Simulation method for carbonate rock pore preservation mechanism under super-deep thermal fluid-structure interaction

Abstract

The application discloses a kind of simulation methods of carbonate rock pore retention mechanism under super deep thermal fluid-solid coupling, it is related to rock physics technical field.The application is prepared by preparing carbonate rock sample, obtains its CT scanning slice image extraction three-dimensional pore information, after laboratory preparation plunger sample is carried out pseudo triaxial experiment, laboratory test result is used to calibrate micro parameter after construction carbonate rock model, cooperate in carbonate rock model and layout measuring ball, dynamically monitor porosity and pore pressure variation, by laboratory experiment, determine the strength reduction function of carbonate rock after, carbonate rock model is applied temperature field and stress field collaborative change true triaxial compression servo environment, using carbonate rock model carries out true triaxial experiment numerical simulation, obtains the pore condition inside carbonate rock of each stage evolution, determines the pore retention mechanism of carbonate rock under super deep thermal fluid-solid coupling, provides technical support for carbonate rock reservoir research.

Description

Technical Field

[0001] This invention relates to the field of numerical simulation technology of rock physical and mechanical behavior, specifically to a simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling. Background Technology

[0002] With the completion of drilling missions exceeding 10,000 meters, the study of the mechanical behavior of ultra-deep rocks under high temperature and high pressure environments and reservoir retention mechanisms has become a current research hotspot. Clarifying the laws of pore evolution, retention limits, and brittle-ductile transition zones will be important references for oil and gas exploration depth, but the controlling factors are complex and diverse, and the coupling relationships are still unclear.

[0003] Carbonate rocks, as an important lithological type for deep and ultra-deep oil and gas reservoirs, directly influence the effective accumulation and migration of oil and gas through their porosity retention characteristics and mechanical behavior. However, with the continuous increase in exploration depth, formation temperature and pressure rise significantly, leading to increasingly complex mechanical properties, porosity retention capacity, and brittle-ductility transformation mechanisms of carbonate rocks in deep environments. Currently, research on the porosity retention mechanism of carbonate rocks mainly relies on experimental testing and traditional numerical simulations, which have the following prominent shortcomings:

[0004] 1. Due to limitations in rock physics experimental conditions, it is difficult to realistically reproduce extreme deep environments;

[0005] At depths of 10,000 meters, the temperature of the strata generally exceeds 200°C, and can even reach 230°C, while the strata pressure is as high as 130-200 MPa. At the same time, the rock mass is subjected to huge and non-uniform triaxial stress, with the vertical stress reaching about 200-250 MPa at a depth of 10,000 meters. The two horizontal principal stresses are strongly affected by regional tectonic movements, and their magnitude and direction show significant anisotropy, forming a strong compressional tectonic environment. The temperature and pressure limits of existing true triaxial experimental devices are usually no more than 200°C and 200 MPa, respectively, which cannot accurately simulate the high temperature and high pressure conditions of 10,000-meter strata. That is, the mechanical degradation, pore compaction and fluid support mechanisms of carbonate rocks under such conditions cannot be fully characterized by experiments, which limits the accurate determination of the lower limit of pore retention and the brittle-ductile transition zone.

[0006] 2. Existing continuous medium models are insufficient for characterizing heterogeneous pore structures;

[0007] Current continuous medium methods such as the finite element method and finite difference method assume that rocks are homogeneous and cannot reflect the multi-scale porosity, fractures, and intergranular structure characteristics developed in carbonate rocks. These methods cannot fully consider key factors such as pore size, morphology, and spatial distribution in carbonate reservoirs. The idealized pore models constructed do not match actual reservoir conditions, and the mesh division scale severely restricts the characterization of the micromechanical interaction mechanism between pores and mineral particles. They have significant limitations in simulating fracture initiation and propagation, intergranular force chain reconstruction, and pore stress transmission, and are unable to reflect the multi-field response mechanism of real rocks at the microscale.

[0008] 3. The multi-field coupling effect is not fully expressed;

[0009] Existing studies are mostly force-fluid dual-field coupled models, which often ignore the influence of the temperature field on rock strength, stress distribution and pore evolution. They lack a fully coupled expression of the three fields of heat, fluid pressure and stress, and cannot reproduce the coupling effects of thermal expansion, thermal stress and thermal convection in the pore evolution process.

[0010] 4. Limited means of monitoring pore pressure and structural evolution;

[0011] Under experimental conditions, it is difficult to monitor the microscopic changes in pore pressure and porosity in real time. Under high pressure, the pipelines transmitting fluid exhibit a "consolidation effect," severely damping and delaying the pressure signal, making it impossible to capture transient fluctuations during the rupture process. Simultaneously, sensors are prone to drift and damage under extreme temperature and pressure conditions. For microscopic changes in porosity, indirect measurement methods suffer from ambiguity and cannot distinguish local cracks; direct imaging techniques, due to the conflict between the thick metal walls of the true triaxial pressure chamber and imaging requirements, result in severe image artifacts and are difficult to integrate. Existing numerical methods mostly employ globally uniform loading, failing to reflect the pressure response and local stress differences between different pores, and unable to reveal the microscopic support mechanism of pore pressure on pore maintenance.

[0012] 5. Conventional loading processes cannot reproduce complex geological burial histories;

[0013] Traditional laboratory triaxial testing and numerical simulation methods cannot achieve coordinated changes in temperature and pressure conditions. Moreover, the temperature and pressure change paths are mostly idealized monotonic loading processes, lacking precise setting of unloading nodes. This makes it difficult to reproduce the multiple uplift and burial processes experienced by ultra-deep reservoirs, and there is also a lack of effective characterization methods for the burial rate and temperature and pressure change gradient at different burial stages.

[0014] In summary, existing technologies suffer from several technical problems, including insufficient accurate characterization of rock properties and pore characteristics, limitations in temperature and pressure conditions during laboratory experiments, and difficulty in flexibly varying stress-strain paths. Therefore, there is an urgent need to propose a simulation method for the pore retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling. This method would effectively improve the accuracy and scientific validity of simulating the pore retention characteristics of carbonate rocks in deep-ultra-deep environments, providing strong support for subsequent research on pore retention capacity assessment, mechanical characteristic classification, determination of main controlling factors, and evaluation of oil and gas reservoirs in carbonate rocks. Summary of the Invention

[0015] This invention aims to address the shortcomings of existing technologies by proposing a simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-structure interaction. It combines digital core construction, pore distribution and thermal-fluid-structure interaction field embedding with true triaxial experimental data simulation, overcoming the limitations of laboratory true triaxial testing in terms of insufficient temperature and stress simulation conditions. By calibrating the mechanical properties of carbonate rocks under multiple temperature conditions, it reconstructs the physical and mechanical characteristics of carbonate rocks with specific lithologies and mineral contact relationships. It directly simulates the contribution and mechanism of pore pressure on porosity retention by applying pore pressure to particles within a specific range. Combined with the establishment of temperature-pressure synergistic variation units to reconstruct complex geological evolution processes, it achieves accurate simulation of the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-structure interaction, providing technical support for oil and gas reservoir evaluation.

[0016] The present invention adopts the following technical solution:

[0017] A simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling includes the following steps:

[0018] Step 1: Prepare carbonate rock samples, perform CT scans on the carbonate rock samples, and obtain CT scan slice images of the carbonate rock samples.

[0019] Step 2: Process CT image slices of carbonate rock samples using the Python database threshold segmentation method, extract three-dimensional pore information from the CT image slices of carbonate rock samples, and obtain the pore morphology, coordinates and volume of the three-dimensional pores;

[0020] Step 3: Obtain multiple plunger samples, conduct pseudo-triaxial experiments on the plunger samples in the laboratory, and use the laboratory test results to calibrate the micro-parameters of the particle flow discrete element software PFC3D 6.0 to obtain the micro-parameter set of carbonate rocks.

[0021] Step 4: In the particle flow discrete element software PFC3D 6.0, construct a carbonate rock model based on the size of the carbonate rock sample, import the carbonate rock pore model into the carbonate rock model, and set the microscopic parameters of the carbonate rock model.

[0022] Step 5: Set the initial pore pressure in the carbonate rock model, arrange targeted and densely packed measuring spheres according to the pore location, dynamically monitor the changes in porosity and pore pressure inside the carbonate rock model during the true triaxial numerical simulation, and obtain the pore pressure field of the carbonate rock model.

[0023] Step 6: In the laboratory, uniaxial compression tests are conducted at different temperatures using multiple plunger samples to determine the strength reduction function of carbonate rocks;

[0024] Step 7: Apply a true triaxial compression servo environment with coordinated changes in temperature and stress fields to the carbonate rock model, and perform true triaxial experimental numerical simulation using the carbonate rock model to obtain the porosity of the carbonate rock model at each stage of evolution, thereby realizing the numerical simulation of the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling.

[0025] Preferably, in step 1, a carbonate rock cube sample is obtained, the carbonate rock cube sample is cut into a standard cube sample to prepare a carbonate rock specimen, and a CT scanner is used to perform a CT scan on the carbonate rock specimen to obtain a CT image slice of the carbonate rock specimen.

[0026] Preferably, in step 2, a dedicated database for image processing and pore analysis is constructed based on a Python database. CT image slices of carbonate rock samples are input into this database. Preprocessing parameters are set, and pores within the carbonate rock sample are extracted from the CT images, with each pore volume generated individually. The number of pores in the carbonate rock sample, as well as the shape and volume of each pore, are determined. A visualized carbonate rock pore model is then established in the particle flow discrete element software PFC3D6.0.

[0027] Preferably, in step 3, multiple plunger samples are prepared. The plunger samples have a cylindrical structure and are drilled from the same carbonate rock block as the carbonate rock cube sample and are spatially adjacent to the carbonate rock cube sample.

[0028] Using displacement control mode and setting stress loading parameters, the prepared plunger specimen was subjected to uniaxial compressive strength test, and the stress-strain curve of the plunger specimen was obtained, thus obtaining the measured stress-strain curve.

[0029] In the calibration module of the particle flow discrete element software PFC3D 6.0, a plunger specimen model was generated based on the plunger specimen. The same stress loading parameters as those in the laboratory pseudo-triaxial experiment were set. The pseudo-triaxial experiment process was simulated in the particle flow discrete element software PFC6.0 using the plunger specimen model to obtain the stress-strain simulation curve, which was compared with the measured stress-strain curve. Based on the trial and error method, the micro-parameters of the plunger specimen model were adjusted so that the stress-strain simulation curve obtained by the plunger specimen model was consistent with the measured stress-strain curve. The micro-parameters of the plunger specimen model at this time were obtained to determine the micro-parameter set of carbonate rocks.

[0030] The microscopic parameters include parallel bond formation spacing, contact elastic modulus, particle stiffness ratio, parallel bond elastic modulus, parallel bond stiffness ratio, parallel bond tensile strength, parallel bond cohesion, friction angle, normal stiffness to tangential stiffness ratio, and friction coefficient.

[0031] Preferably, in step 4, in the sample generation module of the particle flow discrete element software PFC3D 6.0, the computational domain, sample particle size range and number of random seeds are set according to the size of the carbonate rock sample and the extracted three-dimensional pore information to establish a carbonate rock model with a cubic structure.

[0032] Based on the set of microscopic parameters of carbonate rock obtained in step 3, set all the particles and contacts in the carbonate rock model, set the initial porosity of the carbonate rock model, and generate rigid walls on the six outer surfaces of the carbonate rock model to simulate the loading plate for the true triaxial test of the carbonate rock sample.

[0033] Based on the three-dimensional pore information extracted from CT image slices of carbonate rock samples, the extracted pore morphology was imported into the particle flow discrete element software PFC3D 6.0 in the form of rigid clusters. The angular velocity of the rigid clusters was fixed and the moment of inertia was set to prevent the pores in the carbonate rock model from rotating during the stress process.

[0034] The particle bonding model in the carbonate rock model is set as a parallel bonding model, the bonding parameters are set, and the true triaxial experiment process is simulated using the carbonate rock model. Before stress loading, all initial contact forces in the carbonate rock model are cleared, so that the carbonate rock model is in a stress-free initial state.

[0035] Preferably, in step 5, the initial pore pressure value of each pore space in the carbonate rock model is set, and the bulk modulus of the fluid medium filled in each pore space is set in conjunction with the initial pore pressure value to characterize the compressibility of the fluid.

[0036] The position coordinates of all pores in the carbonate rock model are obtained, and a measuring sphere is generated accordingly. The radius of the measuring sphere is determined based on the radius of the equivalent sphere of the pores to ensure that it can cover the pore deformation and surrounding stress disturbance zone. The calculation formula is as follows:

[0037] ;

[0038] In the formula, To measure the radius of a sphere; This is the influence coefficient; The bulk volume of the rigid cluster;

[0039] All the measuring spheres in the carbonate rock model together constitute a pore response monitoring system. The porosity of the carbonate rock model is monitored by each measuring sphere, the pore pressure change caused by the porosity change is obtained, and the pore pressure change is applied to the particles that are in direct contact with the rigid clusters corresponding to the pores, thus achieving bidirectional coupling between the fluid and the solid skeleton of the carbonate rock.

[0040] The internal force preservation function of the carbonate rock model is set to a preservation frequency. The true triaxial test process of the carbonate rock sample is simulated in the computational domain using the carbonate rock model and rigid wall. The changes in porosity and pore pressure inside the carbonate rock model are dynamically monitored and preserved, and the pore pressure field inside the carbonate rock model during the true triaxial test numerical simulation is obtained.

[0041] Preferably, in step 6, after setting the initial temperature of the temperature field of the plunger sample in the uniaxial compression test, each plunger sample is subjected to thermal damage treatment within a preset temperature range to obtain multiple plunger samples treated at different temperatures. The uniaxial compressive strength of each plunger sample is then tested to obtain the uniaxial compressive strength of the plunger sample at different temperatures. The strength reduction function of the carbonate rock is then fitted, and the set of micro-parameters of the carbonate rock calibrated in step 3 is used as the reference value of the strength reduction function. The strength reduction function is then used to dynamically reduce the micro-strength of the carbonate rock according to the current simulated temperature to simulate the weakening effect of temperature on rock strength.

[0042] Preferably, step 7 includes the following sub-steps:

[0043] Step 701: Load the carbonate rock model in the particle flow discrete element software PFC3D 6.0, and delete the rigid clusters in the carbonate rock model. The carbonate rock model allows the internal pores of the carbonate rock to freely deform, compress or close under the combined action of external stress and internal pressure.

[0044] Step 702: Perform true triaxial numerical simulation using a carbonate rock model. Set up the true triaxial compression servo environment for the carbonate rock model, initialize the true triaxial stress field of the carbonate rock model, obtain the initial dimensions and overall stiffness of the carbonate rock model, and apply preset three-directional principal stresses to the carbonate rock model using six rigid walls. Set the initial value of the three-directional principal stresses applied to the carbonate rock model to 0, set the loading rate of the three-directional principal stresses according to the geological burial-uplift rate, and gradually increase the three-directional principal stresses applied to the carbonate rock model to the preset confining pressure value so that the carbonate rock model reaches the preset confining pressure environment. At this time, each rigid wall stably compacts the carbonate rock model.

[0045] Step 703: Set up a temperature and pressure co-variation simulation unit for the carbonate rock model, wherein the temperature and pressure co-variation simulation unit includes the internal temperature change of the simulation unit. Minimum principal stress variation in the simulation element Variation of principal stress in the simulation unit and the maximum principal stress variation of the simulated element ;

[0046] Step 704: Set the burial unit function and the uplift unit function. The burial unit function is used to increase the various changes in the temperature and pressure synergistic change simulation unit, and the uplift unit function is used to decrease the various changes in the temperature and pressure synergistic change simulation unit. During the true triaxial experimental numerical simulation, the burial unit function and the uplift unit function are called multiple times and in stages to combine a complex temperature and pressure evolution path that is consistent with the actual burial history of the target geological block.

[0047] Step 705: Perform a true triaxial servo numerical simulation of thermo-fluid-solid multi-field coupling using a carbonate rock model. Enable stress servo control and temperature field control functions for all rigid walls. Apply preset temperature field, true triaxial stress field, and pore pressure field. Adjust the buried element function and the uplift element function to allow the carbonate rock model to evolve under a preset complex temperature and pressure evolution path. Record the entire evolution process of the carbonate rock model during the numerical simulation. Obtain the stress-strain curve, porosity evolution curve, and pore pressure fluctuation of the carbonate rock model throughout the process. In conjunction with calling the crack monitoring function built into the particle flow discrete element software PFC3D 6.0, obtain the number, spatial location, and generation time of newly formed microcracks in the carbonate rock model during the true triaxial numerical simulation.

[0048] Step 706: After the true triaxial numerical simulation is completed, extract the simulation data of each stage of the carbonate rock model evolution, generate the stress-strain curve, three-dimensional particle displacement, force chain contact, energy dissipation cloud map, porosity evolution curve and pore pressure change curve of the carbonate rock model, and export them from the particle flow discrete element software PFC3D 6.0.

[0049] The present invention has the following beneficial effects:

[0050] (1) This invention proposes a simulation method for the pore retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling. It combines three-dimensional digital core construction, pore distribution and thermal-fluid-solid coupling field embedding with true triaxial servo condition numerical simulation method, which breaks the limitation of insufficient temperature and stress simulation conditions in laboratory true triaxial test. By calibrating the mechanical properties of carbonate rocks under multiple temperature conditions, it realizes the reconstruction of the physical and mechanical characteristics of carbonate rocks with specific lithology and mineral contact relationship. In addition, it directly simulates the contribution and mechanism of pore pressure inside carbonate rocks to pore retention by applying pore pressure to particles within a specific range, effectively avoiding complex seepage field calculations, and realizing the true restoration of the formation environment of carbonate rocks and the effect of pore pressure inside carbonate rocks.

[0051] (2) This invention proposes a simulation method for the pore retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling. It establishes temperature and pressure synergistic change units for complex geological evolution processes. By flexibly controlling the temperature and pressure evolution path from the surface to the ultra-deep layer, it can simulate specific burial-uplift processes and obtain the pore evolution and stress-strain curves of the whole process, thus realizing the true restoration of the temperature and pressure of carbonate rocks with burial depth under ultra-deep thermal-fluid-solid coupling.

[0052] (3) This invention proposes a simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling. It solves the limitations of existing technologies, such as the inability to realistically reproduce the temperature and pressure conditions of rocks, the difficulty in reproducing the physical and mechanical properties and real pore characteristics of rocks during numerical simulation, the lack of exploration of the microscopic mechanism of pore retention under multi-field coupling, and the difficulty in refining and controlling the temperature and pressure change path of rocks. By realistically reproducing the geological burial history, it effectively improves the accuracy and scientific nature of numerical simulation of pore retention characteristics of carbonate rocks in deep-ultra-deep environments. It provides a strong guarantee for subsequent research on pore retention capacity assessment, mechanical characteristic classification, determination of main control factors, and evaluation of oil and gas reservoirs of carbonate rocks with different mineral compositions and pore distribution characteristics. It has extremely high promotion value. Attached Figure Description

[0053] Figure 1 This is a schematic diagram of the simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-structure interaction according to the present invention.

[0054] Figure 2 This is a visualized pore model of algal-stacked dolomite in this invention.

[0055] Figure 3 This is a schematic diagram of the measuring sphere in the algal stromatolite model of the present invention.

[0056] Figure 4 The figures show three-dimensional particle displacement cloud maps obtained from simulations under different initial pore pressure conditions. In the figures, (a) is the particle displacement cloud map of the algal stromatolite model when the initial pore pressure is 0 MPa, and (b) is the particle displacement cloud map of the algal stromatolite model when the initial pore pressure is 30 MPa.

[0057] Figure 5 The figures show the stress-strain curves of algal stromatolite obtained by simulation under different temperature field control conditions according to the present invention. In the figure, (a) is the stress-strain curve of the algal stromatolite model under constant temperature of 25℃, and (b) is the stress-strain curve of the algal stromatolite model under heating conditions of 25℃~250℃.

[0058] Figure 6 This is the porosity evolution curve of the algal stromatolite of this invention.

[0059] Figure 7 This is a curve showing the pore pressure variation of the algal stromatolite of the present invention. Detailed Implementation

[0060] The present invention will now be described in detail with reference to the accompanying drawings and specific embodiments: Example

[0061] This embodiment proposes a simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-structure interaction, such as... Figure 1 As shown, it includes the following steps:

[0062] Step 1: Prepare carbonate rock samples and perform CT scans on the carbonate rock samples to obtain CT scan slice images of the carbonate rock samples.

[0063] Further, carbonate rock cube samples were obtained, and the carbonate rock cube samples were cut into... Standard cubic samples were used to prepare carbonate rock specimens. In order to ensure the uniformity of the mechanical boundaries of the carbonate rock specimens and the accuracy of subsequent simulations, it is necessary to strictly screen the carbonate rock specimens so that there are no macroscopic defects, significant mineral nodules or penetrating cracks visible to the naked eye on the surface of the carbonate rock specimens, and all edges of the carbonate rock specimens must maintain geometric continuity and integrity.

[0064] The prepared carbonate rock samples were non-destructively scanned using a high-precision micron-level computed tomography scanner. To ensure effective identification and reconstruction of mesoscale pores and initial microcracks that significantly influence rock mechanical behavior, the scanning spatial resolution was set to no less than 400 nm. CT image slices of carbonate rock samples were obtained by scanning.

[0065] The CT image slices were output as TIF files and saved to provide complete grayscale information for subsequent construction of the internal pore network of carbonate rocks.

[0066] Step 2: Process CT image slices of carbonate rock samples using the Python database threshold segmentation method, extract three-dimensional pore information from the CT image slices of carbonate rock samples, obtain the pore morphology, coordinates and volume of the three-dimensional pores, and save them as STL files.

[0067] Furthermore, a dedicated database for image processing and porosity analysis was constructed based on a Python database. CT image slices of carbonate rock samples were input into this dedicated database. Specifically, a CT image slice folder was obtained to store the CT image slices of carbonate rock samples, and the entire CT image slice folder was copied to the working directory of the dedicated database for image processing and porosity analysis. This ensured that the program could read all the CT image slices obtained from the scan in the correct sequence.

[0068] Based on the pre-set pore extraction program in the image processing and pore analysis database, preprocessing parameters are set, and the initial sampling rate is set to... The original data volume is sampled at full resolution. If the total number of pores identified under this setting exceeds the computational capacity of the subsequent numerical simulation, the sampling rate is increased in integer multiples, and the data volume needs to be downsampled until the number of pores is within the calculable range. The initial value of the ignored pores is set to 0, and then its pixel threshold is gradually increased until the cumulative volume of the ignored pores accounts for ≤10% of the total volume of the identified pores. The pore extraction program is run to extract each pore in the carbonate rock sample from the CT image of the carbonate rock sample and generate the pore volume one by one. The number of pores in the carbonate rock sample and the shape and volume of each pore are extracted and saved. A visualized carbonate rock pore model is built in the particle flow discrete element software PFC3D 6.0.

[0069] Step 3: Obtain multiple plunger samples and conduct pseudo-triaxial experiments on the plunger samples in the laboratory. Use the laboratory test results to calibrate the micro-parameters of the particle flow discrete element software PFC3D 6.0 and obtain the micro-parameter set of carbonate rocks.

[0070] Furthermore, multiple plunger specimens were prepared. Each plunger specimen had a cylindrical structure with a diameter of 25 mm, a height-to-diameter ratio controlled between 2.0 and 3.0, and flush upper and lower surfaces with tolerances. 0.01 mm. To ensure a high degree of consistency between the plunger sample and the carbonate rock sample in terms of mineral composition, cementation structure, and initial damage state, the plunger sample and the carbonate rock cube sample are drilled from the same carbonate rock block and are spatially adjacent to the carbonate rock cube sample. The deviation of the longitudinal wave velocity test between the two does not exceed 1%, and the plunger sample surface has no obvious structural planes or void distribution.

[0071] Using a displacement control mode and setting stress loading parameters, a pseudo-triaxial experiment was conducted on the prepared plunger specimen. Stress was applied at a constant low strain rate, and the stress-strain curves of the plunger specimen from linear elastic deformation, yielding, peak strength to residual strength were recorded in their entirety. The stress-strain curves of the plunger specimen were obtained, and the measured stress-strain curves were obtained.

[0072] In the calibration module of the particle flow discrete element software PFC3D 6.0, a plunger specimen model was generated based on the plunger specimen. The same stress loading parameters as those in the laboratory pseudo-triaxial experiment were set. The pseudo-triaxial experiment process was simulated in PFC3D 6.0 using the plunger specimen model to obtain the stress-strain simulation curve, which was then compared with the measured stress-strain curve. Based on the trial and error method, the micro-parallel bond formation spacing, contact elastic modulus, particle stiffness ratio, parallel bond elastic modulus, parallel bond stiffness ratio, parallel bond tensile strength, parallel bond cohesion, friction angle, normal stiffness to tangential stiffness ratio, and friction coefficient were adjusted until the deviation of the simulated uniaxial compressive strength did not exceed 5% and the corresponding strain value deviation did not exceed 10%, so that the stress-strain simulation curve obtained by the plunger specimen model was consistent with the measured stress-strain curve. At this point, the micro-parameters of the plunger specimen model were obtained, and the set of micro-parameters of carbonate rocks was determined for macroscopic reproduction of the real rock mechanical behavior of carbonate rocks.

[0073] Step 4: In the particle flow discrete element software PFC3D 6.0, construct a carbonate rock model based on the size of the carbonate rock sample, import the carbonate rock pore model into the carbonate rock model, and set the microscopic parameters of the carbonate rock model.

[0074] Furthermore, in the sample generation module of the particle flow discrete element software PFC3D 6.0, based on the size of the carbonate rock sample and the extracted three-dimensional pore information, a sample with a size of [missing information] was established. The carbonate rock model was used to set the particle size range of the sampled particles based on a Gaussian distribution. The minimum particle size was set to 0.01 times the side length of the carbonate rock model, and the maximum particle size was set to 0.015 times the side length of the carbonate rock model.

[0075] Based on the set of microscopic parameters of carbonate rocks obtained in step 3, set all particles and contacts in the carbonate rock model, set the initial porosity of the carbonate rock model to 10%, generate a tightly packed aggregate of particles through particle expansion and compaction algorithms, and generate rigid walls on the six outer surfaces of the carbonate rock model to simulate the loading plate for true triaxial experiments of carbonate rock samples.

[0076] The STL file containing the three-dimensional pore information of CT image slices of carbonate rock samples is imported into the particle flow discrete element software PFC3D 6.0 in the form of rigid clusters. The rigid clusters are used to accurately characterize the actual pore geometry extracted from the CT images. The angular velocity of the rigid clusters is fixed and the moment of inertia is set to prevent the pores in the carbonate rock model from rotating during the stress process.

[0077] The particle bonding model in the carbonate rock model is set as a parallel bonding model, the bonding parameters are set, and the true triaxial test process is simulated using the carbonate rock model. Before stress loading, all initial contact forces in the carbonate rock model are cleared, so that the carbonate rock model is in a stress-free initial state.

[0078] Step 5: Set the initial pore pressure in the carbonate rock model, and arrange targeted and densely packed measuring spheres according to the pore location. Dynamically monitor the changes in porosity and pore pressure inside the carbonate rock model during the true triaxial numerical simulation to obtain the pore pressure field of the carbonate rock model.

[0079] Furthermore, the initial pore pressure values ​​of each pore space within the carbonate rock model are set, along with the bulk modulus of the fluid medium filling each pore space, to characterize the compressibility of the fluid.

[0080] The position coordinates of all pores in the carbonate rock model are obtained, and a measuring sphere is generated accordingly. The radius of the measuring sphere is determined based on the radius of the equivalent sphere of the pores to ensure that it can cover the pore deformation and surrounding stress disturbance zone. The calculation formula is as follows:

[0081] ;

[0082] In the formula, To measure the radius of a sphere; The influence coefficient is; the influence coefficient is; Let be the bulk volume of the rigid cluster.

[0083] All the measuring spheres within the carbonate rock model together constitute a pore response monitoring system. The porosity of the carbonate rock model is monitored by each measuring sphere, and the pore pressure change caused by the porosity change is obtained. The pore pressure change is then applied to the particles that are in direct contact with the rigid clusters corresponding to the pores, thereby achieving bidirectional coupling between the fluid and the solid skeleton of the carbonate rock.

[0084] The internal force preservation function of the carbonate rock model is set to be preserved at a frequency of 1000 steps / time. The true triaxial test process of the carbonate rock sample is simulated in the computational domain using the carbonate rock model and rigid wall. The changes in porosity and pore pressure inside the carbonate rock model are dynamically monitored and preserved, and the pore pressure field inside the carbonate rock model is obtained during the numerical simulation of the true triaxial test.

[0085] Step 6: In the laboratory, uniaxial compression tests are conducted at different temperatures using multiple plunger samples to determine the strength reduction function of the carbonate rock.

[0086] Furthermore, the initial temperature of the temperature field of the plunger specimen in the uniaxial compression test was set to 25℃. The plunger specimens were subjected to thermal damage treatment within the preset temperature range to obtain multiple plunger specimens treated at different temperatures. The uniaxial compressive strength of each plunger specimen was tested to obtain the uniaxial compressive strength of the plunger specimens at different temperatures. The strength reduction function of the carbonate rock was then fitted.

[0087] The set of microscopic parameters of carbonate rocks obtained in step 3 is used as the reference value of the strength reduction function. During the numerical simulation, the microscopic strength of carbonate rocks is dynamically reduced according to the current simulation temperature using the strength reduction function to simulate the weakening effect of temperature on rock strength.

[0088] Step 7: Apply a true triaxial compression servo environment with coordinated changes in temperature and stress fields to the carbonate rock model, and use the carbonate rock model to perform true triaxial experimental numerical simulation to realize the numerical simulation of the pore retention mechanism of carbonate rocks under ultra-deep thermo-fluid-structure interaction.

[0089] Furthermore, it includes the following sub-steps:

[0090] Step 701: Load the carbonate rock model in the particle flow discrete element software PFC3D 6.0, and delete the rigid clusters in the loaded carbonate rock model. The carbonate rock model allows the internal pores of the carbonate rock to freely deform, compress, or close under the combined action of external stress and internal pressure.

[0091] Step 702: Perform true triaxial numerical simulation using a carbonate rock model. Set up the true triaxial compression servo environment for the carbonate rock model, initialize the true triaxial stress field of the carbonate rock model, obtain the initial dimensions and overall stiffness of the carbonate rock model, and apply preset three-directional principal stresses to the carbonate rock model using six rigid walls. Set the initial value of the three-directional principal stresses applied to the carbonate rock model to 0, set the loading rate of the three-directional principal stresses according to the geological burial-uplift rate, and gradually increase the three-directional principal stresses applied to the carbonate rock model to the preset confining pressure value so that the carbonate rock model reaches the preset confining pressure environment. At this time, each rigid wall stably compacts the carbonate rock model.

[0092] Step 703: Set up a temperature and pressure co-variation simulation unit for the carbonate rock model, wherein the temperature and pressure co-variation simulation unit includes the internal temperature change of the simulation unit. Minimum principal stress variation in the simulation element Variation of principal stress in the simulation unit and the maximum principal stress variation of the simulated element .

[0093] Step 704: Set the burial unit function and the uplift unit function. The burial unit function is used to increase the various changes in the temperature and pressure synergistic change simulation unit, and the uplift unit function is used to decrease the various changes in the temperature and pressure synergistic change simulation unit. During the true triaxial experimental numerical simulation, the burial unit function and the uplift unit function are called multiple times and in stages to flexibly combine a complex temperature and pressure evolution path that is consistent with the actual burial history of the target geological block.

[0094] Step 705: Perform a true triaxial servo numerical simulation of thermo-fluid-solid multi-field coupling using a carbonate rock model. Enable stress servo control and temperature field control functions for all rigid walls, apply preset temperature field, true triaxial stress field, and pore pressure field, and adjust the buried element function and uplift element function to allow the carbonate rock model to evolve under a preset complex temperature and pressure evolution path. The entire evolution process of the carbonate rock model is automatically recorded during the numerical simulation, and the stress-strain curve, porosity evolution curve, and pore pressure fluctuation of the carbonate rock model are obtained throughout the process. In conjunction with calling the crack monitoring function built into the particle flow discrete element software PFC3D 6.0, the number, spatial location, and generation time of newly formed microcracks in the carbonate rock model during the true triaxial numerical simulation are obtained in real time.

[0095] Step 706: After the true triaxial numerical simulation is completed, extract the simulation data of each stage of the carbonate rock model evolution and store them as .sav files. Generate the stress-strain curves, three-dimensional particle displacements, force chain contacts, energy dissipation cloud maps, porosity evolution curves, and pore pressure change curves of the carbonate rock model, and export them from the particle flow discrete element software PFC3D 6.0.

[0096] Example 2

[0097] This embodiment takes an algal stromatolite from a certain block as an example. The algal stromatolite is a type of carbonate rock. The simulation method for the porosity retention mechanism of carbonate rocks under ultra-deep thermal-fluid-solid coupling proposed in Example 1 is adopted, including the following steps:

[0098] Step 1: Prepare algal stromatolite samples and perform CT scans on the algal stromatolite samples to obtain CT scan slice images of the algal stromatolite samples.

[0099] In this embodiment, a cubic sample of algal stromatolite was obtained, and the cubic sample of algal stromatolite was cut into... Standard cubic samples were used to prepare algal stromatolite specimens. The surfaces of these specimens were free of visible macroscopic defects, significant mineral nodules, or penetrating fractures, and all edges were geometrically continuous and intact. The prepared algal stromatolite specimens were then subjected to high-precision micron-level computed tomography (CT) with a precision of 400 nm. The non-destructive scanning process outputs the obtained CT image slices as TIF file format for saving, providing complete grayscale information for subsequent construction of the internal pore network of algal stromatolite.

[0100] Step 2: Process CT image slices of algal stromatolite samples using the Python database threshold segmentation method, extract three-dimensional pore information from the CT image slices of algal stromatolite samples, obtain the pore morphology, coordinates and volume of the three-dimensional pores, and save them as STL files.

[0101] In this embodiment, a dedicated image processing and porosity analysis database is constructed based on a Python database. CT image slices of the algal stromatolite sample are input into this database. The threshold segmentation method of the Python database is used to process the CT image slices of the algal stromatolite sample, with the initial sampling rate set to... The ignored pixel threshold was set to 3 to ensure complete extraction of pore information within the algal stromatolite sample while maintaining computational efficiency. After running the program, 612 pores were extracted from the algal stromatolite sample. The pore volume was generated for each pore individually. The length, width, height, and number of pores in the algal stromatolite sample were saved as text. All pores within the sample were saved to an STL file. Since the image of the entire algal stromatolite sample did not need to be imported into PFC3D 6.0, the first STL file was deleted, the remaining pores were imported, and a visualized carbonate rock pore model was created in the particle flow discrete element software PFC3D 6.0. Figure 2 As shown.

[0102] Step 3: Obtain multiple plunger samples and conduct pseudo-triaxial experiments on the plunger samples in the laboratory. Use the laboratory test results to calibrate the micro-parameters of the particle flow discrete element software PFC3D 6.0 and obtain the micro-parameter set of algal stromatolite.

[0103] In this embodiment, multiple plunger samples are prepared. The plunger samples are cylindrical with a diameter of 25 mm and a height of 60 mm. The plunger samples and the algal stromatolite cube samples are drilled from the same carbonate rock block and are spatially adjacent to the algal stromatolite cube samples. The plunger samples have no obvious structural surfaces or voids.

[0104] A pseudo-triaxial experiment was conducted using a plunger specimen. Stress was applied at a constant low strain rate, and the stress-strain curves of the plunger specimen were recorded throughout the entire process from linear elastic deformation, yielding, peak strength to residual strength. The stress-strain curves of the plunger specimen were obtained, and the measured stress-strain curves were obtained.

[0105] In the calibration module of the granular flow discrete element method software PFC3D 6.0, a plunger specimen model was generated based on the plunger specimen. The same stress loading parameters as those used in the quasi-triaxial experiment were set. The quasi-triaxial experimental process was simulated in PFC3D 6.0 using the plunger specimen model, and the simulated stress-strain curves were obtained and compared with the measured stress-strain curves.

[0106] The micro-parameters of the plunger specimen model were adjusted using a trial-and-error method until the deviation of the simulated uniaxial compressive strength was 4.5% and the corresponding deviation of the strain value was 8%. This ensured that the stress-strain simulation curve obtained by the plunger specimen model was consistent with the measured stress-strain curve, and it was determined that this set of micro-parameters could be used to characterize the physical properties of algal stromatolite.

[0107] Step 4: In the particle flow discrete element software PFC3D 6.0, construct an algal stromatolite model based on the sample size, import the algal stromatolite pore model into the algal stromatolite model, and set the microscopic parameters of the algal stromatolite model. This includes the following sub-steps:

[0108] Step 401: In the sample generation module of the particle flow discrete element software PFC3D 6.0, based on the size of the algal stromatolite dolomite sample and the extracted three-dimensional pore information, establish a sample with dimensions of [missing information]. The algal stromatolite model was used, and the computational domain was set to extend 1.2 times the side length of the algal stromatolite model. The particle size range of the sample was set based on Gaussian distribution, with the minimum particle size set to 0.01 times the side length of the algal stromatolite model and the maximum particle size set to 0.015 times the side length of the algal stromatolite model. 10001 random seeds were set to ensure the reproducibility of the simulation process.

[0109] Step 402: Based on the microscopic parameter set of the algal stromatolite obtained in Step 3, assign values ​​to all particles and contacts within the algal stromatolite model. Set the initial porosity of the algal stromatolite model to 10%, and generate rigid walls on the six outer surfaces of the algal stromatolite model to simulate the loading plates for the true triaxial experiment of the algal stromatolite sample. A tightly packed particle aggregate is generated using a particle expansion and compaction algorithm, and the particle mass within the algal stromatolite model is set to... The damping coefficient is 0.7, and the particle friction coefficient between particles, between particles and rigid clusters, and between particles and rigid walls is set to 0.2, and the stiffness ratio is set to 1.5.

[0110] Step 403: The STL file containing the three-dimensional pore information of the CT image slices of the algal stromatolite sample is imported into the particle flow discrete element software PFC3D 6.0 in the form of rigid clusters. The rigid clusters are used to accurately characterize the real pore geometry extracted from the CT image. The angular velocity of the rigid clusters is fixed and the moment of inertia is set to prevent the pores in the algal stromatolite model from rotating during the stress process. Rigid clusters outside the rigid wall area are deleted.

[0111] Step 404: Set the particle bonding model in the algal stromatolite model to a parallel bonding model, set the bonding parameters, and assign the microscopic parameters of the algal stromatolite determined in Step 3 to the algal stromatolite model, that is, set the parallel bonding spacing of the algal stromatolite model to be [specified value]. The contact elastic modulus is The particle stiffness ratio is 8.0, and the parallel bond elastic modulus is... The parallel bond stiffness ratio is 8.0, and the parallel bond tensile strength is... Parallel adhesive cohesion is The friction angle is 70.0°, the ratio of normal stiffness to tangential stiffness is 0.05, the friction coefficient is 0.577, and the particle separation threshold is set to 0.01 times the particle radius. Before applying stress to the algal stromatolite model, all initial contact forces in the algal stromatolite model are cleared, so that the algal stromatolite model is in a stress-free initial state.

[0112] Step 5: Set the initial pore pressure in the algal stromatolite model. Arrange targeted and densely packed measuring spheres according to the pore locations. Dynamically monitor the changes in porosity and pore pressure inside the algal stromatolite model during the true triaxial numerical simulation to obtain the pore pressure field of the algal stromatolite model. This includes the following sub-steps:

[0113] Step 501: Set the initial pore pressure value of each pore space in the algal stromatolite model to 20 MPa and the bulk modulus of the fluid medium filling the pore space to [value missing]. Pa.

[0114] Step 502: Call the `local.` function to locate the position information of the rigid clusters corresponding to the pores, obtain the position coordinates of all pores in the algal stromatolite model, and generate a corresponding measurement sphere, such as... Figure 3 As shown, the radius of the measuring sphere is determined based on the radius of the pore equivalent sphere, which is used to ensure that the pore deformation and surrounding stress disturbance zone can be covered.

[0115] The formula for calculating the radius of the measuring sphere is as follows:

[0116] ;

[0117] In the formula, To measure the radius of a sphere; The influence coefficient is the coefficient used in this embodiment. The value is 1.2; Let be the bulk volume of the rigid cluster.

[0118] Step 503: All the measuring spheres in the algal stromatolite model together constitute a pore response monitoring system. The porosity of the algal stromatolite model is monitored by each measuring sphere, the pore pressure change caused by the porosity change is obtained, and the pore pressure change is applied to the particles that are in direct contact with the rigid clusters corresponding to the pores.

[0119] Step 504: Set the saving frequency of the internal force saving function of the algal stromatolite model to 1000 steps / time. In the computational domain, use the algal stromatolite model and rigid wall to simulate the true triaxial test process of the algal stromatolite sample. Dynamically monitor and save the changes in porosity and pore pressure in the algal stromatolite model and save them as a CSV file.

[0120] Step 505: Compare the simulation results of the algal stromatolite model when the initial pore pressure is set to 0 MPa and 30 MPa, and compare the three-dimensional particle displacement cloud maps of the two models, as follows: Figure 4 As shown, the mechanical behavior and porosity evolution characteristics of the two are compared.

[0121] Step 6: Conduct uniaxial compression tests at different temperatures using multiple plunger samples in the laboratory to determine the strength reduction function of the algal stromatolite, including the following sub-steps:

[0122] Step 601: Set the initial temperature of the temperature field of the plunger sample in the uniaxial compression test to 25℃.

[0123] Step 602: Perform heat damage treatment on each plunger sample within a preset temperature range of 25℃~400℃ to obtain multiple plunger samples treated at different temperatures. Perform uniaxial compressive strength tests on each plunger sample to obtain the uniaxial compressive strength of the plunger samples at different temperatures, and fit the strength reduction function of the algal stromatolite.

[0124] The strength reduction function of the algal stromatolite is:

[0125] ;

[0126] In the formula, The compressive strength of the algal stromatolite. The current temperature. This is the initial temperature.

[0127] Step 603: Using the microscopic parameter set of the algal stromatolite obtained in Step 3 as the benchmark value of the strength reduction function, substitute it into the strength reduction function. Set up two control groups: a constant temperature of 25℃ and a heated temperature of 25℃~250℃. Calculate the compressive strength of the algal stromatolite dynamically changing under different temperature fields. Compare the differences in the mechanical behavior and porosity evolution of the algal stromatolite under different temperature fields. Figure 5 As shown.

[0128] Step 7: Apply a true triaxial compression servo environment with coordinated changes in temperature and stress fields to the algal stromatolite model. Perform true triaxial experimental numerical simulation using the algal stromatolite model to realize the numerical simulation of the porosity retention mechanism of algal stromatolite under ultra-deep thermo-fluid-structure interaction. This step includes the following sub-steps:

[0129] Step 701: Load the algal stromatolite model into the particle flow discrete element software PFC3D 6.0, delete the rigid clusters in the algal stromatolite model, and allow the internal pores of the algal stromatolite to freely deform, compress, or close under the combined action of external stress and internal pressure.

[0130] Step 702: Perform a true triaxial numerical simulation using the algal stromatolite model. Set up the true triaxial compression servo environment for the algal stromatolite model, initialize the true triaxial stress field of the model, set the initial values ​​of the three principal stresses applied to the model to 0, obtain the initial dimensions and overall stiffness of the model, and apply preset three principal stresses to the model using six rigid walls. The loading rate of the three principal stresses is set to... The triaxial principal stress applied to the algal strobolith model is gradually increased to the preset confining pressure value, so that the algal strobolith model reaches the preset confining pressure environment. At this time, each rigid wall smoothly compacts the algal strobolith model.

[0131] Step 703: Set up the temperature and pressure synergistic variation simulation unit of the algal stromatolite model, and set the temperature change amount inside the simulation unit. The minimum principal stress change of the simulation element is 25℃. The variation of the intermediate principal stress of the simulated element is 15 MPa. For 20 MPa and the maximum principal stress variation of the simulated element It is 25 MPa.

[0132] Step 704: Set the burial unit function and the uplift unit function. In this embodiment, an increment of change in the temperature and pressure co-change simulation unit is used as the burial unit function, and a decrease of change in the temperature and pressure co-change simulation unit is used as the uplift unit function. The number of calls to the burial unit function is set to 10 to simulate the environment from the surface to the ultra-deep burial layer. The temperature of the ultra-deep burial layer is set to 250℃, and the triaxial stresses are set to 250MPa, 200MPa, and 150MPa, respectively, to achieve consistency between the temperature and pressure co-change path and the geological burial history.

[0133] Step 705: Perform a true triaxial servo numerical simulation of thermo-fluid-solid multi-field coupling using the algal strobolith model. Enable stress servo control and temperature field control functions for all rigid walls. Apply a thermo-fluid-solid multi-field coupling true triaxial servo environment to the algal strobolith model, allowing it to evolve under a preset complex temperature and pressure evolution path. Call the fish function to generate the stress-strain curve, porosity, and pore pressure evolution characteristics of the entire process. Define a crack function to detect crack density. Record the number and coordinates of cracks generated during the servo process and store them in a CSV file.

[0134] Step 706: After the true triaxial numerical simulation is completed, extract the simulation data of each stage of the carbonate rock model evolution and save it as a .sav file to generate the stress-strain curves, three-dimensional particle displacements, force chain contacts, energy dissipation contour maps, etc. of the carbonate rock model. Figure 6 The porosity evolution curve shown and as follows Figure 7 The pore pressure variation curve shown is exported from the particle flow discrete element software PFC3D 6.0.

[0135] The method of this invention effectively improves the accuracy and scientific validity of simulating the porosity retention characteristics of carbonate rocks in deep-ultra-deep environments, providing strong support for subsequent research on the assessment of porosity retention capacity, classification of mechanical characteristics, determination of main controlling factors, and evaluation of oil and gas reservoirs of carbonate rocks with different mineral compositions and porosity distribution characteristics.

[0136] Of course, the above description is not intended to limit the present invention, and the present invention is not limited to the examples given above. Any changes, modifications, additions or substitutions made by those skilled in the art within the scope of the present invention should also fall within the protection scope of the present invention.

Claims

1. A method for simulating a pore retention mechanism of a carbonate rock under a super-deep thermal fluid-structure interaction, characterized in that, The method comprises the following steps: Step 1, preparing a carbonate rock sample, CT scanning the carbonate rock sample to obtain a CT scanning slice image of the carbonate rock sample; Step 2, processing the CT image slice of the carbonate rock sample based on a Python database threshold segmentation method, extracting three-dimensional pore information in the CT image slice of the carbonate rock sample, and obtaining pore morphology, coordinates and volume of the three-dimensional pores; Step 3, obtaining a plurality of plunger samples, performing a pseudo-triaxial experiment on the plunger samples in a laboratory, calibrating micro parameters of a particle flow discrete element software PFC3D 6.0 by using the laboratory test results, and obtaining a set of carbonate rock micro parameters; Step 4, in the particle flow discrete element software PFC3D 6.0, constructing a carbonate rock model according to the size of the carbonate rock sample, importing the carbonate rock pore model into the carbonate rock model, and setting the micro parameters of the carbonate rock model; Step 5, setting the initial pore pressure of the pores in the carbonate rock model, arranging the measurement balls with targeted encryption according to the pore positions, dynamically monitoring the changes of the porosity and pore pressure in the carbonate rock model in the process of the true triaxial experiment numerical simulation, and obtaining the pore pressure field of the carbonate rock model; Step 6, performing uniaxial compression tests at different temperatures by using the plurality of plunger samples in the laboratory, and determining the strength reduction function of the carbonate rock; Step 7, applying a true triaxial compression servo environment with the coordinated changes of the temperature field and the stress field to the carbonate rock model, performing a true triaxial experiment numerical simulation by using the carbonate rock model, obtaining the pore conditions in the carbonate rock model at each evolution stage, and realizing the numerical simulation of the carbonate rock pore retention mechanism under the action of the super-deep thermal-fluid coupling.

2. The method according to claim 1, wherein, In the step 1, a carbonate rock cubic sample is obtained, the carbonate rock cubic sample is cut into a standard cubic sample, a carbonate rock sample is prepared, and a CT scanner is used to perform CT scanning on the carbonate rock sample to obtain a CT image slice of the carbonate rock sample.

3. The method according to claim 1, wherein, In the step 2, a special image processing and pore analysis database is constructed based on a Python database, the CT image slice of the carbonate rock sample is input into the special image processing and pore analysis database, preprocessing parameters are set, each pore in the carbonate rock sample is extracted from the CT image of the carbonate rock sample and a pore volume is generated one by one, the number of pores in the carbonate rock sample and the morphology and volume of each pore are determined, and a visual carbonate rock pore model is established in the particle flow discrete element software PFC3D 6.

0.

4. The method according to claim 1, wherein, In the step 3, a plurality of plunger samples are prepared, the plunger samples have a cylindrical structure, are drilled from the same carbonate rock rock mass as the carbonate rock cubic sample, and are adjacent to the carbonate rock cubic sample in space; A displacement control mode is used, stress loading parameters are set, a pseudo-triaxial experiment is performed on the prepared plunger samples, a stress-strain curve of the plunger samples is obtained, and a stress-strain measured curve is obtained; In the calibration module of the particle flow discrete element software PFC3D 6.0, the plunger sample model is generated according to the plunger sample, the same stress loading parameters as the laboratory pseudo-triaxial experiment are set, the plunger sample model is used to simulate the pseudo-triaxial experiment process in the particle flow discrete element software PFC6.0, the stress-strain simulation curve is obtained, and the stress-strain simulation curve is compared with the stress-strain measured curve, the mesoscopic parameters of the plunger sample model are adjusted based on the trial and error method, so that the stress-strain simulation curve obtained by the plunger sample model is consistent with the stress-strain measured curve, the mesoscopic parameters of the plunger sample model at this time are obtained, and the mesoscopic parameter set of the carbonate rock is determined; The mesoscopic parameters include parallel bond formation spacing, contact elastic modulus, particle stiffness ratio, parallel bond elastic modulus, parallel bond stiffness ratio, parallel bond tensile strength, parallel bond cohesion, friction angle, normal stiffness and tangent stiffness ratio, and friction coefficient.

5. The method according to claim 4, wherein, In step 4, in the sample forming module of the particle flow discrete element software PFC3D 6.0, the calculation domain, the particle size range of the sample forming and the number of random seeds are set according to the size of the carbonate rock sample and the extracted three-dimensional pore information, and a carbonate rock model in a cubic structure is established; According to the carbonate rock mesoscopic parameter set obtained in step 3, all particles and contacts in the carbonate rock model are set, the initial porosity of the carbonate rock model is set, and rigid walls are generated on the six outer surfaces of the carbonate rock model to simulate the loading plate of the true triaxial experiment of the carbonate rock sample; Based on the three-dimensional pore information extracted from the CT image slices of the carbonate rock sample, the extracted pore morphology is introduced into the particle flow discrete element software PFC3D 6.0 in the form of rigid clusters, the angular velocity of the rigid clusters is fixed and the moment of inertia is set to prevent the pores in the carbonate rock model from rotating during the stress process; The particle bonding model in the carbonate rock model is set to a parallel bonding model, the bonding parameters are set, the true triaxial experiment process is simulated using the carbonate rock model, before stress loading, all initial contact forces in the carbonate rock model are emptied, so that the carbonate rock model is in an initial stress-free state.

6. The method according to claim 5, wherein, In step 5, the initial pore pressure values of each pore space in the carbonate rock model are set, and the bulk modulus of the fluid medium filled in each pore space is set to represent the compressibility of the fluid; The position coordinates of all pores in the carbonate rock model are obtained and a measurement ball is generated, the radius of the measurement ball is determined according to the pore equivalent sphere radius, which is used to ensure that the pore deformation and the surrounding stress disturbance zone can be covered, and the calculation formula is: ； wherein R is the radius of the sphere; C is the impact coefficient; V is the volume of the block of rigid clusters; All measurement balls in the carbonate rock model form a pore response monitoring system, the porosity of the carbonate rock model is monitored using each measurement ball, the pore pressure change caused by the change of porosity is obtained, and the pore pressure change acts on the particles directly contacted with the rigid clusters corresponding to the pores, and the fluid and the carbonate rock solid skeleton are bidirectionally coupled. The saving frequency of the internal force saving function of the carbonate rock model is set, the triaxial test process of the carbonate rock sample is simulated by using the carbonate rock model and the rigid wall in the calculation domain, the changes of the internal porosity and the pore pressure of the carbonate rock model are dynamically monitored and saved, and the pore pressure field inside the carbonate rock model in the numerical simulation process of the triaxial test is obtained.

7. The method according to claim 6, wherein, In step 6, after setting the initial temperature of the temperature field in which the plunger sample is located in the uniaxial compression test, the thermal damage treatment is performed on each plunger sample in a preset temperature range, and a plurality of plunger samples treated at different temperatures are obtained. The uniaxial compressive strength of the plunger sample at different temperatures is obtained by using each plunger sample for uniaxial compressive strength test, and the strength reduction function of the carbonate rock is fitted. The calibrated set of mesoscopic parameters of the carbonate rock in step 3 is used as the reference value of the strength reduction function, and the mesoscopic strength of the carbonate rock is dynamically reduced according to the current simulation temperature by using the strength reduction function, which is used to simulate the weakening effect of temperature on the strength of the rock.

8. The method according to claim 7, wherein, In step 7, the following sub-steps are included: Step 701, loading the carbonate rock model in the particle flow discrete element software PFC3D 6.0, deleting the rigid cluster in the carbonate rock model, and allowing the internal pores of the carbonate rock to deform, compress or close freely under the combined action of external stress and internal pressure; Step 702, numerical simulation of triaxial test is carried out by using the carbonate rock model, the triaxial compression servo environment of the carbonate rock model is set, the triaxial stress field of the carbonate rock model is initialized, the initial size and overall stiffness of the carbonate rock model are obtained, the preset three-direction principal stress is applied to the carbonate rock model by using six rigid walls, the initial value of the three-direction principal stress applied to the carbonate rock model is set to 0, the loading rate of the three-direction principal stress is set according to the geological burial-lifting rate, the three-direction principal stress applied to the carbonate rock model is gradually increased to the preset confining pressure value, so that the carbonate rock model reaches the preset confining pressure environment, and at this time, the rigid walls are used to compact the carbonate rock model smoothly; Step 703, setting a temperature-pressure synergic change simulation unit of the carbonate rock model, the temperature-pressure synergic change simulation unit comprising a simulation unit internal temperature change amount , a simulation unit minimum principal stress change amount , a simulation unit intermediate principal stress change amount , and a simulation unit maximum principal stress change amount ; Step 704, setting the burial unit function and the lifting unit function, wherein the burial unit function is used to increase the change amount of each change unit of the temperature-pressure co-evolution simulation unit, and the lifting unit function is used to reduce the change amount of each change unit of the temperature-pressure co-evolution simulation unit. During the numerical simulation of the triaxial test, the burial unit function and the lifting unit function are called multiple times and in stages to form a complex temperature-pressure evolution path consistent with the actual burial history of the target geological block. Step 705, numerical simulation of true triaxial servo experiment of thermal-fluid-solid multi-field coupling is carried out by using the carbonate rock model, stress servo control function and temperature field control function of all rigid walls are opened, preset temperature field, true triaxial stress field and pore pressure field are applied, buried unit function and lifting unit function are regulated, so that the carbonate rock model evolves under the preset complex temperature and pressure evolution path, the whole process of carbonate rock model evolution is recorded during numerical simulation, stress-strain curve, porosity evolution curve and pore pressure fluctuation of carbonate rock model in the whole process are obtained, and the number, spatial position and generation time of new micro cracks in the carbonate rock model during the numerical simulation of true triaxial experiment are obtained in real time by calling the crack monitoring function built in the particle flow discrete element software PFC3D 6.0; Step 706, after the numerical simulation of true triaxial experiment is finished, the simulation data of each stage of carbonate rock model evolution is extracted, the stress-strain curve, three-dimensional particle displacement, force link contact, energy dissipation cloud picture, porosity evolution curve and pore pressure change curve of the carbonate rock model are generated, and are exported from the particle flow discrete element software PFC3D 6.0.

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