A diagenetic numerical simulation method based on multi-mineral digital core

Abstract

The present application belongs to the technical field of oil and gas reservoir rock data identification, and particularly relates to a diagenesis numerical simulation method based on a multi-mineral digital core. The diagenesis numerical simulation method according to the present application can simulate cementation by a nucleation-growth algorithm and an expansion algorithm in sequence of diagenetic evolution sequence; the four-parameter structure method is improved to simulate dissolution and metasomatism, and the improved four-parameter structure method can simulate the precipitation in the dissolution pores of secondary minerals due to dissolution and the precipitation outside the dissolution pores, and can also simulate metasomatism of different shapes. The diagenesis numerical simulation method based on a three-dimensional multi-mineral digital core can not only provide a new technical means for analyzing the microstructure and physical property response of a reservoir, but also provide an effective way for further exploring the control relationship between diagenesis and reservoir physical properties.

Description

Technical Field

[0001] This invention belongs to the field of oil and gas reservoir rock data identification and numerical simulation technology, and particularly relates to a numerical simulation method for diagenesis based on multi-mineral digital cores. Background Technology

[0002] Diagenesis is a key geological process controlling the evolution of pore structure and differences in reservoir properties. It is complex in type and diverse in timing, profoundly influencing the formation and distribution of oil and gas reservoirs at different scales. Numerical simulation of diagenesis, as a cutting-edge interdisciplinary field integrating oil and gas reservoir geology and computational geosciences, is deeply intertwined with innovations in computer technology and rock physics analysis methods. Its core objective is to reconstruct the diagenetic evolution process and reveal the laws governing reservoir quality evolution through quantitative modeling and dynamic simulation. It has evolved from single-process analysis to multi-process coupling, and from static quantification to dynamic visualization, with continuous improvement in its technical system and expanding application scenarios.

[0003] Traditional diagenetic studies primarily rely on core experiments, thin section observations, and geochemical analysis. While these methods have yielded significant results in qualitative understanding and local quantitative analysis, they still have considerable limitations in reconstructing the dynamic evolution of diagenetic processes, quantitatively characterizing changes in microstructure, and analyzing the coupled responses of multiple physical properties. In particular, they struggle to directly depict the intrinsic relationship between the evolution of micropore structure and changes in macroscopic physical properties, falling short of the "quantitative and dynamic" development requirements of numerical simulations of diagenesis. With the continuous development of digital rock physics (DLP), DLP has gradually become an important tool for studying the relationship between reservoir microstructure and physical properties (Blunt et al., 2013). Among these, three-dimensional multi-mineral digital cores, by reconstructing the true microstructure of rocks in digital space, provide a new technical path for reservoir property analysis (Andrä et al., 2013) and have become a core carrier for multi-process, multi-scale coupled simulations in recent years. However, existing digital core studies are mostly focused on static structural analysis, which makes it difficult to reflect the complex diagenetic evolution process that reservoirs undergo during geological history. This limits their application in diagenetic mechanism analysis, reservoir evolution prediction, and the study of high-quality reservoir formation mechanisms.

[0004] Diagenetic simulation based on three-dimensional multi-mineral digital cores, by numerically representing and visualizing diagenetic processes such as compaction, cementation, dissolution, precipitation, and metasomatism, achieves dynamic reconstruction of reservoir microstructure as it evolves with diagenesis. This provides a new research approach for revealing the control mechanism of diagenesis on pore structure and physical property evolution. This method not only realistically depicts the evolutionary characteristics of pore structure and mineral composition but also further enables quantitative characterization of various reservoir properties such as porosity, permeability, mechanical properties, and electrical parameters as they evolve with diagenesis, aligning with the development trend of numerical simulation of diagenesis "from static quantification to dynamic visualization." Therefore, systematically conducting research on diagenetic simulation methods based on three-dimensional multi-mineral digital cores and their application in reservoir property analysis has significant theoretical and practical value for deepening the understanding of the microstructure-property response relationship, exploring the formation mechanism of high-quality reservoirs, improving reservoir evaluation methods, and serving the efficient development of oil and gas resources.

[0005] Existing numerical simulation studies on diagenesis mostly focus on conventional sandstone and carbonate reservoirs, with limited research on simulations of special reservoirs, further highlighting the limitations of current technologies. In summary, the specific problems and shortcomings of existing technologies are as follows:

[0006] (1) Existing numerical simulations of diagenesis are mostly limited to the study of single minerals. Most existing methods focus on diagenesis simulations of a specific mineral, such as studying quartz cementation or feldspar dissolution alone. This makes it difficult to reflect the complex characteristics of multiple mineral components coexisting and influencing each other in actual reservoirs, resulting in low consistency with actual geological conditions. This contradicts the trend of numerical simulations of diagenesis towards multi-mineral and multi-process coupling and cannot meet the research needs of complex reservoirs.

[0007] (2) Existing numerical simulations of diagenesis mostly rely on idealized theoretical models. Existing simulation methods often oversimplify the morphology, distribution and development process of diagenesis, which differs greatly from the heterogeneity and complex structure of minerals in the real geological environment. This results in limited geological applicability and engineering reference value of the models, and fails to accurately replicate the diagenetic process.

[0008] (3) Existing numerical simulations of diagenesis have not yet achieved synergistic simulation of multiple diagenetic processes. Current studies are mostly focused on single diagenetic processes and lack methods for combined simulation and continuous characterization of multiple diagenetic processes such as cementation, dissolution, and metasomatism according to the actual diagenetic evolution sequence. It is difficult to systematically reveal the evolution process of reservoir pore structure and physical properties jointly controlled by different diagenetic processes, which is different from the current mainstream trend of multi-process and multi-scale coupled simulation. Summary of the Invention

[0009] To overcome the problems existing in the prior art, the present invention provides a numerical simulation method for diagenesis based on multi-mineral digital cores.

[0010] To achieve the above objectives, the present invention includes the following steps:

[0011] S1. Obtaining Diagenetic Characteristics: Prepare rock thin sections and observe diagenetic phenomena in the rock thin sections under an electron microscope to identify the diagenetic type and evolutionary process of the target reservoir, and determine the morphological characteristics related to cementation, dissolution, and metasomatism. 𝑛 and quantitative information 𝑄 𝑛 Morphological characteristics 𝑛 Including the location, distribution, and spatial characteristics of diagenesis, quantitative information 𝑄 𝑛 Information includes the quantity, extent, and proportion of diagenetic processes.

[0012] S2. Determination of diagenetic control parameters: Based on the morphological features obtained in S1 𝑛 With quantitative information 𝑛 Numerical simulation control rules were established for cementation, dissolution, and metasomatism, including the control conditions for the scope, morphological type, and quantity of these processes, and the corresponding algorithm parameters were set. Specifically, based on the morphological characteristics corresponding to different diagenetic processes... 𝑛 Determine its geometric shape, spatial distribution, and position of action in the numerical model; based on the quantization information... 𝑛 The simulated volume, scale of action, or degree of development are determined. By setting the above parameters, the morphological simulation and quantitative control of cement formation, mineral dissolution, and mineral replacement processes can be achieved.

[0013] S3. Numerical Simulation of Diagenesis: Based on different diagenetic control rules, numerical simulation of diagenesis is performed according to the sequence of diagenetic evolution. Specifically, cementation is simulated using expansion and nucleation-growth algorithms to obtain digital cores, while dissolution and metasomatism are simulated using an improved four-parameter structure algorithm. The mineral and pore structures in the target digital cores are generated, removed, replaced, or filled to achieve numerical simulation of diagenesis.

[0014] S4. Structure Update and Result Output: Update the structure of the digital core after diagenesis simulation and output the digital core after diagenesis numerical simulation.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0016] (1) The present invention can realize the comprehensive simulation of multiple mineral components. Compared with the existing methods, which are mostly limited to the study of single minerals, the present invention is oriented towards multi-component digital cores, and can simultaneously consider the coexistence and interaction of multiple minerals, thereby more realistically reflecting the complex mineral composition characteristics in actual reservoirs.

[0017] (2) This invention improves the geological realism of the simulation results. In the simulation process, this invention introduces the morphological characteristics, development degree and spatial distribution information of actual diagenesis, avoiding the oversimplification problem of traditional idealized models, so that the simulation results can better reflect the heterogeneity and complexity of diagenesis under real geological conditions.

[0018] (3) This invention can realize the synergistic and sequential simulation of multiple diagenetic processes. This invention can combine multiple diagenetic processes such as cementation, dissolution and replacement, and continuously simulate them according to the actual diagenetic evolution sequence, thereby systematically characterizing the comprehensive influence of multiple diagenetic processes on the evolution of reservoir pore structure and physical properties. Attached Figure Description

[0019] The present invention will now be described in further detail with reference to the accompanying drawings and specific embodiments.

[0020] Figure 1 This is a schematic diagram illustrating the simulation of secondary enlargement of quartz using an expansion algorithm, provided in an embodiment of the present invention.

[0021] Figure 2 This is a schematic diagram of simulating quartz microcrystal precipitation using a nucleation-growth algorithm provided in an embodiment of the present invention;

[0022] Figure 3 This is a schematic diagram of the simulation of feldspar edge dissolution using the improved four-parameter structural method provided in this embodiment of the invention;

[0023] Figure 4 This is a schematic diagram of the simulation of intragranular dissolution of feldspar using the improved four-parameter structural method provided in this embodiment of the invention;

[0024] Figure 5 This is a schematic diagram of the simulation of feldspar dissolution along cleavage fractures using the improved four-parameter structural method provided in this embodiment of the invention;

[0025] Figure 6 This is a schematic diagram illustrating the process of albite replacing potassium feldspar along the edge of potassium feldspar, provided by an embodiment of the present invention.

[0026] Figure 7 This is a schematic diagram illustrating the process of albite alteration along potassium feldspar using an improved four-parameter structural method, as provided in an embodiment of the present invention.

[0027] Figure 8This is a three-dimensional diagenetic evolution model based on multi-component digital cores provided in this embodiment of the invention. Detailed Implementation

[0028] The technical solutions of the present invention will be clearly and completely described below with reference to 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 of ordinary skill in the art without creative effort are within the scope of protection of the present invention.

[0029] This invention provides a simulation of diagenesis based on multi-mineral digital cores. The specific implementation steps of this method are described in detail below in logical order:

[0030] S1. Obtaining Diagenetic Characteristics: Thin rock sections are prepared, mechanically pre-polished, and treated with an argon ion polisher. Then, platinum is sprayed onto the sections, and diagenetic processes are observed under an electron microscope. Based on the diagenetic evolution process and diagenetic types experienced by the target reservoir, the morphological characteristics corresponding to cementation, dissolution, and metasomatism are determined. 𝑛 and quantitative information 𝑄 𝑛 Among them, morphological characteristics 𝑛 Used to characterize the geometric manifestations of different diagenetic processes in terms of pore structure, morphology, etc.; quantifying information 𝑄 𝑛 It is used to describe the development degree, scope and volume fraction of various diagenetic processes, providing basic data for subsequent establishment of reservoir microstructure models and diagenetic simulation.

[0031] S2. Determination of diagenetic control parameters: Based on the morphological characteristics obtained in S1. 𝑛 With quantitative information 𝑛 Numerical simulation control rules were established for cementation, dissolution, and metasomatism, and corresponding algorithm parameters were set. Specifically, based on the morphological characteristics corresponding to different diagenetic processes... 𝑛 Determine its geometric shape, spatial distribution, and position of action in the numerical model; based on the quantization information... 𝑛 The simulated volume, scale of action, or degree of development are determined. By setting the above parameters, the morphological simulation and quantitative control of cement formation, mineral dissolution, and mineral replacement processes can be achieved.

[0032] S3. Numerical Simulation of Diagenesis: Based on the control parameter settings completed in S2, and using a three-dimensional digital core model, numerical simulation algorithms corresponding to cementation, dissolution, and metasomatism are called and executed respectively. The diagenetic algorithm follows the preset morphological characteristics. 𝑛 Quantitative information 𝑛The system uses control rules to update the structure of pores, particles, and mineral components in three-dimensional digital cores, thereby simulating diagenetic evolution processes such as cement precipitation, pore dissolution and expansion, and mineral replacement.

[0033] ① Simulation of Cementation: The cementation process of minerals can be simulated using the dilation operation in image morphology. This method adds a structuring element to the original particle object in the image, expanding the particle surface and thus simulating cementation. The shape of the structuring element can be rhombus, disk, octagon, line segment, rectangle, cube, cuboid, or sphere, etc. The mathematical expression for the dilation operation is:

[0034]

[0035] in, The set of mineral grains to be processed represents the set of locations of all mineral phase pixels in the digital core image; : Morphological expansion operator, used to achieve the outward expansion of mineral grains to simulate cement growth; As a structural element, it is a predefined geometric shape (such as a disk or sphere) used to control the form and degree of bonding. These are the new mineral, cement, and voxel locations selected by the cementation expansion operation in the digital core image. is the Euclidean space where the digital core is located, and is the set of all pixels / voxels in the image; Represents structural element Symmetrical form, u is Euclidean space The points in the diagram are used to define the symmetric form of structural elements.

[0036] Furthermore, by changing the size of structural elements to control the degree of cementation, this method provides a simple and effective technical approach for simulating cementation in digital cores.

[0037] Cementation is achieved based on the nucleation-growth theory. At the interface between the pore space and the mineral to be cemented, nucleation occurs according to a pre-set probability. Nucleation points were randomly selected using the Bernoulli distribution as the starting points for cement formation. Each candidate voxel located at the interface between the pore space and the mineral was randomly selected according to the Bernoulli distribution.

[0038]

[0039] Among them, when =1 indicates the voxel point For nucleation points, =0 indicates no nucleation.

[0040] The set of all nucleating voxels is defined as:

[0041]

[0042] in, The cemented seed voxels, representing the nucleation stage, are the smallest spatial units in the three-dimensional model (corresponding to pixels in a two-dimensional image), representing a spatial location in the core. Subsequently, based on these nucleation points, the gradual expansion of cemented minerals on grain surfaces and within pores is simulated by controlling the crystal growth rate.

[0043]

[0044] Where, p grow Indicates the probability of growth; =1 indicates that the voxel has been occupied by growth and becomes a cemented voxel. =0 indicates that it is not occupied. The set of new growth voxels generated in this round is:

[0045]

[0046] in, This represents the set of newly grown cemented voxels in the current iteration of round t+1. The newly added cementing voxels, representing the growth stage, are the smallest spatial units in the three-dimensional model (corresponding to pixels in a two-dimensional image), representing a spatial location in the core.

[0047] The cumulative growth collection has been updated to:

[0048]

[0049] This represents the cumulative set of cemented voxels at the end of iteration t+1. Let represent the cumulative set of cemented voxels at the end of the t-th iteration.

[0050] The model not only features adjustable nucleation rate and crystal growth rate, but also allows for precise control of the cementing amount of cementing minerals, thus enabling highly accurate regulation of the cementing process.

[0051] Under the same crystal growth rate, by adjusting the nucleation rate, the diversity of cementation distribution can be effectively achieved. This can simulate the formation of homogeneous cementation as well as reproduce the spatial distribution characteristics of heterogeneous cementation. It is worth noting that both homogeneous and heterogeneous cementation have a significant impact on reservoir permeability and other physical properties. Therefore, in practical applications, it is necessary to combine specific geological environments and reservoir conditions to rationally select appropriate cementation modes in order to accurately reflect the physical properties and fluid flow characteristics of the reservoir.

[0052] like Figure 1 As shown in the figure, this embodiment of the invention provides a schematic diagram of the secondary enlargement process of quartz based on the expansion algorithm, which is used to show the spatial morphological characteristics of secondary enlargement growth of quartz particles along the particle boundary or surface under the action of diagenetic cementation. Figure 2 This is a schematic diagram simulating the precipitation process of quartz microcrystals based on the nucleation-growth algorithm. The diagram shows the spatial distribution characteristics of quartz microcrystals nucleating, growing, and eventually forming precipitated cement in the pore space or on the particle surface.

[0053] ② Simulation of Dissolution: The improved four-parameter structural method (QSGSA) was used to simulate the dissolution of minerals. The traditional four-parameter structural method involves the following steps: Several nodes are randomly selected in the target mineral as centers of dissolution pores. The number of centers is controlled by a nucleus distribution probability, which depends on the pore size and volume fraction. Particles grow from the centers in 26 directions, their growth limited by the growth probability of these 26 directions (a directional probability model can be used). When the total volume fraction of dissolution pores reaches or exceeds a preset value, particle growth terminates. This study improves the four-parameter structural method, with the following specific steps:

[0054] I. Determining the Dissolution Shape And the direction of dissolution d;

[0055] II. Randomly select several points at the interface between the pore space and the mineral to be dissolved as the starting point for mineral dissolution, and carry out the initial dissolution operation according to the preset dissolution shape and direction:

[0056]

[0057]

[0058] in, These are randomly selected dissolution points at the interface between the pore space and the mineral to be dissolved. In the interface collection Above, based on probability Perform uniform random sampling; This is the dissolution area defined in this dissolution operation, which is a set of mineral voxels to be dissolved that meet the conditions; It is an aggregate of mineral voxels to be dissolved; These are the dissolution shape parameters, used to define the geometry of the dissolution region; It is a point In dissolution shape Under the constraint of the dissolution direction d Normalized distance, =1 represents the boundary of the dissolution zone. <1 represents the interior;

[0059] III. Based on the existing dissolution area, continue to expand the dissolution range along the set direction. The specific operation is similar to step II, except that the starting point of dissolution is selected at the contact surface between the already dissoluted area and the mineral to be dissolved.

[0060] IV. Determine whether the current cumulative erosion volume has reached the preset value: If it has, terminate the operation; if it has not, repeat steps II and III until the erosion volume requirement is met.

[0061] The improved four-parameter structure generation method has significant advantages. It not only allows for initial dissolution by selecting dissolution points but also enables expansion based on existing dissolution areas, making the simulation process closer to actual geological dissolution characteristics. Furthermore, this method supports different types of dissolution shapes and can simulate various dissolution types, such as feldspar dissolution along cleavage fractures, edge dissolution, and intragranular dissolution. In addition, this method allows for precise control of the dissolution volume, improving the accuracy of the simulation.

[0062] Figure 3 The present invention provides a schematic diagram of the feldspar edge dissolution process based on the improved four-parameter structural method, which is used to show the irregular dissolution and pore space expansion of the feldspar particle edges under the influence of dissolution, and to characterize the morphological evolution and spatial distribution characteristics of feldspar edge dissolution.

[0063] Figure 4 The present invention provides a schematic diagram of the simulation of intragranular dissolution process of feldspar based on the improved four-parameter structural method, which is used to show the formation of intragranular pores inside feldspar particles under the influence of dissolution, and to characterize the morphological evolution and spatial distribution characteristics of intragranular dissolution.

[0064] Figure 5 The present invention provides a schematic diagram of the feldspar dissolution process along cleavage fractures based on the improved four-parameter structural method. It is used to demonstrate the simulated process of selective dissolution of feldspar particles inside or at the edge along the direction of cleavage fractures, the gradual expansion of cleavage fractures and the formation of banded dissolution pores, and to characterize the morphological evolution and spatial distribution characteristics of feldspar dissolution along cleavage fractures.

[0065] Under enclosed conditions, the dissolution process of feldspar is usually accompanied by the precipitation of quartz and clay minerals, and the process can be represented as follows:

[0066] 1.5KAlSi3O8 (potassium feldspar) + H + =0.5KAl3Si3O 10 (OH)₂(illite) + 3SiO₂ + K +

[0067] These precipitates may fill the interior of the dissolution pores or be deposited on the exterior of the pores. The proposed improved four-parameter structure generation method can also simulate both precipitation modes, thus more realistically reflecting the spatial evolution characteristics of the dissolution-precipitation process.

[0068] ③ Replacement Simulation: Replacement can also be simulated using the improved four-parameter simulation method. First, the replacement shape and direction are determined. Then, several points are randomly selected at the interface between the replacing mineral and the replaced mineral as replacement starting points, and initial replacement operations are carried out according to the preset replacement shape and direction. Based on the existing replacement area, the replacement range continues to expand along the set direction, and it is determined whether the current cumulative replacement volume has reached the preset value. If it has, the operation is terminated; if not, the above steps are repeated until the replacement volume requirement is met.

[0069] Figure 6 The present invention provides a schematic diagram of the process of albite replacing potassium feldspar at the edge based on the improved four-parameter structural method, which is used to illustrate the simulated process of albite replacing potassium feldspar at the edge and to characterize the morphological evolution and spatial distribution characteristics of albite replacing potassium feldspar at the edge.

[0070] Figure 7 The present invention provides a schematic diagram of the process of albite replacing potassium feldspar along cleavage, based on the improved four-parameter structural method, to illustrate the simulation process of albite selectively replacing potassium feldspar along the cleavage fracture direction, and to characterize the morphological evolution and spatial distribution characteristics of albite selectively replacing potassium feldspar along the cleavage fracture direction.

[0071] S4. Structural Update and Result Output: The pore structure, mineral composition, cement, and dissolution pores in the 3D digital core model are updated, and the corresponding simulation results are output. To ensure consistency and comparability of different simulation results in visualization, color values ​​corresponding to various minerals, cements, and dissolution pores are pre-set, giving different components and pore types a unified and clear color identifier in the image. Through this color mapping method, not only can mineral types, cement distribution, and pore development characteristics be intuitively distinguished, but it also facilitates subsequent 3D visualization analysis, model comparison, result display, and quantitative evaluation.

[0072] Figure 8This invention provides a schematic diagram of a three-dimensional diagenetic evolution model based on multi-component digital cores. The model first determines the evolutionary sequence of diagenetic events such as cementation, dissolution, and metasomatism, and then executes corresponding numerical simulation algorithms sequentially according to this diagenetic evolution sequence, thereby reconstructing the three-dimensional diagenetic evolution process based on multi-component digital cores. The diagenetic process of laminated felsic shale is divided into three key stages: early diagenetic stage B, intermediate diagenetic stage A, and intermediate diagenetic stage B, comprising a total of five consecutive evolutionary steps. This model can intuitively characterize the alteration effects of different diagenetic stages on pore structure, mineral distribution, and rock microstructure, providing a visual basis for reservoir diagenetic evolution analysis and quantitative evaluation of pore structure.

[0073] The model corresponds to the diagenetic geological effects of each evolutionary step, clarifying the main controlling diagenetic events at different stages and their impact on the reservoir: the early diagenetic B stage is dominated by weak clay mineral transformation and initial dolomitization, with only weak diagenetic alteration occurring; the intermediate diagenetic A stage is the key period of dissolution, with organic acid dissolution driven by organic matter thermal evolution being the core mechanism for secondary porosity development, accompanied by clay mineral transformation and early quartz cementation; the intermediate diagenetic B stage is characterized by large-scale siliceous cementation, with multiple stages of secondary cementation filling the pore space, leading to reservoir compaction. This model, through a diagenetic evolution sequence, sequentially executes numerical simulation algorithms for diagenetic events such as cementation, dissolution, and metasomatism, achieving dynamic and quantitative reconstruction of the three-dimensional diagenetic evolution process of lamellar felsic shale. It breaks through the limitations of traditional diagenetic evolution studies that rely solely on two-dimensional thin sections or static characterization, and can intuitively represent the effects of different diagenetic stages on pore structure, mineral distribution, and rock microstructure. This provides a visual and quantitative basis for reservoir diagenetic evolution analysis, quantitative evaluation of pore structure, and prediction of reservoir sweet spots.

[0074] This invention proposes a nucleation-growth algorithm that, by adjusting the crystal growth rate and nucleation rate, achieves diversity in cementation distribution, thereby simulating cementation. This algorithm can more realistically reflect the heterogeneous characteristics of cementation in pore space and on grain surfaces. It can also use an expansion algorithm to directly and quickly simulate uniform cementation phenomena. An improved four-parameter structural method is used to simulate dissolution, which not only allows for initial dissolution by selecting dissolution points but also enables further expansion based on existing dissolution areas, better reflecting the gradual development, local enhancement, and continuous expansion of dissolution under actual geological conditions. Simultaneously, this method supports different types of dissolution shapes, such as feldspar dissolution along cleavage fractures, edge dissolution, and intragranular dissolution, and allows for precise control of dissolution volume, thereby improving the realism, accuracy, and controllability of the simulation. The improved four-parameter structural method can also simulate the intrapore and extrapore precipitation of secondary minerals caused by dissolution, as well as metasomatism. The numerical simulation methods for cementation, dissolution, and metasomatism proposed in this invention can provide quantitative and visual simulation of diagenetic processes. Based on actual reservoir diagenetic characteristics, and fully considering the morphological differences, development degree, spatial distribution, and evolutionary sequence of different diagenetic processes, this invention can more realistically reconstruct the changes in pore structure, mineral composition, and micromorphology of reservoirs during diagenesis, making the simulation results more consistent with actual geological conditions. This invention significantly improves the realism of numerical simulations of diagenesis, providing a more realistic and effective technical means for numerical simulations of diagenesis based on three-dimensional digital cores, and also offering an effective approach to further explore the control relationship between diagenesis and reservoir properties.

[0075] The above embodiments are only used to illustrate the technical solutions of the present invention, and are not intended to limit it. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features therein. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention, and they should all be covered within the protection scope of the claims and specification of the present invention.

Claims

1. A numerical simulation method for diagenesis based on multi-mineral digital cores, characterized in that, Includes the following steps: S1. Obtaining diagenetic characteristics: preparing rock thin sections, observing diagenetic phenomena in the rock thin sections under an electron microscope, clarifying the diagenetic type and evolutionary process of the target reservoir, and determining the morphological characteristics related to cementation, dissolution, and metasomatism. 𝑛 and quantitative information 𝑄 𝑛 ; S2, Diagenetic control parameters were determined based on the morphological features obtained in S1. 𝑛 With quantitative information 𝑛 Numerical simulation control rules for cementation, dissolution and replacement were established, including the control conditions for the range, morphology and quantity of action, and the corresponding algorithm parameters were set. S3. Numerical simulation of diagenesis: Based on different diagenetic control rules, numerical simulation of diagenesis is performed according to the sequence of diagenetic evolution. Cementation is simulated using expansion and nucleation-growth algorithms to obtain digital cores, while dissolution and metasomatism are simulated using an improved four-parameter structure algorithm to obtain digital cores. The mineral structure and pore structure in the target digital cores are generated, removed, replaced, or filled. The specific steps of the improved four-parameter structure algorithm are as follows: I. Determine the dissolution shape φ s And the direction of dissolution; II. Randomly select several points at the interface between the pore space and the mineral to be dissolved as the starting point for mineral dissolution, and carry out the initial dissolution operation according to the preset dissolution shape and direction: ; ;in, These are randomly selected dissolution points at the interface between the pore space and the mineral to be dissolved. In the interface collection Above, based on nucleation probability Perform uniform random sampling; This is the dissolution area defined in this dissolution operation, which is a set of mineral voxels to be dissolved that meet the conditions; It is an aggregate of mineral voxels to be dissolved; These are the dissolution shape parameters, used to define the geometry of the dissolution region; It is a point In dissolution shape Under the constraint of the dissolution direction d Normalized distance, =1 represents the boundary of the dissolution zone. <1 represents the interior; III. Based on the existing dissolution area, continue to expand the dissolution range along the set direction. The specific operation is similar to step II, except that the starting point of dissolution is selected at the contact surface between the already dissoluted area and the mineral to be dissolved. IV. Determine whether the current cumulative dissolution volume has reached the preset value: If it has, terminate the operation; if it has not, repeat steps II and III until the dissolution volume requirement is met. S4. Structure Update and Result Output: Update the structure of the digital core after diagenesis simulation and output the digital core after diagenesis numerical simulation.

2. The numerical simulation method for diagenesis based on multi-mineral digital cores according to claim 1, characterized in that, In step S1, the morphological feature 𝐶 𝑛 This includes the location, distribution pattern, and spatial distribution characteristics of diagenesis, the quantitative information 𝑄 𝑛 This includes information on the quantity, extent, and proportion of diagenetic processes.

3. The numerical simulation method for diagenesis based on multi-mineral digital cores according to claim 1, characterized in that, The specific approach for S2 is as follows: based on the morphological characteristics corresponding to different diagenetic processes... 𝑛 Determine its geometric shape, spatial distribution, and position of action in the numerical model; based on the quantization information... 𝑛 The simulated volume, scale of action, or degree of development are determined. By setting the above parameters, the morphological simulation and quantitative control of cement formation, mineral dissolution, and mineral replacement processes can be achieved.

4. The numerical simulation method for diagenesis based on multi-mineral digital cores according to claim 1, characterized in that, The mathematical expression for the expansion algorithm is: ;in, The set of mineral grains to be processed represents the set of locations of all mineral phase pixels in the digital core image; This is a morphological expansion operator used to achieve the outward expansion of mineral grains to simulate cement growth; As a structural element, it is a predefined geometric shape used to control the form and degree of bonding. These are the new mineral, cement, and voxel locations selected by the cementation expansion operation in the digital core image. is the Euclidean space where the digital core is located, and is the set of all pixels / voxels in the image; Represents structural element Symmetrical form, , For Euclidean space The points in the diagram are used to define the symmetric form of structural elements.

5. The numerical simulation method for diagenesis based on multi-mineral digital cores according to claim 1, characterized in that, The specific implementation of the nucleation-growth algorithm is as follows: At the interface between the pore space and the mineral to be cemented, nucleation occurs according to a pre-set probability. Nucleation points were randomly selected using the Bernoulli distribution as the starting points for cement formation. Each candidate voxel located at the interface between the pore space and the mineral was randomly selected according to the Bernoulli distribution. Among them, when =1 indicates the voxel point For nucleation points, =0 indicates no nucleation; The set of all nucleating voxels is defined as: ;in, The cemented seed voxel, representing the nucleation stage, is the smallest spatial unit of the three-dimensional model, representing a spatial location in the core. Subsequently, based on these nucleation points, the gradual expansion process of cemented minerals on the grain surface and in pores is simulated by controlling the crystal growth rate. ; where p grow Indicates the probability of growth; =1 indicates that the voxel has been occupied by growth and becomes a cemented voxel. =0 indicates that the space is not occupied; The new set of growth voxels generated in this round is: ;in, This represents the set of newly grown cemented voxels in the current iteration of round t+1. The newly added cementing elements representing the growth stage are the smallest spatial units in the three-dimensional model, representing a spatial location in the core. The cumulative growth collection has been updated to: ;in, This represents the cumulative set of cemented voxels at the end of iteration t+1. Let represent the cumulative set of cemented voxels at the end of the t-th iteration.

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