Three-dimensional ground stress prediction method based on complex geological modeling and application thereof

Abstract

The invention discloses a three-dimensional ground stress prediction method based on complex geological modeling and application thereof, and relates to the technical field of oil exploration and development. The three-dimensional ground stress prediction method based on complex geological modeling comprises the following steps: establishing a geological geometric model and performing fine correction on the geological geometric model according to logging data; constructing a geological parameter model and establishing an enantiomer relationship between the geological parameter model and a geological geometric model, and further completing three-dimensional crustal stress prediction based on complex geological modeling by combining tectonic mechanics according to logging data iteration updating of a new drilling well; compared with the prior art, the method has the advantages that the three-dimensional crustal stress prediction of the complex sedimentary environment is realized, the three-dimensional crustal stress of the complex sedimentary environment is effectively predicted by means of data correction, specific mode modeling, data iteration and combination with tectonic mechanics, guidance is provided for drilling work, and the drilling efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of oil exploration and development, and mainly relates to a three-dimensional in-situ stress prediction method based on complex geological modeling and its application. Background Art

[0002] Geological stress prediction refers to the methods and techniques for predicting the distribution and variation of geological tectonic stresses on or inside the Earth's surface. This prediction is mainly based on the knowledge and principles of disciplines such as geology, geophysics, and rock mechanics, combined with technical means such as mathematical modeling and computer simulation.

[0003] The main purpose of geological stress prediction is to understand the stress state and variation trend of geological structures, so as to provide important guiding basis for fields such as geological engineering, seismic research, and mineral resource development. For example, in oil and gas exploitation, geological stress prediction can help evaluate the stability and safety of formations, optimize drilling and exploitation plans, and improve exploitation efficiency and safety.

[0004] With the improvement of computing power and the development of numerical simulation technology, people have begun to use numerical simulation methods for stress prediction. By establishing a detailed numerical model and simulating the mechanical behavior and deformation process of the formation, the stress state of the formation can be predicted more accurately. This method takes into account more geological details and boundary conditions and can more accurately reflect the actual situation of the formation. Numerical simulation has become one of the main methods for current stress prediction.

[0005] CN107121703A discloses a method for predicting the in-situ stress of a shale gas formation based on three-dimensional seismic data, belonging to the field of shale gas geophysical exploration. This method first performs pre-stack elastic parameter inversion on the shale gas formation using three-dimensional pre-stack seismic data and logging data to obtain the elastic parameters of the shale gas formation; then calculates the formation pressure using the seismic layer velocity obtained based on three-dimensional post-stack seismic data and stacking velocity data; then calculates the curvature of the shale gas formation and the tectonic strain in the horizontal direction based on three-dimensional post-stack seismic data and seismic horizon data; finally, according to the linear isotropic combined spring model, calculates the maximum horizontal principal stress, minimum horizontal principal stress, and horizontal stress difference of the shale gas formation using three-dimensional data volumes such as elastic parameters, formation pressure, and tectonic strain; however, this invention mainly focuses on the in-situ stress prediction of the shale gas formation using seismic data, and the accuracy of in-situ stress prediction for complex sedimentary environments is insufficient.

[0006] CN116227335A discloses a three-dimensional in-situ stress prediction method based on a physically constrained parallel neural network, including collecting borehole data in the target area and augmenting the borehole data; collecting logging data of the drilled wells in the target area, and obtaining the in-situ stress attribute data of each well by logging interpretation; constructing a physically constrained parallel neural network model; training the model and predicting the three-dimensional in-situ stress of the entity. The model of the present invention based on physical constraints + parallel neural network predicts in-situ stress only relying on three-dimensional spatial coordinates. Its essence is to make up for the lack of measured in-situ stress data. Starting from the three-dimensional spatial data derived from the terrain, using the strong fitting function of the neural network, combined with the constraints of the in-situ stress analysis model, predicting in-situ stress by the method of physical constraints + data-driven. This method not only integrates the relationship between the terrain structure and in-situ stress, but also effectively improves the accuracy and interpretability of the neural network model through the constraints of the mechanism model. However, due to the adoption of the parallel neural network algorithm in the algorithm provided by the present invention, its robustness is poor when dealing with complex and non-linear relationships; this means that when dealing with complex problems in practical applications, its performance is not stable enough and it is difficult to fully guide the actual work.

[0007] Therefore, how to improve the accuracy and efficiency of three-dimensional in-situ stress prediction in the face of complex tectonic environments in the area and complex intersection relationships between faults and between faults and horizons by improving the three-dimensional geological modeling mechanism, and provide a three-dimensional in-situ stress prediction method is of great significance for guiding the development of geological resources. Summary of the Invention

[0008] Aiming at the problem that the existing algorithms are difficult to effectively act on complex sedimentary environments and lack the prediction effectiveness in the face of complex tectonic environments in the area and complex intersection relationships between faults and between faults and horizons, the present invention provides a three-dimensional in-situ stress prediction method and its application based on complex geological modeling to effectively predict the three-dimensional in-situ stress in complex sedimentary environments and improve the drilling efficiency of actual geological resource development.

[0009] To achieve the above object, the technical solution adopted by the present invention is as follows:

[0010] A three-dimensional in-situ stress prediction method based on complex geological modeling includes the following steps:

[0011] S1. Establish a complex geological geometric model of the three-dimensional in-situ stress to be measured, perform fine processing, select grid parameters, and obtain the structural model of the target interval;

[0012] S2. Collect the single-well logging data of the complex geology of the three-dimensional in-situ stress to be measured, perform fine correction, and obtain the corrected data;

[0013] S3. Based on the calibration data and rock mechanical parameters obtained in step S2, a geological parameter model is established by modeling based on the target interval structural model obtained in step S1.

[0014] S4. According to the geological parameter model obtained in step S3, the average distribution of the geological parameters of the target interval structural model obtained in step S1 is extracted to obtain the relationship model between each geological parameter and the geometric model.

[0015] S5. By means of new drilling, steps S2 - S4 are carried out again or multiple times to obtain the average distribution of the geological parameters obtained in the new step S4, and then the relationship model between each geological parameter and the geometric model obtained in step S4 is iteratively updated to obtain a three-dimensional geological attribute parameter model.

[0016] S6. Based on the three-dimensional geological attribute parameter model obtained in step S5, combined with structural mechanics, a three-dimensional in-situ stress prediction model is obtained to carry out the three-dimensional in-situ stress prediction of the complex geological modeling.

[0017] Preferably, the objectives of the fine processing in step S1 include: processing the intersection relationships between faults and faults, faults and horizons, etc. in the geometric model to restore the complex geological true structural form of the three-dimensional in-situ stress to be measured.

[0018] Preferably, the lateral value of the grid parameters in step S1 is 20 - 30m * 20 - 30m, and the longitudinal value is 5 - 7m.

[0019] Preferably, the single-well logging data in step S2 includes the density body of pre-stack inversion data, the P-wave impedance body of pre-stack inversion data, and the S-wave impedance body of pre-stack inversion data.

[0020] Preferably, the objectives of the fine calibration in step S2 include: completing the correction and consistency processing of the density body of pre-stack inversion data, the P-wave impedance body of pre-stack inversion data, and the S-wave impedance body of pre-stack inversion data to eliminate singular values.

[0021] Preferably, the rock mechanical parameters in step S3 include: uniaxial compressive strength UCS, Young's modulus E, Poisson's ratio v, and internal friction angle.

[0022] Preferably, the modeling method in step S3 is: body constraint of inversion data volume, using the sequential Gaussian method, and adjusting the variogram.

[0023] Half of the variance of the difference between two points of the regionalized variable Z(x) and Z(x + h) is defined as the variogram of Z(x), and the specific calculation formula is as follows:

[0024]

[0025] where h is the lag distance and i is the sample number.

[0026] Preferably, the geological parameters in step S4 all include: the density body of pre-stack inversion data, the P-wave impedance body of pre-stack inversion data, the S-wave impedance body of pre-stack inversion data, the uniaxial compressive strength UCS, Young's modulus E, Poisson's ratio v, and internal friction angle.

[0027] Preferably, the method of combining structural mechanics in step S6 includes: establishing a geomechanical grid, and mapping the three-dimensional geological attribute parameters obtained in step S5 to the geomechanical grid.

[0028] Preferably, the three-dimensional in-situ stress prediction model in step S6 can estimate the stress field of the structure, including the curvature tensor, deformation tensor, and stress field tensor of the formation, so as to obtain the principal curvature, principal strain, and principal stress; and can simulate the maximum principal stress model and minimum principal stress model according to the tectonic stress field, as well as the overburden pressure model, rock tensile strength model, formation pore pressure model, Young's modulus model, Poisson's ratio model, uniaxial compressive strength model, and internal friction angle model.

[0029] The present invention also provides an application of the three-dimensional in-situ stress prediction method using the above complex geological modeling in drilling.

[0030] The drilling includes the following steps:

[0031] According to the three-dimensional in-situ stress prediction method of the complex geological modeling, calculate the collapse pressure model, fracture pressure model, and leakage pressure model, and predict the collapse pressure, fracture pressure, and leakage pressure, so as to provide a basis for the design of the new well trajectory, drilling risk, and completion method.

[0032] Preferably, the calculation method of the collapse pressure model is:

[0033]

[0034] In the formula: B p is the formation collapse pressure, MPa; σ H , σ h are the maximum and minimum horizontal principal stresses, MPa; K = tan -1 (π / 4 - φ / 2), φ is the internal friction angle, generally taking π / 6; τ is the rock cohesion, MPa; α is the Biot elastic coefficient, dimensionless; p p is the pore pressure of the formation, MPa; η is the stress nonlinear correction coefficient, dimensionless. The key to calculating the formation collapse pressure is to accurately obtain parameters such as α, p p , σ H , σ h , τ, φ, η, etc. using well logging data;

[0035] The calculation method of the fracture pressure model is: p f = 3σ h - σ H - p p + S t , when S t = 0, it is the natural fracture pressure p f0 = p m = 3σ h - σ H - αp p ;

[0036] In the above formula, except that p f is the fracture pressure and S t is the rock tensile strength, the meanings of the other variables are the same as those in the collapse pressure model;

[0037] The calculation method of the leakage pressure model is: for faults and fractures in a closed state under formation conditions, when the density of drilling mud is too high, the pore pressure of the faults and fracture faces passing through the well increases, which will cause a decrease in effective stress, and may thus lead to the sliding of faults and micro-displacements of fractures, making the faults and fractures permeable and resulting in leakage. Jaeger and Cook pointed out that when the critical direction fault is at the friction limit, the following formula is satisfied:

[0038]

[0039] In the above formula, P p = (3.1S 3 - S 1 ) / 2.1;

[0040] σ h is the maximum horizontal principal stress, σ H is the minimum horizontal principal stress, S 1 and S 3 are respectively the same as the values of σ h and σ H . When μ takes a constant value, the critical pressure P p passing through the formation well fault and fracture surface can be calculated, and P p is the drilling leakage pressure.

[0041] Compared with the prior art, the present invention has the following beneficial effects:

[0042] The present invention realizes the three-dimensional in-situ stress prediction for complex sedimentary environments. By means of data correction, specific modeling methods, data iteration, and combining with tectonic mechanics, it effectively predicts the three-dimensional in-situ stress in complex sedimentary environments, provides guidance for drilling operations, and improves drilling efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 This is a flowchart of the three-dimensional in-situ stress prediction method for complex geological modeling in the embodiments of the present invention. Specific implementation mode

[0044] Embodiment A three-dimensional in-situ stress prediction method for complex geological modeling

[0045] S1. Establish a complex geological geometric model of the three-dimensional in-situ stress to be measured, and focus on processing the intersection relationships between faults and faults, faults and horizons, etc. in the geometric model to restore the true structural form of the complex geology of the three-dimensional in-situ stress to be measured; select appropriate grid parameters, with a horizontal value of 25m * 25m and a longitudinal value of 5 - 7m for the target layer, and design the research accuracy according to the computer configuration to complete the establishment of the structural, lithofacies, and fracture structure models;

[0046] S2. Fine-correct the pre-stack inversion data density body, the pre-stack inversion data P-wave impedance body, and the pre-stack inversion data S-wave impedance body in the single-well logging data, especially the data near the faults, to eliminate singular values and lay a solid foundation for structural modeling and attribute modeling;

[0047] S3. Based on the single-well logging data and the analysis results of rock mechanics parameters such as uniaxial compressive strength UCS, Young's modulus E, Poisson's ratio v, and internal friction angle, through the constraints of the structural model and the inversion data volume, use the sequential Gaussian method to establish the geological parameter models required for the three-dimensional in-situ stress model by adjusting the variogram;

[0048] S4. Extract the model parameters of the target layer section using the geological parameter model, form the average value distribution maps of each parameter for the plane feature analysis of the target layer, and complete the attribute models of density, P-wave impedance, S-wave impedance, uniaxial compressive strength UCS, Young's modulus E, Poisson's ratio v, and internal friction angle;

[0049] S5. Based on the current attribute modeling methods, combine the geological parameters of density, P-wave impedance, and S-wave impedance of the newly drilled wells to complete the iterative update of the geological model and the attribute model of rock mechanics parameters, and obtain a more accurate three-dimensional geological attribute parameter model;

[0050] S6. Starting from structural mechanics, use the geometric information and rock mechanics parameters of the structural model to estimate the stress field of the structure, including the curvature tensor, deformation tensor, and stress field tensor of the formation, so as to obtain the principal curvature, principal strain, and principal stress, and the maximum principal stress model and minimum principal stress model can be simulated according to the structural stress field, as well as the overburden pressure model, rock tensile strength model, formation pore pressure model, Young's modulus model, Poisson's ratio model, uniaxial compressive strength model, and internal friction angle model;

[0051] According to the model obtained in S6 above, finally, the collapse pressure model, fracture pressure model, and leakage pressure model are calculated, and the collapse pressure, fracture pressure, and leakage pressure are predicted, providing a basis for the new well trajectory design, drilling risk, and completion method, as well as for drilling risk and completion method, etc.;

[0052] The calculation method of the collapse pressure model is as follows:

[0053]

[0054] In the formula: B p is the formation collapse pressure, MPa; σ H , σ h are the maximum and minimum horizontal principal stresses, MPa respectively; K = tan -1 (π / 4 - φ / 2), where φ is the internal friction angle, generally taken as π / 6; τ is the rock cohesion, MPa; α is the Biot elastic coefficient, dimensionless; p p is the pore pressure of the formation, MPa; η is the stress nonlinear correction coefficient, dimensionless. The key to calculating the formation collapse pressure is to accurately obtain parameters such as α, p p , σ H , σ h , τ, φ, η, etc. using well logging data;

[0055] The calculation method of the fracture pressure model is: p f = 3σ h - σ H - p p + S t , when S t = 0, it is the natural fracture pressure p f0 = p m = 3σ h - σ H - αp p ;

[0056] In the above formula, except that p f is the fracture pressure and S t is the rock tensile strength, the meanings of the remaining variables are the same as those in the collapse pressure model;

[0057] The calculation method of the leakage pressure model is as follows: For faults and fractures in a closed state under formation conditions, when the density of drilling mud is too high, the pore pressure of the fault and fracture faces passing through the well increases, which will cause a decrease in effective stress, and may thus lead to the sliding of the fault and the occurrence of micro-displacements in the fractures, making the fault and fracture permeable and resulting in leakage. Jaeger and Cook pointed out that when the critical direction fault is at the friction limit, the following formula is satisfied:

[0058]

[0059] In the above formula, P p =(3.1S 3 -S 1 ) / 2.1;

[0060] σ h is the maximum horizontal principal stress, σ H is the minimum horizontal principal stress, S 1 and S 3 are respectively consistent with the values of σ h and σ H When μ takes a constant value, the critical pressure P p passing through the formation cross-well faults and fracture surfaces can be calculated, and P p is the drilling fluid loss pressure.

[0061] The above embodiments have been applied to actual engineering:

[0062] The applied area is: Shunbei No. 8 Zone;

[0063] The geology is: ultra-deep carbonate reservoir;

[0064] The problems that occurred are: during the drilling process of the Shunbei area formation, fracture zones were encountered, severe fluid loss occurred in some well sections, wellbore instability occurred frequently, the drillability of the formation was poor, the existing speed-up technology had poor effects, the bit was severely cored after coming out of the well, and the drilling cycle was long;

[0065] The effects after application: The coincidence rate of formation pressure and pore pressure prediction in the Shunbei area increased from 45% to 85%. This technology was applied in the new well deployment in Shunbei No. 4 Zone, No. 6 Zone, No. 8 Zone, as well as the main block and peripheral blocks of Tahe. The drilling cycle in the Shunbei area was controlled within about 150 days, effectively promoting the integrated geological and engineering work such as well location optimization, well trajectory optimization, and drilling engineering design.

[0066] Finally, it should be noted that the above content is only used to illustrate the technical solution of the present invention, rather than a limitation on the protection scope of the present invention. Any simple modification or equivalent replacement of the technical solution of the present invention by those of ordinary skill in the art does not depart from the essence and scope of the technical solution of the present invention.

Claims

1. A three-dimensional in-situ stress prediction method for complex geological modeling, characterized in that, it includes the following steps: S1. Establish a complex geological geometric model of the three-dimensional in-situ stress to be measured, perform fine processing, select grid parameters, and obtain a structural model of the target interval; S2. Collect single-well logging data of the complex geology of the three-dimensional in-situ stress to be measured, perform fine correction, and obtain corrected data; S3. Based on the corrected data and rock mechanics parameters obtained in step S2, and based on the structural model of the target interval obtained in step S1, build a geological parameter model; S4. According to the geological parameter model obtained in step S3, extract the average distribution of the geological parameters of the structural model of the target interval obtained in step S1, and obtain a relationship model between each geological parameter and the geometric model; S5. By means of new drilling, repeat step S2 - S4 once or multiple times to obtain the average distribution of the geological parameters obtained in the new step S4, and then iteratively update the relationship model between each geological parameter and the geometric model obtained in step S4; Obtain a three-dimensional geological attribute parameter model; S6. On the basis of the three-dimensional geological attribute parameter model obtained in step S5, combined with structural mechanics, obtain a three-dimensional in-situ stress prediction model to perform three-dimensional in-situ stress prediction for the complex geological modeling.

2. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the objectives of the fine processing in step S1 include: processing the intersection relationships between faults and faults, faults and horizons, etc. in the geometric model to restore the true structural form of the complex geology of the three-dimensional in-situ stress to be measured.

3. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the horizontal value of the grid parameters in step S1 is 20 - 30m * 20 - 30m, and the vertical value is 5 - 7m.

4. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the single-well logging data in step S2 includes the density body of pre-stack inversion data, the longitudinal wave impedance body of pre-stack inversion data, and the shear wave impedance body of pre-stack inversion data.

5. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the objectives of the fine correction in step S2 include: completing the correction and consistency processing of the density body of pre-stack inversion data, the longitudinal wave impedance body of pre-stack inversion data, and the shear wave impedance body of pre-stack inversion data to eliminate singular values.

6. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the rock mechanics parameters in step S3 include: uniaxial compressive strength, Young's modulus, Poisson's ratio, and internal friction angle.

7. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the method of modeling in step S3 is: body constraint of inversion data volume, using the sequential Gaussian method, and adjusting the variogram; Half of the variance of the difference between two points of the regionalized variable Z(x) and Z(x + h) is defined as the variogram of Z(x), and the specific calculation formula is as follows: where h is the lag distance and i is the sample number.

8. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the geological parameters in step S4 all include: the density body of pre-stack inversion data, the longitudinal wave impedance body of pre-stack inversion data, the shear wave impedance body of pre-stack inversion data, uniaxial compressive strength, Young's modulus, Poisson's ratio, and internal friction angle.

9. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the method of combining structural mechanics in step S6 includes: establishing a geomechanics grid, and mapping the three-dimensional geological attribute parameter model obtained in step S5 to the geomechanics grid.

10. The three-dimensional in-situ stress prediction method for complex geological modeling according to claim 1, characterized in that, the three-dimensional in-situ stress prediction model in step S6 can estimate the stress field of the structure, including the curvature tensor, deformation tensor, and stress field tensor of the formation, so as to obtain the principal curvature, principal strain, and principal stress; and can simulate the maximum principal stress model and the minimum principal stress model according to the tectonic stress field, as well as the overburden pressure model, rock tensile strength model, formation pore pressure model, Young's modulus model, Poisson's ratio model, uniaxial compressive strength model, and internal friction angle model.

11. Application of the three-dimensional in-situ stress prediction method for complex geological modeling according to any one of claims 1-10 in drilling.

12. The application according to claim 11, characterized in that, the drilling includes the following steps: According to the three-dimensional in-situ stress prediction method for complex geological modeling, calculate the collapse pressure model, fracture pressure model, and leakage pressure model, and predict the collapse pressure, fracture pressure, and leakage pressure, so as to provide a basis for the design of the new well trajectory, drilling risks, and completion methods.

13. The application according to claim 12, characterized in that, the calculation method of the collapse pressure model is: Where: B p is the formation collapse pressure, MPa; σ H , σ h are the maximum and minimum horizontal principal stresses, MPa respectively; K = tan -1 (π / 4 - φ / 2), where φ is the angle of internal friction, generally taken as π / 6; τ is the cohesive force of the rock, MPa; α is the Biot elastic coefficient, dimensionless; p p is the pore pressure of the formation, MPa; η is the stress nonlinear correction coefficient, dimensionless.

14. The application according to claim 13, characterized in that, the calculation method of the fracture pressure model is: p f = 3σ h -σ H -p p +S t ; When S t = 0, it is the natural fracture pressure p f0 = p m = 3σ h - σ H - αp p ; In the above two equations, except for p f being the fracture pressure and S t being the tensile strength of the rock, the meanings of the remaining variables are the same as those in the collapse pressure model.

15. The application according to claim 14, characterized in that, the calculation method of the leakage pressure model is: At the critical friction limit, the following formula is satisfied: In the above formula, P p = (3.1S 3 - S 1 ) / 2.1; σ h is the maximum horizontal principal stress, σ H is the minimum horizontal principal stress, S 1 and S 3 are respectively consistent with the values of σ h and σ H When μ takes a constant value, the critical pressure P p passing through the formation cross-well faults and fracture surfaces can be calculated, and P p is the drilling fluid loss pressure.

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