Shale compressive strength logging prediction method

Abstract

The invention relates to a shale compressive strength logging prediction method, which comprehensively considers the influence of stratum stress, temperature and hydration, and specifically comprises the following steps of: preparing a shale standard cylindrical core, sequentially carrying out ultrasonic testing and drilling fluid hydration treatment on undisturbed shale under different temperature and confining pressure conditions, and carrying out shale compressive strength logging prediction. Performing ultrasonic testing under the same condition after the hydration to obtain longitudinal and transverse wave time difference before and after the hydration of the shale; based on hydration, after interval transit time is extracted, a shale compressive strength experiment is carried out. According to the method, the influence of stratum stress and temperature is considered, so that the prediction result is more accurate and reliable; the logging data is used for prediction, the efficiency is improved, and time consumption and high cost of laboratory testing can be reduced. The method is not only suitable for the field of petroleum and natural gas exploration, but also can be applied to the fields of geotechnical engineering, underground storage and the like, and the application range and the market potential are expanded.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of geological engineering, and particularly relates to a mud shale compressive strength logging prediction method. BACKGROUND

[0002] The present oil and gas industry is facing significant challenges in developing mud shale reservoirs. Mud shale is a type of tight rock with unique geological characteristics, its significant low porosity and low permeability characteristics make it difficult for traditional exploration and development techniques to be effectively applied. In order to more effectively utilize these difficult-to-access resources, accurate prediction of the mechanical properties of mud shale has become a key requirement, in which compressive strength is an important parameter for evaluating its mechanical behavior.

[0003] Formation stress and temperature are two major factors affecting the mechanical properties of mud shale. Formation stress, including pressure caused by geological structure and rock self-weight, directly affects the stress state and structural stability of the rock. Temperature changes affect the physical and chemical properties of the rock, such as elastic modulus and tensile strength, further affecting its compressive strength. In addition, hydration has a significant impact on the mechanical properties of mud shale. When water comes into contact with mud shale, it can cause the rock to swell, soften or weaken, thereby affecting its structural stability and compressive strength.

[0004] In the past, the compressive strength test of rock was mainly carried out in laboratory conditions, these tests are time-consuming and costly, and cannot fully consider the actual influence of formation conditions on the mechanical properties of mud shale. Laboratory tests, while providing important basic data, lack the comprehensive effects of actual underground environments, especially ignoring the influence of geological environmental factors such as hydration on the properties of mud shale. SUMMARY

[0005] The present application provides a prediction method for the compressive strength of a specific type of rock, which comprehensively considers the influence of formation stress and temperature and hydration on the mechanical properties of mud shale, uses mathematical models and physical laws to construct a prediction algorithm, thereby accurately evaluating the compressive strength of mud shale formation under actual drilling conditions.

[0006] The present application is realized by the following technical scheme:

[0007] The present application provides a mud shale compressive strength logging prediction method, which comprehensively considers the influence of formation stress, temperature and hydration, specifically including the following steps:

[0008] S1, preparing a mud shale standard cylindrical core.

[0009] S2, carrying out acoustic travel time extraction test under normal temperature and pressure conditions on the core, obtaining the longitudinal wave travel time and the transverse wave travel time under normal temperature and pressure conditions;

[0010] S3, carry out acoustic travel time extraction test under the condition of temperature and pressure on the core, and obtain the longitudinal wave travel time and the transverse wave travel time under the condition of temperature and pressure;

[0011] S4, carry out hydration treatment on the part of shale whose acoustic travel time extraction test is completed under the same temperature, the same confining pressure and different time;

[0012] S5, carry out acoustic travel time extraction test under the condition of temperature and pressure on the core after hydration treatment, and obtain the longitudinal wave travel time and the transverse wave travel time under the condition of temperature and pressure after hydration treatment;

[0013] S6, carry out rock mechanics compressive strength test on the original core and the core after hydration, and obtain the compressive strength of the core;

[0014] S7, establish a rock compressive strength prediction model which comprehensively considers the influence of formation stress, temperature, acoustic travel time and hydration;

[0015] S8, predict the compressive strength of shale based on the rock compressive strength prediction model and using logging data.

[0016] Further, S7 includes the following steps:

[0017] According to the longitudinal wave travel time, the transverse wave travel time and the compressive strength data obtained by the steps S2-S6;

[0018] Comprehensive original core test data, and establish a preliminary model of compressive strength, acoustic travel time, temperature and minimum principal stress, as follows:

[0019] σ1=f(Δt,T,σ3)

[0020] In the formula, σ1 is the compressive strength, Δt is the acoustic travel time, T is the temperature, and σ3 is the minimum principal stress;

[0021] Analyze the influence of hydration time on acoustic travel time and compressive strength, and use experimental data to introduce the attenuation coefficient of hydration time by least square method to correct the compressive strength, so as to obtain a rock compressive strength prediction model which comprehensively considers the influence of formation stress, temperature, acoustic travel time and hydration, as follows:

[0022] σ1=f(Δt,T,σ3,t)

[0023] In the formula, σ1 is the compressive strength, Δt is the acoustic travel time, T is the temperature, σ3 is the minimum principal stress, and t is the hydration time.

[0024] Optionally, the well wall stress distribution includes radial stress and tangential stress, and the well wall stress of a vertical well is expressed as:

[0025]

[0026] In the above formula, σ r is the radial stress, σ θ is the tangential stress, P p is the wellbore pressure, P o is the original in-situ stress outside the well, a is the radius of the wellbore, and r is the distance from the center of the well.

[0027] Optionally, the minimum principal stress is calculated using the following formula:

[0028]

[0029] In the above formula, σ1 is the compressive strength, σ3 is the minimum principal stress, σ2 is the intermediate principal stress, C is the cohesion, is the internal friction angle.

[0030] Optionally, the relationship between the acoustic travel time and the compressive strength of the rock under the influence of temperature, confining pressure and hydration time is simulated by the Arrhenius equation, and the simulation equation is as follows:

[0031]

[0032] In the above formula, A, B, C, D, E, and F are experimental parameter influence coefficients, σ3 is the minimum principal stress, Δt is the acoustic travel time, t is the hydration time, and T is the hydration temperature.

[0033] Preferably, the acoustic travel time, formation stress, and temperature prediction model for predicting the compressive strength of the rock is:

[0034]

[0035] In the above formula, A, B, C, D, E, and F are experimental parameter influence coefficients, σ3 is the minimum principal stress, Δt is the acoustic travel time, t is the hydration time, and T is the hydration temperature.

[0036] Optionally, S8 comprises the following steps:

[0037] Based on the logging information, the shale bottom formation temperature distribution, acoustic travel time distribution profile, and drilling and completion construction log can be directly obtained to match the downhole hydration time parameter. According to the vertical well wall stress calculation formula, the following formula is obtained:

[0038]

[0039] In the above formula, σ r is the radial stress, σ θ is the tangential stress, P p is the wellbore pressure, P ois the original stress outside the well, a is the radius of the wellbore, r is the distance from the well center. Each parameter can be directly taken from the logging curve or field data, and the radial stress and tangential stress values can be obtained by the above formula, and the smaller value of the two is the minimum principal stress, so as to obtain the minimum principal stress profile;

[0040] The minimum principal stress, acoustic time difference, temperature and hydration time distribution profile calculated from the logging information are substituted into the rock compressive strength prediction model, so as to establish the compressive strength distribution at different longitudinal positions of the formation, and complete the dynamic monitoring of the rock compressive strength.

[0041] Compared with the prior art, the present application has at least the following beneficial effects:

[0042] 1. The present application considers the influence of formation stress and temperature, so that the prediction result is more accurate and reliable;

[0043] 2. The present application uses logging data for prediction, which improves the efficiency and reduces the time-consuming and high cost of laboratory testing;

[0044] 3. The present application can more accurately predict the uniaxial compressive strength of shale by constructing a quantitative corresponding equation of shale acoustic time difference and uniaxial compressive strength under different confining pressures and temperatures, thereby improving the prediction accuracy;

[0045] 4. Since the present application uses logging data for prediction, real-time monitoring and evaluation of the mechanical properties of the formation can be realized, and timely and reliable data support can be provided for oil and gas exploration and production;

[0046] 5. The present application is not only suitable for oil and gas exploration, but also can be applied in geotechnical engineering, underground storage and other fields, which expands its application range and market potential.

[0047] Of course, implementing any of the schemes of the present application does not necessarily need to achieve all the advantages described above at the same time. BRIEF DESCRIPTION OF DRAWINGS

[0048] In order to more clearly illustrate the technical schemes of the embodiments of the present application, the following will briefly introduce the drawings needed to be used in the embodiments. It should be understood that the following drawings only show some embodiments of the present application, and therefore should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can also be obtained without creative labor on the basis of these drawings.

[0049] Figure 1 Flow chart of a shale compressive strength logging prediction method in the embodiments;

[0050] Figure 2 Degree of influence of hydration on longitudinal wave time difference of rock sample

[0051] Figure 3 Figure for the influence of hydration on the S-wave transit time of the rock sample in the example;

[0052] Figure 4 Figure for the relationship between the P-wave transit time and the compressive strength of the rock in the example;

[0053] Figure 5 Figure for the relationship between the S-wave transit time and the compressive strength of the rock in the example;

[0054] Figure 6 Figure for the influence of temperature and confining pressure on the P-wave transit time of the rock sample in the example;

[0055] Figure 7 Figure for the influence of temperature and confining pressure on the S-wave transit time of the rock sample in the example;

[0056] Figure 8 Figure for the influence of hydration time on the P-wave transit time and the compressive strength in the example;

[0057] Figure 9 Figure for the prediction of the compressive strength profile of the rock based on the model established in the example. DETAILED DESCRIPTION

[0058] In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only some of the embodiments of the present application, but not all the embodiments of the present application.

[0059] It should be noted that the embodiments and the features in the embodiments in the present application can be combined with each other without conflict. It should be noted that each embodiment in the present specification is described in a progressive manner, and each embodiment mainly describes the difference from other embodiments, and the same and similar parts in each embodiment can be referred to each other.

[0060] The present embodiment is a gray-black shale in the Longmaxi Formation of a block in Sichuan Basin, China, and the experimental sample parameter characteristics are as follows: the sampling depth is 3600-4000 m, the rock sample density is 2.56-2.70 g / cm 3The average value is 2.63 g / cm3, the horizontal minimum stress is 2.2 g / cm3, the horizontal maximum stress is 2.5 g / cm3, the formation pore pressure is 1.9 g / cm3, the acoustic wave frequency band is 100 kHz longitudinal wave at normal temperature and pressure, the longitudinal wave time difference is 190.23-206.07 μs / m, the average value is 199.58 μs / m, the oil-based drilling fluid density used for hydration treatment is 1.91-2.3 g / cm3, the viscosity is less than or equal to 90 mPa s, the oil-water ratio is 85-95%, the soaking temperature is 100 DEG C, and the soaking pressure is 3 MPa.

[0061] As shown in Figure 1 The shale compressive strength logging prediction method disclosed in the embodiment comprises the following steps:

[0062] S1, preparing a shale standard cylindrical core.

[0063] Optionally, the diameter of the standard cylindrical core is 25 mm, and the length is 40 mm.

[0064] S2, carrying out ultrasonic testing on all rock samples to be tested under indoor environmental temperature and pressure to obtain the longitudinal wave time difference and the transverse wave time difference of the rock samples to be tested.

[0065] S3, carrying out ultrasonic testing on all rock samples to be tested under different temperatures and confining pressures to obtain the longitudinal wave time difference and the transverse wave time difference of the rock samples to be tested.

[0066] Optionally, the temperature of this step can be 40 DEG C, 55 DEG C or 70 DEG C.

[0067] Optionally, the confining pressure of this step can be 10 MPa, 15 MPa or 20 MPa.

[0068] S4, according to the experimental design, part of the rock samples after acoustic wave time difference extraction are selected for drilling fluid (drilling site drilling fluid) hydration treatment, and the treatment is ensured under the same temperature, the same confining pressure environment and different time.

[0069] Optionally, the temperature of this step can be 100 DEG C.

[0070] Optionally, the confining pressure environment of this step can be 3 MPa.

[0071] Optionally, the different time of this step is divided into 24 H and 48 H.

[0072] S5, the rock samples after hydration treatment in S4 are tested according to the operation requirements in S3 to complete the extraction of the longitudinal wave time difference and the transverse wave time difference of the rock samples after hydration treatment. According to the experimental results, under the same confining pressure and temperature conditions, the longitudinal wave time difference and the transverse wave time difference are increased, as shown in Figure 2 , Figure 3 ​

[0073] S6. Conduct rock mechanical compressive strength tests on undisturbed cores and cores after hydration to obtain the compressive strength of the cores at different hydration times and the undisturbed compressive strength.

[0074] The compressive strength of the rock is obtained by using the confining pressure value (i.e., the minimum principal stress σ3) set in the experimental test, combined with the Mohr-Coulomb fracture criterion. The specific process is as follows:

[0075] S601, the compressive strength under different confining pressures can be obtained by formulating the following:

[0076]

[0077] In the above formula, σ3 is the minimum principal stress, σ1 is the compressive strength, and C is the cohesion. It is the internal friction angle.

[0078] In experiments, its strain (axial strain ε) can be used to measure this strain. a Radial strain ε r Volumetric strain ε v The change in the relationship yields the internal friction angle. As shown below:

[0079]

[0080] Based on the maximum shear stress σ at rock failure obtained directly during mechanical experiments max Normal stress σ and internal friction angle at failure The cohesion C is calculated using the following formula:

[0081]

[0082] When σ3=0, we have At this point, σ1 is called the uniaxial compressive strength.

[0083] S602. Based on classical elastic wave theory and Hooke's law, a relationship is established between the extracted acoustic transit time and the elastic parameters of the rock. The relationship between acoustic transit time and rock elastic parameters is as follows:

[0084]

[0085] In the above formula, E is the elastic modulus, ρ is the rock density, μ is Poisson's ratio, and Δt p For the P-wave time difference, Δt s This refers to the transverse wave time difference.

[0086] S603, establishes the relationship between acoustic transit time and rock compressive strength, such as Figure 4 , Figure 5 As shown; the relationship between sound wave transit time and rock compressive strength is as follows:

[0087]

[0088] S7, the hydration time is nonlinearly fitted with the acoustic time difference and the compressive strength to obtain a regression equation.

[0089] First, according to the obtained longitudinal wave time difference, transverse wave time difference and compressive strength data, the original core test data are comprehensively analyzed, and a preliminary model of the compressive strength and the acoustic time difference, temperature and confining pressure is established, as shown in the following formula:

[0090] σ1=f(Δt,T,σ3)(6)

[0091] In the above formula, σ1 is the compressive strength, Δt is the acoustic time difference, T is the temperature, and σ3 is the confining pressure (i.e. the minimum principal stress);

[0092] Then, the influence of the hydration time on the acoustic time difference and the compressive strength is analyzed, the experimental data are used, the attenuation coefficient of the hydration time is introduced by the least square method to correct the compressive strength, and thus a rock compressive strength prediction model under the conditions of the acoustic time difference, temperature, confining pressure and hydration time is obtained, as shown in the following formula:

[0093] σ1=f(Δt,T,σ3,t) (7)

[0094] In the above formula, σ1 is the compressive strength, Δt is the acoustic time difference, T is the temperature, σ3 is the minimum principal stress, and t is the hydration time.

[0095] As shown in the following formula: Figure 6 , Figure 7 The original rock sample has different performances and change trends on the acoustic time difference under the influence of temperature and confining pressure, which creates a theoretical basis for obtaining the attenuation coefficient of the hydration time on the acoustic time difference and the compressive strength parameters.

[0096] The influence of the hydration condition on the acoustic time difference is shown in the following formula: Figure 2 and Figure 3 Through part of the case data shown in Table 1, the relationship between the hydration time and the compressive strength and the acoustic time difference is obtained, as shown in the following formula: Figure 8

[0097] Table 1, measured case data (part)

[0098] Hydration time / h Time difference / ps / m Compressive strength / MPa 0 192.008 79.69942 0 195.302 71.82358 0 234.4953 66.45269 0 296.5666 63.93509 24 194.7954 52.01608 24 202.9641 48.13452 24 209.0102 47.84119 24 257.1781 46.48096 24 309.2834 44.93069 24 329.6053 44.22657 48 200.7528 44.01608 48 233.0587 40.13452 48 280.4843 36.84119 48 312.5103 35.48096 48 320.6069 34.93069 48 391.4807 33.22657

[0099] The regression equation is obtained by nonlinearly fitting the hydration time, the acoustic time difference and the compressive strength in the case data:

[0100] σ1=92.5392e -0.004167t-0.002083Δt (8)

[0101] ​In the formula, σ1 is the compressive strength, t is the hydration time, and Δt is the acoustic travel time.

[0102] The regression equation shows that the influence coefficient of hydration time is 0.004167, which is the attenuation coefficient of the compressive strength of the rock with the increase of the hydration time by 1 hour.

[0103] S7, the acoustic travel time and the formation temperature of the actual logging curve are extracted, and the formation pressure vertical distribution is obtained according to the hydration time and the specific situation on site.

[0104] The wellbore stress distribution considers the radial and tangential stresses, and the wellbore stress can be obtained by Kirsch equations. For a vertical well, it can be expressed as:

[0105]

[0106] In the formula, σ r is the radial stress, σ θ is the tangential stress, P p is the wellbore pressure, P o is the original in-situ stress outside the well, a is the radius of the wellbore, and r is the distance from the well center.

[0107] Through the analysis of the distribution of the wellbore stress, the direction and size of the minimum principal stress are determined by combining the Mohr-Coulomb failure criterion, which can be expressed as:

[0108]

[0109] In the formula, σ1 is the compressive strength, σ3 is the minimum principal stress, σ2 is the intermediate principal stress, C is the cohesion, is the internal friction angle.

[0110] S8, according to the temperature and the minimum principal stress distribution of the shale formation, and the quantitative corresponding equation of the shale acoustic travel time and triaxial compressive strength under different confining pressures and temperatures established in the laboratory (formula (12)).

[0111] First, the relationship between the acoustic travel time and the compressive strength of the rock under the influence of hydration time under the action of temperature and confining pressure is simulated by the Arrhenius equation, and the simulation equation is as follows:

[0112]

[0113] In the formula, A, B, C, D, E, and F are experimental parameter influence coefficients, σ3 is the minimum principal stress, Δt is the acoustic travel time, t is the hydration time, and T is the hydration temperature.

[0114] In combination with the Kirsch equation (formula (9)), the Mohr-Coulomb failure criterion (formula (10)) and the Arrhenius equation (formula (11)) in the step S8 above, a rock compressive strength prediction model is established, and the real-time rock compressive strength of the wellbore surrounding rock can be obtained. The calculation method is introduced into the logging curve to establish the rock compressive strength profile.

[0115] The case test data are shown in Table 2 as follows:

[0116] Table 2, measured case data (part)

[0117]

[0118]

[0119] Note: In Table 2, the hydration time of 0 means the original state of the core.

[0120] By using the experimental data to fit the values of the influence coefficients B and D determined by the temperature and confining pressure conditions and the values of the remaining constant terms, the rock compressive strength prediction model is obtained as follows:

[0121]

[0122] In the above formula, σ3 is the minimum principal stress, Δt is the acoustic time difference, t is the hydration time, and T is the hydration temperature.

[0123] The regression equation indicates the relationship between the influence coefficient of the coupling of temperature and confining pressure and the acoustic time difference and the rock compressive strength. When the influence factor changes by one unit, the corresponding compressive strength decays exponentially.

[0124] Using the field acoustic time difference logging data, the minimum principal stress and the temperature distribution calculated from other data, and the quantitative equation in the step S8, the compressive strength of the shale at different depths can be calculated, the shale compressive strength logging prediction considering the formation stress and temperature influence is realized, and the shale formation compressive strength distribution profile is established. The calculated case is applied in the actual logging curve as shown in Figure 9 , and the rock compressive strength profile is established.

[0125] The present embodiment comprehensively considers the influence of temperature and confining pressure on shale acoustic travel time and the damage effect of hydration on rock compressive strength, and forms a shale rock compressive strength prediction model using acoustic travel time. This method can not only accurately predict the compressive strength of shale, but also comprehensively consider the influence of factors such as formation stress, temperature and hydration. This method will provide important technical support for the effective development of shale reservoirs, help optimize drilling and production strategies, reduce development risks, and improve oil and gas recovery. By more accurately assessing the mechanical properties and stability of shale, more scientific and economic exploration and development plans can be implemented, contributing to the sustainable development of the oil and gas industry.

[0126] The above merely describes the preferred embodiments of the present application, and is not intended to limit the present application. The present application can have various modifications and changes for those skilled in the art. Any modification, equivalent replacement, improvement, etc. within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method of predicting compressive strength of shale from well logs, characterized by, The method comprises the following steps: S1, preparing a shale standard cylindrical core. S2, performing acoustic travel time extraction testing on the core under normal temperature and pressure conditions to obtain the longitudinal wave travel time and the transverse wave travel time under the normal temperature and pressure conditions; S3, performing acoustic travel time extraction testing on the core under temperature and pressure conditions to obtain the longitudinal wave travel time and the transverse wave travel time under the temperature and pressure conditions; S4, performing hydration treatment on part of the shale whose acoustic travel time extraction testing is completed under the same temperature, the same confining pressure and different times; S5, performing acoustic travel time extraction testing on the core after the hydration treatment under the temperature and pressure conditions to obtain the longitudinal wave travel time and the transverse wave travel time under the temperature and pressure conditions after the hydration treatment; S6, performing rock mechanics compressive strength testing on the original core and the core after the hydration to obtain the compressive strength of the core; S7, establishing a rock compressive strength prediction model which comprehensively considers the influences of the formation stress, the temperature, the acoustic travel time and the hydration; S8, predicting the shale compressive strength by using logging data based on the rock compressive strength prediction model.

2. The method of predicting the compressive strength of shale according to claim 1, wherein S7 comprises the following steps: obtaining the longitudinal wave travel time, the transverse wave travel time and the compressive strength data according to the steps S2-S6; comprehensively establishing a preliminary model of the compressive strength, the acoustic travel time, the temperature and the minimum principal stress by using the original core testing data, as shown in the following formula: σ1=f(Δt,T,σ3) In the above formula, σ1 is the compressive strength, Δt is the acoustic travel time, T is the temperature and σ3 is the minimum principal stress; analyzing the influences of the hydration time on the acoustic travel time and the compressive strength, introducing the attenuation coefficient of the hydration time by using the least square method to correct the compressive strength, and thus obtaining the rock compressive strength prediction model which comprehensively considers the influences of the formation stress, the temperature, the acoustic travel time and the hydration, as shown in the following formula: σ1=f(Δt,T,σ3,t) In the above formula, σ1 is the compressive strength, Δt is the acoustic travel time, T is the temperature, σ3 is the minimum principal stress and t is the hydration time.

3. The method of predicting the compressive strength of shale according to claim 1 or 2, characterized in that, The wellbore stress distribution includes the radial stress and the tangential stress, and the wellbore stress of a vertical well is expressed as: In the above equation, σ r is the radial stress, σ θ is the tangential stress, P p is the wellbore pressure, P o is the original in-situ stress outside the well, a is the radius of the wellbore, and r is the distance from the center of the well.

4. The method of predicting the compressive strength of shale according to claim 1 or 2, characterized in that, The minimum principal stress is calculated by using the following formula: In the above formula, σ1 is the compressive strength, σ3 is the minimum principal stress, σ2 is the intermediate principal stress, C is the cohesion, is the internal friction angle.

5. The method of predicting the compressive strength of shale according to claim 1 or 2, wherein The relationship between the acoustic travel time and the rock compressive strength under the influences of the temperature, the confining pressure and the hydration time is simulated by using the Arrhenius equation, and the simulation equation is as follows: In the above formula, A, B, C, D, E and F are experimental parameter influence coefficients, σ3 is the minimum principal stress, Δt is the acoustic travel time, t is the hydration time and T is the hydration temperature.

6. The method of predicting the compressive strength of shale according to claim 4, wherein The rock compressive strength prediction model which predicts the rock compressive strength by using the acoustic travel time, the formation stress and the temperature is as follows: In the above formula, A, B, C, D, E and F are experimental parameter influence coefficients, σ3 is the minimum principal stress, Δt is the acoustic travel time, t is the hydration time and T is the hydration temperature.

7. The method of predicting the compressive strength of shale according to claim 1, wherein S8 comprises the following steps: The shale bottom formation temperature distribution and the acoustic travel time distribution profile can be directly obtained based on the logging information, and the downhole hydration time parameter can be matched by using the drilling and completion log. Then, the shale wellbore stress distribution profile is obtained by using the above vertical well wellbore stress calculation formula. The minimum principal stress distribution is determined according to the shale formation wellbore stress distribution; The minimum principal stress acoustic time, temperature and hydration time distribution profiles calculated from the logging information are substituted into the rock compressive strength prediction model, thereby establishing the compressive strength distribution at different positions in the vertical direction of the formation, and completing dynamic monitoring of the rock compressive strength.

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