Method for constructing shale temperature-pressure model based on logging information and its application

Abstract

The present invention discloses a method for constructing a shale temperature-pressure model based on logging information and its application. The model construction method includes: constructing a shale matrix microscopic geometric distribution model; obtaining the values of shale compaction geometric parameters based on the microscopic geometric distribution model and logging information; constructing a shale temperature-pressure model based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity; substituting the obtained values of the shale compaction geometric parameters into the shale temperature-pressure model after determining the fitting parameters to obtain the shale temperature-pressure model based on logging information. The present invention can process the logging information to extract the temperature-pressure elastic parameters of shale, which can not only support the subsequent forward and inverse inversion technologies, but also prepare for the scientific analysis of the elastic characteristics of shale.

Description

Technical Field

[0001] The present invention relates to the technical field of geological exploration, and more particularly to the technical field of a method for calculating the elastic stiffness matrix of mudstone. Background Art

[0002] According to Hooke's law, the linear change coefficient between stress and strain is a characterization parameter for describing the elasticity of an object. The elastic characteristics of a complete object can be represented by elastic coefficients corresponding to stress and strain in 81 different directions. For underground media, it can be simplified to 27 elastic parameters. The petrophysical model for mudstone can be further simplified to 5 independent elastic parameters based on its sedimentary characteristics. According to the corresponding stress surfaces and forces, these 5 independent elastic coefficients can be placed into a standard 6×6 stiffness matrix, thereby obtaining the elastic stiffness matrix of mudstone.

[0003] On the other hand, the main geophysical exploration techniques include core experiments, logging, and seismic methods. In these three techniques, the acoustic wave velocity can be measured. Therefore, using the acoustic wave velocity and combining the interpretations of various geophysical exploration methods can greatly improve the persuasiveness and accuracy of data analysis results.

[0004] From a microscopic perspective, the propagation of acoustic waves in rocks is a process of continuous transmission of medium vibrations. The ability of medium vibration transmission is determined by the elastic stiffness matrix, and the vibration ability of rocks can be converted into acoustic wave velocity. Therefore, the acoustic wave velocity can be obtained based on the stiffness matrix. If the stiffness matrices obtained from the results using the petrophysical model in rock elastic experiments, seismic exploration, and logging exploration are consistent, it indicates that the three methods have obtained reliable results and a scientific petrophysical model. Based on the scientific petrophysical model, the most important pore permeability parameters in current resource exploration, such as porosity, permeability, and saturation, can be further extracted. In addition, the stiffness matrix is also a characterization of rock strength and can be used to describe the stability of underground structures in engineering exploration. At the same time, the elastic stiffness matrix plays a huge role in the accuracy of forward and inverse modeling in geophysics and can also be an important reference object for time-lapse seismic inversion laws.

[0005] Currently, the temperature and pressure testing techniques for mudstone are not yet mature, resulting in difficulties in obtaining the elastic stiffness matrix of mudstone. At the same time, there is a lack of a dedicated temperature-pressure elastic model for mudstone in the existing technology, and the elastic parameters obtained by extrapolating through general temperature-pressure models are not reliable.

[0006] In addition, in the prior art, the methods for obtaining the elastic parameters of rock materials include: (1) directly measuring the elastic parameters through elastic tests, which are costly, require extremely high equipment and core quality, have a very strong correspondence in the obtained test laws, are only applicable to specific work areas, have high requirements for personnel operation ability, low test repeatability, and low fault tolerance; (2) establishing shale parameters at normal temperature and pressure through general rock physics elastic models, converting the parameters into acoustic velocities, and then using a velocity-temperature-pressure model that characterizes the relationship between velocity and temperature and pressure to calculate the velocity corresponding to shale and temperature and pressure, and obtaining the elastic parameters through velocity conversion. In this method, most of the velocity-temperature-pressure models are empirical models with poor analytical ability, and the reliability of the method lacks theoretical support and needs to be verified. Moreover, in fact, there are many influencing factors of velocity, and temperature and pressure are not the only control factors, which may result in a large number of unreliable errors in the obtained results. Summary of the Invention

[0007] Aiming at the defects of the prior art, the object of the present invention is to propose a method for constructing an effective and reliable shale temperature-pressure model, and to propose a method for accurately obtaining the elastic stiffness matrix of shale at different temperatures and pressures through this temperature-pressure model.

[0008] The technical solution of the present invention is as follows:

[0009] A method for constructing a shale temperature-pressure model based on logging information, which includes:

[0010] S1 Construct a microscopic geometric distribution model of shale matrix based on the shale matrix direction distribution function, and the microscopic geometric distribution model refers to an equivalent mathematical model representing the arrangement and combination of shale microscopic structural units;

[0011] S2 Based on the microscopic geometric distribution model and logging information, obtain the values of shale compaction geometric parameters, and the shale compaction geometric parameters refer to the equivalent parameters of the microscopic geometric distribution model corresponding to the shale microscopic structure under sedimentary compaction, and specifically include:

[0012] S21 Based on the microscopic geometric distribution model, obtain the matrix direction distribution function of shale under compaction containing shale compaction geometric parameters;

[0013] S22 Based on the matrix direction distribution function of shale under compaction containing shale compaction geometric parameters, construct a shale velocity model containing shale velocity and the first fitting parameter;

[0014] S23 Determine the fitting parameters of the shale velocity model through the shale velocity and shale geometric parameters obtained by experiments, and obtain the shale velocity model after the fitting parameters are determined;

[0015] S24 Substitute the shale interval velocity obtained from the logging information into the shale velocity model after determining the fitting parameters to obtain the value of the shale compaction geometric parameter;

[0016] S3 Based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity, construct a shale temperature-pressure model, which specifically includes:

[0017] S31 Based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity, construct a shale temperature-pressure model including shale compaction geometric parameters, temperature, pressure, and the second fitting parameter;

[0018] S32 Determine the fitting parameters of the shale temperature-pressure model through the temperature and pressure obtained by experiments to obtain the shale temperature-pressure model after determining the fitting parameters;

[0019] S4 Substitute the value of the obtained shale compaction geometric parameter into the shale temperature-pressure model after determining the fitting parameters to obtain the shale temperature-pressure model based on the logging information.

[0020] According to some preferred embodiments of the present invention, the shale matrix microscopic geometric distribution model is constructed as follows:

[0021]

[0022]

[0023] where ξ, ψ, φ respectively represent the angles between the xoy plane and the XOY plane, the xoz plane and the XOZ plane, and the yoz plane and the YOZ plane formed by two coordinate axis systems when the shale matrix spreads in three-dimensional space. The two coordinate axis systems include: a spatial coordinate axis system (x, o, y) with the positive up, down, front, back, left, and right in space as the coordinate axes, and an object coordinate axis system (X, O, Y) with the positive up, down, front, back, left, and right of the matrix object in space as the coordinate axes. w(ξ, ψ, φ) represents the direction distribution function of the shale matrix, and W lmn represents the Legendre coefficient corresponding to the spherical harmonic function, and Z lmn (ξ) represents the spherical harmonic function expanded based on the ξ angle, e represents the natural exponent, i represents the imaginary unit, and l, m, n are the Legendre coefficients corresponding to the expansion function.

[0024] According to some preferred embodiments of the present invention, the matrix direction distribution function under shale compaction is as follows:

[0025]

[0026] where W(ξ) represents the distribution function expanded based on the ξ angle, and A represents the shale compaction geometric parameter.

[0027] According to some preferred embodiments of the present invention, the shale velocity model is constructed as follows:

[0028] A = ((V P / 1000 - Ac1) / (Bc1))^(-1) (13)

[0029] where Ac1 and Bc1 are the first fitting parameters, A is the shale compaction geometric parameter, and V P is the P-wave velocity of the shale.

[0030] According to some preferred embodiments of the present invention, the shale temperature and pressure model is constructed as follows:

[0031] A = (Ac2 * P + Bc2) * exp((Ac3 * P + Bc3) * T) + (Ac4 * P + 0.027) (14)

[0032] where A is the shale compaction geometric parameter, T represents temperature, P represents pressure, and Ac2, Ac3, Ac4, Bc2, and Bc3 are the second fitting parameters.

[0033] The present invention further provides an application method of the method for constructing the shale temperature and pressure model based on the above logging information, which is to obtain the elastic stiffness matrix of the shale according to the shale temperature and pressure model based on the logging information.

[0034] According to some preferred embodiments of the present invention, the application method includes:

[0035] S51 Construct a temperature and pressure model for the shale section of the conventional logging;

[0036] S52 Based on the temperature and pressure model of the shale section, obtain the values of the temperature and pressure of the shale section through the conventional logging data;

[0037] S53 Substitute the values of the temperature and pressure of the shale section into the shale temperature and pressure model based on the logging information to obtain the shale compaction geometric parameter A of the shale section;

[0038] S54 Obtain the stiffness matrix of the shale according to the shale compaction geometric parameter A of the shale section.

[0039] According to some preferred embodiments of the present invention, the temperature and pressure model of the shale section is constructed as follows:

[0040] Pressure model:

[0041] Pz == MD * ρ * g; (15)

[0042] Ppore = MD * ρ_fluid * g * Pcoeffcient (16)

[0043] P = Pz - Ppore (17)

[0044] Wherein, Pz, Ppore, and P respectively represent the overburden pressure, formation pressure, and effective pressure; ρ and ρ_fluid respectively represent the overburden rock density and fluid density; Pcoeffcient represents the formation pressure coefficient; MD represents the depth; and g represents the acceleration due to gravity.

[0045] Temperature model:

[0046] T = Tcoeffcient * (MD - MD 0 ) / 100 + T 0 (18)

[0047] Wherein, T represents the temperature, Tcoeffcient represents the temperature gradient, MD 0 represents the depth of the target layer, and T 0 represents the temperature of the target layer.

[0048] According to some preferred embodiments of the present invention, the application method includes: obtaining the elastic parameters of the elastic stiffness matrix through the following calculation model:

[0049]

[0050]

[0051]

[0052]

[0053]

[0054]

[0055] Wherein:

[0056]

[0057]

[0058]

[0059]

[0060]

[0061] Wherein, C aThe stiffness tensor with the spatial coordinate axes of the mudstone completely aligned with the object coordinate axes. The spatial coordinate axes extend in the directions of positive up, down, front, back, left, and right in space, and the object coordinate axes extend in the directions of positive up, down, front, back, left, and right of the matrix object in space; a 1 、a 2 、a 3 、L, M are matrix elastic parameters; C 11 、C 12 、C 13 、C 33 、C 44 are five independent elastic parameters of the microstructure of the small mudstone plate, and C 66 represents the elastic parameters that can be mutually replaced by C 11 、C 12 .

[0062] The present invention has the following beneficial effects:

[0063] The present invention can process the logging information to extract the temperature-pressure elastic parameters of the mudstone, which can not only support the subsequent forward and inverse modeling techniques, but also prepare for the scientific analysis of the elastic characteristics of the mudstone, and is more scientific and has lower cost compared with other methods.

[0064] The present invention can obtain a scientific temperature-pressure mudstone model based on logging and core rock physics experiments, and can simultaneously verify the reliability of the model parameters based on logging, core, and seismic tests, without the need for additional temperature-pressure experiments, greatly saving costs.

[0065] The elastic parameters extracted by the present invention can provide very necessary technical and application support for the subsequent extraction of porosity, permeability, and saturation parameters, four-dimensional seismic analysis, and seismic forward and inverse modeling techniques. BRIEF DESCRIPTION OF THE DRAWINGS

[0066] Figure 1 is a schematic flow chart for obtaining an elastic stiffness matrix through a mudstone temperature-pressure model in the specific implementation manner.

[0067] Figure 2 is a microscopic geometric distribution model of the mudstone matrix in the specific implementation manner.

[0068] Figure 3 is a schematic diagram of the three-dimensional angles of crystals in the microscopic geometric distribution model involved in the specific implementation manner.

[0069] Figure 4 is a comparison diagram of the predicted elastic results obtained in Example 1 and the measured longitudinal wave velocity elastic results.

[0070] Figure 5 is a calibration result diagram of the mudstone temperature-pressure model of the geometric parameter A obtained in Example 1. SPECIFIC IMPLEMENTATION MANNER

[0071] The present invention will be described in detail below in conjunction with embodiments and the accompanying drawings. However, it should be understood that the embodiments and the drawings are only used for exemplary description of the present invention, and cannot constitute any limitation to the protection scope of the present invention. All reasonable transformations and combinations within the scope of the inventive concept of the present invention fall within the protection scope of the present invention.

[0072] Referring to the attached Figure 1 , according to the technical solution of the present invention, some specific embodiments of the method for constructing a shale temperature and pressure model based on logging information include the following steps:

[0073] S1 Construct a microscopic geometric distribution model of the shale matrix, where the microscopic geometric distribution model is an equivalent mathematical model representing the arrangement and combination of microscopic structural units of the shale.

[0074] S2 Based on the microscopic geometric distribution model and logging information, obtain the shale compaction geometric parameter A, where the shale compaction geometric parameter is an equivalent parameter of the microscopic geometric distribution model corresponding to the microscopic structure of the shale under sedimentary compaction.

[0075] Specifically, it includes:

[0076] S21 Based on the microscopic geometric distribution model, obtain the matrix direction distribution function of the shale under compaction containing the shale compaction geometric parameter A.

[0077] S22 Based on the matrix direction distribution function of the shale under compaction containing the shale compaction geometric parameter A, construct a shale velocity model function1 containing shale velocity and the first fitting parameter.

[0078] S23 Determine the fitting parameters of the shale velocity model through the shale velocity and shale geometric parameters obtained from the core microscopic structure measurement experiment, and obtain the shale velocity model function1 after determining the fitting parameters.

[0079] S24 Substitute the shale section velocity obtained from the logging information into the shale velocity model function1 after determining the fitting parameters to obtain the shale compaction geometric parameter A.

[0080] S3 Based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity, construct a shale temperature and pressure model function2, where the temperature and pressure model is a calculation model for calculating the parameters corresponding to the microscopic structure of the shale under the corresponding temperature and pressure using temperature and pressure.

[0081] Specifically, it includes:

[0082] S31 constructs the shale temperature and pressure model function2 containing the shale compaction geometric parameter A, temperature, pressure, and the second fitting parameter based on the micro-geometric distribution model and the conversion of the stiffness matrix and velocity;

[0083] S32 determines the fitting parameters of the shale temperature and pressure model through the temperature and pressure obtained from the temperature and pressure measurement experiment, and obtains the shale temperature and pressure model function2 after the fitting parameters are determined;

[0084] S4 substitutes the obtained shale compaction geometric parameter A into the shale temperature and pressure model function2 after the fitting parameters are determined, and obtains the shale temperature and pressure model based on the logging information.

[0085] The logging information includes: the velocity in the shale section, and the temperature and pressure in the shale section, which can be obtained through formation temperature and pressure logging

[0086] Further, according to some preferred embodiments of the present invention, the logging information includes: the velocity in the shale section, and the temperature and pressure in the shale section, which can be obtained through formation temperature and pressure logging, wherein the shale section refers to the section greater than 80% in the logging VSH curve or the shale section interpreted in the logging interpretation.

[0087] Further, referring to the appendix Figure 1 , some specific embodiments of the method for obtaining the elastic stiffness matrix based on the obtained shale temperature and pressure model based on the logging information include the following steps:

[0088] S51 constructs the temperature and pressure model of the shale section in the conventional logging;

[0089] S52 obtains the temperature and pressure of the shale section through the conventional logging data based on the temperature and pressure model of the shale section;

[0090] S53 substitutes the temperature and pressure of the shale section into the shale temperature and pressure model based on the logging information, and obtains the shale compaction geometric parameter A of the shale section;

[0091] S54 obtains the stiffness matrix of the shale according to the shale compaction geometric parameter A of the shale section.

[0092] Further, referring to the appendix Figure 2 , in some preferred embodiments, in S1, the microstructure and direction of the shale matrix in the three-dimensional space can be equivalently represented by two polar coordinate axes in the space coordinate system, one of which is the space coordinate axis (x, o, y) with the positive up, down, front, back, left, and right of the space as the coordinate axes, and the other is the object coordinate axis (X, O, Y) with the positive up, down, front, back, left, and right of the object as the coordinate axes.

[0093] Therefore, the direction function of the shale can be expressed as:

[0094]

[0095] Among them, ξ, ψ, and φ respectively represent the angles between the xoy and XOY, xoz and XOZ, and yoz and YOZ planes in two coordinate axis systems. w(ξ, ψ, φ) is the directional distribution function of the shale matrix, which can be expanded into a series of angle-related spherical harmonic functions through Roe's X-ray diffraction data (Roe RJ. Description Of Crystallite Orientation In Polycrystalline Materials. Iii. General Solution To Pole Figure Inversion[J]. Journal Of Applied Physics, 1965, 36(6):204 - 221) as follows:

[0096]

[0097] Among them, W lmn represents the Legendre coefficient corresponding to the spherical harmonic function, Z lmn (ξ) represents the spherical harmonic function expanded based on the ξ angle, e represents the natural exponential, i represents the imaginary unit, and l, m, n are the Legendre coefficients corresponding to the expansion function (Roe, 1965).

[0098] Furthermore, it can be inversely deduced that:

[0099]

[0100] Furthermore, referring to the appendix Figure 3 , in some preferred embodiments, according to the above microscopic geometric distribution model, in S21, the process of obtaining the directional distribution function of the matrix under shale compaction containing the shale compaction geometric parameter A is as follows:

[0101] According to Sayers' method (Sayers C M. Anisotropic Velocity Analysis[J]. Geophysical Prospecting, 1995, 43(4):541 - 568.), after assuming that the matrix after shale compaction is a transversely isotropic medium and supplementing the stress characteristics of the shale during compaction, the relationship between the average stiffness tensor of the shale small plate and the Legendre coefficients (W 400 , W 200 ) of two spherical harmonic functions related to the plane is as follows:

[0102]

[0103]

[0104]

[0105]

[0106]

[0107]

[0108] Wherein:

[0109]

[0110]

[0111]

[0112]

[0113]

[0114] Wherein, C a is the stiffness tensor with the spatial coordinate axes of the mudstone completely aligned with the object coordinate axes, that is, the stiffness tensor of the mudstone small plate without directional arrangement itself, a 1 , a 2 , a 3 , L, M are matrix elastic parameters, which can be obtained from the stiffness tensor of the mudstone matrix (the mudstone matrix can generally be directly measured by logging or rock physics experiments), C 11 , C 12 , C 13 , C 33 , C 44 are five independent elastic parameters of the microstructure of the mudstone small plate, C 66 represents the elastic parameter in which C 11 and C 12 are interchangeable

[0115] Wherein, for the VTI medium of mudstone (transversely isotropic medium with a vertical symmetry axis), W 200 and W 400 can be expressed as:

[0116]

[0117]

[0118] Where P l , l = 2 or 4 is the Legendre polynomial of order l, and its expression is:

[0119]

[0120]

[0121] Then, for the distribution function under the compaction of general mudstone, it conforms to the following formula:

[0122]

[0123] Among them, W(ξ) represents the distribution function expanded based on the angle ξ, and A is the compaction geometric parameter of the mudstone. This formula can establish the functional relationship between the compaction geometric parameter A of the mudstone and the stiffness matrix.

[0124] Furthermore, in some preferred embodiments, in S22, the mudstone velocity model is constructed as follows:

[0125] Convert the stiffness matrix to a velocity quantity as follows:

[0126]

[0127] Among them, ρ is the mudstone density, V p is the longitudinal wave velocity of the mudstone, and Vs is the shear wave velocity of the mudstone;

[0128] Furthermore, the relational expression between process A and velocity in (1)-(12) can be simplified to function1, and function1 is as follows:

[0129] A = ((V P / 1000 - Ac1) / (Bc1))^(-1) (13)

[0130] Among them, Ac1 and Bc1 are fitting parameters, which can be obtained through core microstructure measurement experiments, such as geometric parameter A obtained by measuring the aspect ratio in the mudstone microstructure based on GB / T23413-2009 or directly measuring the aspect ratio of mudstone thin-film crystals from thin-film analysis; V P is the longitudinal wave velocity of the mudstone, which is the velocity measured corresponding to the mudstone core or the mudstone velocity measured by logging at the corresponding depth of the mudstone core.

[0131] Furthermore, in some preferred embodiments, in S31, the mudstone temperature-pressure model function2 is constructed as follows:

[0132] A = (Ac2 * P + Bc2) * exp((Ac3 * P + Bc3) * T) + (Ac4 * P + 0.027) (14)

[0133] Among them, T represents temperature, P represents pressure, and Ac2, Ac3, Ac4, Bc2, and Bc3 are fitting parameters.

[0134] Furthermore, in some preferred embodiments, S32 includes:

[0135] The temperature and pressure obtained from daily logging are fitted with A, and the parameters Ac2, Ac3, Ac4, Bc2, and Bc3 are inversely calculated, so as to obtain the temperature-pressure model determined by the fitting parameters of the mudstone.

[0136] Furthermore, in some preferred embodiments, in S51, the temperature and pressure models of the mudstone section are constructed as follows:

[0137] Pressure model:

[0138] Pz == MD * ρ * g; (15)

[0139] Ppore = MD * ρ_fluid * g * Pcoeffcient (16)

[0140] P = Pz - Ppore (17)

[0141] Wherein, Pz, Ppore, and P are the overburden pressure, formation pressure, and effective pressure respectively, ρ and ρ_fluid are the overburden rock density and fluid density, Pcoeffcient is the formation pressure coefficient, MD is the depth, and g is the acceleration due to gravity;

[0142] Temperature model:

[0143] T = Tcoeffcient * (MD - MD 0 ) / 100 + T 0 (18)

[0144] Wherein, T is the temperature, Tcoeffcient is the temperature gradient, MD 0 is the depth of the target layer, and T 0 is the temperature of the target layer.

[0145] Furthermore, using the obtained P, T, and the temperature-pressure model function2 based on logging information, the mudstone geometric parameter A of other wells can be obtained. Through A, the elastic stiffness matrix of the mudstone in logging can be calculated.

[0146] According to the above specific embodiments, the present invention can obtain the mudstone velocity VP corresponding to the mudstone compaction geometric parameter A through the mudstone velocity model shown in formula (13) according to the mudstone core and imaging logging information in the work area, and through the mudstone velocities VP corresponding to multiple mudstone compaction geometric parameters A, inversely obtain the fitting parameters Ac1 and Bc1 in the mudstone velocity model, and obtain the modified mudstone velocity model.

[0147] According to the above specific embodiments, the present invention can extract the acoustic velocity, logging interpretation conclusion, and shale content from one or two logs with pressure and temperature parameters in the work area.

[0148] According to the above specific embodiments, in the shale section of the obtained logging interpretation conclusion (if there is no interpretation data, the section with a shale content greater than 95% can be selected), the shale compaction geometric parameter A can be obtained by using the shale velocity model conversion, so as to obtain a series of shale compaction geometric parameters A corresponding to temperature and pressure. After substituting into Equation (14), the parameters Ac2, Ac3, Ac4, Bc2, and Bc3 can be obtained by inverse calculation, and the corrected shale temperature-pressure model can be obtained.

[0149] According to the above specific embodiments, the present invention can substitute the temperature and pressure obtained from any conventional logging into Equations (15)-(18), and use the corrected shale temperature-pressure model to obtain the geometric parameter A.

[0150] According to the above specific embodiments, the present invention can use the geometric parameter A to inversely calculate C in the reverse order of Equations (1)-(12). 11 、C 33 、C 12 、C 13 、C 44 、C 66 。

[0151] Example 1

[0152] According to the above specific embodiments, the parameters of the elastic stiffness matrix are obtained as follows:

[0153] The corresponding VP is obtained from the formation with VSH>0.8, and the A parameter corresponding to VP is obtained by referring to the XRD microscopic test of the existing cores within the corresponding depth. The shale matrix stiffness tensor is obtained from the regional background data. The three parameters corresponding to the depths of all shale cores within the VSH>0.8 section are used to calibrate Function1 together, and the calibration results are as shown in the appendix. Figure 5 shown. The T and P of the target layer in the work area are obtained by referring. The temperature and pressure of the target layer are extended to the depths corresponding to all shale cores within the previous VSH>0.8 section by using Equations (15)-(18), and then T, P, and A are used to calibrate function2 together. The temperature and pressure of any layer section are calculated by using Equations (15)-(18), and then A is obtained by converting T and P by using function2. The rock velocity vp_rock diagram can be calculated by using function1, as shown in Figure 4 shown. It can be seen that the difference between the vp_rock and vp curves is small, and it is considered that the parameters and process of this model are scientific and reliable. Further, by combining A with Equations (7), (8), (9), (10), and (11), W 200 ,W 400 can be obtained, and then the stiffness tensor of the shale small plate can be obtained by using (1)-(5).

[0154] The above embodiments are only the preferred embodiments of the present invention, and the protection scope of the present invention is not limited to the above embodiments. All technical solutions falling within the concept of the present invention belong to the protection scope of the present invention. It should be noted that for those of ordinary skill in the art, improvements and refinements made without departing from the principle of the present invention should also be regarded as within the protection scope of the present invention.

Claims

1. Method for constructing shale temperature and pressure model based on logging information, characterized in that, it includes: S1 Construct a microscopic geometric distribution model of shale matrix based on the shale matrix direction distribution function, and the microscopic geometric distribution model refers to an equivalent mathematical model representing the arrangement and combination of shale microscopic structural units; S2 Based on the microscopic geometric distribution model and logging information, obtain the values of shale compaction geometric parameters, and the shale compaction geometric parameters refer to the equivalent parameters of the microscopic geometric distribution model corresponding to the shale microscopic structure under sedimentary compaction, and specifically include: S21 Based on the microscopic geometric distribution model, obtain the matrix direction distribution function under shale compaction containing shale compaction geometric parameters; S22 Based on the matrix direction distribution function under shale compaction containing shale compaction geometric parameters, construct a shale velocity model containing shale velocity and the first fitting parameter; S23 Determine the fitting parameters of the shale velocity model through the shale velocity and shale geometric parameters obtained by experiments to obtain the shale velocity model after determining the fitting parameters; S24 Substitute the shale section velocity obtained from the logging information into the shale velocity model after determining the fitting parameters to obtain the values of the shale compaction geometric parameters; S3 Based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity, construct a shale temperature and pressure model, which specifically includes: S31 Based on the microscopic geometric distribution model and the conversion between the stiffness matrix and velocity, construct a shale temperature and pressure model containing shale compaction geometric parameters, temperature, pressure and the second fitting parameter; S32 Determine the fitting parameters of the shale temperature and pressure model through the temperature and pressure obtained by experiments to obtain the shale temperature and pressure model after determining the fitting parameters; S4 Substitute the obtained values of the shale compaction geometric parameters into the shale temperature and pressure model after determining the fitting parameters to obtain the shale temperature and pressure model based on logging information.

2. The method for constructing a shale temperature and pressure model based on logging information according to claim 1, characterized in that, the construction of the microscopic geometric distribution model of the shale matrix is as follows: Among them, ξ, ψ, and φ respectively represent the angles between the xoy plane and the XOY plane, the xoz plane and the XOZ plane, and the yoz plane and the YOZ plane formed by two coordinate axis systems when the mudstone matrix is distributed in three-dimensional space. The two coordinate axis systems include: a spatial coordinate axis system (x, o, y) with the positive up, down, front, back, left, and right in space as the coordinate axes, and an object coordinate axis system (X, O, Y) with the positive up, down, front, back, left, and right of the matrix object in space as the coordinate axes. w(ξ, ψ, φ) represents the directional distribution function of the mudstone matrix, and W lmn represents the Legendre coefficient corresponding to the spherical harmonic function, and Z lmn (ξ) represents the spherical harmonic function expanded based on the ξ angle, e represents the natural exponent, i represents the imaginary unit, and l, m, and n are the Legendre coefficients corresponding to the expansion function.

3. The method for constructing a shale temperature and pressure model based on logging information according to claim 2, characterized in that, the matrix direction distribution function under shale compaction is as follows: where W(ξ) represents the distribution function expanded based on the ξ angle, and A represents the shale compaction geometric parameter.

4. The method for constructing a shale temperature and pressure model based on logging information according to claim 1, characterized in that, the construction of the shale velocity model is as follows: A = ((V P / 1000 - Ac1) / (Bc1))^(-1) (13) Among them, Ac1 and Bc1 are the first fitting parameters, A is the shale compaction geometric parameter, and V P is the P-wave velocity of the shale.

5. The method for constructing a shale temperature and pressure model based on logging information according to claim 1, characterized in that, the construction of the shale temperature and pressure model is as follows: A=(Ac2*P + Bc2)*exp((Ac3*P + Bc3)*T)+(Ac4*P + 0.027)(14) where A is the shale compaction geometric parameter, T represents temperature, P represents pressure, and Ac2, Ac3, Ac4, Bc2, Bc3 are the second fitting parameters.

6. The application method of the shale temperature and pressure model construction method based on well logging information according to any one of claims 1-5, which is to obtain the elastic stiffness matrix of shale according to the shale temperature and pressure model based on well logging information.

7. According to the application method described in claim 6, it is characterized in that it includes: S51 Construct a temperature and pressure model for the shale section of conventional well logging; S52 Based on the temperature and pressure model of the shale section, obtain the values of the temperature and pressure of the shale section through conventional well logging data; S53 Substitute the values of the temperature and pressure of the shale section into the shale temperature and pressure model based on well logging information to obtain the shale compaction geometric parameter A of the shale section; S54 Obtain the stiffness matrix of shale according to the shale compaction geometric parameter A of the shale section.

8. According to the application method described in claim 7, it is characterized in that the temperature and pressure model of the shale section is constructed as follows: Pressure model: Pz == MD * ρ * g; (15) Ppore = MD * ρ_fluid * g * Pcoeffcient (16) P = Pz - Ppore (17) where Pz, Ppore, and P respectively represent overburden pressure, formation pressure, and pressure, ρ and ρ_fluid respectively represent overburden rock density and fluid density, Pcoeffcient represents formation pressure coefficient, MD represents depth, and g represents gravitational acceleration; Temperature model: T = Tcoeffcient * (MD - MD 0 ) / 100 + T 0 (18) Among them, T represents temperature, Tcoeffcient represents temperature gradient, MD 0 represents the depth of the target layer, and T 0 represents the temperature of the target layer.

9. According to the application method described in claim 6, it is characterized in that the elastic parameters of the elastic stiffness matrix are obtained through the following calculation model: where: Among them, C a is the stiffness tensor with the spatial coordinate axes of the mudstone completely aligned with the object coordinate axes. The spatial coordinate axes extend in the directions of positive up, down, front, back, left, and right in space, and the object coordinate axes extend in the directions of positive up, down, front, back, left, and right of the matrix object in space; a 1 、a 2 、a 3 、L, and M are matrix elastic parameters; C 11 、C 12 、C 13 、C 33 、C 44 are five independent elastic parameters of the microstructure of the small mudstone plate, and C 66 represents the elastic parameters that are mutually replaceable between C 11 and C 12 .

Images