Digital core technology-based complex conductivity acquisition method, system, equipment and medium

Abstract

The invention belongs to the technical field of rock physics, and relates to a complex conductivity acquisition method, system and equipment based on a digital core technology, and a medium. The method comprises the following steps: establishing a sedimentary model and a compaction model which have similar pore structures with sedimentary rocks; respectively obtaining the mean particle size, the porosity and the specific volume per unit pore surface area of the sedimentary model and the compaction model; according to the mean particle size, the porosity and the unit pore surface area specific volume of the sedimentary model and the compaction model, the equivalent particle size of the sedimentary model and the compaction model is obtained; obtaining the conductivity of the liquid phase of the double electric layer, and obtaining the conductivity of the solid phase of the double electric layer according to the equivalent particle size and the vacuum dielectric constant; gridding the sedimentary model and the compaction model, and acquiring node potential of each unit after gridding according to the conductivity of the solid phase and the conductivity of the liquid phase; and solving the complex conductivity of the compaction model by combining the node potential of each unit through a finite difference method. According to the method, the complex conductivity of the deposition and compaction model can be accurately calculated.

Description

Technical Field

[0001] This invention belongs to the field of rock physics technology and relates to a method, system, device and medium for obtaining complex conductivity based on digital core technology. Background Technology

[0002] Excited polarization, as an important component of electromagnetic exploration, has been widely applied in oil and gas resource exploration, mineral prospecting, environmental monitoring, hydrogeophysics, and biogeophysics. The fundamental reason for the low-frequency excited polarization effect in saturated porous media without metallic minerals is the ion movement generated at the solid / liquid interface under the influence of an external electric field. The ion double layer consists of the Stern layer and the diffusion layer. The dominant polarization mechanism differs across frequency bands. When the frequency is below 100 Hz, the migration and concentration diffusion of bound ions in the Stern layer dominate the polarization. Currently, two polarization mechanisms exist in this frequency band: electrochemical polarization and film polarization.

[0003] In recent years, the simulation of transport characteristics based on digital core technology has been widely developed. In the field of rock electrical properties, numerical simulation studies of DC electric fields and medium-to-high frequency electric fields have been mainly carried out. These studies target porous media with different lithologies and physical properties, including shale, sandstone, and carbonate rocks. The three-dimensional digital cores used are either obtained through CT scans or generated through numerical reconstruction algorithms. In addition, some scholars have simulated the effects of fractures and saturation on the electrical properties of rocks using the successive random addition method or mathematical morphology method. However, research on numerical simulation methods for low-frequency induced polarization effects is relatively limited. Until 2017, some scholars proposed a numerical simulation method for induced polarization effects at the pore scale and compared it with glass microsphere experiments, verifying the correctness of the method. Foreign scholars have also used random pore network models to numerically calculate the complex conductivity of sandstone. These numerical simulation works provide technical support for discussing the influence of structural parameters on induced polarization effects.

[0004] Currently, there is no existing technology for calculating the complex resistivity of a compaction model. Summary of the Invention

[0005] In order to overcome the shortcomings of the prior art, the purpose of this invention is to provide a method, system, device and medium for obtaining complex conductivity based on digital core technology. This invention can accurately calculate the complex conductivity of sedimentation and compaction models.

[0006] To achieve the above objectives, the present invention employs the following technical solution: In a first aspect, the present invention provides a method for obtaining complex conductivity based on digital core technology, comprising the following steps: Establish sedimentary and compaction models with similar pore structures to sedimentary rocks; The mean particle size, porosity, and volume ratio per unit pore surface area were obtained for both the sedimentation model and the compaction model. The equivalent particle size of the sedimentation model and the compaction model is obtained based on the mean particle size, porosity, and volume ratio of unit pore surface area to volume of the sedimentation model and the compaction model. The conductivity of the liquid phase with the double electric layer is obtained, and the conductivity of the solid phase with the double electric layer is obtained based on the equivalent particle size and the vacuum dielectric constant. The deposition model and compaction model are meshed, and the nodal potential of each unit after meshing is obtained based on the electrical conductivity of the solid phase and the electrical conductivity of the liquid phase. The complex conductivity of the compaction model is solved by combining the finite difference method with the nodal potential of each element.

[0007] Secondly, the present invention provides a complex conductivity acquisition system based on digital core technology, comprising a model building module, a structural parameter acquisition module, an equivalent grain size acquisition module, a conductivity acquisition module, a nodal potential acquisition module, and a complex conductivity acquisition module, wherein: Model building module: used to create sedimentary and compaction models with similar pore structures to sedimentary rocks; Structural parameter acquisition module: used to acquire the mean particle size, porosity, and volume ratio per unit pore surface area for the deposition model and the compaction model, respectively; Equivalent particle size acquisition module: used to obtain the equivalent particle size of the sedimentation model and the compaction model based on the mean particle size, porosity and unit pore surface area to volume ratio of the sedimentation model and the compaction model; Conductivity acquisition module: used to acquire the conductivity of the liquid phase of the double layer, and to acquire the conductivity of the solid phase of the double layer based on the equivalent particle size and vacuum dielectric constant; Node potential acquisition module: used to mesh the deposition model and compaction model, and obtain the node potential of each cell after meshing based on the electrical conductivity of the solid phase and the electrical conductivity of the liquid phase; Complex conductivity acquisition module: used to solve the complex conductivity of the compaction model by combining the nodal potential of each element with the finite difference method.

[0008] Thirdly, the present invention provides an electronic device, comprising: a processor; a memory for storing computer program instructions; and steps for implementing a method for obtaining complex conductivity based on digital core technology when executing the computer program.

[0009] Fourthly, the present invention provides a storage medium storing computer program instructions, which are loaded and executed by a processor, wherein the processor executes a method for obtaining complex conductivity based on digital core technology.

[0010] Fifthly, the present invention provides a computer program product, the computer program product including computer instructions, the computer instructions instructing a computer to execute a method for obtaining complex conductivity based on digital core technology.

[0011] Compared with the prior art, the present invention has the following beneficial effects: 1. The method of this invention establishes sedimentary and compaction models with similar pore structures to sedimentary rocks. By simulating the pore structure of real sedimentary rocks, it ensures that the physical basis of subsequent analysis closely approximates reality. The mean grain size, porosity, and volume ratio per unit pore surface area of ​​the sedimentary and compaction models are obtained respectively. Based on the mean grain size, porosity, and volume ratio per unit pore surface area of ​​the sedimentary and compaction models, the equivalent grain size of the sedimentary and compaction models is obtained, facilitating subsequent conductivity calculations. The conductivity of the liquid phase in the double layer is obtained, and the solid phase conductivity of the double layer is obtained based on the equivalent grain size and vacuum dielectric constant. The electrical conductivity of the phases can more accurately describe the electrical properties inside the rock, making the results closer to reality. Meshization of the sedimentation and compaction models allows for more refined model analysis, capturing local potential changes. The nodal potentials of each gridded element are obtained based on the electrical conductivity of the solid and liquid phases, and numerical methods are used to solve for these nodal potentials, providing fundamental data for subsequent complex conductivity calculations. By combining the finite difference method with the nodal potentials of each element, the complex conductivity of the compaction model is solved. This invention can accurately calculate the complex conductivity of both sedimentation and compaction models.

[0012] 2. The system of this invention includes a model building module, a structural parameter acquisition module, an equivalent grain size acquisition module, an electrical conductivity acquisition module, a nodal potential acquisition module, and a complex electrical conductivity acquisition module, wherein: the model building module is used to establish a sedimentary model and a compaction model with similar pore structure to the sedimentary rock; the structural parameter acquisition module is used to obtain the mean grain size, porosity, and volume ratio per unit pore surface area of ​​the sedimentary model and the compaction model, respectively; the equivalent grain size acquisition module is used to obtain the mean grain size, porosity, and volume ratio per unit pore surface area of ​​the sedimentary model and the compaction model based on the mean grain size, porosity, and volume ratio of the sedimentary model and the compaction model. The system employs a unit pore surface area to volume ratio module to obtain the equivalent particle size for both the deposition and compaction models. A conductivity acquisition module is used to obtain the conductivity of the liquid phase in the double electric layer, and the conductivity of the solid phase in the double electric layer is obtained based on the equivalent particle size and vacuum dielectric constant. A nodal potential acquisition module is used to mesh the deposition and compaction models, and the nodal potential of each meshed element is obtained based on the conductivity of the solid and liquid phases. A complex conductivity acquisition module is used to solve for the complex conductivity of the compaction model using the finite difference method combined with the nodal potential of each element. The various modules of this invention work together to accurately calculate the complex conductivity of the deposition and compaction models.

[0013] 3. The equipment, medium, and program products of this invention can also accurately calculate the complex conductivity of deposition and compaction models. Attached Figure Description

[0014] Figure 1 This is a two-dimensional slice diagram of the particle deposition model according to an embodiment of the present invention; Figure 2 for Figure 1 Enlarged view of region A; Figure 3 The diagrams show the sedimentation and compaction models reconstructed using the process method in this embodiment of the invention, where (b), (k), and (l) represent the sedimentation models, and (c) to (j) represent the compaction models; (a) Sedimentation model A1: Grain size distribution; (b) Sedimentation model A1: Uncompacted; (c) Compaction model A2: =0.04 (d) Compaction model A3: =0.08(e) Compaction Model A4: =0.1(f) Compaction Model A5: =0.14 (g) Compaction Model A6: =0.18 (h) Compaction Model A7: =0.2(i) Compaction model A8: =0.22(j)A9: =0.24 (k) Sedimentary model C1: Uncompacted (l) Sedimentary model D1: Uncompacted; Figure 3a for Figure 3 (a) Enlarged view; Figure 4 This is a schematic diagram of three-dimensional digital core mesh partitioning according to an embodiment of the present invention, specifically a regular mesh partitioning result; Figure 5 This is a schematic diagram of the three-dimensional digital core mesh generation according to an embodiment of the present invention, specifically showing the element nodes and labels; Figure 6 This is a graph showing the effect of particle size variation on complex conductivity in an embodiment of the present invention, specifically an amplitude-frequency curve. Figure 7 This is a diagram showing the effect of particle size variation on complex conductivity in an embodiment of the present invention, specifically a phase frequency curve. Figure 8 This is a diagram showing the effect of the compaction process on the equivalent particle size and mean particle size in an embodiment of the present invention. Figure 9 This is a graph showing the effect of the compaction coefficient on the complex conductivity in an embodiment of the present invention, specifically an amplitude-frequency curve. Figure 10 This is a diagram showing the effect of the compaction coefficient on the complex conductivity in an embodiment of the present invention, specifically a phase frequency curve. Figure 11 This is a correlation diagram between orthogonal conductivity and structural parameters in an embodiment of the present invention, specifically... ~ The color code represents the compaction coefficient; Figure 12 This is a correlation diagram between orthogonal conductivity and structural parameters in an embodiment of the present invention, specifically... ~ as well as ~ ; Figure 13 This is a flowchart of the method of the present invention; Figure 14 This is a system module diagram of the present invention. Detailed Implementation

[0015] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0016] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0017] The present invention will now be described in further detail with reference to the accompanying drawings: See Figure 13 This invention discloses a method for obtaining complex conductivity based on digital core technology, comprising the following steps: S1. Establish sedimentary and compaction models with similar pore structures to sedimentary rocks. The specific steps are as follows: Within a defined area, particles of different sizes are sequentially deposited to generate a particle accumulation with porous structure characteristics, thus obtaining a sedimentation model. A compaction model is obtained by performing compaction simulation on the sedimentation model body.

[0018] When generating a deposition model using the process method, only the final equilibrium position of the particles is considered. In compaction simulation, all particles are assumed to be spherical rigid bodies, meaning that their volume and shape do not change during compaction, and particle rotation and breakage are not considered.

[0019] S2. Obtain the mean particle size, porosity, and volume ratio per unit pore surface area for both the deposition model and the compaction model; S3. Obtain the equivalent particle size of the sedimentation model and the compaction model based on the mean particle size, porosity, and unit pore surface area to volume ratio of the sedimentation model and the compaction model; Preferably, the steps for obtaining the equivalent grain size of the deposition model are as follows: The mean grain size of the deposition model is the equivalent grain size.

[0020] Preferably, the formula for obtaining the equivalent particle size of the compaction model is as follows:

[0021] in, For equivalent particle size, The ratio of surface area per unit pore to volume. Porosity.

[0022] S4. Obtain the conductivity of the liquid phase of the double layer. The conductivity of the solid phase of the double layer is obtained based on the equivalent particle size and vacuum permittivity, as detailed below: The volumetric complex conductivity of a single particle is obtained based on the equivalent particle size and the vacuum dielectric constant, as shown in the following formula:

[0023] in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

[0024] The conductivity of the solid phase with an electric double layer is obtained from the volumetric complex conductivity of a single particle.

[0025] S5. Mesh the deposition and compaction models, and obtain the nodal potential of each element after meshing based on the electrical conductivity of the solid phase and the liquid phase. The specific formula is as follows:

[0026] in, For nodes With the surrounding The conductivity of the bonds between nodes. For the surrounding area The potential of each node, ; Let be the node potential.

[0027] S6. Solve the complex conductivity of the compaction model by combining the finite difference method with the nodal potential of each element.

[0028] See Figure 13 In another feasible embodiment of the present invention, the following modifications are made as appropriate. The steps include: By establishing sedimentary and compaction models with similar pore structures to sedimentary rocks, and by simulating the pore structure of real sedimentary rocks, we can ensure that the physical basis of subsequent analysis is close to the actual situation. The mean particle size, porosity, and volume ratio per unit pore surface area obtained from the sedimentation model and the compaction model respectively provide the necessary data support for subsequent calculation of equivalent particle size and complex conductivity; The equivalent particle size of the sedimentation model and the compaction model is obtained based on the mean particle size, porosity, and volume ratio of unit pore surface area, which facilitates subsequent electrical conductivity calculation. Obtaining the electrical conductivity of the liquid phase of the double electric layer and the electrical conductivity of the solid phase of the double electric layer based on the equivalent particle size and vacuum dielectric constant can more accurately describe the electrical properties inside the rock, making the results closer to the actual situation. The deposition and compaction models are meshed, which makes the model analysis more refined and can capture local potential changes. The nodal potential of each unit after meshing is obtained based on the conductivity of the solid phase and the conductivity of the liquid phase. The nodal potential is solved by numerical methods, providing basic data for subsequent complex conductivity calculation. The complex conductivity of the compaction model is solved by combining the finite difference method with the nodal potential of each element. This invention can accurately calculate the complex conductivity of deposition and compaction models.

[0029] Example 1: See Figure 13 This invention discloses a method for obtaining complex conductivity based on digital core technology, comprising the following steps: Step 1: Create a virtual rock with a similar pore structure to sedimentary rocks using a procedural method. The virtual rock includes a sedimentary model and a compaction model. See [link to relevant documentation]. Figure 3 and Figure 3a This method includes three processes: deposition, compaction, and diagenesis.

[0030] The deposition process refers to the process in which particles of different sizes are deposited sequentially within a defined area, forming a particle accumulation with porous structure characteristics.

[0031] To simulate the squeezing effect caused by overlying strata pressure, the particle pack needs to be compacted. This invention assumes that all particles are rigid spherical bodies, meaning their volume and shape do not change during compaction, and does not consider particle rotation or breakage. The compaction process acts in the x, y, and z directions. The change in the position of the center of each particle after compaction can be expressed as:

[0032] in The original coordinates of the particle's center are... These are the coordinates of the center of the compacted particles. This is the compaction coefficient. To avoid situations where the space is not fully filled during modeling or where sub-blocks contain boundaries, the modeling space is set to... A cube.

[0033] Step 2: Calculate the structural parameters of the deposition and compaction models using Avizo software. First, threshold segmentation is performed on all two-dimensional slices; see [link to relevant documentation]. Figure 1 and Figure 2 Identify pixels Pores or particles, pores granules Then, the watershed algorithm is used to divide each pore in the three-dimensional data volume. and granules Then calculate each pore surface area and volume and length ,width and height This allows us to obtain the major axis of each pore. and short axis Similarly, the calculations for each particle were performed. surface area and volume subscript Represents pores, subscript The representative particle. The structural parameters involved in this invention are shown in Table 1.

[0034] Table 1. Virtual core structure parameters, symbols, definitions, and calculation formulas used in this invention.

[0035] Step 3: Calculate the equivalent particle size of the compaction model. The compaction process causes the center coordinates of all particles to shift towards the origin, and previously tangent particles gradually intersect. This results in more particles being squeezed into the representative volume element. If the same size representative volume element is still used for analysis, the influence of other variables (e.g., particle number) will be introduced, making it impossible to analyze whether the changes in structural parameters are caused by the compaction process or by changes in particle number, thus rendering subsequent discussions incomparable. Therefore, as the compaction process continues, the size of the representative volume element will be reduced proportionally.

[0036] This invention proposes to equate the compaction process to a particle volume expansion process and introduces an equivalent particle size. This is used to characterize the degree of compaction. We found that the compaction process causes the calculation of porosity and the volume ratio per unit pore surface area to be affected. The equivalent particle size changes for spherical particle samples. The ratio of volume to unit pore surface area and calculation of porosity The calculation is expressed as:

[0037] in, For equivalent particle size, The ratio of surface area per unit pore to volume. Porosity.

[0038] Step 4, particle upgrading or porosity upgrading. For porous media composed of a single mineral, they can be considered as two-phase or three-medium materials. The two phases refer to the solid and liquid phases, and the three media refer to the insulating matrix, the conductive electrolyte, and the electric double layer with perturbation properties. This invention equates the surface complex conductivity contributed by the electric double layer to the volume complex conductivity of the particles or solution, i.e., particle upgrading or porosity upgrading. Taking particle upgrading as an example, for a radius of... For particles, assuming that the surface complex conductivity of insulating particles with an electric double layer can be equivalent to the volume complex conductivity of conductive particles without an electric double layer, that is, averaging the surface complex conductivity contributed by the electric double layer over the particle volume to obtain the volume complex conductivity of a single particle. , is represented as:

[0039] in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

[0040] After particle upgrading, the electrical conductivity of the solid phase becomes: The conductivity of the liquid phase remains unchanged, and is still: subscript Represents the solid phase. Represents the liquid phase. The vacuum permittivity, The relative permittivity of the solid phase is denoted as . Let be the relative permittivity of the liquid phase. Similarly, the surface conductivity contributed by the double layer can be averaged in the pore space to achieve porosity enhancement.

[0041] Step 5, see Figure 4 and Figure 5 The sedimentation and compaction models were meshed. Regular hexahedrons were used to divide the three-dimensional digital core into elements, and the number of each element after discretization was represented by its central node.

[0042] Step 6: Numerically solve for the complex conductivity of the deposition model and the compaction model using the finite difference method. For any node... Its nodal potential It can be represented as:

[0043] in, For nodes With the surrounding The conductivity of the bonds between nodes. For the surrounding area The potential of each node, ; Let be the node potential.

[0044] node potential Simplify to the following formula:

[0045] In the discretized three-dimensional digital core, the potential of each node can be represented by the simplified formula above, where the node... With nodes Conductivity of the link bonds Calculated using the conductivity of the voxel unit it belongs to.

[0046] The invention is further characterized by: In step 1, when generating the deposition model using the process method, only the final equilibrium position of the particles is considered. During the compaction simulation, it is assumed that all particles are spherical rigid bodies, meaning that their volume and shape do not change during the compaction process, and particle rotation and breakage are not considered.

[0047] The method for calculating the structural parameters of the deposition and compaction models in step 2 is an image processing technique based on the watershed algorithm.

[0048] In step 3, porosity and the volume ratio of unit pore surface area are introduced to calculate the equivalent particle size, thereby correcting the error caused by the compaction process.

[0049] In step 4, the surface conductivity at the solid-liquid interface was averaged over both particle volume and pore volume, thus converting the surface conductivity into volume conductivity.

[0050] In step 5, regular hexahedrons are used for mesh generation, which reduces the amount of computation.

[0051] This invention can accurately calculate the complex conductivity of deposition and compaction models, and thus analyze the influence of structural parameters on the induced polarization effect.

[0052] Example 2: See Figure 13 This embodiment discusses the effect of different particle sizes on the excitation polarization effect.

[0053] Step 1: Deposit spheres with different particle size distributions in the modeling space using the deposition algorithm in the process method to obtain a deposition model with different particle size distributions.

[0054] Step 2: Calculate the structural parameters of different sedimentary models using the watershed algorithm with Avizo software. The structural parameters of each sedimentary model are shown in Table 2.

[0055] Table 2. Structural parameter statistics of the compaction model:

[0056] Step 3: Since these models are generated by the deposition process, the error caused by the compaction process is not considered. That is, the mean particle size can be used to represent the true particle size of the model, i.e., the equivalent particle size.

[0057] Step 4: The surface conductivity effect is averaged across both particle volume and pore volume, effectively converting the surface conductivity to bulk conductivity. The formula is as follows:

[0058] in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

[0059] Particle size The mean grain size is shown in Table 2. The mean grain size is different for each sedimentation model.

[0060] Step 5: Grid the sedimentation model.

[0061] Step 6: Numerically solve the complex conductivity of the deposition model using the finite difference method. The results are as follows... Figure 6 and Figure 7 As shown.

[0062] Numerical simulations show that both the amplitude and phase of the complex conductivity exhibit dispersion. The ratio of unit pore surface area to volume in deposition model E1 is... The particle size is the largest, therefore its amplitude dispersion is the greatest. In the phase-frequency curve, it can be observed that the frequency of the electrochemical polarization characteristic relaxation peak increases with decreasing particle size. Furthermore, the phase value corresponding to the electrochemical polarization relaxation peak also increases with decreasing particle size. This means that the polarization intensity increases with decreasing particle size. As shown in Table 3, the ratio of unit pore surface area to volume... The intensity of electrochemical polarization increases with decreasing particle size, therefore it is believed that the intensity of electrochemical polarization is related to... It is positively correlated. Furthermore, numerical simulation results show that Maxwell-Wagner polarization is independent of particle size.

[0063] Example 3: See Figure 13 This embodiment discusses the effect of different compaction coefficients on the induced polarization effect.

[0064] Step 1: Using the deposition algorithm in the process method, the compaction coefficient is changed to perform a compaction operation on the deposition model A1. The compaction coefficient is set to 0.04, 0.08, 0.1, 0.14, 0.18, 0.2, 0.22, 0.24, 0.28, and compaction models A2-A10 are obtained.

[0065] Step 2: Calculate the structural parameters of different compaction models using the watershed algorithm in Avizo software. The structural parameters of each compaction model are shown in Table 3.

[0066] Table 3. Statistical analysis of structural parameters of the sedimentation model:

[0067] Step 3, as shown in Table 3, shows that the mean particle size decreases only slightly with increasing compaction coefficient (this change is negligible). This means that the compaction process does not change the actual volume of the particles, but rather alters their spatial positions, changing them from tangential to intersecting, thus compressing the pore volume. Simultaneously, considering that the size of the representative volume unit gradually decreases with increasing compaction coefficient, the particle volume relative to the compressed representative volume unit is actually increasing. Therefore, the compaction process is equivalent to a particle volume expansion process, and an equivalent particle size is introduced. To characterize the degree of compaction.

[0068] Step 4: The surface conductivity effect was averaged over both particle volume and pore volume, effectively converting the surface conductivity to bulk conductivity. This is illustrated in the following equation:

[0069] in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

[0070] Particle size This is the equivalent particle size. For example... Figure 8 As shown, the equivalent particle size increases with the increase of the compaction coefficient, while the change in the mean particle size is very small.

[0071] Step 5: Mesh the compaction model.

[0072] Step 6: Numerically solve the complex conductivity of the compaction model using the finite difference method. The results are as follows... Figure 9 and Figure 10 As shown.

[0073] Numerical simulations show that both the amplitude and phase of the complex conductivity are dispersed, with the phase dispersion being greater. The amplitude of the complex conductivity decreases with increasing compaction coefficient, indicating that the pore space for free charge transport is compressed, leading to a decrease in conductivity. This is especially true when the compaction coefficient changes from 0.14 to 0.2, where the amplitude of the complex conductivity changes by more than an order of magnitude.

[0074] In the phase-frequency curve, the frequency of the characteristic peak of electrochemical polarization decreases with increasing compaction coefficient. This is a result of using the particle expansion equivalent compaction process, i.e., the equivalent particle size increases with increasing compaction coefficient, leading to an increase in relaxation time and a decrease in characteristic relaxation frequency. This also reflects that electrochemical polarization at low frequencies is related to particle size. The phase value corresponding to the characteristic relaxation peak of electrochemical polarization increases with increasing compaction coefficient, and the increase in compaction coefficient makes the unit pore surface area to volume ratio... The phase value corresponding to the characteristic relaxation peak of electrochemical polarization increases, therefore, the phase value is related to... A positive correlation exists. Furthermore, as the compaction coefficient increases, a second characteristic relaxation peak gradually appears in the transition region between electrochemical polarization and Maxwell-Wagner polarization. This relaxation peak may be related to the surface roughness of the particles. Numerical simulation results also show that the intensity of Maxwell-Wagner polarization increases with increasing compaction coefficient.

[0075] Example 4: See Figure 13 This embodiment discusses the influence of different structural parameters on the excitation polarization parameters.

[0076] Step 1: Using the deposition and compaction algorithms in the process method, virtual digital cores with different structural parameters are generated.

[0077] Step 2: Calculate the structural parameters of different virtual core models using the Avizo software based on the watershed algorithm.

[0078] Step 3: For the deposition model, the equivalent particle size is not considered; for the compaction model, the compaction process is characterized by the equivalent particle size.

[0079] Step 4: The surface conductivity effect was averaged over both particle volume and pore volume, effectively converting the surface conductivity to bulk conductivity. This is illustrated in the following equation:

[0080] in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

[0081] For sedimentation models, grain size For the mean grain size, the grain size is... The equivalent particle size.

[0082] Step 5: Mesh the deposition model and the compaction model.

[0083] Step 6: The complex conductivity of the deposition model is numerically solved using the finite difference method. The relationship between structural parameters and induced polarization parameters is then discussed.

[0084] See Figure 11 and Figure 12 ,parameter and Both vary with the unit pore surface area to volume ratio The value initially increases and then decreases. This indicates that for samples with low porosity, the relationship between the excited polarization effect and structural parameters may be reversed. This represents the imaginary part of the complex conductivity at 1 Hz.

[0085] The purpose of this invention is to provide a method for numerical simulation of the induced polarization effect in porous media. Specifically, based on digital core reconstruction technology, this method combines complex conductivity numerical simulation to discuss the influence of structural parameters in sedimentation and compaction models on the induced polarization effect, thus providing a numerical simulation technique for the study of the mechanism of induced polarization effect in porous media.

[0086] Based on the above method, this invention also discloses a complex conductivity acquisition system based on digital core technology, see [link to relevant documentation]. Figure 14 It includes a model building module, a structural parameter acquisition module, an equivalent particle size acquisition module, a conductivity acquisition module, a nodal potential acquisition module, and a complex conductivity acquisition module, wherein: Model building module: used to create sedimentary and compaction models with similar pore structures to sedimentary rocks; Structural parameter acquisition module: used to acquire the mean particle size, porosity, and volume ratio per unit pore surface area for the deposition model and the compaction model, respectively; Equivalent particle size acquisition module: used to obtain the equivalent particle size of the sedimentation model and the compaction model based on the mean particle size, porosity and unit pore surface area to volume ratio of the sedimentation model and the compaction model; Conductivity acquisition module: used to acquire the conductivity of the liquid phase of the double layer, and to acquire the conductivity of the solid phase of the double layer based on the equivalent particle size and vacuum dielectric constant; Node potential acquisition module: used to mesh the deposition model and compaction model, and obtain the node potential of each cell after meshing based on the electrical conductivity of the solid phase and the electrical conductivity of the liquid phase; Complex conductivity acquisition module: used to solve the complex conductivity of the compaction model by combining the nodal potential of each element with the finite difference method.

[0087] The various modules of the system of this invention work together to accurately calculate the complex conductivity of the deposition and compaction models.

[0088] An electronic device includes: a processor; a memory for storing computer program instructions; and steps for implementing a method for obtaining complex conductivity based on digital core technology when executing the computer program.

[0089] A storage medium storing computer program instructions, which are loaded and executed by a processor, wherein the processor performs a method for obtaining complex conductivity based on digital core technology.

[0090] A computer program product comprising computer instructions that instruct a computer to execute a method for obtaining complex conductivity based on digital core technology.

[0091] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0092] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0093] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0094] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0095] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. A method for obtaining complex conductivity based on digital core technology, characterized in that, Includes the following steps: Establish sedimentary and compaction models with similar pore structures to sedimentary rocks; The mean particle size, porosity, and volume ratio per unit pore surface area were obtained for both the sedimentation model and the compaction model. The equivalent particle size of the sedimentation model and the compaction model is obtained based on the mean particle size, porosity, and volume ratio of unit pore surface area to volume of the sedimentation model and the compaction model. The conductivity of the liquid phase with the double electric layer is obtained, and the conductivity of the solid phase with the double electric layer is obtained based on the equivalent particle size and the vacuum dielectric constant. The deposition model and compaction model are meshed, and the nodal potential of each unit after meshing is obtained based on the electrical conductivity of the solid phase and the electrical conductivity of the liquid phase. The complex conductivity of the compaction model is solved by combining the finite difference method with the nodal potential of each element.

2. The method for obtaining complex conductivity based on digital core technology according to claim 1, characterized in that, The specific steps for establishing sedimentary and compaction models with similar pore structures to sedimentary rocks are as follows: Within a defined area, particles of different sizes are sequentially deposited to generate a particle accumulation with porous structure characteristics, thus obtaining a sedimentation model. A compaction model is obtained by performing compaction simulation on the sedimentation model body.

3. The method for obtaining complex conductivity based on digital core technology according to claim 1, characterized in that, In the step of obtaining the equivalent grain size of the deposition model and the compaction model, the step of obtaining the equivalent grain size of the deposition model is as follows: The mean grain size of the deposition model is the equivalent grain size.

4. The method for obtaining complex conductivity based on digital core technology according to claim 1, characterized in that, In the step of obtaining the equivalent particle size of the deposition model and the compaction model, the formula for obtaining the equivalent particle size of the compaction model is as follows: in, For equivalent particle size, The ratio of surface area per unit pore to volume. Porosity.

5. The method for obtaining complex conductivity based on digital core technology according to claim 1, characterized in that, The specific steps for obtaining the conductivity of the solid phase and the conductivity of the liquid phase of the double layer based on the equivalent particle size and the vacuum dielectric constant are as follows: The volumetric complex conductivity of a single particle is obtained based on the equivalent particle size and the vacuum dielectric constant. The conductivity of the solid phase with an electric double layer is obtained from the volumetric complex conductivity of a single particle.

6. The method for obtaining complex conductivity based on digital core technology according to claim 5, characterized in that, The formula for obtaining the volumetric complex conductivity of a single particle based on the equivalent particle size and vacuum dielectric constant is as follows: in, The volumetric complex conductivity of a single particle. For equivalent particle size, Angular frequency, For relaxation time, The imaginary unit, The mobility of ions in the Stern layer. The mobility of ions in the diffusion layer. The surface conductivity of the particles is the complex conductivity. The DC resistivity of the particle surface. This represents the ion density in the Stern layer. The ion density in the diffusion layer. denoted as , where is the charge density of hydrogen ions.

7. The method for obtaining complex conductivity based on digital core technology according to claim 1, characterized in that, The specific formula for obtaining the nodal potential of each gridded element based on the conductivity of the solid phase and the conductivity of the liquid phase is as follows: in, For nodes With the surrounding The conductivity of the bonds between nodes. For the surrounding area The potential of each node, ; Let be the node potential.

8. A system for obtaining complex electrical conductivity based on digital core technology, characterized in that, It includes a model building module, a structural parameter acquisition module, an equivalent particle size acquisition module, a conductivity acquisition module, a nodal potential acquisition module, and a complex conductivity acquisition module, wherein: Model building module: used to create sedimentary and compaction models with similar pore structures to sedimentary rocks; Structural parameter acquisition module: used to acquire the mean particle size, porosity, and volume ratio per unit pore surface area for the deposition model and the compaction model, respectively; Equivalent particle size acquisition module: used to obtain the equivalent particle size of the sedimentation model and the compaction model based on the mean particle size, porosity and unit pore surface area to volume ratio of the sedimentation model and the compaction model; Conductivity acquisition module: used to acquire the conductivity of the liquid phase of the double layer, and to acquire the conductivity of the solid phase of the double layer based on the equivalent particle size and vacuum dielectric constant; Node potential acquisition module: used to mesh the deposition model and compaction model, and obtain the node potential of each cell after meshing based on the electrical conductivity of the solid phase and the electrical conductivity of the liquid phase; Complex conductivity acquisition module: used to solve the complex conductivity of the compaction model by combining the nodal potential of each element with the finite difference method.

9. An electronic device, comprising: A processor; a memory, an electronic device for storing computer program instructions; characterized in that, when executing the computer program, it implements the steps of the complex conductivity acquisition method based on digital core technology as described in any one of claims 1-7.

10. A storage medium storing computer program instructions, characterized in that, When the computer program instructions are loaded and run by the processor, the processor executes the complex conductivity acquisition method based on digital core technology as described in any one of claims 1-7.

11. A computer program product, said computer program product comprising computer instructions, characterized in that, The computer instructions instruct the computer to execute the complex conductivity acquisition method based on digital core technology as described in any one of claims 1-7.

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