stages; The two-dimensional images acquired from CT scans were processed, and image segmentation algorithms were used to extract the pore structure information of the rock. Pores were classified and labeled to distinguish between pore, fracture, and matrix regions, ensuring the integrity of the pore structure. Three-dimensional images of the rock core were reconstructed from the two-dimensional images. Figure 5 An image reconstruction algorithm is used to ensure that the reconstructed image accurately reflects the pore structure of the rock. Figure 6 The reconstructed 3D image is verified by comparing it with the 2D image to check the continuity and integrity of the pore structure; the specific calculation process of tortuosity in the digital core is as follows ( Figure 7 ): Based on three-dimensional images, the porosity and tortuosity of rocks at different fracture stages were calculated; the variation patterns of porosity and tortuosity were analyzed to study the influence of fracture generation and propagation on pore structure; and a comparative analysis of porosity and tortuosity at different fracture stages was conducted to determine the mechanism by which fractures affect reservoir porosity and permeability. Figure 8 ).
[0034] The sixth step uses granular flow modeling to determine the macroscopic structural evolution stages of the fold-thrust belt; The fold-thrust zone in the study area was modeled using the particle flow software PFC. Figure 9 Based on the geological and tectonic background of the study area, the initial conditions of the model were set, including the mechanical parameters of the rocks, boundary conditions, and tectonic stress field, to simulate its macroscopic tectonic evolution process and determine the macroscopic tectonic evolution stages of the fold-thrust belt. Figure 10 ).
[0035] The seventh step, based on the macroscopic structural evolution stages and combined with digital core modeling, examines the reservoir fracture evolution stages and porosity-permeability responses. By combining the strain magnitudes at different tectonic locations in the study area and utilizing the rock porosity and tortuosity calculated in digital core modeling at different fracture stages, the reservoir fracture evolution stages and porosity-permeability response were determined. Figure 11 ).
[0036] The present invention has been described above by way of example, but the present invention is not limited to the specific embodiments described above. Any modifications or variations made based on the present invention are within the scope of protection claimed by the present invention.
Claims
1. A method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters, characterized in that, Includes the following steps: The first step is rock sample screening, preparing two sets of samples, A and B; Select representative core samples, ensuring that the samples are intact, without obvious cracks, damage or impurities. Process them to specific dimensions according to the experimental setup requirements, and use a grinder or lathe to process the sample end faces to keep them parallel, ensuring uniform stress during the experiment. Divide the processed samples into two sets, A and B, to ensure that the two sets of samples are consistent in material composition, diagenetic strength, and sampling depth, and number the two sets of samples. The second step is to conduct rock mechanics experiments on sample A to determine the rock stress-strain curve. Sample A is placed into the rock mechanics testing equipment, ensuring close contact between the sample and the loading plate of the equipment; the testing machine is preloaded, and the sample is checked for displacement or loosening during the loading process to ensure the stability of the test; pressure is applied to sample A at a constant loading rate, and the stress, strain data and fracture characteristics of the sample are recorded during the test. The characteristics of the stress-strain curve are analyzed to determine the Young's modulus, Poisson's ratio, and compressive strength of the rock. The third step is to determine the CT scan points of sample B based on the stress and strain curves. Based on the stress-strain curve of sample A, the critical fracture point is determined. The scanning position corresponding to the critical fracture point of sample A is marked on sample B to ensure that the scanning point can cover the rock's initiation point, propagation path and final fracture area. The fourth step involves conducting rock mechanics experiments on sample B and performing CT scans at the corresponding scanning points. Mount sample B onto the rock mechanics testing machine and ensure that the scanning device can be accurately aligned with the marked scanning points; while performing a compression test on sample B, perform a CT scan on the marked scanning points; apply pressure at the same loading rate and record the stress and strain data, as well as the CT scan images, in real time during the experiment; ensure that the resolution and contrast of the CT scan images meet the requirements. The fifth step is digital core modeling, which calculates the porosity and tortuosity of the rock at different fracture stages; Two-dimensional images acquired from CT scans were processed, and image modeling was used to extract pore structure information from rock samples. Pores were classified and labeled to distinguish between pore, fracture, and matrix regions, ensuring the integrity of the pore structure. Three-dimensional images of the rock cores were reconstructed using the two-dimensional images, employing image reconstruction algorithms to ensure the reconstructed images accurately reflect the pore structure of the rock samples. The reconstructed three-dimensional images were validated by comparing them with the two-dimensional images to check the continuity and integrity of the pore structure. Based on the three-dimensional images, the porosity and tortuosity of the rock at different fracture stages were calculated. The variation patterns of porosity and tortuosity were analyzed to study the impact of fracture generation and propagation on the pore structure. A comparative analysis of porosity and tortuosity at different fracture stages was conducted to determine the mechanism by which fractures affect reservoir porosity and permeability. The sixth step uses granular flow modeling to determine the macroscopic structural evolution stages of the fold-thrust belt; The fold-thrust belt in the study area was modeled using the particle flow software PFC. Based on the geological and structural background of the study area, the initial conditions of the model were set, including the mechanical parameters of the rocks, boundary conditions and tectonic stress field, to simulate its macroscopic tectonic evolution process and determine the macroscopic tectonic evolution stage of the fold-thrust belt. The seventh step, based on the macroscopic structural evolution stages and combined with digital core modeling, examines the reservoir fracture evolution stages and porosity-permeability responses. By combining the strain magnitude at different tectonic locations in the study area, and using the rock porosity and tortuosity calculated in digital core modeling at different fracture stages, the reservoir fracture evolution stage and porosity-permeability response were determined.
2. The method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: Ensuring consistency in material composition and diagenetic strength between the two sets of samples refers to using whole-rock mineral testing and analysis methods to analyze the material composition of the samples, comparing the mineral composition, grain size distribution, and microscopic characteristics of the two sets of samples, calculating diagenetic parameters, and ensuring their consistency.
3. The method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: The specific steps for analyzing the characteristics of the stress-strain curve and determining the Young's modulus, Poisson's ratio, and compressive strength of the rock are as follows: Determine the elastic modulus and Poisson's ratio of the rock based on the stress-strain curve: （1） （2） In formula (1)-(2), E s , μ s —These represent the elastic modulus and Poisson's ratio of the rock, respectively; Δ σ —Increment in axial stress; Δ ε 1 — Axial strain increment; Δ ε 2—Transverse strain increment; When calculating the elastic modulus and Poisson's ratio of rock, the elastic state segment of its stress-strain curve should be used; The maximum load was recorded by continuously loading the specimen until it fractured. P max Compressive strength through σ c = P max / A Calculation determined, where A This represents the cross-sectional area.
4. The method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: Ensuring that the resolution and contrast of the CT scan images meet the requirements means that the images can clearly reflect the internal structural changes of the rock; Record stress and strain data, as well as CT scan images, during the experiment to ensure data integrity and accuracy; preprocess the CT scan images to remove noise and artifacts, and extract the pore structure information of the rock.
5. The method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: The calculation of rock porosity and tortuosity at different fracture stages refers to the following: porosity here refers to total porosity, which macroscopically manifests as an increase in rock porosity, the expansion of cracks, the development of internal pores, and enhanced connectivity of the pore structure; microcracks extend around carbonate minerals, and microcracks may terminate at mechanically stable minerals; tortuosity is the ratio of the actual seepage path of fluid to its apparent seepage path, which is an important parameter describing the seepage in a rough fracture structure; its calculation formula is the ratio of the actual seepage distance of fluid to the apparent seepage distance of fluid, and the larger the value, the worse the connectivity of the pore structure.
6. The method for co-characterizing reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: The simulation of the macroscopic tectonic evolution process defines the macroscopic tectonic evolution stages of the fold-thrust belt as including fold formation, fault development, and tectonic deformation evolution. The simulation results are compared with geological exploration data to verify the model's accuracy. Based on the simulation results, the macroscopic tectonic evolution stages of the fold-thrust belt are determined, and different evolution stages are divided, including the fold formation stage, fold evolution stage, fault development stage, and tectonic stability stage. The tectonic characteristics and deformation patterns of different evolution stages are analyzed to provide a macroscopic background for subsequent research.
7. The method for synergistic characterization of reservoir fracture evolution stages and porosity-permeability parameters according to claim 1, characterized in that: The determination of reservoir fracture evolution stages and porosity-permeability response refers to analyzing the strain magnitude at different evolution stages based on the geological and structural background and experimental data of the study area to determine the evolution stages of reservoir fracture; dividing the evolution stages of reservoir fracture by combining macroscopic structural evolution stages and microscopic pore structure changes; and studying the response relationship between reservoir fracture evolution stages and parameters such as porosity and permeability by combining digital core modeling results and strain analysis. The study analyzes the impact mechanism of fracture generation and propagation on porosity and permeability, and determines the variation law of porosity and permeability parameters in reservoirs at different structural locations. The research results are discussed and compared with actual geological exploration data to ensure the accuracy and reliability of the results.
8. An electronic device, characterized in that, include: Memory and processor; The memory is used to store program instructions; The processor is used to invoke program instructions in the memory to execute the method as described in any one of claims 1-7.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program; when the computer program is executed, it implements a method for co-characterizing reservoir fracture evolution stages and porosity-permeability parameters as described in any one of claims 1-7.
10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the method for co-characterizing reservoir fracture evolution stages and porosity-permeability parameters as described in any one of claims 1-7.