Method and device for determining fracture fluid indication factor of deep coal bed gas reservoir

Abstract

The invention provides a method and a device for determining a fracture fluid indication factor of a deep coal bed gas reservoir, and relates to the technical field of deep coal bed gas exploration. The method comprises the following steps: firstly, constructing a deep coal bed gas reservoir approximate PP wave reflection coefficient equation directly expressed by six reservoir parameters including wave impedance, longitudinal wave velocity, shear modulus, anisotropic parameters, fracture fluid indication factors and fracture tangential weakness; then, a target functional used for inverting reservoir parameters of the deep coalbed methane reservoir is constructed in combination with synthetic azimuth gather seismic data of the deep coalbed methane reservoir of the target work area, and finally, the fracture fluid indication factor of the deep coalbed methane reservoir can be directly inverted by solving the target functional. According to the method, the problem of error accumulation existing in indirect inversion of the fracture fluid indicator factor is avoided, so that the technical problem of poor inversion result accuracy existing in an existing determination method of the fracture fluid indicator factor of the deep coal bed gas reservoir can be effectively relieved.

Description

Technical Field

[0001] The present invention relates to the technical field of deep coalbed methane exploration, and in particular, to a method and device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir. Background Art

[0002] With the continuous progress of wide-azimuth three-dimensional seismic acquisition technology and azimuthal anisotropy processing technology, the use of azimuthal seismic data to achieve fracture reservoir characterization inversion and fluid prediction has received increasing attention. The fracture fluid indicator factor is an important parameter for guiding the identification of the fracture filling fluid type in deep coalbed methane reservoirs. The accurate prediction of the fracture fluid indicator factor in deep coalbed methane reservoirs is of great significance for reservoir accurate characterization and well location optimization.

[0003] However, in the prior art, most existing studies are indirect inversions based on rock physics relationships, and the fracture fluid indicator factor is indirectly calculated using the inversion target parameters, which will cause error propagation and increase the uncertainty of the inversion results. That is, the existing method for determining the fracture fluid indicator factor of deep coalbed methane reservoirs has the technical problem of poor accuracy of the inversion results. Summary of the Invention

[0004] The purpose of the present invention is to provide a method and device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, so as to alleviate the technical problem of poor accuracy of the inversion results existing in the existing method for determining the fracture fluid indicator factor of deep coalbed methane reservoirs.

[0005] In a first aspect, the present invention provides a method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, including: obtaining synthetic azimuthal gather seismic data and logging data of a deep coalbed methane reservoir in a target work area; constructing an initial reservoir parameter model of the deep coalbed methane reservoir based on the logging data; wherein the reservoir parameters include: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness; constructing an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by reservoir parameters; constructing an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir; solving the objective functional under the constraints of the initial reservoir parameter model and the logging data to obtain an inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0006] In an alternative embodiment, an approximate PP-wave reflection coefficient equation for a deep coalbed methane reservoir expressed in terms of reservoir parameters is constructed, including: obtaining the PP-wave reflection coefficient equation for an orthotropic medium; substituting the relationship between the anisotropy parameter and the difference in fracture weakness and the relationships that both the vertical tangential fracture weakness and the horizontal tangential fracture weakness are equal to the tangential fracture weakness into the PP-wave reflection coefficient equation for the orthotropic medium to obtain a first PP-wave reflection coefficient equation expressed in terms of wave impedance, P-wave velocity, shear modulus, anisotropy parameter, tangential fracture weakness, and normal fracture weakness; arranging the first PP-wave reflection coefficient equation and removing its high-order terms to retain up to the second-order angular terms to obtain a second PP-wave reflection coefficient equation; and performing parameter substitution on the second PP-wave reflection coefficient equation based on the algebraic relationship between the fracture fluid indicator factor and the tangential fracture weakness and the normal fracture weakness to obtain an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0007] In an alternative embodiment, based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed under the Bayesian inversion framework, including: extracting the seismic wavelet from the synthetic azimuthal gather seismic data; constructing an arithmetic expression for forward modeling the seismic data based on the approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir and the seismic wavelet; and constructing the target functional under the Bayesian inversion framework with the premise that the prior distribution of the reservoir parameters follows a Cauchy distribution and the maximization of the posterior distribution of the reservoir parameters as the objective, based on the synthetic azimuthal gather seismic data and the arithmetic expression for forward modeling the seismic data.

[0008] In an alternative embodiment, under the constraints of the initial reservoir parameter model and well logging data, the objective functional is solved, including: determining an equation for the perturbation amount of reservoir parameters based on the objective functional; iteratively updating a first subset of reservoir parameters based on the initial reservoir parameter model, the equation for the perturbation amount of reservoir parameters, and seismic data with an azimuth of 90 degrees in the synthetic azimuthal gather seismic data until a preset number of iterations is reached to obtain a target model of the first subset of reservoir parameters; wherein, the first subset of reservoir parameters includes: acoustic impedance, P-wave velocity, shear modulus, and anisotropy parameters; forward modeling seismic data with an azimuth of 90 degrees using the target model of the first subset of reservoir parameters to obtain target forward modeling seismic data; calculating the difference between the seismic data with an azimuth other than 90 degrees in the synthetic azimuthal gather seismic data and the target forward modeling seismic data to obtain target seismic data; iteratively updating a second subset of reservoir parameters based on the initial reservoir parameter model, the equation for the perturbation amount of reservoir parameters, and the target seismic data until a preset number of iterations is reached to obtain a target model of the second subset of reservoir parameters; wherein, the second subset of reservoir parameters includes: fracture fluid indicator factor and fracture tangential weakness; calculating the inversion error of the target model of reservoir parameters based on well logging data; wherein, the target model of reservoir parameters represents the set of the target model of the first subset of reservoir parameters and the target model of the second subset of reservoir parameters; in the case where it is determined that the inversion error is greater than or equal to a first preset threshold, continue to iteratively update the target model of reservoir parameters until the inversion error is less than the first preset threshold; in the case where it is determined that the inversion error is less than the first preset threshold, use the fracture fluid indicator factor in the target model of reservoir parameters as the inversion result of the fracture fluid indicator factor.

[0009] In an alternative embodiment, after obtaining the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir, it further includes: in the case where the fracture fluid indicator factor is less than or equal to a second preset threshold, determining that the fracture fluid filling type is liquid; in the case where the fracture fluid indicator factor is greater than the second preset threshold, determining that the fracture fluid filling type is gas.

[0010] In an alternative embodiment, the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir is expressed as: ; wherein, , , ; represents the incident angle, represents the azimuth relative to the fracture normal plane, represents the acoustic impedance, represents the P-wave velocity, , represents the S-wave velocity, represents the shear modulus, , both represent the anisotropy parameters of the transversely isotropic background medium, Indicates the tangential weakness of the fracture. Indicates the fracture fluid indication factor. The symbol ￣ represents the average value of two adjacent formation parameters above and below. The symbol Indicates the difference between two adjacent formation parameters above and below.

[0011] In an alternative embodiment, the objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir is expressed as: ; where Indicates the synthetic azimuthal gather seismic data, Indicates the forward modeled seismic data, , Indicates the seismic wavelet, Indicates the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, Indicates the matrix composed of reservoir parameters, Indicates the covariance matrix of the noise, Indicates the th formation, Indicates the total number of formations, Indicates the covariance matrix, Indicates the regularization matrix.

[0012] In a second aspect, the present invention provides a device for determining the fracture fluid indication factor of a deep coalbed methane reservoir, including: an acquisition module for acquiring the synthetic azimuthal gather seismic data and well logging data of the deep coalbed methane reservoir in a target work area; a first construction module for constructing an initial model of the reservoir parameters of the deep coalbed methane reservoir based on the well logging data; where the reservoir parameters include: wave impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indication factor, and tangential weakness of the fracture; a second construction module for constructing an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed in terms of reservoir parameters; a third construction module for constructing an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir; a solution module for solving the objective functional under the constraints of the initial model of the reservoir parameters and the well logging data to obtain the inversion result of the fracture fluid indication factor of the deep coalbed methane reservoir.

[0013] In a third aspect, the present invention provides an electronic device, including a memory and a processor. A computer program is stored on the memory and can run on the processor. When the processor executes the computer program, it implements the method for determining the fracture fluid indication factor of the deep coalbed methane reservoir according to any one of the foregoing embodiments.

[0014] Fourthly, the present invention provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the method for determining the fracture fluid indication factor of a deep coalbed methane reservoir described in any one of the foregoing embodiments.

[0015] The present invention provides a method for determining the fracture fluid indication factor of a deep coalbed methane reservoir. The method first constructs an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir directly expressed by six reservoir parameters including wave impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indication factor, and fracture tangential weakness. Then, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed by combining the synthetic azimuth gather seismic data of the deep coalbed methane reservoir in the target work area. Finally, the fracture fluid indication factor of the deep coalbed methane reservoir can be directly inverted by solving the target functional. This method avoids the error accumulation problem existing in the indirect inversion of the fracture fluid indication factor, and therefore can effectively alleviate the technical problem of poor accuracy of the inversion results in the existing methods for determining the fracture fluid indication factor of deep coalbed methane reservoirs. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] In order to more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following will briefly introduce the drawings required for the description of the specific embodiments or the prior art. Obviously, the following drawings are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a flowchart of a method for determining the fracture fluid indication factor of a deep coalbed methane reservoir provided by an embodiment of the present invention; Figure 2 It is a schematic diagram of an orthotropic medium provided by an embodiment of the present invention; Figure 3 It is a schematic diagram of the actual values of reservoir parameters in a logging area provided by an embodiment of the present invention; Figure 4 It is a schematic diagram of a 90° azimuth synthetic seismic record provided by an embodiment of the present invention; Figure 5 It is a comparison diagram of the inversion results between the method of the embodiment of the present invention and the existing method for indirectly inverting the fracture fluid indication factor; Figure 6 It is a functional module diagram of a device for determining the fracture fluid indication factor of a deep coalbed methane reservoir provided by an embodiment of the present invention; Figure 7 It is a schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. Components of the embodiments of the present invention described and illustrated herein can generally be arranged and designed in a variety of different configurations.

[0019] Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but merely represents selected embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts fall within the scope of protection of the present invention.

[0020] The following will describe in detail some embodiments of the present invention with reference to the accompanying drawings. Without conflict, the following embodiments and the features in the embodiments can be combined with each other.

[0021] Embodiment 1 Figure 1 is a flowchart of a method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention. As Figure 1 shown, the method specifically includes the following steps: Step S102, obtain the synthetic azimuth gather seismic data and logging data of the deep coalbed methane reservoir in the target work area.

[0022] Step S104, construct an initial reservoir parameter model of the deep coalbed methane reservoir based on the logging data.

[0023] Among them, the reservoir parameters include: acoustic impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness.

[0024] Specifically, the synthetic azimuth gather seismic data is the data obtained after seismic exploration of the deep coalbed methane reservoir in the target work area using professional data acquisition equipment. The logging data is directly or indirectly calculated from the logging curves obtained by logging the deep coalbed methane reservoir in the target work area. The embodiments of the present invention do not specifically limit the data types included in the logging data, as long as the above-mentioned reservoir parameters can be directly or indirectly obtained.

[0025] Regarding the fracture tangential weakness in the reservoir parameters, existing ultrasonic logging imaging data has confirmed that the deep coalbed methane reservoir generally has continuous bedding and is accompanied by the development of vertical or nearly vertical fractures. Under the assumption of seismic long wavelength, the deep coalbed methane reservoir can be approximated as Figure 2For the orthotropic medium shown, when the fractures in the medium are vertical or nearly vertical fractures, the fracture vertical tangential weakness is approximately equal to the fracture horizontal tangential weakness, and they are collectively referred to as the fracture tangential weakness.

[0026] It is known that reservoir parameters of a logging area can be calculated based on logging data, and they are denoted as the actual values of the reservoir parameters in the logging area. Figure 3 This is a schematic diagram of the actual values of the reservoir parameters in a logging area provided by an embodiment of the present invention. Next, by performing interpolation processing or low-pass filtering processing on the actual values of the reservoir parameters in the logging area, an initial model of the reservoir parameters of the deep coalbed methane reservoir can be constructed.

[0027] Step S106: Construct an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0028] To avoid the problem of error accumulation caused by indirectly inverting the fracture fluid indicator factor, an embodiment of the present invention performs a series of processes on the PP-wave reflection coefficient equation of the existing orthotropic medium to introduce the fracture fluid indicator factor into the PP-wave reflection coefficient equation, and obtains an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir directly expressed by wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness.

[0029] Step S108: Based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir, construct an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework.

[0030] It is known that there is the following relationship between the azimuthal seismic observation data and the forward modeling seismic data: , where represents the synthetic azimuthal gather seismic data, , represents the forward modeling seismic data, represents the seismic wavelet, represents the approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir, represents the matrix composed of reservoir parameters, represents the noise of the azimuthal seismic observation data.

[0031] Therefore, after obtaining the approximate longitudinal wave reflection coefficient equation that can be directly used to invert the fracture fluid indicator factor, based on the relationship between the above-mentioned azimuthal seismic observation data and the forward modeling seismic data, under the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters follows a Cauchy distribution and the maximization of the posterior distribution of the reservoir parameters as the goal, an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir can be constructed.

[0032] Step S110, under the constraints of the initial reservoir parameter model and well logging data, solve the objective functional to obtain the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0033] The embodiments of the present invention do not specifically limit the method for solving the objective functional, as long as the initial reservoir parameter model is used as the initial data of the storage parameters, and it is ensured that the error between the reservoir parameters in the well logging area in the inversion result and the actual values of the reservoir parameters in the well logging area calculated based on the well logging data is less than a preset threshold. Optionally, the generalized linear inversion and the iteratively reweighted least squares algorithm can be combined to solve the objective functional.

[0034] By solving the objective functional, the target model of the reservoir parameters can be obtained, that is, the target model of the wave impedance, the target model of the P-wave velocity, the target model of the shear modulus, the target model of the anisotropy parameter, the target model of the fracture fluid indicator factor, and the target model of the fracture tangential weakness can be obtained. Finally, the target model of the fracture fluid indicator factor is used as the inversion result of the fracture fluid indicator factor.

[0035] The embodiments of the present invention provide a method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir. The method first constructs an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir directly expressed by six reservoir parameters including wave impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness. Then, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed by combining the synthetic azimuthal gather seismic data of the deep coalbed methane reservoir in the target work area. Finally, the fracture fluid indicator factor of the deep coalbed methane reservoir can be directly inverted by solving the target functional. This method avoids the problem of error accumulation in the indirect inversion of the fracture fluid indicator factor, and therefore can effectively alleviate the technical problem of poor accuracy of the inversion result in the existing method for determining the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0036] In an optional embodiment, in the above step S106, constructing an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by reservoir parameters specifically includes the following steps: Step S1061, obtain the PP-wave reflection coefficient equation of the orthotropic medium.

[0037] Specifically, the PP-wave reflection coefficient equation of the orthotropic medium is expressed as: (Formula 1); where represents the azimuthal seismic reflection coefficient, represents the incident angle, represents the azimuth angle relative to the fracture normal plane, represents the wave impedance, represents the P-wave velocity, , represents the shear wave velocity, represents the shear modulus, represents the velocity anisotropy parameter in different symmetry planes of the orthotropic medium. The symbol ￣ represents the average value of the parameters of two adjacent strata above and below, and the symbol represents the difference between the parameters of two adjacent strata above and below.

[0038] Step S1062: Substitute the relational expressions between the anisotropy parameter and the crack weakness difference, and the relational expressions that the crack vertical tangential weakness and the crack horizontal tangential weakness are both equal to the crack tangential weakness into the PP-wave reflection coefficient equation of the orthotropic medium, so as to obtain the first PP-wave reflection coefficient equation expressed in terms of wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, crack tangential weakness, and crack normal weakness.

[0039] Starting from the elastic stiffness matrix, according to the definition of the orthotropic parameter the relational expression between the anisotropy parameter and the crack weakness difference is: (Formula 2); where represents the anisotropy parameter of the transversely isotropic background medium. The medium obtained by adding vertical cracks to the transversely isotropic background medium is the orthotropic medium. represents the crack vertical tangential weakness, represents the crack horizontal tangential weakness, represents the crack normal weakness, and all are dimensionless parameters.

[0040] When the cracks contained in the medium are vertical or nearly vertical cracks, the crack vertical tangential weakness is approximately equal to the crack horizontal tangential weakness, and they are collectively referred to as the crack tangential weakness , that is, , and further (Formula 3).

[0041] Substitute the above Formula 2 and Formula 3 into Formula 1 to obtain the first PP-wave reflection coefficient equation: (Formula 4); Obviously, Formula 4 is an expression about wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, crack tangential weakness, and crack normal weakness.

[0042] Step S1063: Rearrange the first PP-wave reflection coefficient equation and eliminate its high-order terms to retain up to the second-order angular terms, so as to obtain the second PP-wave reflection coefficient equation.

[0043] The embodiments of the present invention cite the following trigonometric identities in the field of mathematics to rearrange the first PP-wave reflection coefficient equation: , , , based on the above trigonometric identities, rearranging Formula 4 gives: (Formula 5).

[0044] Next, ignore the terms of the fourth order and above (such as , , etc.), and retain the terms up to the second-order angular terms. The second PP-wave reflection coefficient equation obtained after simplification is expressed as: (Equation 6). Obviously, the fracture weakness term and the main influencing terms are completely retained, that is, the simplified equation can still reflect the characteristics of the medium's orthorhombic anisotropy.

[0045] Step S1064: Based on the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and the fracture normal weakness, perform parameter substitution on the second PP-wave reflection coefficient equation to obtain an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0046] The above Equation 6 can be regarded as the sum of the R term affected by the vertical fracture and the R term not affected by the vertical fracture, that is: (Equation 7), where , (Equation 8).

[0047] Next, taking the logarithm of gives: (Equation 9). Based on Euler's formula, we can obtain: , (Equation 10). Substituting Equation 10 into Equation 9 gives: (Equation 11).

[0048] Schoenberg and Sayers (1995) proposed that can be used to indicate fracture fluid, and its value is usually large when the reservoir contains gas. In the embodiments of the present invention, the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and the fracture normal weakness is set as the following equation: (Equation 12).

[0049] Rewrite Equation 12 as: (Equation 13), and take the total differential of , and the result is: (Equation 14), where , , . Divide both sides of Equation 14 by the fracture normal weakness to obtain: (Equation 15). Substitute Equation 15 into the above Equation 11 to obtain: (Equation 16).

[0050] In order to highlight the functional relationship between the PP-wave reflection coefficient equation and the reservoir parameters to be inverted, therefore, abbreviate as , For , For , the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir is obtained and expressed as: ; where , , ; denotes the incident angle, denotes the azimuth angle relative to the normal plane of the fracture, denotes the wave impedance, denotes the P-wave velocity, , denotes the S-wave velocity, denotes the shear modulus, , both denote the anisotropic parameters of the transversely isotropic background medium, denotes the fracture tangential weakness, denotes the fracture fluid indicator factor, the symbol ￣ denotes the average value of the parameters of two adjacent strata above and below, and the symbol denotes the difference between the parameters of two adjacent strata above and below.

[0051] In an alternative embodiment, in step S108 above, based on the synthetic azimuth angle gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, under the Bayesian inversion framework, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed, specifically including the following steps: Step S1081, extract the seismic wavelet from the synthetic azimuth angle gather seismic data.

[0052] Step S1082, based on the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir and the seismic wavelet, construct an arithmetic expression for forward modeling the seismic data.

[0053] Specifically, the method of extracting the seismic wavelet from the synthetic azimuth angle gather seismic data is a well-known technique in the art, and the embodiments of the present invention will not elaborate on this. According to the above description, the arithmetic expression for forward modeling the seismic data is: , denotes the seismic wavelet, denotes the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, denotes the matrix composed of reservoir parameters.

[0054] Step S1083, under the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters follows a Cauchy distribution and the maximization of the posterior distribution of the reservoir parameters as the goal, based on the synthetic azimuth angle gather seismic data and the arithmetic expression for forward modeling the seismic data, construct the target functional.

[0055] Posterior Probability Distribution of Parameters to be Inverted in Pre-stack Seismic Inversion under Bayesian Framework can be expressed as the joint distribution of the prior probability and the likelihood function , that is, (Equation 17), where is the assumed prior distribution satisfied, is the probability distribution of obtaining the observed data under this model, is the distribution of the observed data.

[0056] Assume that the noise of seismic data follows a Gaussian distribution and is independent. The distribution of the synthetic azimuth gather seismic data noise can be written in the following form: (Equation 18), where represents a preset constant, represents the covariance matrix of the noise, represents the synthetic azimuth gather seismic data noise.

[0057] It is known that there is the following relationship between the synthetic azimuth gather seismic data and the forward modeled seismic data: (Equation 19). Substituting Equation 19 into Equation 18, the likelihood function can be obtained: (Equation 20).

[0058] Based on Equation 17, the expression form of the posterior distribution of the reservoir parameters to be inverted can be obtained: (Equation 21). Assume that the prior distribution of the reservoir parameters follows a Cauchy distribution, that is (Equation 22), where represents the covariance matrix of the reservoir parameters, that is, the covariance matrix, whose order is determined by the number of reservoir parameters, and characterizes the statistical correlation between the reservoir parameters to be inverted, represents the adjustment matrix, making include the statistical correlation between the reservoir parameters. Based on this, Equation 21 can be rewritten in the following form: (Equation 23).

[0059] According to the maximum a posteriori probability estimation, the objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir in the embodiment of the present invention can be constructed, expressed as: ; where represents the synthetic azimuth gather seismic data, represents the forward modeled seismic data, , represents the seismic wavelet, represents the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, represents a matrix composed of reservoir parameters, represents the covariance matrix of noise, represents the th formation, represents the total number of formations, represents the covariance matrix, represents the adjustment matrix, which is used to adjust the dimension of the covariance matrix and establish the statistical correlation between reservoir parameters. According to Formula 23 and the expression of the objective functional, it can be known that the larger, the posterior probability the smaller, on the contrary, the smaller, the posterior probability the larger.

[0060] In an optional implementation manner, in the above step S110, under the constraints of the initial model of reservoir parameters and well logging data, the objective functional is solved, which specifically includes the following steps: Step S1101, determine the calculation formula of the perturbation amount of reservoir parameters based on the objective functional.

[0061] Optionally, the generalized linear inversion and iterative reweighted least squares algorithm are used to process the objective functional. Specifically, first, according to the generalized linear inversion theory, the objective functional is expanded at the initial model of reservoir parameters by the first-order Taylor expansion to obtain the objective function of reservoir parameters, and then the partial derivative of the objective function of reservoir parameters with respect to the perturbation amount of reservoir parameters is calculated to obtain the partial derivative function; next, let the partial derivative function be equal to 0 to obtain the solution expression of the perturbation amount of reservoir parameters, and finally, the above solution expression is simplified according to the iterative reweighted least squares joint algorithm to obtain the calculation formula of the perturbation amount of reservoir parameters: , where represents the variance of the noise of the synthetic azimuthal gather seismic data.

[0062] Step S1102, based on the initial model of reservoir parameters, the calculation formula of the perturbation amount of reservoir parameters, and the seismic data with an azimuth of 90 degrees in the synthetic azimuthal gather seismic data, iterate and update the first subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the first subset of reservoir parameters; wherein, the first subset of reservoir parameters includes: acoustic impedance, P-wave velocity, shear modulus, and anisotropy parameters.

[0063] Figure 4 is a schematic diagram of a 90° azimuth synthetic seismic record provided by an embodiment of the present invention. According to the expression of the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir in the above text, it can be known that when the azimuth takes a value of 90 degrees, is 0, that is, the seismic data with an azimuth angle of 90° is not affected by the vertically developed fractures in the formation. Therefore, in the embodiments of the present invention, first, the seismic data with an azimuth angle of 90° in the synthetic azimuth angle gather seismic data is used to invert four reservoir parameters in the first subset of reservoir parameters, and the initial model of the known reservoir parameters (only the initial model of the first subset of reservoir parameters is used in this step), and the calculation formula of the reservoir parameter perturbation amount , substitute in the reservoir parameter perturbation amount calculation formula into the seismic data with an azimuth angle of 90°, and iterate a specified number of times to obtain the target model of the first subset of reservoir parameters.

[0064] Step S1103, forward model the seismic data with an azimuth angle of 90° using the target model of the first subset of reservoir parameters to obtain the target forward modeled seismic data.

[0065] Next, based on the forward modeling formula , forward model the seismic data with an azimuth angle of 90° using the target model of the first subset of reservoir parameters to obtain the target forward modeled seismic data , where represents the matrix composed of the first subset of reservoir parameters.

[0066] Step S1104, calculate the difference between the seismic data with an azimuth angle other than 90° in the synthetic azimuth angle gather seismic data and the target forward modeled seismic data to obtain the target seismic data.

[0067] That is, the target seismic data is expressed as: . Where represents the seismic data with an azimuth angle other than 90° in the synthetic azimuth angle gather seismic data, represents the target seismic data.

[0068] Step S1105, based on the initial model of the reservoir parameters, the calculation formula of the reservoir parameter perturbation amount, and the target seismic data, iteratively update the second subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the second subset of reservoir parameters; where the second subset of reservoir parameters includes: fracture fluid indicator factor and fracture tangential weakness.

[0069] According to the expression of the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, if the incident angle is the same, then are equal. Then, according to the distributive law of convolution, subtracting the seismic data with an azimuth angle other than 90° in the synthetic azimuth angle gather seismic data from the forward modeled seismic data with an azimuth angle of 90° can eliminate the seismic records affected by . That is, the target seismic data is the seismic record only affected by .

[0070] In view of this, based on the initial model of known reservoir parameters (only using the initial model of the second reservoir parameter subset in this step), and the calculation formula of the perturbation amount of reservoir parameters Substitute the in the calculation formula of the perturbation amount of reservoir parameters into the target seismic data , and iterate a specified number of times to obtain the target model of the second reservoir parameter subset.

[0071] Step S1106: Calculate the inversion error of the target model of reservoir parameters based on well logging data; wherein, the target model of reservoir parameters represents the set of the target model of the first reservoir parameter subset and the target model of the second reservoir parameter subset.

[0072] Step S1107: When it is determined that the inversion error is greater than or equal to the first preset threshold, continue to iteratively update the target model of reservoir parameters until the inversion error is less than the first preset threshold.

[0073] Step S1108: When it is determined that the inversion error is less than the first preset threshold, use the fracture fluid indicator factor in the target model of reservoir parameters as the inversion result of the fracture fluid indicator factor.

[0074] Generally, when inversing reservoir parameters, in order to obtain a stable inversion result, a relatively large number of iterations need to be set. However, practice has proved that after a certain number of iterations, the change amount of the inversion result will gradually decrease. Then, a large number of subsequent iterative updates do not substantially improve the inversion result itself. Therefore, in the embodiments of the present invention, the actual value of the reservoir parameters in the well logging area calculated based on well logging data is used as reference data, and the error between the inversion result and the actual value of the well logging area in the reservoir parameters obtained after a preset number of iterations (set according to experience) is recorded as the inversion error. The embodiments of the present invention do not specifically limit the calculation method of the inversion error, as long as the numerical difference situation can be reflected. For example, the sum of the errors between the inversion result and the actual value of each reservoir parameter at multiple sampling points can be calculated first, and then an error weight can be set for each reservoir parameter, and the inversion error can be calculated through weighted calculation.

[0075] When the inversion error is greater than or equal to the first preset threshold, it indicates that the inversion accuracy is insufficient, and the currently obtained target model needs to be further iterated. During iteration, the operations in the above steps S1102 - S1105 are still followed, and only the initial model of the reservoir parameters needs to be replaced with the currently reached target model. Optionally, the user can choose to calculate the inversion error after iterating a specified number of times (Method 1), or calculate the inversion error each time the model is iterated (Method 2). Specifically, which of the above methods to choose can be set according to the calculation result of the previous inversion error. If the gap between the inversion error and the first preset threshold is greater than the specified value, Method 1 is selected; if the gap between the inversion error and the first preset threshold is less than or equal to the specified value, Method 2 is selected.

[0076] After iterating multiple times, if the inversion error is less than the first preset threshold, it indicates that the inversion accuracy meets the requirements, and the fracture fluid indicator factor in the reservoir parameter target model can be used as the inversion result of the fracture fluid indicator factor. Figure 5 This is a comparison chart of the inversion results between the method of the embodiment of the present invention and the existing method for indirectly inverting the fracture fluid indicator factor. Figure 5 In it, the solid line is the actual value of the fracture fluid indicator factor, the dotted line is the predicted value of the existing indirect inversion method, that is, the predicted value of the ordinary method, and the dashed line is the inversion result based on the method provided by the embodiment of the present invention, that is, the predicted value of this method. Through Figure 5 It can be seen that the fracture fluid indicator factor of the deep coalbed methane reservoir is significantly different from that of the surrounding rock. Compared with the indirect inversion method, the inversion result of the method provided by the embodiment of the present invention is more consistent with the actual value, that is, the method of the present invention is more effective and feasible.

[0077] Based on the method for solving the target functional provided above, the embodiment of the present invention can effectively reduce the number of inversion iterations while ensuring the inversion accuracy of reservoir parameters, reduce the running time of the method, and thus improve the execution efficiency.

[0078] In an optional implementation manner, after obtaining the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir, the embodiment of the present invention further includes the following content: When the fracture fluid indicator factor is less than or equal to the second preset threshold, it is determined that the fracture fluid filling type is liquid.

[0079] When the fracture fluid indicator factor is greater than the second preset threshold, it is determined that the fracture fluid filling type is gas.

[0080] That is, the numerical value of the fracture fluid indicator factor can be used to accurately identify the fracture fluid filling type of the deep coalbed methane reservoir. When the reservoir fractures are saturated with liquid (oil or water), the fracture fluid indicator factor is close to 0; when the fractures are saturated with gas, the fracture fluid indicator factor is much greater than 0.

[0081] Example 2 The embodiment of the present invention also provides a device for determining the fracture fluid indication factor of a deep coalbed methane reservoir. This device is mainly used to execute the method for determining the fracture fluid indication factor of the deep coalbed methane reservoir provided in the above Example 1. The following is a specific introduction to the device for determining the fracture fluid indication factor of the deep coalbed methane reservoir provided by the embodiment of the present invention.

[0082] Figure 6 is a functional module diagram of a device for determining the fracture fluid indication factor of a deep coalbed methane reservoir provided by an embodiment of the present invention, as Figure 6 shown, this device mainly includes: an acquisition module 10, a first construction module 20, a second construction module 30, a third construction module 40, and a solution module 50, where: The acquisition module 10 is used to acquire the synthetic azimuth gather seismic data and logging data of the deep coalbed methane reservoir in the target work area.

[0083] The first construction module 20 is used to construct an initial reservoir parameter model of the deep coalbed methane reservoir based on the logging data; among them, the reservoir parameters include: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indication factor, and fracture tangential weakness.

[0084] The second construction module 30 is used to construct an approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir expressed by reservoir parameters.

[0085] The third construction module 40 is used to construct an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir.

[0086] The solution module 50 is used to solve the objective functional under the constraints of the initial reservoir parameter model and the logging data to obtain the inversion result of the fracture fluid indication factor of the deep coalbed methane reservoir.

[0087] An embodiment of the present invention provides a device for determining a fracture fluid indication factor of a deep coalbed methane reservoir. The device first constructs an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir directly expressed by six reservoir parameters including wave impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indication factor, and fracture tangential weakness. Then, in combination with the synthetic azimuth gather seismic data of the deep coalbed methane reservoir in the target work area, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed. Finally, by solving the target functional, the fracture fluid indication factor of the deep coalbed methane reservoir can be directly inverted. The device avoids the problem of error accumulation in the indirect inversion of the fracture fluid indication factor, and thus can effectively alleviate the technical problem of poor accuracy of the inversion results in the existing methods for determining the fracture fluid indication factor of the deep coalbed methane reservoir.

[0088] Optionally, the second construction module 30 is specifically configured to: Obtain the PP-wave reflection coefficient equation of the orthotropic medium.

[0089] Substitute the relational expressions between the anisotropy parameter and the fracture weakness difference, and the relational expressions that the fracture vertical tangential weakness and the fracture horizontal tangential weakness are both equal to the fracture tangential weakness into the PP-wave reflection coefficient equation of the orthotropic medium to obtain a first PP-wave reflection coefficient equation expressed by wave impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture tangential weakness, and fracture normal weakness.

[0090] Sort out the first PP-wave reflection coefficient equation, and eliminate its high-order terms to retain up to the second-order angular term to obtain a second PP-wave reflection coefficient equation.

[0091] Based on the algebraic relationship between the fracture fluid indication factor and the fracture tangential weakness and the fracture normal weakness, perform parameter substitution on the second PP-wave reflection coefficient equation to obtain an approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir expressed by reservoir parameters.

[0092] Optionally, the third construction module 40 is specifically configured to: Extract the seismic wavelet from the synthetic azimuth gather seismic data.

[0093] Based on the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir and the seismic wavelet, construct an arithmetic expression for forward modeling of seismic data.

[0094] Under the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters follows a Cauchy distribution and the maximization of the posterior distribution of the reservoir parameters as the goal, based on the synthetic azimuth gather seismic data and the arithmetic expression for forward modeling of seismic data, construct a target functional.

[0095] Optionally, the solving module 50 is specifically configured to: Determine an arithmetic expression for the perturbation amount of the reservoir parameters based on the target functional.

[0096] Based on the initial model of reservoir parameters, the calculation formula of the perturbation amount of reservoir parameters, and the seismic data with an azimuth of 90 degrees in the synthetic azimuth gather seismic data, iterate and update the first subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the first subset of reservoir parameters; wherein, the first subset of reservoir parameters includes: acoustic impedance, P-wave velocity, shear modulus, and anisotropy parameters.

[0097] Use the target model of the first subset of reservoir parameters to forward model the seismic data with an azimuth of 90 degrees to obtain the target forward modeled seismic data.

[0098] Calculate the difference between the seismic data with an azimuth other than 90 degrees in the synthetic azimuth gather seismic data and the target forward modeled seismic data to obtain the target seismic data.

[0099] Based on the initial model of reservoir parameters, the calculation formula of the perturbation amount of reservoir parameters, and the target seismic data, iterate and update the second subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the second subset of reservoir parameters; wherein, the second subset of reservoir parameters includes: fracture fluid indicator factor and fracture tangential weakness.

[0100] Calculate the inversion error of the target model of reservoir parameters based on well logging data; wherein, the target model of reservoir parameters represents the set of the target model of the first subset of reservoir parameters and the target model of the second subset of reservoir parameters.

[0101] When it is determined that the inversion error is greater than or equal to the first preset threshold, continue to iterate and update the target model of reservoir parameters until the inversion error is less than the first preset threshold.

[0102] When it is determined that the inversion error is less than the first preset threshold, use the fracture fluid indicator factor in the target model of reservoir parameters as the inversion result of the fracture fluid indicator factor.

[0103] Optionally, the device is further configured to: When the fracture fluid indicator factor is less than or equal to the second preset threshold, determine that the fracture fluid filling type is liquid.

[0104] When the fracture fluid indicator factor is greater than the second preset threshold, determine that the fracture fluid filling type is gas.

[0105] Optionally, the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir is expressed as: ; wherein, , , ; represents the incident angle, represents the azimuth relative to the fracture normal plane, represents the acoustic impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, , all represent the anisotropic parameters of the transversely isotropic background medium, represents the fracture tangential weakness, represents the fracture fluid indicator factor, the symbol ￣ represents the average value of the parameters of two adjacent upper and lower formations, and the symbol represents the difference between the parameters of two adjacent upper and lower formations.

[0106] Optionally, the objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir is expressed as: ; where represents the synthetic azimuthal gather seismic data, represents the forward modeled seismic data, , represents the seismic wavelet, represents the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, represents the matrix composed of reservoir parameters, represents the covariance matrix of the noise, represents the th formation, represents the total number of formations, represents the covariance matrix, represents the regularization matrix.

[0107] Example Three Referring to Figure 7 , an embodiment of the present invention provides an electronic device, which includes: a processor 60, a memory 61, a bus 62, and a communication interface 63. The processor 60, the communication interface 63, and the memory 61 are connected through the bus 62; the processor 60 is configured to execute an executable module stored in the memory 61, such as a computer program.

[0108] Among them, the memory 61 may include a high-speed random access memory (RAM, Random Access Memory), and may also include a non-volatile memory, such as at least one disk memory. Through at least one communication interface 63 (which can be wired or wireless), a communication connection is realized between this system network element and at least one other network element, and the Internet, wide area network, local area network, metropolitan area network, etc. can be used.

[0109] The bus 62 can be an ISA bus, a PCI bus, or an EISA bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the sake of representation,Figure 7 is represented by only one bidirectional arrow, but it does not mean that there is only one bus or one type of bus.

[0110] Among them, the memory 61 is used to store a program. After receiving an execution instruction, the processor 60 executes the program. The method executed by the device defined by the process disclosed in any embodiment of the foregoing embodiments of the present invention can be applied to or implemented by the processor 60.

[0111] The processor 60 may be an integrated circuit chip with signal processing capabilities. In the implementation process, each step of the above method can be completed by the integrated logic circuit in the hardware of the processor 60 or the instructions in the form of software. The above-mentioned processor 60 may be a general-purpose processor, including a central processing unit (CPU for short), a network processor (NP for short), etc.; it may also be a digital signal processor (DSP for short), an application specific integrated circuit (ASIC for short), a field-programmable gate array (FPGA for short), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components. It can implement or execute the various methods, steps and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or the processor may also be any conventional processor, etc. The steps of the method disclosed in combination with the embodiments of the present invention can be directly embodied as being executed and completed by a hardware decoding processor, or executed and completed by a combination of hardware and software modules in the decoding processor. The software module may be located in a mature storage medium in the art such as a random access memory, a flash memory, a read-only memory, a programmable read-only memory, or an electrically erasable programmable memory, a register, etc. This storage medium is located in the memory 61, and the processor 60 reads the information in the memory 61 and combines its hardware to complete the steps of the above method.

[0112] A computer program product of a method and device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention includes a computer-readable storage medium storing non-volatile program code executable by a processor. The instructions included in the program code can be used to execute the method described in the foregoing method embodiments. For specific implementation, reference can be made to the method embodiments and will not be elaborated herein.

[0113] In addition, in each embodiment of the present invention, the functional units can be integrated in a processing unit, or each unit can exist physically alone, or two or more units can be integrated in one unit.

[0114] When the above-mentioned functions are implemented in the form of software function units and sold or used as independent products, they can be stored in a non-volatile computer-readable storage medium executable by a processor. Based on such understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0115] It should be noted that: similar reference numerals and letters represent similar items in the following drawings. Therefore, once an item is defined in one drawing, it does not need to be further defined and explained in subsequent drawings.

[0116] In the description of the present invention, it should be noted that the orientation or positional relationship indicated by the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc. is based on the orientation or positional relationship shown in the drawings, or the orientation or positional relationship in which the product of this invention is usually placed during use. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore should not be construed as a limitation to the present invention. In addition, the terms "first", "second", "third", etc. are only used for distinguishing descriptions and cannot be understood as indicating or implying relative importance.

[0117] In addition, the terms "horizontal", "vertical", "hanging", etc. do not mean that the components are required to be absolutely horizontal or hanging, but can be slightly inclined. For example, "horizontal" only means that its direction is more horizontal relative to "vertical", and does not mean that this structure must be completely horizontal, but can be slightly inclined.

[0118] In the description of the present invention, it should also be noted that unless otherwise clearly specified and limited, the terms "set", "install", "connect", "couple" should be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be directly connected or indirectly connected through an intermediate medium, and it can be the internal communication of two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0119] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some or all of the technical features; and these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. A method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, characterized in that Including: Obtaining synthetic azimuthal gather seismic data and logging data of a deep coalbed methane reservoir in a target work area; Constructing an initial reservoir parameter model of the deep coalbed methane reservoir based on the logging data; wherein, the reservoir parameters include: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness; Constructing an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by the reservoir parameters; Based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, constructing an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework; Under the constraints of the initial reservoir parameter model and the logging data, solving the objective functional to obtain the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

2. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, characterized in that Constructing an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by the reservoir parameters includes: Obtaining the PP-wave reflection coefficient equation of an orthotropic medium; Substituting the relational expressions between the anisotropy parameter and the difference in fracture weakness and the relational expressions that both the vertical tangential fracture weakness and the horizontal tangential fracture weakness are equal to the fracture tangential weakness into the PP-wave reflection coefficient equation of the orthotropic medium to obtain a first PP-wave reflection coefficient equation expressed by wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture tangential weakness, and fracture normal weakness; Rearranging the first PP-wave reflection coefficient equation and removing its high-order terms to retain up to the second-order angular term to obtain a second PP-wave reflection coefficient equation; Based on the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and the fracture normal weakness, performing parameter substitution on the second PP-wave reflection coefficient equation to obtain an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by the reservoir parameters.

3. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, characterized in that, Based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, constructing an objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework includes: Extracting a seismic wavelet from the synthetic azimuthal gather seismic data; Based on the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir and the seismic wavelet, constructing an arithmetic expression for forward modeling seismic data; Under the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters follows a Cauchy distribution and the maximization of the posterior distribution of the reservoir parameters as the objective, constructing the objective functional based on the synthetic azimuthal gather seismic data and the arithmetic expression for forward modeling seismic data.

4. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, wherein Under the constraints of the initial reservoir parameter model and the logging data, solving the objective functional includes: Determining an arithmetic expression for the perturbation amount of the reservoir parameters based on the objective functional; Based on the initial reservoir parameter model, the calculation formula of the reservoir parameter perturbation amount, and the seismic data with an azimuth of 90 degrees in the synthetic azimuthal gather seismic data, iterate and update the first subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the first subset of reservoir parameters; wherein, the first subset of reservoir parameters includes: acoustic impedance, P-wave velocity, shear modulus, and anisotropy parameter; Forward model the seismic data with an azimuth of 90 degrees using the target model of the first subset of reservoir parameters to obtain the target forward modeled seismic data; Calculate the difference between the seismic data with an azimuth other than 90 degrees in the synthetic azimuthal gather seismic data and the target forward modeled seismic data to obtain the target seismic data; Based on the initial reservoir parameter model, the calculation formula of the reservoir parameter perturbation amount, and the target seismic data, iterate and update the second subset of reservoir parameters until the preset number of iterations is reached to obtain the target model of the second subset of reservoir parameters; wherein, the second subset of reservoir parameters includes: fracture fluid indicator factor and fracture tangential weakness; Calculate the inversion error of the reservoir parameter target model based on the well logging data; wherein, the reservoir parameter target model represents the set of the target models of the first subset of reservoir parameters and the second subset of reservoir parameters; In the case where it is determined that the inversion error is greater than or equal to the first preset threshold, continue to iterate and update the reservoir parameter target model until the inversion error is less than the first preset threshold; In the case where it is determined that the inversion error is less than the first preset threshold, use the fracture fluid indicator factor in the reservoir parameter target model as the inversion result of the fracture fluid indicator factor.

5. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, characterized in that, After obtaining the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir, it further includes: In the case where the fracture fluid indicator factor is less than or equal to the second preset threshold, determine that the fracture fluid filling type is liquid; In the case where the fracture fluid indicator factor is greater than the second preset threshold, determine that the fracture fluid filling type is gas.

6. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, wherein The approximate PP-wave reflection coefficient equation for the deep coalbed methane reservoir is expressed as: ; where , , ; denotes the incident angle, denotes the azimuth angle relative to the normal plane of the fracture, denotes the wave impedance, denotes the P-wave velocity, , denotes the S-wave velocity, denotes the shear modulus, , both denote the anisotropic parameters of the transversely isotropic background medium, denotes the fracture tangential weakness, denotes the fracture fluid indicator factor. The symbol ￣ represents the average value of the parameters of two adjacent strata above and below, and the symbol denotes the difference between the parameters of two adjacent strata above and below.

7. The method for determining the fracture fluid indication factor of a deep coalbed methane reservoir according to claim 3, characterized in that, The objective functional for inverting the reservoir parameters of the deep coalbed methane reservoir is expressed as: ; where represents the synthetic azimuth gather seismic data, represents the forward modeled seismic data, , represents the seismic wavelet, represents the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir, represents the matrix composed of reservoir parameters, represents the covariance matrix of noise, represents the th formation, represents the total number of formations, represents the covariance matrix, represents the regularization matrix.

8. An apparatus for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, characterized in that, It includes: An acquisition module, configured to acquire the synthetic azimuthal gather seismic data and well logging data of the deep coalbed methane reservoir in the target work area; A first construction module, configured to construct the initial reservoir parameter model of the deep coalbed methane reservoir based on the well logging data; wherein, the reservoir parameters include: acoustic impedance, P-wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness; A second construction module, configured to construct an approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir expressed by the reservoir parameters; A third construction module, configured to construct a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir under the Bayesian inversion framework based on the synthetic azimuthal gather seismic data and the approximate PP-wave reflection coefficient equation of the deep coalbed methane reservoir; A solution module, configured to solve the target functional under the constraints of the initial reservoir parameter model and the well logging data to obtain the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

9. An electronic device, comprising a memory and a processor, wherein a computer program capable of running on the processor is stored on the memory, characterized in that, When the processor executes the computer program, it implements the method for determining the fracture fluid indication factor of the deep coalbed methane reservoir according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by the processor, it implements the method for determining the fracture fluid indication factor of the deep coalbed methane reservoir according to any one of claims 1 to 7.

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