Shale oil borehole wall collapse pressure prediction method

Abstract

The invention relates to a shale oil borehole wall collapse pressure prediction method. The method comprises the following steps: acquiring components, structures and physicochemical properties of a shale oil reservoir; carrying out soaking-nuclear magnetism-sound wave-triaxial stress combined measurement experiments of different drilling fluid systems; constructing a shale oil reservoir rock heterogeneous water absorption and strength degradation equation; establishing ground stress and pore pressure profiles; converting the far-field crustal stress into a borehole and bedding coordinate system; calculating a well periphery stress field generated by water absorption of the surrounding rock; simulating and calculating the temperature field distribution of the rock and calculating a thermal stress value; the well periphery stress value under the force-chemical-thermal-bedding coupling effect is calculated in a superposition mode; constructing a well surrounding rock matrix and weak plane shear failure discrimination function and condition; constructing a shale oil reservoir collapse pressure numerical simulation iterative trial algorithm; determining a formation collapse pressure density control factor and a control mechanism; and the shale oil borehole wall collapse risk is reduced through optimization. According to the method, the shale oil borehole wall collapse pressure under the force-chemical-thermal-bedding coupling effect can be predicted more accurately.

Description

Technical Field

[0001] The present invention relates to the technical field of safe shale oil drilling, and more specifically, to a method for predicting shale oil well wall collapse pressure. Background Art

[0002] In recent years, my country has discovered abundant shale oil reserves, which are mainly formed in the organic-rich mudstone strata of continental lake basins, and the reservoir geological conditions are relatively complex. Shale contains many clay minerals such as illite, illite-montmorillonite mixed layers, and montmorillonite, and has structural weak surfaces such as bedding. Drilling fluid easily enters the formation, and mechanical and chemical reactions occur between the drilling fluid and the wellbore wall, resulting in the redistribution of stress around the well and the deterioration of rock strength, inducing frequent wellbore collapse accidents during drilling, greatly increasing the drilling cycle and cost, and restricting the exploration and development process.

[0003] Traditional collapse pressure research mostly assumes that the formation is a continuous isotropic medium, and there is a relative lack of systematic research on hard, brittle, heterogeneous, and well-bedding shale oil reservoirs. For example, Chinese invention patent CN104806233A discloses a method for predicting the collapse pressure equivalent density window of weak-surface formations, and proposes the division of the tight section and the fracture section of the wellbore, and the mechanical strength test of the rock body and the fracture surface; on this basis, the near-wellbore pore pressure and stress analysis is carried out based on the fluid-solid coupling mean model, and the wellbore damage state and collapse pressure are determined in combination with the strength criterion. Chinese invention patent CN113356843A discloses a method for predicting the collapse pressure equivalent density window of weak-surface formations. This method collects the formation's anisotropic pressure parameters and obtains the formation rock constitutive parameters; on this basis, combined with the ground stress state and the wellbore force model, the wellbore stability analysis under the coupling and coordination of the mean formation multi-physical field coupling is realized, thereby helping to optimize drilling parameters on site in the oil field. Chinese invention patent CN114526058A discloses a method and system for designing drilling collapse pressure, which collects the target formation drilling type and the circumferential integrity of the wellbore, and obtains the wellbore stress characteristics at different positions according to the ground stress information; on this basis, the minimum wellbore safety area during safe drilling construction accounts for the proportion of the wellbore circumferential area, and the drilling collapse pressure is calculated from the collapse pressure equivalent density, so as to achieve the purpose of reducing the drilling fluid density and increasing the safe drilling speed. Chinese invention patent CN113095593A provides a drilling wellbore state determination method, device and equipment, which 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 state of the drilled section to improve the reliability of the evaluation, and on this basis predicts the wellbore state evaluation parameters and risk prediction results of the undrilled section below the drilled section. Chinese invention patent CN114547906A discloses a wellbore stability logging interpretation method for deep formations with weak structural surfaces. By collecting logging data and actual drilling and completion data, the formation pressure and geostress profiles are established, and the maximum horizontal principal stress orientation, bedding dip and strike are determined; on this basis, three pressure profiles are drawn. This method considers the influence of bedding structural surfaces on the basis of conventional logging methods to improve the prediction accuracy, thereby effectively guiding safe and efficient drilling in deep complex formations. Chinese invention patent CN111980667 discloses a quantitative evaluation method for the influence of anisotropy on the collapse pressure of shale wellbore. The geostress parameters, bedding occurrence, wellbore trajectory and formation pressure of the target well area are obtained under the known geodetic coordinate system, and the rock mechanics parameters of the rock body and fracture surface are determined; the principal stress is converted to the wellbore periphery and bedding surface by coordinate transformation, and the critical collapse pressure on the wellbore periphery is obtained based on the matlab Newton iteration method in combination with the MC, MGC, ML and MWC strength criteria.

[0004] In fact, during the entire drilling cycle, the wellbore collapse of shale oil reservoirs is a problem of multiple superposition and coupling. Due to the low temperature of the drilling fluid in the wellbore, the shale oil reservoir experiences heat transfer and temperature changes to the wellbore. Thermal stress will cause changes in the near-well stress field. At the same time, due to capillary force, clay mineral crystal layer structure, mineralization difference between drilling fluid and formation fluid, and pressure difference between bottom hole pressure and formation pressure, it will induce imbibition, hydration, diffusion and penetration during shale oil drilling, leading to changes in wellbore stress, formation fluid pressure and rock strength. In addition, the control of the bedding structure on the dominant direction of water absorption and seepage and the rate of strength degradation aggravates the wellbore collapse.

[0005] Therefore, the prior art needs to be improved. Summary of the invention

[0006] The present invention mainly solves the shortcomings of the existing shale oil well wall collapse pressure prediction technology and proposes a shale oil well wall collapse pressure prediction method. This method can more accurately predict the shale oil well wall collapse pressure under the coupling of force, chemical, heat and bedding, and provide guarantee for efficient and safe shale oil drilling.

[0007] The technical solution adopted by the present invention is as follows:

[0008] According to one aspect of the present invention, a method for predicting shale oil well wall 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-NMR-acoustic-triaxial stress joint measurement experiments with different drilling fluid systems to dynamically evaluate various characteristics of shale oil reservoir rocks in different bedding directions under the coupling effect of drilling fluids;

[0011] S3: Construct the water saturation equation of shale oil reservoir rock heterogeneity water absorption, the relationship equation between expansion strain and water content, and the rock strength degradation equation;

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

[0013] S5: using the coordinate transformation relationship, the far-field stress is transformed into the borehole coordinate system and the bedding coordinate system, and the wellbore stress induced by the far-field stress and the normal stress and shear stress on the bedding plane are calculated;

[0014] S6: Calculate the water absorption and shale expansion strain at different spatial positions of the shale oil reservoir at different drilling times, and calculate the stress field around the well caused by water absorption of 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 the condition of drilling fluid circulation, and calculate the thermal stress value;

[0016] S8: Superimposed calculation of the stress value around the well under the coupling of mechanical-chemical-thermal-stratification;

[0017] S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion and weak plane strength criterion, the discriminant function and discriminant conditions of shear failure of the rock matrix and weak plane around the well are constructed;

[0018] S10: Substitute the stress around the well and the rock mechanical parameters under the coupling of force, chemical, heat and bedding into the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and construct an iterative trial algorithm for numerical simulation of shale oil reservoir collapse pressure under different wellbore trajectories and liquid 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 time, and obtain the influence of various factors on the wellbore collapse pressure of shale oil reservoirs, and then determine the control factors and control mechanisms of formation collapse pressure density;

[0020] S12: Reduce the risk of shale oil well wall collapse by optimizing the drilling fluid system, wellbore trajectory and drilling process parameters.

[0021] In one embodiment of the present invention, in S1, the composition, structure and physical and chemical properties of the shale oil reservoir are obtained by conducting XRD diffraction experiments on shale oil reservoirs, macroscopic, microscopic and microstructural feature experiments, wettability experiments and permeability anisotropy experiments; and S1 includes the following steps:

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

[0023] A2: Carry out thin section analysis, scanning electron microscopy and high-pressure mercury injection experiments to analyze the macroscopic, mesoscopic and microstructural characteristics of shale oil, and provide a basis for the selection of drilling plugging agents;

[0024] A3: Carry out wettability experiments and use the baseline circle method to determine the wetting angle of the drilling fluid system composed of clean water, kerosene, hydrophobic agent and plugging agent to provide a basis for the selection of the drilling fluid system;

[0025] A4: Conduct water absorption and diffusion experiments in the directions parallel to and perpendicular to the bedding, 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 the shale oil reservoir with significant bedding characteristics in A4 is as follows:

[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 is the saturated water content at the well wall; w0 is the water content in the original formation.

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

[0034] B1: Immerse the shale oil reservoir core in different drilling fluid systems, measure the longitudinal and transverse wave velocity curves of the rock at multiple time points, and calculate the dynamic mechanical parameters of the rock after immersion in different drilling fluids;

[0035] B2: measuring the nuclear magnetic resonance characteristics of the core at the multiple time points, obtaining the relaxation time and amplitude change characteristics, evaluating the dynamic water absorption characteristics of the shale oil reservoir and the change law of pore size and pore volume, and establishing a dynamic water absorption equation;

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

[0037] B4: At the aforementioned time nodes, based on the triaxial stress test results of each rock type, the limiting Mohr stress circle and strength envelope of each core at each time node are drawn, and the cohesion and internal friction angle are calculated.

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

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

[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 the relationship equations between static elastic modulus, static Poisson's ratio, cohesion and internal friction angle and water absorption.

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

[0043] D1: Calculate vertical stress by accumulating or integrating density logging data in sections, or by using static geostress gradient calculation, or by combining the two;

[0044] D2: The maximum horizontal geostress and the minimum horizontal geostress are obtained through indoor core experiments combining paleomagnetism, Kessel effect, differential strain and wave velocity anisotropy, or inverted using field data from wellbore caving method and micro-fracturing experiments;

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

[0046] In one embodiment of the present invention, in S5, according to the in-situ stress direction of the shale oil reservoir, the wellbore direction and the bedding strike, the coordinate conversion relationship is used to perform conversion with the geodetic coordinate system as the intermediate conversion value; and S5 includes the following steps:

[0047] E1: Based on the in-situ stress direction of the shale oil reservoir and the wellbore direction, the far-field stress is converted into the wellbore coordinate system using the coordinate conversion relationship;

[0048] E2: After obtaining the stress tensor around the well using the magnitude and direction of the ground stress, the stress distribution state around the well is converted to the bedding weak plane.

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

[0050]

[0051] in

[0052]

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

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

[0055]

[0056] in:

[0057]

[0058] Where: θ is the well circumference angle.

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

[0060]

[0061] Stress distribution around the well after hydration:

[0062]

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

[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 under the condition of drilling fluid circulation is simulated and calculated;

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

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

[0068]

[0069] Where: rT , σ θT , σ zT are the additional thermal stresses due to temperature difference in radial, circumferential and axial directions, MPa; α T is the thermal expansion coefficient of rock, 1 / ℃; E is the elastic modulus of rock, MPa; υ is the Poisson's ratio of rock; T fis the formation temperature difference, °C; r w is the wellbore radius, m.

[0070] In one embodiment of the present invention, in S8, based on the stress components generated by the ground stress, the drilling fluid column pressure, the pore pressure, the hydration stress, and the temperature stress, the superposition principle is adopted to calculate the stress value around the well under the mechanical-chemical-thermal-stratification coupling effect; and S8 includes the following steps:

[0071] G1: Assuming that the rock is a small deformation elastic body, the wellbore stress components induced by vertical stress, maximum horizontal ground stress, and minimum horizontal ground stress are calculated respectively, and superimposed as the static value of wellbore stress;

[0072] G2: According to the contact time between the shale reservoir and the drilling fluid, the borehole wall stress components generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress are analyzed and superimposed as the dynamic value of the borehole wall stress;

[0073] G3: The static and dynamic values ​​of the wellbore stress are superimposed and calculated to obtain the total wellbore stress value at different contact times between the shale oil reservoir and the drilling fluid under the coupling of force, chemical, heat and bedding.

[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:

[0076]

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

[0078]

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

[0080]

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

[0082]

[0083] H5: Using the weak plane strength criterion, the shear failure function in the shale layer is constructed as:

[0084]

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

[0086] Among them, in the formula, 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, α is the thermal expansion coefficient of the rock, is the weak surface internal friction angle, is the principal stress on the weak plane, is the shear strength of the weak surface, C is the cohesion, is the weak surface cohesion, η is the material constant, and a, b, and S are all constants.

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

[0088] I1: Assume a drilling fluid density, calculate the stress around the well and rock mechanical parameters under the coupling of force, chemical, thermal and bedding, substitute the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and calculate f i ;

[0089] I2: If f i When at least one of the following is less than -5%, the drilling fluid density is 0.01 g / cm 3 Increase, recalculate f i ; if f i When both are greater than 5%, the drilling fluid density is 0.01g / cm 3 Reduce and recalculate f i ; If -5% ≤ all f i When ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density;

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

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

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

[0093] J2: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs at different well inclination angles 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 time, and obtain the influence of drilling fluid properties on the collapse cycle;

[0095] J4: Integrate geological and engineering factors to determine the controlling factors and mechanisms of shale oil reservoir collapse pressure.

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

[0097] K1: Add plugging agents and hydrophobic agents, adjust the drilling fluid system, increase the density of the well wall, increase the contact angle of the drilling fluid on the rock surface, reduce the surface free energy of clay minerals, and prevent and reduce the entry of drilling fluid;.

[0098] K2: Optimize the wellbore trajectory, reasonably select the inclination point and the orientation of the directional and horizontal well sections, and avoid the coincidence of the wellbore orientation with the maximum ground stress orientation 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] The present invention realizes a shale oil well wall collapse pressure prediction method taking into account the influence of comprehensive factors such as formation temperature, bedding and matrix rock water absorption heterogeneity, bedding matrix rock strength degradation, rock expansion under water absorption moisture content difference, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings required for use in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0102] Figure 1 A flow chart showing a method for predicting shale oil well wall collapse pressure provided by the present invention is shown;

[0103] Figure 2 The multi-scale structural characteristics of the shale oil reservoir in the embodiment of the present invention are shown;

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

[0105] Figure 4 (a) and (b) show the Mohr circle and envelope of the shale oil reservoir rock in the embodiment of the present invention at 0h and after immersion for 24h respectively;

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

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

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

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

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

[0111] Fig.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. DETAILED DESCRIPTION

[0112] In order to make the objectives, technical solutions and advantages of the present invention more clearly understood, the embodiments of the present invention are further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0113] like Figure 1 As shown, a method for predicting shale oil well wall collapse pressure of the present invention comprises the following steps:

[0114] S1: Carry out XRD diffraction experiments on shale oil reservoirs, macroscopic, microscopic and microstructural feature experiments, wettability experiments and permeability anisotropy experiments to obtain the composition, structure and physical and chemical properties of shale oil reservoirs. The specific process of step S1 is as follows:

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

[0116] A2: Carry out core, thin section analysis, scanning electron microscopy and other structural characteristics evaluation at different scales to analyze the macroscopic, mesoscopic and microscopic structural characteristics of shale oil and provide a basis for the selection of drilling plugging agents. In this example, a shale oil reservoir in Dagang Oilfield was used. Its structural characteristics at the core, thin section and electron microscope scales are as follows: Figure 2 As shown, cracks are ubiquitous, and the pore sizes range from tens of nanometers to hundreds of microns.

[0117] A3: Carry out wettability experiments and use the baseline circle method to determine the wetting angle of the drilling fluid system composed of clean water, kerosene, hydrophobic agent and plugging agent to provide a basis for the selection of the drilling fluid system.

[0118] A4: Conduct water absorption and diffusion experiments in the directions parallel to and perpendicular to the bedding, 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 formula. The 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, is the equivalent water absorption diffusion coefficient tensor; w a is the saturated water content at the well wall; w0 is the water content in the original formation.

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

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

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

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

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

[0131] S3: Considering the control effect of shale bedding on the dominant direction of water absorption, the water saturation equation of shale oil reservoir rock heterogeneity water absorption, the relationship equation between expansion strain and water content, and the rock strength degradation equation are constructed. The specific process of step S3 is:

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

[0133] C2: Combine the experimental results of B1B3 and B4 to establish the relationship equation between static parameters and dynamic parameters;

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

[0135] S4: Based on the well logging data, the mine data and the indoor experimental data, the vertical stress, the maximum horizontal ground stress, the minimum horizontal ground stress and the pore pressure profile are established. The specific process of step S4 is:

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

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

[0138] D3: Pore pressure is estimated from logging data or sonic time difference logging data using the sonic time difference method, DC index method, etc.

[0139] S5: Based on the geostress direction of the shale oil reservoir, the borehole direction and the bedding strike, the far-field stress is converted to the borehole coordinate system and the bedding coordinate system using the coordinate conversion relationship, and 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 shale oil reservoir in-situ stress direction and wellbore direction, using coordinate transformation relations, 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: H ,σ h ,σ v are the maximum horizontal in-situ stress, minimum horizontal in-situ stress and vertical stress, MPa, respectively; are the stress components of the in-situ stress acting on the surrounding rock of the wellbore, MPa; α b is the well inclination azimuth; β b It is the well inclination angle.

[0145] E2: After obtaining the stress tensor around the well using the magnitude and direction of the ground stress, the stress distribution state around the well can be converted to the bedding weak plane. The expression of the weak plane stress is:

[0146]

[0147] in:

[0148]

[0149] Where: θ is the well circumference angle.

[0150] S6: Calculate the water absorption and shale expansion strain at different spatial positions of the shale oil reservoir at different drilling times, and calculate the stress field around the well caused by the surrounding rock water absorption by combining the surrounding rock equilibrium state equation and boundary conditions. The specific process of step S6 is:

[0151] The relationship between water absorption expansion strain and water content is:

[0152]

[0153] Stress distribution around the well after hydration:

[0154]

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

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

[0157] F1: Considering 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 under the condition of drilling fluid circulation is simulated and calculated. In this embodiment, a shale well in the Songliao Basin is taken as an example. The temperature field of the well wall at different circulation times is as follows: Figure 6 shown.

[0158]

[0159] Where: rT , σ θT , σ zT are the additional thermal stresses due to temperature difference in radial, circumferential and axial directions, MPa; α T is the thermal expansion coefficient of rock, 1 / ℃; E is the elastic modulus of rock, MPa; υ is the Poisson's ratio of rock; T f is the formation temperature difference, °C; r w is the wellbore radius, m.

[0160] S8: Considering the stress components generated by geostress, drilling fluid column pressure, pore pressure, hydration stress, and temperature stress, the superposition principle is used to calculate the stress value around the well under the coupling of force-chemistry-heat-stratification. The specific process of step S8 is as follows:

[0161] G1: Assuming that the rock is a small deformation elastic body, the wellbore stress components induced by vertical stress, maximum horizontal ground stress, and minimum horizontal ground stress are calculated respectively, and superimposed as the static values ​​of wellbore stress.

[0162] G2: According to the contact time between the shale reservoir and the drilling fluid, the components of the wellbore stress generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress are analyzed and superimposed as the dynamic value of the wellbore stress.

[0163] G3: The static and dynamic values ​​of the wellbore stress are superimposed and calculated to obtain the total wellbore stress value at different contact times between the shale oil reservoir and the drilling fluid under the coupling of force, chemical, heat and bedding.

[0164] S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion and weak plane strength criterion, construct the shear failure discriminant function and discriminant conditions of the rock matrix and weak plane around the well. The specific process of step S9 is:

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

[0166]

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

[0168]

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

[0170]

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

[0172]

[0173] H5: Using the weak plane strength criterion, the shear failure function in the shale layer is constructed as:

[0174]

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

[0176] Among them, in the formula, the above function f i The physical meaning of the expression is the shear strength of the rock matrix minus the shear stress acting on the surrounding rock of the well wall. 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, α is the thermal expansion coefficient of the rock, is the weak surface internal friction angle, is the principal stress on the weak plane, is the shear strength of the weak surface, C is the cohesion, is the weak surface cohesion, η is the material constant, and a, b, and S are all constants.

[0177] S10: Substitute the wellbore stress and rock mechanics parameters under the coupling of force, chemical, heat and bedding into the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and construct an iterative trial algorithm for numerical simulation of shale oil reservoir collapse pressure under different wellbore trajectories and liquid absorption times. The specific process of step S10 is:

[0178] I1: Assume a drilling fluid density, calculate the stress around the well and rock mechanical parameters under the coupling of force, chemical, thermal and bedding, substitute the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and calculate f i .

[0179] I2: If f i When at least one of the following is less than -5%, the drilling fluid density is 0.01 g / cm 3 Increase, recalculate f i ; if f i When both are greater than 5%, the drilling fluid density is 0.01g / cm 3 Reduce and recalculate f i ; If -5% ≤ all f i When ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density.

[0180] I3: According to equation (1)-(15), iterative calculation is performed to obtain the collapse pressure equivalent density range. The iterative calculation process is as follows: Figure 7 shown.

[0181] S11: Calculate the influence of different well inclination angles, azimuth angles, structural planes, drilling fluid systems and action time on the wellbore collapse pressure of shale oil reservoirs, and obtain the control factors and control mechanisms of formation collapse pressure density. The specific process of step S11 is:

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

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

[0184] J3: Calculate the wellbore collapse pressure of shale oil reservoirs under different drilling fluid systems and action time, and obtain the influence of drilling fluid properties on the collapse cycle. In this example, for a shale oil reservoir in a certain oil field, the influence of immersion time on the equivalent density of collapse pressure is as follows: Fig.10 shown.

[0185] J4: Integrate geological and engineering factors to determine the controlling factors and mechanisms of shale oil reservoir collapse pressure.

[0186] S12: Reduce the risk of shale oil well wall collapse by optimizing the drilling fluid system, wellbore trajectory and drilling process parameters. The specific process of step S12 is:

[0187] K1: Add plugging agents and hydrophobic agents, adjust the drilling fluid system, increase the density of the well wall, increase the contact angle of the drilling fluid on the rock surface, reduce the surface free energy of clay minerals, and prevent and reduce the entry of drilling fluid. For example, the pore size of a shale oil reservoir in a certain oil field ranges from tens of nanometers to hundreds of microns. It is difficult for a single plugging agent to form an effective plugging. Nano-micron plugging agent particle size grading was performed to achieve a better plugging effect.

[0188] K2: Optimize the wellbore trajectory, reasonably select the inclination point, and the orientation of the directional and horizontal well sections, and try to avoid the coincidence of the wellbore orientation with the maximum ground stress orientation to reduce the risk of wellbore instability.

[0189] It can be seen that the present invention realizes a shale oil well wall collapse pressure prediction method under the influence of comprehensive factors such as formation temperature, bedding and matrix rock water absorption heterogeneity, bedding matrix rock strength degradation, rock expansion under water absorption moisture content difference. The method of the present invention can more accurately predict the shale oil well wall collapse pressure under the coupling of force-chemistry-heat-bedding, providing guarantee for efficient and safe shale oil drilling.

[0190] The above description is only a preferred embodiment of the present invention and is not intended to limit the scope of implementation of the present invention. If the present invention is modified or replaced by equivalents without departing from the spirit and scope of the present invention, it should be covered by the protection scope of the claims of the present invention.

Claims

1. A method for predicting shale oil well wall collapse pressure, characterized in that: The following steps are involved: S1: Obtain the composition, structure and physicochemical properties of shale oil reservoirs; S2: Conduct immersion-NMR-acoustic-triaxial stress joint measurement experiments with different drilling fluid systems to dynamically evaluate various characteristics of shale oil reservoir rocks in different bedding directions under the coupling effect of drilling fluids; S3: Construct the water saturation equation of shale oil reservoir rock heterogeneity water absorption, the relationship equation between expansion strain and water content, and the rock strength degradation equation; S4: Establish vertical stress, maximum horizontal geostress, minimum horizontal geostress and pore pressure profiles; S5: using the coordinate transformation relationship, the far-field stress is transformed into the borehole coordinate system and the bedding coordinate system, and the wellbore stress induced by the far-field stress and the normal stress and shear stress on the bedding plane are calculated; S6: Calculate the water absorption and shale expansion strain at different spatial positions of the shale oil reservoir at different drilling times, and calculate the stress field around the well caused by water absorption of 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 the condition of drilling fluid circulation, and calculate the thermal stress value; S8: Superimposed calculation of the stress value around the well under the coupling of mechanical-chemical-thermal-stratification; S9: Using the MC strength criterion, DP strength criterion, MG-C strength criterion, modified Lade strength criterion and weak plane strength criterion, the discriminant function and discriminant conditions of shear failure of the rock matrix and weak plane around the well are constructed; S10: Substitute the stress around the well and the rock mechanical parameters under the coupling of force, chemical, heat and bedding into the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and construct an iterative trial algorithm for numerical simulation of shale oil reservoir collapse pressure under different wellbore trajectories and liquid 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 time, and obtain the influence of various factors on the wellbore collapse pressure of shale oil reservoirs, and then determine the control factors and control mechanisms of formation collapse pressure density; S12: Reduce the risk of shale oil well wall collapse by optimizing the drilling fluid system, wellbore trajectory and drilling process parameters.

2. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S1, the composition, structure and physical and chemical properties of the shale oil reservoir are obtained by conducting XRD diffraction experiments, macroscopic, microscopic and microstructural characteristics experiments, wettability experiments and permeability anisotropy experiments of the shale oil reservoir; and S1 includes the following steps: A1: Carry out XRD diffraction experiments to analyze the whole-rock mineral components and clay mineral components of shale oil reservoirs; A2: Carry out thin section analysis, scanning electron microscopy and high-pressure mercury injection experiments to analyze the macroscopic, mesoscopic and microstructural characteristics of shale oil, and provide a basis for the selection of drilling plugging agents; A3: Carry out wettability experiments and use the baseline circle method to determine the wetting angle of the drilling fluid system composed of clean water, kerosene, hydrophobic agent and plugging agent to provide a basis for the selection of the drilling fluid system; A4: Conduct water absorption and diffusion experiments in the directions parallel to and perpendicular to the bedding, 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 well wall collapse pressure according to claim 2, characterized in that: The water absorption and diffusion model of the shale oil reservoir with significant bedding characteristics in A4 is as follows: in: Initial boundary conditions: In the formula, is the equivalent water absorption diffusion coefficient tensor; w a is the saturated water content at the well wall; w0 is the water content in the original formation.

4. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S2, the various characteristics include dynamic water absorption characteristics, T2 spectrum dynamic change characteristics, dynamic and static mechanical parameter change characteristics; and S2 includes the following steps: B1: Immerse the shale oil reservoir core in different drilling fluid systems, measure the longitudinal and transverse wave velocity curves of the rock at multiple time points, and calculate the dynamic mechanical parameters of the rock after immersion in different drilling fluids; B2: measuring the nuclear magnetic resonance characteristics of the core at the multiple time points, obtaining the relaxation time and amplitude change characteristics, evaluating the dynamic water absorption characteristics of the shale oil reservoir and the change law of pore size and pore volume, and establishing a dynamic water absorption equation; B3: Select multiple cores at some of the multiple time nodes, carry out triaxial stress tests under different confining pressures, obtain full stress-strain relationship curves, and calculate compressive strength, elastic modulus and Poisson's ratio; B4: At the aforementioned time nodes, based on the triaxial stress test results of each rock type, the limiting Mohr stress circle and strength envelope of each core at each time node are drawn, and the cohesion and internal friction angle are calculated.

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

6. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S4, vertical stress, maximum horizontal geostress, minimum horizontal geostress and pore pressure profiles are established based on well logging data, field data and indoor experimental data; and S4 includes the following steps: D1: Calculate vertical stress by accumulating or integrating density logging data in sections, or by using static geostress gradient calculation, or by combining the two; D2: The maximum horizontal geostress and the minimum horizontal geostress are obtained through indoor core experiments combining paleomagnetism, Kessel effect, differential strain and wave velocity anisotropy, or inverted using field data from wellbore caving method and micro-fracturing experiments; D3: Based on the logging data or sonic time difference logging data, the pore pressure is estimated using the sonic time difference method and the DC index method.

7. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S5, according to the in-situ stress direction of the shale oil reservoir, the wellbore direction and the bedding strike, the geodetic coordinate system is used as the intermediate conversion value and the coordinate conversion relationship is used for conversion; And S5 comprises the following steps: E1: Based on the in-situ stress direction of the shale oil reservoir and the wellbore direction, the far-field stress is converted into the wellbore coordinate system using the coordinate conversion relationship; E2: After obtaining the stress tensor around the well using the magnitude and direction of the ground stress, the stress distribution state around the well is converted to the bedding weak plane.

8. The method for predicting shale oil well wall collapse pressure according to claim 7, characterized in that: In E1, the expression for far-field stress is: in Where: H ,σ h ,σ v are the maximum horizontal in-situ stress, minimum horizontal in-situ stress and vertical stress, MPa, respectively; are the stress components of the in-situ stress acting on the surrounding rock of the wellbore, MPa; α b is the well inclination azimuth; β b is the well inclination angle; In E2, the weak surface stress expression is: in: Where: θ is the well circumference angle.

9. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S6, the relationship between water absorption expansion strain and water content is: Stress distribution around the well after hydration: In the formula, ε v , ε h are the vertical and horizontal strains, respectively; Δω is the rate of change of water content; ε rr , ε θθ , ε zz are the radial, circumferential and axial strain components of the shale in the well site under hydration; σ r , σ θ , σ z They are the radial, circumferential and axial stress components of the shale in the well site under hydration, MPa; E is the elastic modulus of rock; υ is the Poisson's ratio of rock.

10. The method for predicting shale oil well wall 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 under the condition of drilling fluid circulation is simulated and calculated; F2: Calculate the corresponding additional thermal stress on the well wall based on the temperature field distribution of the rock around the well.

11. The method for predicting shale oil well wall collapse pressure according to claim 10, characterized in that: The temperature field distribution of the rock around the well is as follows: Where: rT , σ θT , σ zT are the additional thermal stresses of radial, circumferential and axial temperature differences, MPa; α T is the thermal expansion coefficient of rock, 1 / ℃; E is the elastic modulus of rock, MPa; υ is the Poisson's ratio of rock; T f is the formation temperature difference, °C; r w is the wellbore radius, m.

12. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: In S8, based on the stress components generated by the ground stress, the drilling fluid column pressure, the pore pressure, the hydration stress, and the temperature stress, the superposition principle is adopted to calculate the stress value around the well under the coupling of mechanical-chemical-thermal-stratification; and S8 includes the following steps: G1: Assuming that the rock is a small deformation elastic body, the wellbore stress components induced by vertical stress, maximum horizontal ground stress, and minimum horizontal ground stress are calculated respectively, and superimposed as the static value of wellbore stress; G2: According to the contact time between the shale reservoir and the drilling fluid, the borehole wall stress components generated by the drilling fluid column pressure, pore pressure, hydration stress, and temperature stress are analyzed and superimposed as the dynamic value of the borehole wall stress; G3: The static and dynamic values ​​of the wellbore stress are superimposed and calculated to obtain the total wellbore stress value at different contact times between the shale oil reservoir and the drilling fluid under the coupling of force, chemical, heat and bedding.

13. The method for predicting shale oil well wall 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: H2: Using the DP strength criterion, the shear failure function of the shale matrix is ​​constructed as: H3: Using the MG-C strength criterion, the shear failure function of the shale matrix is ​​constructed as: H4: Using the modified Lade strength criterion, the shear failure function in the shale layer is constructed as: H5: Using the weak plane strength criterion, the shear failure function in the shale layer is constructed as: H6: When f i When at least one of (i=1, 2, 3, 4, 5) is less than 0, it is judged that the surrounding rock of the well wall has shear failure and the well wall is in a state of collapse and instability; when f i When both are equal to 0, it is judged that the surrounding rock of the well wall is in the critical state of shear failure and the well wall stability is in the critical state; when f i When both are greater than 0, it is judged that the surrounding rock of the well wall does not suffer shear failure and the well wall is in a stable state. Among them, in the formula, 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, α is the thermal expansion coefficient of the rock, is the weak surface internal friction angle, is the principal stress on the weak plane, is the shear strength of the weak surface, C is the cohesion, is the weak surface cohesion, η is the material constant, and a, b, and S are all constants.

14. The method for predicting shale oil well wall collapse pressure according to claim 13, characterized in that: S10 includes the following steps: I1: Assume a drilling fluid density, calculate the stress around the well and rock mechanical parameters under the coupling of force, chemical, thermal and bedding, substitute the discriminant function and conditions of shear failure of the rock matrix and weak plane around the well, and calculate f i ; I2: If f i When at least one of the following is less than -5%, the drilling fluid density is 0.01 g / cm 3 Increase, recalculate f i ; if f i When both are greater than 5%, the drilling fluid density is 0.01g / cm 3 Reduce and recalculate f i ; If -5% ≤ all f i When ≤5%, the corresponding drilling fluid density is defined as the collapse pressure equivalent density; I3: Iterative calculation to obtain the collapse pressure equivalent density range.

15. The method for predicting shale oil well wall 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 physical and chemical properties to obtain the influence of geological factors on collapse stress; J2: Simulate and calculate the wellbore collapse pressure of shale oil reservoirs at different well inclination angles 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 time, and obtain the influence of drilling fluid properties on the collapse cycle; J4: Integrate geological and engineering factors to determine the controlling factors and mechanisms of shale oil reservoir collapse pressure.

16. The method for predicting shale oil well wall collapse pressure according to claim 1, characterized in that: S12 includes the following steps: K1: Add plugging agents and hydrophobic agents, adjust the drilling fluid system, increase the density of the well wall, increase the contact angle of the drilling fluid on the rock surface, reduce the surface free energy of clay minerals, and prevent and reduce the entry of drilling fluid;. K2: Optimize the wellbore trajectory, reasonably select the inclination point and the orientation of the directional and horizontal well sections, and avoid the coincidence of the wellbore orientation with the maximum ground stress orientation to reduce the risk of wellbore instability.

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