A shale oil well wall collapse pressure prediction method

Abstract

This invention relates to a method for predicting shale oil wellbore collapse pressure. The steps include: obtaining the composition, structure, and physicochemical properties of the shale oil reservoir; conducting immersion-NMR-sonic-triaxial stress measurement experiments with different drilling fluid systems; constructing equations for heterogeneous water absorption and strength degradation of the shale oil reservoir rock; establishing geostress and pore pressure profiles; converting far-field stress to the wellbore and bedding coordinate systems; calculating the wellbore stress field generated by water absorption in the surrounding rock; simulating and calculating the temperature field distribution of the rock and calculating thermal stress values; superimposing and calculating the wellbore stress values ​​under the coupled effects of force, chemistry, heat, and bedding; constructing the discriminant function and conditions for shear failure of the surrounding rock matrix and weak surfaces; constructing an iterative algorithm for numerical simulation of shale oil reservoir collapse pressure; determining the density control factors and mechanisms of formation collapse pressure; and reducing the risk of shale oil wellbore collapse through optimization. This invention can more accurately predict shale oil wellbore collapse pressure under the coupled effects of force, chemistry, heat, and bedding.

Description

Technical Field

[0001] This invention relates to the field of shale oil safe drilling technology, and more specifically, to a method for predicting shale oil wellbore collapse pressure. Background Technology

[0002] In recent years, my country has discovered substantial shale oil reserves, primarily formed in organic-rich mudstone and shale formations within continental lacustrine basins, where reservoir geology is quite complex. Shale often contains clay minerals such as illite, illite-montmorillonite mixed layers, and montmorillonite, and also exhibits weak structural surfaces like bedding planes. Drilling fluids easily penetrate the formation, engaging in mechanical and chemical reactions with the wellbore, leading to a redistribution of wellbore stress and deterioration of rock strength. This frequently induces wellbore collapses during drilling, significantly increasing drilling time and costs, and hindering exploration and development.

[0003] Traditional collapse pressure studies often assume the formation is a continuous isotropic medium, resulting in a relative lack of systematic research on shale oil reservoirs that are hard, brittle, heterogeneous, and have well-developed bedding. For example, Chinese invention patent CN104806233A discloses a method for predicting the equivalent density window of collapse pressure in weak-plane formations. This method proposes the division of the wellbore into tight and fractured sections, and the testing of the mechanical strength of the rock matrix and fracture surfaces. Based on this, it conducts near-wellbore pore pressure and stress analysis using a fluid-structure interaction mean model, and determines the wellbore failure state and collapse pressure using strength criteria. Chinese invention patent CN113356843A discloses another method for predicting the equivalent density window of collapse pressure in weak-plane formations. This method collects formation isotropic pressure parameters and obtains formation rock constitutive parameters. Based on this, it combines the geostress state and wellbore stress model to achieve wellbore stability analysis under the coupling and synergy of multi-physics fields in mean formations, thereby assisting in the optimization of drilling parameters in oilfield operations. Chinese invention patent CN114526058A discloses a method and system for designing drilling collapse pressure. This method collects information on the target formation drilling type and wellbore circumference integrity, and obtains wellbore stress characteristics at different azimuths based on geostress information. Based on this, it statistically analyzes the proportion of the minimum safe wellbore area to the wellbore circumference during safe drilling operations, thereby calculating the drilling collapse pressure from the collapse pressure equivalent density, achieving the goal of reducing drilling fluid density and increasing safe drilling speed. Chinese invention patent CN113095593A provides a method, device, and equipment for determining drilling wellbore condition. It collects relevant data such as formation pressure, wellbore pressure, and drilling engineering parameters of the drilled section, and uses an intelligent learning algorithm to evaluate the wellbore condition of the drilled section, improving the reliability of the evaluation. Based on this, it predicts the wellbore condition evaluation parameters and risk prediction results for the un-drilled section below the drilled section. Chinese invention patent CN114547906A discloses a wellbore stability logging interpretation method for deep formations containing weak structural planes. By collecting logging data and actual drilling and completion data, it establishes formation pressure and stress profiles and determines the azimuth of the maximum horizontal principal stress, bedding dip angle, and strike. Based on this, a three-pressure profile is drawn. This method, based on conventional logging methods, considers the influence of bedding structural planes, improving prediction accuracy and effectively guiding safe and efficient drilling in deep and complex formations. Chinese invention patent CN111980667 discloses a quantitative evaluation method for the influence of anisotropy on shale wellbore collapse pressure. It obtains target well area stress parameters, bedding attitude, wellbore trajectory, and formation pressure in a known geodetic coordinate system, and measures the rock mechanical parameters of the rock body and fracture surfaces. Using coordinate transformation, the principal stresses are transferred to the wellbore perimeter and bedding planes. Combining the MC, MGC, ML, and MWC strength criteria, the critical collapse pressure at the wellbore perimeter is obtained using the MATLAB Newton iteration method.

[0004] In reality, wellbore collapse in shale oil reservoirs is a multi-factor coupled problem throughout the entire drilling cycle. Due to the low temperature of the drilling fluid in the wellbore, the shale oil reservoir undergoes heat transfer and temperature changes to the wellbore. Thermal stress leads to changes in the near-wellbore stress field. At the same time, capillary forces, the crystal structure of clay minerals, the difference in salinity between drilling fluid and formation fluid, and the pressure difference between bottom hole pressure and formation pressure can induce adsorption, hydration, diffusion, and permeation during shale oil drilling. This leads to changes in wellbore stress, formation fluid pressure, and rock strength. In addition, the bedding structure controls the direction of water absorption and seepage and the rate of strength degradation, which exacerbates wellbore collapse.

[0005] Therefore, existing technologies need to be improved. Summary of the Invention

[0006] This invention addresses the shortcomings of existing shale oil wellbore collapse pressure prediction technologies by proposing a new method for predicting shale oil wellbore collapse pressure. This method can more accurately predict shale oil wellbore collapse pressure under the coupled effects of force, chemistry, heat, and stratification, thus ensuring efficient and safe shale oil drilling.

[0007] The technical solution adopted in this invention is as follows:

[0008] According to one aspect of the present invention, a method for predicting shale oil wellbore collapse pressure is provided, comprising the following steps:

[0009] S1: Obtain the composition, structure, and physicochemical properties of shale oil reservoirs;

[0010] S2: Conduct immersion-nuclear magnetic resonance-acoustic wave-triaxial stress measurement experiments with different drilling fluid systems to dynamically evaluate the various properties of shale oil reservoir rocks and drilling fluids under the coupling effect of different bedding directions;

[0011] S3: Construct equations for water saturation in heterogeneous shale oil reservoir rocks, equations for the relationship between expansion strain and water content, and equations for rock strength degradation.

[0012] S4: Establish profiles of vertical stress, maximum horizontal stress, minimum horizontal stress, and pore pressure;

[0013] S5: Using coordinate transformation relationships, transform the far-field stress into the borehole coordinate system and the bedding coordinate system, and calculate the peri-well stress induced by the far-field stress as well as the normal stress and shear stress on the bedding surface.

[0014] S6: Calculate the water absorption and shale expansion strain at different spatial locations of shale oil reservoirs at different drilling times, and calculate the wellbore stress field caused by water absorption in the surrounding rock in combination with the surrounding rock equilibrium state equation and boundary conditions;

[0015] S7: Simulate and calculate the temperature field distribution of the wellbore rock under drilling fluid circulation conditions, and calculate the thermal stress value;

[0016] S8: Overlay calculation of wellbore stress values ​​under the coupled effects of force, chemical, thermal and stratification;

[0017] S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion, and weak surface strength criterion, construct the discriminant function and discriminant condition for the shear failure of the surrounding rock matrix and weak surface;

[0018] S10: Substitute the wellbore stress and rock mechanics parameters under the coupled action of force-chemical-thermal-stratification into the discriminant function and discriminant condition of the wellbore matrix and weak surface shear failure of the surrounding rock matrix, and construct a numerical simulation iterative test algorithm for shale oil reservoir collapse pressure under different wellbore trajectories and fluid absorption times;

[0019] S11: Calculate the wellbore collapse pressure of shale oil reservoirs under different well inclination angles, azimuth angles, structural planes, drilling fluid systems and action times, and obtain the influence of each factor on the wellbore collapse pressure of shale oil reservoirs. Then, determine the formation collapse pressure density control factors and control mechanisms.

[0020] S12: Reduce the risk of shale oil wellbore collapse by optimizing drilling fluid systems, wellbore trajectories, and drilling process parameters.

[0021] In one embodiment of the present invention, in S1, the composition, structure, and physicochemical properties of the shale oil reservoir are obtained by conducting XRD diffraction experiments, macroscopic, mesoscopic, and microscopic structural characteristic experiments, wettability experiments, and permeability anisotropy experiments; and S1 includes the following steps:

[0022] A1: Conduct XRD diffraction experiments to analyze the whole-rock mineral composition and clay mineral composition of shale oil reservoirs;

[0023] A2: Conduct thin section analysis, scanning electron microscopy, and high-pressure mercury intrusion experiments to analyze the macroscopic, mesoscopic, and microscopic structural characteristics of shale oil, providing a basis for the selection of plugging agent formulations during drilling;

[0024] A3: Conduct wettability tests and use the baseline circle method to determine the wetting angle of a drilling fluid system composed of water, kerosene, hydrophobic agent, and plugging agent, so as to provide a basis for the selection of drilling fluid systems;

[0025] A4: Conduct water absorption and diffusion experiments in the direction parallel to and perpendicular to bedding to obtain the anisotropic characteristics of the water absorption and diffusion coefficient, and establish a water absorption and diffusion model and numerical simulation method for shale oil reservoirs with significant bedding characteristics.

[0026] In one embodiment of the present invention, the water absorption and diffusion model of a shale oil reservoir with significant bedding characteristics in A4 is shown in the following equation:

[0027]

[0028] in:

[0029]

[0030] Initial boundary conditions:

[0031]

[0032] In the formula, C ij eff is the equivalent water absorption diffusion coefficient tensor; w a w0 is the saturated water content at the wellbore; w0 is the water content in the original formation.

[0033] In one embodiment of the present invention, in S2, various characteristics include dynamic water absorption characteristics, dynamic change characteristics of T2 spectrum, and dynamic and static mechanical parameter change characteristics; and S2 includes the following steps:

[0034] B1: Shale oil reservoir cores were immersed in different drilling fluid systems, and the longitudinal and transverse wave velocity curves of the rocks were measured at multiple time points. The dynamic mechanical parameters of the rocks after immersion in different drilling fluids were calculated.

[0035] B2: Measure the nuclear magnetic resonance characteristics of the core at multiple time points to obtain the relaxation time and amplitude variation characteristics, evaluate the dynamic water absorption characteristics of shale oil reservoirs and the variation law of pore size and pore volume, and establish a dynamic water absorption equation;

[0036] B3: Select multiple core samples at some of the multiple time points, conduct triaxial stress tests under different confining pressures, obtain the full stress-strain relationship curves, and calculate the compressive strength, elastic modulus, and Poisson's ratio;

[0037] B4: At the specified time points, based on the triaxial stress test results of each rock type, plot the ultimate Mohr stress circle and strength envelope of each rock core at each time point, and calculate the cohesion and internal friction angle.

[0038] In one embodiment of the present invention, in S3, a corresponding equation is constructed based on the controlling effect of shale bedding planes on the direction of water absorption dominance; and S3 includes the following steps:

[0039] C1: Based on the experimental results of B1 and B2, establish the relationship equation between rock dynamic parameters and water absorption;

[0040] C2: Based on the experimental results of B1, B3 and B4, establish the relationship equation between static parameters and dynamic parameters;

[0041] C3: Construct equations relating static elastic modulus, static Poisson's ratio, cohesion, and internal friction angle to water absorption.

[0042] In one embodiment of the present invention, in S4, vertical stress, maximum horizontal stress, minimum horizontal stress, and pore pressure profiles are established based on well logging data, mine field data, and laboratory experimental data; and S4 includes the following steps:

[0043] D1: Vertical stress is calculated by accumulating or integrating segments using density logging data, or by calculating static stress gradient, or by combining both methods.

[0044] D2: The maximum and minimum horizontal geostresses are obtained through indoor core experiments combining paleomagnetism, Kaiser effect, differential strain and wave velocity anisotropy, or through inversion using field data from wellbore collapse method and micro-fracture experiments.

[0045] D3: Based on logging data or sonic transit time logging data, pore pressure is estimated using the sonic transit time method and the DC exponent method.

[0046] In one embodiment of the present invention, in step S5, based on the shale oil reservoir stress direction, wellbore direction, and bedding strike, a transformation is performed using the geodetic coordinate system as an intermediate transformation value and coordinate transformation relationships are utilized; and step S5 includes the following steps:

[0047] E1: Based on the geostress direction of the shale oil reservoir and the wellbore direction, the geostress is transformed into the wellbore coordinate system using coordinate transformation relationships;

[0048] E2: After obtaining the wellbore stress tensor using the magnitude and direction of geostress, the wellbore stress distribution state is transformed to the weak surface of the bedding.

[0049] In one embodiment of the present invention, in E1, the expression for the far-field stress is:

[0050]

[0051] in

[0052]

[0053] Where: σ H ,σ h ,σ v These are the maximum horizontal ground stress, minimum horizontal ground stress, and vertical stress, respectively, in MPa; These are the stress components of in-situ stress acting on the surrounding rock of the wellbore, in MPa; α b It is the well inclination azimuth; β b It is the well inclination angle;

[0054] In E2, the expression for the weak surface stress is:

[0055]

[0056] in:

[0057]

[0058] In the formula: θ is the well perimeter angle.

[0059] In one embodiment of the present invention, in S6, the relationship between the water absorption swelling strain and the water content is as follows:

[0060]

[0061] Wellbore stress distribution after hydration:

[0062]

[0063] In the formula, ε v ε h These represent the vertical and horizontal strains, respectively; Δω is the rate of change of water content; ε rr ε θθ ε zz These are the radial, circumferential, and axial strain components of the mudstone and shale at the well site under hydration; σ r σ θ σ z These are the radial, circumferential, and axial stress components of the mudstone and shale at the well site under hydration, in MPa; E is the rock elastic modulus; and υ is the rock Poisson's ratio.

[0064] In one embodiment of the present invention, S7 includes the following steps:

[0065] F1: Based on the heat exchange between drilling fluid in the drill string, drill string, annular drilling fluid, and formation, the temperature field distribution of the rock around the well is simulated and calculated under drilling fluid circulation conditions.

[0066] F2: Calculate the corresponding additional thermal stress on the well wall based on the temperature field distribution of the surrounding rocks.

[0067] In one embodiment of the present invention, the temperature field distribution of the surrounding rock is as follows:

[0068]

[0069] Where: σ rT σ θT σ zT These are the radial, circumferential, and axial thermal stresses caused by temperature differences, respectively, in MPa; α T υ is the coefficient of thermal expansion of rock, 1 / ℃; E is the elastic modulus of rock, MPa; υ is the Poisson's ratio of rock; T fIt is the temperature difference in the formation, in °C; r w It is the wellbore radius, in meters (m).

[0070] In one embodiment of the present invention, in S8, based on the stress components generated by in-situ stress, drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, the wellbore stress value under the coupling effect of force-chemical-thermal-stratification is calculated using the superposition principle; and S8 includes the following steps:

[0071] G1: Assuming the rock is a small-deformation elastic body, calculate the wellbore stress components induced by vertical stress, maximum horizontal stress, and minimum horizontal stress respectively, and superimpose them as static values ​​of wellbore stress.

[0072] G2: Based on the contact time between the shale reservoir and the drilling fluid, analyze the wellbore stress components generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, and use them as dynamic values ​​of wellbore stress for superposition calculation.

[0073] G3: The static and dynamic values ​​of wellbore stress are superimposed to obtain the total wellbore stress value under different contact times between shale oil reservoir and drilling fluid under the coupling effect of force-chemical-thermal-stratification.

[0074] In one embodiment of the present invention, S9 includes the following steps:

[0075] H1: Using the MC strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0076]

[0077] H2: Using the DP strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0078]

[0079] H3: Using the MG-C strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0080]

[0081] H4: Using the modified Lade strength criterion, the shear failure function within the shale layer is constructed as follows:

[0082]

[0083] H5: Using the weak surface strength criterion, the shear failure function within the shale layer is constructed as follows:

[0084]

[0085] H6: When f iWhen at least one of (i = 1, 2, 3, 4, 5) is less than 0, it is determined that the surrounding rock of the well wall has undergone shear failure and the well wall is in a state of collapse and instability; when f i When both f are equal to 0, the surrounding rock of the wellbore is judged to be in a critical state of shear failure, and the wellbore stability is in a critical state; when f i When all values ​​are greater than 0, it is determined that the surrounding rock of the well wall does not undergo shear failure and the well wall is in a stable state.

[0086] In the formula, σ is the internal friction angle of the matrix, σ1 is the first principal stress, σ2 is the second principal stress, σ3 is the third principal stress, k is the permeability, and α is the thermal expansion coefficient of the rock. It is the internal friction angle of the weak surface. It is the principal stress on the weak surface. C is the shear strength of the weak surface, and C is the cohesion. It is the cohesive force of the weak surface, η is the material constant, and a, b, and S are all constants.

[0087] In one embodiment of the present invention, S10 includes the following steps:

[0088] I1: Given a drilling fluid density, calculate the wellbore stress and rock mechanics parameters under the coupled effects of mechanical-chemical-thermal-stratification processes. Substitute these parameters with the discriminant functions and criteria for shear failure of the surrounding rock matrix and weak surfaces to calculate f. i ;

[0089] I2: If f i When at least one of the components is less than -5%, the drilling fluid density is 0.01 g / cm³. 3 Increase, recalculate f i If f i When all values ​​are greater than 5%, the drilling fluid density is 0.01 g / cm³. 3 Reduce, recalculate f i If -5% ≤ all f i When the content is ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density;

[0090] I3: Iterative calculation to obtain the range of equivalent density of collapse pressure.

[0091] In one embodiment of the present invention, S11 includes the following steps:

[0092] J1: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs under different bedding planes and physicochemical properties to obtain the influence of geological factors on collapse stress;

[0093] J2: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs under different inclination and azimuth angles to obtain the influence of wellbore trajectory factors on collapse stress;

[0094] J3: Calculate the wellbore collapse pressure of shale oil reservoirs under different drilling fluid systems and action times to obtain the influence of drilling fluid properties on the collapse cycle;

[0095] J4: Integrating geological and engineering factors, determine the factors and mechanisms controlling shale oil reservoir collapse pressure.

[0096] In one embodiment of the present invention, S12 includes the following steps:

[0097] K1: Adding plugging and hydrophobic agents adjusts the drilling fluid system, increases the tightness of the wellbore, increases the contact angle of the drilling fluid on the rock surface, reduces the free energy of the clay mineral surface, and prevents and reduces the entry of drilling fluid.

[0098] K2: Optimize the wellbore trajectory, rationally select the direction point and the orientation of directional and horizontal well sections, and avoid the wellbore orientation coinciding with the orientation of maximum geostress to reduce the risk of wellbore instability.

[0099] By adopting the above technical solution, the present invention has at least the following beneficial effects:

[0100] This invention realizes a method for predicting shale oil wellbore collapse pressure considering the combined effects of factors such as formation temperature, bedding and matrix rock water absorption heterogeneity, bedding matrix rock strength degradation, and rock expansion due to differences in water absorption and water content. Attached Figure Description

[0101] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0102] Figure 1 A flowchart of a shale oil wellbore collapse pressure prediction method provided by the present invention is shown;

[0103] Figure 2 The multi-scale structural features of shale oil reservoirs in embodiments of the present invention are shown.

[0104] Figure 3 Figures (a) and (b) show the simulation results of water absorption and diffusion in the structure inside the layer in an embodiment of the present invention;

[0105] Figure 4 Figures (a) and (b) show the Mohr circles and envelopes of shale oil reservoir rocks after soaking for 0 h and 24 h, respectively, in embodiments of the present invention.

[0106] Figure 5 Figures (a) and (b) show the transformation between the geostress coordinate system and the wellbore coordinate system in an embodiment of the present invention, respectively;

[0107] Figure 6 The simulation results of temperature field at different cycle times in embodiments of the present invention are shown;

[0108] Figure 7 The iterative calculation process for shale oil reservoir collapse pressure in an embodiment of the present invention is shown;

[0109] Figure 8 A graph showing the effect of shale oil reservoir bedding angle on collapse pressure in an embodiment of the present invention is shown;

[0110] Figure 9 A diagram showing the effect of well inclination angle on collapse pressure in an embodiment of the present invention is shown;

[0111] Figure 10 A graph showing the effect of the contact time between the shale oil reservoir and the drilling fluid on the collapse pressure in an embodiment of the present invention is shown. Detailed Implementation

[0112] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below with reference to specific examples and the accompanying drawings.

[0113] like Figure 1 As shown, a method for predicting shale oil wellbore collapse pressure according to the present invention includes the following steps:

[0114] S1: Conduct XRD diffraction experiments, macroscopic, mesoscopic, and microscopic structural characteristic experiments, wettability experiments, and permeability anisotropy experiments on shale oil reservoirs to obtain the composition, structure, and physicochemical properties of the shale oil reservoirs. The specific process of step S1 is as follows:

[0115] A1: Conduct XRD diffraction experiments to analyze the whole-rock mineral composition and clay mineral composition of shale oil reservoirs.

[0116] A2: Conduct structural feature evaluation at different scales, including core analysis, thin section analysis, and scanning electron microscopy, to analyze the macroscopic, mesoscopic, and microscopic structural characteristics of shale oil, providing a basis for the selection of plugging agent formulations during drilling. In this example, a shale oil reservoir from the Dagang Oilfield is used, and its structural features at the core, thin section, and electron microscopy scales are as follows: Figure 2 As shown, cracks are ubiquitous, with pore sizes ranging from tens of nanometers to hundreds of micrometers.

[0117] A3: Conduct wettability tests and use the baseline circle method to determine the wetting angle of a drilling fluid system composed of water, kerosene, hydrophobic agent, and plugging agent, so as to provide a basis for the selection of drilling fluid systems.

[0118] A4: Conduct water absorption and diffusion experiments in the direction parallel to and perpendicular to bedding to obtain the anisotropic characteristics of the water absorption and diffusion coefficient, and establish a water absorption and diffusion model and numerical simulation method for shale oil reservoirs with significant bedding characteristics.

[0119] The water absorption and diffusion model of shale oil reservoirs with significant bedding characteristics is shown in the following equation. Numerical simulation results are as follows: Figure 3 As shown in (a) and (b).

[0120]

[0121] in:

[0122]

[0123] Initial boundary conditions:

[0124]

[0125] In the formula, It is the equivalent water absorption diffusion coefficient tensor; w a w0 is the saturated water content at the wellbore; w0 is the water content in the original formation.

[0126] S2: Conduct immersion-NMR-acoustic-triaxial stress measurement experiments with different drilling fluid systems to dynamically evaluate the dynamic water absorption characteristics, dynamic changes in T2 spectra, and dynamic and static mechanical parameter changes of shale oil reservoir rocks under the coupling effect of drilling fluid in different bedding directions. The specific process of step S2 is as follows:

[0127] B1: Shale oil reservoir cores were immersed in different drilling fluid systems, and the longitudinal and transverse wave velocity curves of the rocks were measured at 0h, 0.5h, 1h, 2h, 4h, 8h, 16h, 24h, 48h and 96h, respectively. The dynamic mechanical parameters of the rocks after immersion in different drilling fluids were calculated.

[0128] B2: Nuclear magnetic resonance characteristics of core samples were measured at time points of 0h, 0.5h, 1h, 2h, 4h, 8h, 16h, 24h, 48h and 96h to obtain relaxation time and amplitude variation characteristics, evaluate the dynamic water absorption characteristics of shale oil reservoirs, and the variation law of pore size and pore volume, and establish dynamic water absorption equation.

[0129] B3: Select 3-5 core samples at time points of 0h, 2h, 8h, and 24h, conduct triaxial stress tests under different confining pressures, obtain the full stress-strain relationship curves, and calculate the compressive strength, elastic modulus, and Poisson's ratio.

[0130] B4: At time points of 0h, 2h, 8h, and 24h, based on the triaxial stress test results, plot the ultimate Mohr stress circle and strength envelope for each core sample at each time point, and calculate the cohesion and internal friction angle. In this embodiment, the Mohr circles and envelopes of a shale oil reservoir rock from the Dagang Oilfield after 0h and 24h soaking are used, as shown below. Figure 4 As shown in (a) and (b).

[0131] S3: Considering the controlling effect of shale bedding planes on the direction of water absorption dominance, construct the heterogeneous water absorption saturation equation, the relationship equation between expansion strain and water content, and the rock strength degradation equation for shale oil reservoirs. The specific process of step S3 is as follows:

[0132] C1: Based on the experimental results of B1 and B2, establish the relationship equation between rock dynamic parameters and water absorption;

[0133] C2: Based on the experimental results of B1B3 and B4, establish the equation relating static and dynamic parameters;

[0134] C3: Construct equations relating static elastic modulus, static Poisson's ratio, cohesion, and internal friction angle to water absorption.

[0135] S4: Based on well logging data, field data, and laboratory experimental data, establish profiles of vertical stress, maximum horizontal stress, minimum horizontal stress, and pore pressure. The specific process of step S4 is as follows:

[0136] D1: Vertical stress is calculated by segmented accumulation or integration using density logging data, or by using static stress gradient or a combination of both.

[0137] D2: The maximum and minimum horizontal geostresses are obtained through indoor core experiments combining paleomagnetism, the Kaiser effect, differential strain, and wave velocity anisotropy, or through inversion using field data such as wellbore collapse method and micro-fracture experiments.

[0138] D3: Pore pressure is estimated from logging data or sonic transit time logging data using methods such as sonic transit time method and DC exponent method.

[0139] S5: Based on the direction of geostress in the shale oil reservoir, the wellbore direction, and the bedding strike, using the geodetic coordinate system as an intermediate transformation value, the far-field stress is transformed into the wellbore coordinate system and the bedding coordinate system using coordinate transformation relationships. Then, the wellbore stress induced by the far-field stress, as well as the normal stress and shear stress on the bedding plane, are calculated. The specific process of step S5 is as follows:

[0140] E1: Based on the direction of geostress in the shale oil reservoir and the wellbore direction, using coordinate transformation relationships, such as... Figure 5 As shown in (a) and (b), the far-field stress is transformed into the wellbore coordinate system.

[0141]

[0142] in

[0143]

[0144] Where: σ H ,σ h ,σ v These are the maximum horizontal ground stress, minimum horizontal ground stress, and vertical stress, respectively, in MPa; These are the stress components of in-situ stress acting on the surrounding rock of the wellbore, in MPa; α b It is the well inclination azimuth; β b It is the well inclination angle.

[0145] E2: After obtaining the wellbore stress tensor using the magnitude and direction of the geostress, the wellbore stress distribution can be transformed to the weak surface of the bedding. The expression for the stress on the weak surface is:

[0146]

[0147] in:

[0148]

[0149] In the formula: θ is the well perimeter angle.

[0150] S6: Calculate the water absorption and shale expansion strain at different spatial locations of the shale oil reservoir at different drilling times. Combined with the surrounding rock equilibrium equation and boundary conditions, calculate the wellbore stress field generated by water absorption in the surrounding rock. The specific process of step S6 is as follows:

[0151] The relationship between water absorption swelling strain and water content is as follows:

[0152]

[0153] Wellbore stress distribution after hydration:

[0154]

[0155] In the formula, ε v ε h These represent the vertical and horizontal strains, respectively; Δω is the rate of change of water content; ε rr ε θθ ε zz These are the radial, circumferential, and axial strain components of the mudstone and shale at the well site under hydration; σ r σ θ σ z These are the radial, circumferential, and axial stress components of the mudstone and shale at the well site under hydration, in MPa; E is the rock elastic modulus; and υ is the rock Poisson's ratio.

[0156] S7: Considering the heat exchange between drilling fluid, drill string, annular drilling fluid, and formation within the drill string, simulate and calculate the temperature field distribution of the wellbore rock under drilling fluid circulation conditions, and calculate the thermal stress value and the additional collapse pressure caused by temperature stress. The specific process of step S7 is as follows:

[0157] F1: Considering the heat exchange between drilling fluid within the drill string, the drill string, the annular drilling fluid, and the formation, the temperature field distribution of the surrounding rock under drilling fluid circulation conditions is simulated and calculated. In this embodiment, a shale well in the Songliao Basin is used as an example, and the wellbore temperature field at different circulation times is as follows: Figure 6 As shown.

[0158]

[0159] Where: σ rT σ θT σ zT These are the radial, circumferential, and axial thermal stresses caused by temperature differences, respectively, in MPa; α T υ is the coefficient of thermal expansion of rock, 1 / ℃; E is the elastic modulus of rock, MPa; υ is the Poisson's ratio of rock; T f It is the temperature difference in the formation, in °C; r w It is the wellbore radius, in meters (m).

[0160] S8: Considering the stress components generated by in-situ stress, drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, the wellbore stress value under the coupled effects of force, chemistry, heat, and bedding is calculated using the superposition principle. The specific process of step S8 is as follows:

[0161] G1: Assuming the rock is a small-deformation elastic body, calculate the wellbore stress components induced by vertical stress, maximum horizontal stress, and minimum horizontal stress respectively, and then superimpose them as static values ​​of wellbore stress.

[0162] G2: Based on the contact time between the shale reservoir and the drilling fluid, analyze the wellbore stress components generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, and use them as dynamic values ​​of wellbore stress for superposition calculation.

[0163] G3: The static and dynamic values ​​of wellbore stress are superimposed to obtain the total wellbore stress value under different contact times between shale oil reservoir and drilling fluid under the coupling effect of force-chemical-thermal-stratification.

[0164] S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion, and weak surface strength criterion, construct the discriminant function and discrimination conditions for shear failure of the surrounding rock matrix and weak surface. The specific process of step S9 is as follows:

[0165] H1: Using the MC strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0166]

[0167] H2: Using the DP strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0168]

[0169] H3: Using the MG-C strength criterion, the shear failure function of the shale matrix is ​​constructed as follows:

[0170]

[0171] H4: Using the modified Lade strength criterion, the shear failure function within the shale layer is constructed as follows:

[0172]

[0173] H5: Using the weak surface strength criterion, the shear failure function within the shale layer is constructed as follows:

[0174]

[0175] H6: When f i When at least one of (i = 1, 2, 3, 4, 5) is less than 0, it is determined that the surrounding rock of the well wall has undergone shear failure and the well wall is in a state of collapse and instability; when f i When both f are equal to 0, the surrounding rock of the wellbore is judged to be in a critical state of shear failure, and the wellbore stability is in a critical state; when f i When all values ​​are greater than 0, it is determined that the surrounding rock of the well wall does not undergo shear failure and the well wall is in a stable state.

[0176] In the formula, the above function f i The physical meaning is the shear strength of the rock matrix minus the shear stress acting on the surrounding rock of the wellbore. σ is the internal friction angle of the matrix, σ1 is the first principal stress, σ2 is the second principal stress, σ3 is the third principal stress, k is the permeability, and α is the thermal expansion coefficient of the rock. It is the internal friction angle of the weak surface. It is the principal stress on the weak surface. C is the shear strength of the weak surface, and C is the cohesion. It is the cohesive force of the weak surface, η is the material constant, and a, b, and S are all constants.

[0177] S10: Substituting the wellbore stress and rock mechanics parameters under the coupled action of force, chemistry, heat, and bedding into the discriminant function and criteria for shear failure of the surrounding rock matrix and weak surfaces, an iterative numerical simulation algorithm for shale oil reservoir collapse pressure under different wellbore trajectories and fluid absorption times is constructed. The specific process of step S10 is as follows:

[0178] I1: Given a drilling fluid density, calculate the wellbore stress and rock mechanics parameters under the coupled effects of mechanical-chemical-thermal-stratification processes. Substitute these parameters with the discriminant functions and criteria for shear failure of the surrounding rock matrix and weak surfaces to calculate f. i .

[0179] I2: If f i When at least one of the components is less than -5%, the drilling fluid density is 0.01 g / cm³. 3 Increase, recalculate f i If f i When all values ​​are greater than 5%, the drilling fluid density is 0.01 g / cm³. 3 Reduce, recalculate f i If -5% ≤ all f i When the content is ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density.

[0180] I3: Based on the iterative calculation of equations (1)-(15), the range of equivalent density of collapse pressure is obtained. The iterative calculation process is as follows: Figure 7 As shown.

[0181] S11: Calculate the impact of different well inclination angles, azimuth angles, structural planes, drilling fluid systems, and operating times on the wellbore collapse pressure of shale oil reservoirs, and obtain the controlling factors and mechanisms of formation collapse pressure density. The specific process of step S11 is as follows:

[0182] J1: Calculate the wellbore collapse pressure of shale oil reservoirs under different bedding planes and physicochemical properties to obtain the influence of geological factors on collapse stress. In this example, the influence of bedding angle on the equivalent density of collapse pressure in a shale oil reservoir of a certain oilfield is shown below. Figure 8 As shown.

[0183] J2: Calculate the wellbore collapse pressure of shale oil reservoirs under different inclination and azimuth angles to obtain the influence of wellbore trajectory factors on collapse stress. In this example, for a shale oil reservoir in a certain oilfield, the influence of well inclination angle on the equivalent density of collapse pressure is as follows: Figure 9 As shown.

[0184] J3: Calculate the wellbore collapse pressure of shale oil reservoirs under different drilling fluid systems and application times to obtain the influence of drilling fluid properties on the collapse cycle. In this example, for a shale oil reservoir in a certain oilfield, the influence of soaking time on the collapse pressure equivalent density is as follows: Figure 10 As shown.

[0185] J4: Integrating geological and engineering factors, determine the factors and mechanisms controlling shale oil reservoir collapse pressure.

[0186] S12: Reduce the risk of shale oil wellbore collapse through optimization of drilling fluid system, wellbore trajectory, and drilling process parameters. The specific process of step S12 is as follows:

[0187] K1: Adding plugging agents and hydrophobic agents adjusts the drilling fluid system, increases wellbore tightness, increases the contact angle of the drilling fluid on the rock surface, reduces the surface free energy of clay minerals, and prevents and reduces drilling fluid ingress. For example, in a certain shale oil reservoir of an oilfield, the pore size ranges from tens of nanometers to hundreds of micrometers. A single plugging agent is insufficient to achieve effective plugging. Nano-micrometer scaled plugging agent particle size distribution was carried out, achieving better plugging effect.

[0188] K2: Optimize the wellbore trajectory, rationally select the build-up point, and the orientation of directional and horizontal well sections, and try to avoid the wellbore orientation coinciding with the orientation of maximum geostress in order to reduce the risk of wellbore instability.

[0189] Therefore, this invention provides a method for predicting shale oil wellbore collapse pressure by considering the combined effects of formation temperature, bedding and matrix rock water absorption heterogeneity, strength degradation of bedding matrix rocks, and rock expansion due to differences in water absorption and water content. This method can more accurately predict shale oil wellbore collapse pressure under the coupled effects of force, chemistry, heat, and bedding, thus ensuring efficient and safe shale oil drilling.

[0190] The above description is merely a preferred embodiment of the present invention and is not intended to limit the scope of the present invention. Any modifications or equivalent substitutions made to the present invention without departing from the spirit and scope thereof should be covered within the protection scope of the claims of the present invention.

Claims

1. A method for predicting shale oil wellbore collapse pressure, characterized in that, Includes the following steps: S1: Obtain the composition, structure, and physicochemical properties of shale oil reservoirs; S2: Conduct immersion-nuclear magnetic resonance-acoustic wave-triaxial stress measurement experiments with different drilling fluid systems to dynamically evaluate various characteristics of shale oil reservoir rocks and drilling fluids under the coupling effect of different bedding directions. Among them, various characteristics include dynamic water absorption characteristics, dynamic change characteristics of T2 spectrum, and dynamic and static mechanical parameter change characteristics. S3: Construct equations for water saturation in heterogeneous shale oil reservoir rocks, equations for the relationship between expansion strain and water content, and equations for rock strength degradation. S4: Establish profiles of vertical stress, maximum horizontal stress, minimum horizontal stress, and pore pressure; S5: Using coordinate transformation relationships, transform the far-field stress into the borehole coordinate system and the bedding coordinate system, and calculate the peri-well stress induced by the far-field stress as well as the normal stress and shear stress on the bedding surface. S6: Calculate the water absorption and shale expansion strain at different spatial locations of shale oil reservoirs at different drilling times, and calculate the wellbore stress field caused by water absorption in the surrounding rock in combination with the surrounding rock equilibrium state equation and boundary conditions; S7: Simulate and calculate the temperature field distribution of the wellbore rock under drilling fluid circulation conditions, and calculate the thermal stress value; S8: Overlay calculation of wellbore stress values ​​under the coupled effects of force, chemical, thermal and stratification; S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion, and weak surface strength criterion, construct the discriminant function and discriminant condition for the shear failure of the surrounding rock matrix and weak surface; S10: Substitute the wellbore stress and rock mechanics parameters under the coupled action of force-chemical-thermal-stratification into the discriminant function and discriminant condition of the wellbore matrix and weak surface shear failure of the surrounding rock matrix, and construct a numerical simulation iterative test algorithm for shale oil reservoir collapse pressure under different wellbore trajectories and fluid absorption times; S11: Calculate the wellbore collapse pressure of shale oil reservoirs under different well inclination angles, azimuth angles, structural planes, drilling fluid systems and action times, and obtain the influence of each factor on the wellbore collapse pressure of shale oil reservoirs. Then, determine the formation collapse pressure density control factors and control mechanisms. S12: Reduce the risk of shale oil wellbore collapse by optimizing drilling fluid systems, wellbore trajectories, and drilling process parameters.

2. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, In S1, the composition, structure, and physicochemical properties of shale oil reservoirs are obtained through XRD diffraction experiments, macroscopic, mesoscopic, and microscopic structural characteristic experiments, wettability experiments, and permeability anisotropy experiments. S1 includes the following steps: A1: Conduct XRD diffraction experiments to analyze the whole-rock mineral composition and clay mineral composition of shale oil reservoirs; A2: Conduct thin section analysis, scanning electron microscopy, and high-pressure mercury intrusion experiments to analyze the macroscopic, mesoscopic, and microscopic structural characteristics of shale oil, providing a basis for the selection of plugging agent formulations during drilling; A3: Conduct wettability tests and use the baseline circle method to determine the wetting angle of a drilling fluid system composed of water, kerosene, hydrophobic agent, and plugging agent, so as to provide a basis for the selection of drilling fluid systems; A4: Conduct water absorption and diffusion experiments in the direction parallel to and perpendicular to bedding to obtain the anisotropic characteristics of the water absorption and diffusion coefficient, and establish a water absorption and diffusion model and numerical simulation method for shale oil reservoirs with significant bedding characteristics.

3. The method for predicting shale oil wellbore collapse pressure according to claim 2, characterized in that, The water absorption and diffusion model for shale oil reservoirs with significant bedding characteristics in A4 is shown in the following equation: ， in: ， Initial boundary conditions: ， In the formula, It is the equivalent water absorption diffusion coefficient tensor; It is the saturated water content at the well wall; It is the water content in the original strata.

4. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, S2 includes the following steps: B1: Shale oil reservoir cores were immersed in different drilling fluid systems, and the longitudinal and transverse wave velocity curves of the rocks were measured at multiple time points. The dynamic mechanical parameters of the rocks after immersion in different drilling fluids were calculated. B2: Measure the nuclear magnetic resonance characteristics of the core at multiple time points to obtain the relaxation time and amplitude variation characteristics, evaluate the dynamic water absorption characteristics of shale oil reservoirs and the variation law of pore size and pore volume, and establish a dynamic water absorption equation; B3: Select multiple core samples at some of the multiple time points, conduct triaxial stress tests under different confining pressures, obtain the full stress-strain relationship curves, and calculate the compressive strength, elastic modulus, and Poisson's ratio; B4: At the specified time points, based on the triaxial stress test results of each rock type, plot the ultimate Mohr stress circle and strength envelope of each rock core at each time point, and calculate the cohesion and internal friction angle.

5. The method for predicting shale oil wellbore collapse pressure according to claim 4, characterized in that, In S3, the corresponding equations are constructed based on the controlling effect of shale bedding planes on the direction of water absorption dominance; and S3 includes the following steps: C1: Based on the experimental results of B1 and B2, establish the relationship equation between rock dynamic parameters and water absorption; C2: Based on the experimental results of B1, B3 and B4, establish the relationship equation between static parameters and dynamic parameters; C3: Construct equations relating static elastic modulus, static Poisson's ratio, cohesion, and internal friction angle to water absorption.

6. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, In S4, vertical stress, maximum horizontal stress, minimum horizontal stress, and pore pressure profiles are established based on well logging data, field data, and laboratory experimental data; and S4 includes the following steps: D1: Vertical stress is calculated by accumulating or integrating segments using density logging data, or by calculating static stress gradient, or by combining both methods. D2: The maximum and minimum horizontal geostresses are obtained through indoor core experiments combining paleomagnetism, Kaiser effect, differential strain and wave velocity anisotropy, or through inversion using field data from wellbore collapse method and micro-fracture experiments. D3: Based on logging data or sonic transit time logging data, pore pressure is estimated using the sonic transit time method and the DC exponent method.

7. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, In S5, based on the geostress direction of the shale oil reservoir, the wellbore direction, and the bedding strike, the geodetic coordinate system is used as the intermediate transformation value, and the coordinate transformation relationship is used for transformation. And S5 includes the following steps: E1: Based on the geostress direction of the shale oil reservoir and the wellbore direction, the geostress is transformed into the wellbore coordinate system using coordinate transformation relationships; E2: After obtaining the wellbore stress tensor using the magnitude and direction of geostress, the wellbore stress distribution state is transformed to the weak surface of the bedding.

8. The method for predicting shale oil wellbore collapse pressure according to claim 7, characterized in that, In E1, the expression for the far-field stress is: ， in ， In the formula: These are the maximum horizontal ground stress, minimum horizontal ground stress, and vertical stress, respectively, in MPa; , , , , , , , , , These are the stress components of in-situ stress acting on the surrounding rock of the wellbore, in MPa; It is the azimuth of the well inclination; It is the well inclination angle; In E2, the expression for the weak surface stress is: ， in: ， In the formula: It is the perimeter angle of the well.

9. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, In S6, the relationship between water absorption swelling strain and water content is as follows: ， Wellbore stress distribution after hydration: ， In the formula, , These are the vertical and horizontal strains, respectively. It is the rate of change of water content; , , These are the radial, circumferential, and axial strain components of the mudstone and shale at the well site under hydration. , , These are the radial, circumferential, and axial stress components of the mudstone and shale at the well site under hydration, in MPa; The elastic modulus of the rock; The Poisson's ratio for rocks.

10. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, S7 includes the following steps: F1: Based on the heat exchange between drilling fluid in the drill string, drill string, annular drilling fluid, and formation, the temperature field distribution of the rock around the well is simulated and calculated under drilling fluid circulation conditions. F2: Calculate the corresponding additional thermal stress on the well wall based on the temperature field distribution of the surrounding rocks.

11. The method for predicting shale oil wellbore collapse pressure according to claim 10, characterized in that, The temperature field distribution of the rocks around the well is as follows: ， In the formula: , , These are the radial, circumferential, and axial thermal stresses caused by temperature differences, respectively, in MPa; It is the coefficient of thermal expansion of rock, 1 / ℃; It is the elastic modulus of rock, in MPa; It is the Poisson's ratio of the rock; It is the temperature difference in the geological strata, in °C; It is the wellbore radius, in meters (m).

12. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, In S8, based on the stress components generated by in-situ stress, drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, the superposition principle is used to calculate the wellbore stress value under the coupled action of force-chemical-thermal-stratification; and S8 includes the following steps: G1: Assuming the rock is a small-deformation elastic body, calculate the wellbore stress components induced by vertical stress, maximum horizontal stress, and minimum horizontal stress respectively, and superimpose them as static values ​​of wellbore stress. G2: Based on the contact time between the shale reservoir and the drilling fluid, analyze the wellbore stress components generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, and use them as dynamic values ​​of wellbore stress for superposition calculation. G3: The static and dynamic values ​​of wellbore stress are superimposed to obtain the total wellbore stress value under different contact times between shale oil reservoir and drilling fluid under the coupling effect of force-chemical-thermal-stratification.

13. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, S9 includes the following steps: H1: Using the MC strength criterion, the shear failure function of the shale matrix is ​​constructed as follows: ； H2: Using the DP strength criterion, the shear failure function of the shale matrix is ​​constructed as follows: ； H3: Using the MG-C strength criterion, the shear failure function of the shale matrix is ​​constructed as follows: ； H4: Using the modified Lade strength criterion, the shear failure function within the shale layer is constructed as follows: ； H5: Using the weak surface strength criterion, the shear failure function within the shale layer is constructed as follows: ； H6: When f i When at least one of (i=1, 2, 3, 4, 5) is less than 0, it is determined that the surrounding rock of the well wall has undergone shear failure and the well wall is in a state of collapse and instability; when f i When all values ​​are equal to 0, the surrounding rock of the wellbore is judged to be in a critical state of shear failure, and the wellbore stability is in a critical state; when f i When all values ​​are greater than 0, it is determined that the surrounding rock of the well wall does not undergo shear failure and the well wall is in a stable state. In the formula, It is the internal friction angle of the matrix. It is the first principal stress. It is the second principal stress. It is the third principal stress. k It's penetration rate. It is the coefficient of thermal expansion of the rock. It is the internal friction angle of the weak surface. It is the principal stress on the weak surface. C is the shear strength of the weak surface, and C is the cohesion. It is a weak cohesive force. η These are material constants; a, b, and S are all constants.

14. The method for predicting shale oil wellbore collapse pressure according to claim 13, characterized in that, S10 includes the following steps: I1: Given a drilling fluid density, calculate the wellbore stress and rock mechanics parameters under the coupled effects of mechanical-chemical-thermal-stratification processes. Substitute these parameters into the discriminant functions and criteria for shear failure of the surrounding rock matrix and weak surfaces, and calculate... f i ; I2: If f i When at least one of the components is less than -5%, the drilling fluid density is 0.01 g / cm³. 3 Increase, recalculate f i ;if f i When all values ​​are greater than 5%, the drilling fluid density is 0.01 g / cm³. 3 Reduce, recalculate f i If -5% ≤ all f i When the density is ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density; I3: Iterative calculation to obtain the range of equivalent density of collapse pressure.

15. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, S11 includes the following steps: J1: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs under different bedding planes and physicochemical properties to obtain the influence of geological factors on collapse stress; J2: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs under different inclination and azimuth angles to obtain the influence of wellbore trajectory factors on collapse stress; J3: Calculate the wellbore collapse pressure of shale oil reservoirs under different drilling fluid systems and action times to obtain the influence of drilling fluid properties on the collapse cycle; J4: Integrating geological and engineering factors, determine the factors and mechanisms controlling shale oil reservoir collapse pressure.

16. The method for predicting shale oil wellbore collapse pressure according to claim 1, characterized in that, S12 includes the following steps: K1: Adding plugging and hydrophobic agents to adjust the drilling fluid system, increase the tightness of the wellbore, increase the contact angle of the drilling fluid on the rock surface, reduce the free energy of the clay mineral surface, and prevent and reduce the entry of drilling fluid; K2: Optimize the wellbore trajectory, rationally select the direction point and the orientation of directional and horizontal well sections, and avoid the wellbore orientation coinciding with the orientation of maximum geostress to reduce the risk of wellbore instability.

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