A method for predicting three-dimensional ground stress of ultra-deep fault-controlled fracture-cave carbonate reservoir and application thereof

Abstract

The application discloses a kind of super deep layer fracture control fracture-cave type carbonate reservoir three-dimensional ground stress prediction method and application thereof, and it is related to the technical field of petroleum and natural gas exploration and research.The prediction method comprises the following steps: according to the data provided by seismic data interpretation, a modeling method is used to establish a three-dimensional tectonic geological model; finite element mesh is divided to the three-dimensional tectonic geological model, a triangular mesh finite element model is generated, and a three-dimensional rock mechanics parameter model is established using prestack inversion data and test data; stress prediction is carried out by finite element analysis method.The application discloses a kind of super deep layer fracture control fracture-cave type carbonate reservoir three-dimensional ground stress prediction method, realizes the three-dimensional ground stress prediction of super deep layer fracture control fracture-cave type carbonate reservoir, and improves the prediction accuracy of three-dimensional ground stress, and lays a solid foundation for oil and gas exploration and development.

Description

Technical Field

[0001] This invention relates to the field of oil and gas exploration and research technology, and in particular to a method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs and its application. Background Technology

[0002] In-situ stress research and analysis is a fundamental and crucial research area in oil and gas exploration and development. It is widely used to address issues related to the distribution of oil and gas enrichment zones, wellbore stability, reservoir stimulation fracture distribution, hydraulic fracturing initiation and propagation pressures, casing deformation, and engineering design optimization. By establishing three-dimensional geological and rock mechanics models to simulate the distribution and evolution of in-situ stress, important theoretical basis and technical support can be provided for oil and gas exploration.

[0003] In recent years, various methods have been used for inversion analysis and fitting calculation of three-dimensional geostress fields, such as using finite element mathematical models to regress and analyze the initial stress field of rock masses, and using stress functions to perform trend analysis of the initial stress field of rock masses.

[0004] Reference 1, “Sun Lijian, Zhu Yuanqing, Yin Jiyao. Preliminary analysis of the influence of faults on borehole stress measurement [J]. Progress in Geophysics, 2009, 24(03): 1104-1108,” uses the finite element method to simulate and study the influence of fault structure on the distribution of geostress field, and analyzes the main factors affecting the distribution of stress field at and near the fault tip.

[0005] Reference 2, “Gou Guangxiu, Wu Shaoying. Three-dimensional inversion of geostress field in deep reservoirs [J]. Geological Hazards and Environmental Protection, 2014, 25(01): 102-106.” A finite element three-dimensional numerical model was established for the Xuerduan reservoir in the Xinchang gas field with a burial depth of more than 4600m. The finite element inversion of the regional stress field was used to achieve the best coupling between the direction and magnitude of the maximum principal stress and the measured value, thereby obtaining the overall distribution characteristics of the deep stress field in the study area.

[0006] Reference 3, “Wei Xinwei. Numerical simulation evaluation of three-dimensional geostress field in heterogeneous tight oil reservoirs—taking the Y176 block of Bohai Oilfield as an example [J]. Frontiers in Earth Science (Hans), 2023, 13(9): 1023-1031.” Based on high-precision three-dimensional stratigraphic and fault seismic interpretation data, a regional three-dimensional geological model was constructed. The distribution of rock mechanical parameters in heterogeneous tight oil reservoirs was determined by the joint modeling method of single-well logging interpretation and inter-well seismic body data. Furthermore, the tectonic strain coefficient method was applied to carry out three-dimensional geostress field simulation. The results were in good agreement with the magnitude and direction of the geostress measured at well points.

[0007] The aforementioned three-dimensional geostress prediction method mainly relies on measured geostress data, combined with lithological characteristics, fault and fracture development, and other conditions, to perform inversion calculations of the initial geostress field in order to obtain the geostress field distribution over a larger area. However, it fails to consider the background of deep carbonate rocks being deeply buried, having developed natural fractures and solution cavities, exhibiting strong heterogeneity, and having complex geostress distribution, and is therefore not suitable for three-dimensional geostress prediction of deep carbonate rocks.

[0008] In view of this, in order to overcome the shortcomings of the existing technology, the present invention provides a method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs and its application. Summary of the Invention

[0009] The purpose of this invention is to provide a method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs and its application, thereby improving the accuracy of three-dimensional geostress prediction and laying a solid foundation for oil and gas exploration and development.

[0010] To achieve the above-mentioned objectives, the technical solution of this invention is as follows:

[0011] On the one hand, this invention provides a method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, comprising the following steps:

[0012] Step S1: Based on the data provided by the seismic data interpretation, a three-dimensional structural geological model is established using modeling methods;

[0013] Step S2: Perform finite element meshing on the three-dimensional structural geological model to generate a triangular mesh finite element model, and establish a three-dimensional rock mechanics parameter model using pre-stack inversion data and test data;

[0014] Step S3: Perform stress prediction using the finite element analysis method.

[0015] Preferably, in step S1, the data includes fault data, bedding plane data, single-well geological stratification data, reservoir development characteristics, changes in stratum thickness distribution under tectonic background, and contact relationships between sub-layers.

[0016] Preferably, in step S1, the modeling method is an interactive modeling method combining corner mesh and construction frame methods.

[0017] Preferably, in step S2, the specific steps for performing finite element mesh generation on the three-dimensional structural geological model are as follows: Based on fault data and bedding plane data, combined with well point geological stratification and intrusive rocks, the intersection relationships between faults and faults and between faults and bedding planes are processed to restore the true structural distribution. Appropriate mesh parameters are selected, and a high-quality triangulation is generated by adopting an improved triangulation method, following the "minimum angle maximum" and "empty sphere" criteria. The three-dimensional structural geological model is then meshed using a combination of node degree optimization and element angle optimization.

[0018] Preferably, the specific steps of step S3 are as follows:

[0019] Step S31: (1) Determine the model range based on the geological structure distribution characteristics; (2) Define the grid size based on the geological structure and rock type distribution characteristics; (3) Create different rock materials and rock physical parameters based on experimental test data; (4) Determine the boundary conditions based on the regional tectonic environment and motion characteristics; (5) Form a stress field according to the boundary action characteristics, thereby determining the load.

[0020] Step S32: Perform simulation calculations to assemble the elements into a total matrix equation for the entire discrete domain. The solution to the total matrix equation is an approximate value of the state variables at the element nodes.

[0021] Step S33: Extract the plane distribution map and well profile of different geostress attributes for each stratum, analyze the distribution characteristics of different attributes in the plane and profile, and combine the geological structure and rock physical characteristics to analyze the distribution characteristics of the geostress field and make stress prediction.

[0022] More preferably, in step (1) of step S31, the rock material includes intact rock mass material and discontinuous rock mass material.

[0023] More preferably, in step (1) of step S31, the physical parameters of the intact rock mass material include Young's modulus, Poisson's ratio, internal friction angle, uniaxial compressive strength, tensile strength and coefficient of thermal expansion.

[0024] More preferably, in step (1) of step S31, the physical parameters of the discontinuous material include faults, cracks, stiffness, strength and spacing of the unit wellbore through which it passes.

[0025] More preferably, in step (5) of step S31, the specific steps for forming a stress field according to the boundary action characteristics are as follows: According to the boundary action characteristics, firstly, the stratum has gravity, then a tectonic stress is added in the direction of the maximum / minimum horizontal stress. By adding force on the boundary, the force will be distributed throughout the model to form a stress field.

[0026] More preferably, in step S32, the solution to the total matrix equation can be obtained using a direct method or an iterative method.

[0027] Furthermore, this invention also provides the application of the above-mentioned prediction method in the oil and gas exploration process.

[0028] Preferably, the oil and gas exploration process refers to the exploration process of ultra-deep fault-controlled fracture-vuggy carbonate reservoirs.

[0029] Furthermore, this invention also provides the application of the above-mentioned prediction method in the oil and gas development process.

[0030] Preferably, the oil and gas development process refers to the development process of ultra-deep fault-controlled fracture-vuggy carbonate reservoirs.

[0031] In another aspect, the present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described prediction method.

[0032] Finally, the present invention also provides a device for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, including a storage medium and a processor, wherein the processor executes a computer program on the storage medium to implement the steps of the above-described prediction method.

[0033] The beneficial effects of this invention are as follows:

[0034] This invention discloses a method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs. It realizes the prediction of three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs and improves the prediction accuracy of three-dimensional geostress, laying a solid foundation for oil and gas exploration and development. Attached Figure Description

[0035] Figure 1 This is a flowchart of the three-dimensional geostress prediction method for deep carbonate rocks in Embodiment 1 of the present invention.

[0036] Figure 2 This is a three-dimensional structural model diagram of Embodiment 1 of the present invention.

[0037] Figure 3 This is a three-dimensional geological model diagram from Embodiment 1 of the present invention.

[0038] Figure 4 This is a three-dimensional finite element model diagram of the stress field analysis in Embodiment 1 of the present invention.

[0039] Figure 5 This is a three-dimensional pore pressure plane diagram for stress field analysis in Embodiment 2 of the present invention.

[0040] Figure 6 This is a three-dimensional minimum horizontal principal stress plane diagram for stress field analysis in Embodiment 2 of the present invention.

[0041] Figure 7 This is a three-dimensional total stress vector plane diagram of the stress field analysis in Embodiment 2 of the present invention. Detailed Implementation

[0042] The following non-limiting embodiments are intended to enable those skilled in the art to gain a more comprehensive understanding of the present invention, but do not limit the invention in any way. The following description is merely an exemplary illustration of the scope of protection of the present invention, and those skilled in the art can make various changes and modifications to the invention based on the disclosed content, which should also fall within the scope of protection of the present invention.

[0043] The present invention will be further described below by way of specific embodiments. Unless otherwise specified, all chemical reagents used in the embodiments of the present invention were obtained through conventional commercial means. Unless otherwise specified, all contents mentioned below are mass contents. Unless otherwise specified, it is understood that the process was carried out at room temperature.

[0044] Example 1

[0045] Due to the strong heterogeneity of ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, the presence of faults, fractures, and pores leads to abnormal changes in the local stress field. This invention, utilizing geological modeling of fault-controlled fracture-vuggy carbonate reservoirs, provides a method for predicting three-dimensional in-situ stress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, comprising the following steps:

[0046] Step S1: Based on fault data, bedding plane data, and single-well geological stratification data provided by seismic data interpretation, and combined with reservoir development characteristics, stratigraphic thickness distribution variations within the tectonic context, and contact relationships between sub-layers, an interactive modeling method combining corner mesh and structural frame methods is employed to establish a high-precision three-dimensional structural geological model. The corner mesh simulates faults by defining fault bars in space, generating a frame using the upper, middle, and lower points of each fault bar, requiring all fault bars to have approximately the same spatial height. The corner mesh supports subdivision under complex structural constraints, flexibly representing geological objects such as folds, overlaps, and faults, establishing a high-precision three-dimensional structural geological model. The model is then checked and its quality controlled using three-dimensional seismic data volumes and drilling data.

[0047] Step S2: Based on the fault and bedding data provided by the seismic data interpretation, combined with well point geological stratification and intrusive rocks, handle the intersection relationships between faults and between faults and bedding planes, restore the true structural distribution, select appropriate grid parameters, and use an improved triangulation method, following the "minimum angle maximum" and "empty sphere" criteria, to generate high-quality triangulation. By combining node degree optimization and element angle optimization, perform finite element meshing on the three-dimensional structural geological model to generate a triangular mesh finite element model that meets actual needs. Finally, use pre-stack inversion data and test data to establish a three-dimensional rock mechanics parameter model.

[0048] In this embodiment, following the modeling approach of "hierarchical constraints, genetic control, and step-by-step modeling" for fracture-dissolution systems, a large strike-slip fracture stratigraphic framework is first established based on the strike-slip fracture pattern. Within this framework, an external contour model of the fracture-dissolution body is further constructed. Then, a classification and fusion model of large cavities, dissolution pores, and fracture zones within the contour is established. A combination of deterministic and stochastic modeling methods is applied to create a refined reservoir parameter model. This modeling fully utilizes the high vertical resolution of well logging data while incorporating seismic data as a second variable in the geological model simulation. In areas with well distribution, well data is used as the basis, while seismic information is also referenced. In areas without wells, seismic information is the primary reference for simulation calculations. This approach effectively utilizes well data while overcoming the challenge of controlling the structure and reservoir due to low drilling density, resulting in a more reliable geological model.

[0049] Step S3: Finite Element Analysis (FEA) is a widely used numerical computation method that uses mathematical approximations to simulate real physical systems. By dividing the entity under study into simple, interacting elements (i.e., units), the solution domain is considered to consist of many small, interconnected subdomains called finite elements. Each element shares nodes and interacts with others, forming a computational equation that can be solved globally. Under the constraints of boundary conditions, a suitable approximate solution is ultimately obtained for each element.

[0050] Step S31: (1) Determine the model range based on the geological structure distribution characteristics of the study area; (2) Define the grid size according to the research objectives and the characteristics of the geological structure and rock type distribution of the study area; (3) Create different rock materials and rock physical parameters based on experimental test data. Material modeling mainly includes two categories of materials. Intact rock mass: Define the elastic model and yield criterion. Each element must define Young's modulus, Poisson's ratio, internal friction angle, uniaxial compressive strength, tensile strength, thermal expansion coefficient, etc. Discontinuities: Include faults and fractures. Determine the stiffness, strength, and spacing of the wellbore through which they pass. (4) Determine the boundary conditions based on the regional tectonic environment and motion characteristics; (5) According to the boundary action characteristics, the strata first have gravity, and then a tectonic stress is added in the direction of the maximum / minimum horizontal stress. By adding force on the boundary, the force will be distributed throughout the model to form a stress field, thereby determining the load.

[0051] Step S32: Perform simulation calculations using a high-performance computer. A key step is assembling the elements into a global matrix equation for the entire discrete domain—that is, assembling the local matrices of the elements into a global matrix equation for the entire discrete domain. This process, called "assembly" or "integration," involves summing the contributions of each element into the global system matrix and load vector. Ultimately, this forms a joint system of equations that can be used to solve for unknowns in the entire structure, such as displacements and stresses. Assembly is performed at adjacent element nodes. The continuity of state variables and their derivatives (if possible) is established at the nodes. The system of equations can be solved using direct methods or iterative methods. The solution is an approximation of the state variables at the element nodes.

[0052] Step S33: Extract the planar distribution map of different geostress attributes for each stratum segment, as well as the well profile, analyze the distribution characteristics of different attributes in the plane and profile, combine the geological structure and rock physical characteristics, analyze the distribution characteristics of the geostress field, make a more accurate stress prediction, and extract the required geostress information.

[0053] Example 2

[0054] This study selected a 50km area in the Shunbei 43X well zone of the Shunbei 4 belt. 2 The scope of the study includes three-dimensional finite element geostress modeling, with the modeling stratigraphic layers ranging from the top of the Permian Acha Group to the bottom of the Ordovician Yingshan Formation (T5). 0 -T7 6 A total of 7 strata were involved in the modeling, with the faults ranging from the top of the Permian Acha Group to the bottom of the Ordovician Yingshan Formation (T5). 0 -T7 6Two sets of faults were identified. Based on the fault interpretation results of the Shunbei 43X well area, the fault interpretation data were processed, and the contact relationship between the strata and the faults was adjusted to establish a reasonable structural geological model. A three-dimensional finite element geomechanical mesh was established based on the three-dimensional geological model. The three-dimensional geomechanical parameters, including Young's modulus, Poisson's ratio, uniaxial compressive strength, tensile strength, and friction angle, were determined using seismic inversion results and one-dimensional geomechanical research findings. The three-dimensional stress was calculated through three-dimensional stress boundary fitting. The pore pressure coefficients of the Permian top-Carboniferous top range from 0.9 to 1.07 SG; the pore pressure coefficients of the Carboniferous top-Middle Devonian top range from 0.9 to 1.01 SG; the pore pressure coefficients of the Middle Devonian top-Lower Silurian top range from 0.92 to 1.02 SG; the pore pressure coefficients of the Lower Silurian top-Ordovician top range from 0.96 to 1.05 SG; the pore pressure coefficients of the Ordovician top-Yijianfang Formation top range from 1.05 to 1.1 SG; and the pore pressure coefficients of the Yijianfang Formation top-Yingshan Formation bottom range from 1.15 to 1.26 SG. Extracting the distribution maps of the maximum / minimum horizontal principal stress coefficients for each stratum reveals the following: The minimum horizontal principal stress coefficient for the Permian top-Carboniferous top ranges from 1.4 to 1.64 SG, while the maximum ranges from 1.85 to 2.15 SG; the minimum horizontal principal stress coefficient for the Carboniferous top-Middle Devonian top ranges from 1.42 to 1.68 SG, while the maximum ranges from 1.75 to 2.2 SG; the minimum horizontal principal stress coefficient for the Middle Devonian top-Lower Silurian top ranges from 1.58 to 1.66 SG, while the maximum ranges from... The minimum horizontal principal stress coefficients for the Lower Silurian-Ordovician top range from 1.54 to 1.7 SG, while the maximum range is 1.86 to 2.1 SG. For the Ordovician top-Yijianfang Formation top, the minimum horizontal principal stress coefficients range from 1.76 to 1.89 SG, while the maximum range is 2.0 to 2.23 SG. For the Yijianfang Formation top-Yingshan Formation bottom, the minimum horizontal principal stress coefficients range from 1.93 to 2.24 SG, while the maximum range is 2.19 to 2.59 SG. By combining various data sources, the magnitude and direction of the geostress were determined, and the overall consistency rate, based on drilling practice statistics, reached 86%.

[0055] The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, characterized in that, Includes the following steps: Step S1: Based on the data provided by the seismic data interpretation, a three-dimensional structural geological model is established using modeling methods; Step S2: Perform finite element meshing on the three-dimensional structural geological model to generate a triangular mesh finite element model, and establish a three-dimensional rock mechanics parameter model using pre-stack inversion data and test data; Step S3: Perform stress prediction using the finite element analysis method.

2. The prediction method according to claim 1, characterized in that, In step S1, the data includes fault data, bedding plane data, single-well geological stratification data, reservoir development characteristics, changes in stratigraphic thickness distribution under tectonic background, and contact relationships between sub-layers.

3. The prediction method according to claim 1, characterized in that, In step S1, the modeling method is an interactive modeling method combining corner mesh and construction frame methods.

4. The prediction method according to claim 1, characterized in that, In step S2, the specific steps for performing finite element mesh generation on the three-dimensional structural geological model are as follows: Based on fault data and bedding plane data, combined with well point geological stratification and intrusive rocks, the intersection relationships between faults and faults and between faults and bedding planes are processed to restore the true structural distribution. Appropriate mesh parameters are selected, and a high-quality triangulation is generated by adopting an improved triangulation method, following the "minimum angle maximum" and "empty sphere" criteria. The three-dimensional structural geological model is then meshed using a combination of node degree optimization and element angle optimization.

5. The prediction method according to claim 1, characterized in that, The specific steps of step S3 are as follows: Step S31: (1) Determine the model range based on the geological structure distribution characteristics; (2) Define the grid size based on the geological structure and rock type distribution characteristics; (3) Create different rock materials and rock physical parameters based on experimental test data; (4) Determine the boundary conditions based on the regional tectonic environment and motion characteristics; (5) Form a stress field according to the boundary action characteristics, thereby determining the load. Step S32: Perform simulation calculations to assemble the elements into a total matrix equation for the entire discrete domain. The solution to the total matrix equation is an approximate value of the state variables at the element nodes. Step S33: Extract the plane distribution map and well profile of different geostress attributes for each stratum, analyze the distribution characteristics of different attributes in the plane and profile, and combine the geological structure and rock physical characteristics to analyze the distribution characteristics of the geostress field and make stress prediction.

6. The prediction method according to claim 5, characterized in that, In step (1) of step S31, the rock material includes intact rock mass material and discontinuous rock mass material.

7. The prediction method according to claim 6, characterized in that, In step (1) of step S31, the physical parameters of the intact rock mass material include Young's modulus, Poisson's ratio, internal friction angle, uniaxial compressive strength, tensile strength and coefficient of thermal expansion.

8. The prediction method according to claim 6, characterized in that, In step (1) of step S31, the physical parameters of the discontinuous material include faults, cracks, stiffness, strength and spacing of the unit wellbore through which it passes.

9. The prediction method according to claim 5, characterized in that, In step (5) of step S31, the specific steps for forming a stress field according to the boundary action characteristics are as follows: According to the boundary action characteristics, firstly, the strata have gravity, then a tectonic stress is added in the direction of the maximum / minimum horizontal stress. By adding force on the boundary, the force will be distributed throughout the model to form a stress field.

10. The prediction method according to claim 5, characterized in that, In step S32, the solution to the total matrix equation can be obtained using either a direct method or an iterative method.

11. The application of the prediction method according to any one of claims 1-10 in the oil and gas exploration process.

12. The application according to claim 11, characterized in that, The oil and gas exploration process refers to the exploration process of ultra-deep fault-controlled fracture-vuggy carbonate reservoirs.

13. The application of the prediction method according to any one of claims 1-10 in the oil and gas development process.

14. The application according to claim 13, characterized in that, The oil and gas development process refers to the development process of ultra-deep fault-controlled fracture-vuggy carbonate reservoirs.

15. A computer-readable storage medium, characterized in that, It stores a computer program, which, when executed by a processor, implements the prediction method according to any one of claims 1-10.

16. A device for predicting three-dimensional geostress in ultra-deep fault-controlled fracture-vuggy carbonate reservoirs, characterized in that, It includes a storage medium and a processor, wherein the processor executes a computer program on the storage medium to implement the steps of the prediction method according to any one of claims 1-10.

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