Method and device for determining fracture fluid indicator factors in deep coalbed methane reservoirs

Abstract

The present invention provides a method and apparatus for determining a fracture fluid indicator factor in a deep coalbed methane reservoir, relating to the technical field of deep coalbed methane exploration. The method first constructs an approximate PP wave reflection coefficient equation for the deep coalbed methane reservoir, directly expressed by six reservoir parameters: wave impedance, compressional wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness. The method then combines synthetic azimuth gather seismic data from the deep coalbed methane reservoir in the target work area to construct a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir. Finally, by solving the target functional, the fracture fluid indicator factor of the deep coalbed methane reservoir can be directly inverted. This method avoids the error accumulation problem associated with indirect inversion of the fracture fluid indicator factor, thereby effectively alleviating the technical problem of poor inversion accuracy associated with existing methods for determining the fracture fluid indicator factor of deep coalbed methane reservoirs.

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 advancement of wide-azimuth 3D seismic acquisition technology and azimuthal anisotropy processing techniques, the use of azimuthal seismic data for fracture reservoir characterization and fluid prediction is gaining increasing attention. Fracture fluid indicator factors are important parameters for identifying the type of fluid filling fractures in deep coalbed methane reservoirs. Accurate prediction of these factors is crucial for precise reservoir characterization and well placement optimization.

[0003] However, existing research has mostly relied on indirect inversion based on rock physics relationships, using inversion target parameters to indirectly calculate fracture fluid indicator factors. This can lead to error propagation and increase uncertainty in the inversion results. In other words, existing methods for determining fracture fluid indicator factors in deep coalbed methane reservoirs suffer from the technical problem of poor inversion accuracy. Summary of the Invention

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

[0005] In a first aspect, the present invention provides a method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, comprising: obtaining synthetic azimuth gather seismic data and well 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 well 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 in terms of reservoir parameters; based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir, constructing a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir under a Bayesian inversion framework; under the constraints of the initial reservoir parameter model and the well logging data, solving the target functional to obtain an inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0006] In an optional embodiment, an approximate PP-wave reflection coefficient equation for a deep coalbed methane reservoir expressed in terms of reservoir parameters is constructed, including: obtaining a PP-wave reflection coefficient equation for an orthotropic medium; substituting a relationship between anisotropic parameters and the difference in fracture weakness and a relationship in which both the vertical tangential weakness of the fracture and the horizontal tangential weakness of the fracture are equal to the tangential weakness of the fracture 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, longitudinal wave velocity, shear modulus, anisotropic parameters, fracture tangential weakness, and fracture normal weakness; arranging the first PP-wave reflection coefficient equation and eliminating its high-order terms to retain the second-order angular terms to obtain a second PP-wave reflection coefficient equation; performing parameter substitution on the 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 to obtain an approximate PP-wave reflection coefficient equation for a deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0007] In an optional embodiment, based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of 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 seismic wavelets from the synthetic azimuth gather seismic data; constructing a formula for forward simulation of seismic data based on the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir and the seismic wavelets; under the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters obeys the Cauchy distribution and the goal of maximizing the posterior distribution of the reservoir parameters, a target functional is constructed based on the formula of the synthetic azimuth gather seismic data and the forward simulation seismic data.

[0008] In an optional embodiment, under the constraints of the initial model of reservoir parameters and logging data, solving the target functional includes: determining a formula for the reservoir parameter perturbation amount based on the target functional; iteratively updating the first reservoir parameter subset based on the initial model of reservoir parameters, the formula for the reservoir parameter perturbation amount and the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data until a preset number of iterations is reached to obtain a target model of the first reservoir parameter subset; wherein the first reservoir parameter subset includes: wave impedance, longitudinal wave velocity, shear modulus and anisotropy parameters; forward modeling the seismic data with an azimuth angle of 90 degrees using the target model of the first reservoir parameter subset to obtain target forward modeling seismic data; calculating the difference between the seismic data with an azimuth angle of non-90 degrees and the target forward modeling seismic data in the synthetic azimuth gather seismic data to obtain the target seismic data; based on the reservoir parameter subset, The method comprises the following steps: calculating an inversion error of the reservoir parameter target model based on the logging data; calculating the inversion error of the reservoir parameter target model ...

[0009] In an optional embodiment, after obtaining the inversion results of the fracture fluid indicator factor of the deep coalbed methane reservoir, it also includes: when the fracture fluid indicator factor is less than or equal to a second preset threshold, determining the fracture fluid filling type as liquid; when the fracture fluid indicator factor is greater than the second preset threshold, determining the fracture fluid filling type as gas.

[0010] In an optional embodiment, the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir is expressed as: ;in, , , ; represents the angle of incidence, represents the azimuth relative to the crack normal plane, represents the wave impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, , Both represent the anisotropic parameters of the transversely isotropic background medium, Indicates the tangential weakness of the crack, represents the fracture fluid indicator factor, the symbol ￣ represents the average value of the parameters of the two adjacent formations above and below, and the symbol Indicates the difference between the parameters of two adjacent strata.

[0011] In an optional embodiment, the target functional for inverting the reservoir parameters of a deep coalbed methane reservoir is expressed as: ;in, represents synthetic azimuth gather seismic data, represents the forward modeling seismic data, , represents the seismic wavelet, represents the approximate PP wave reflection coefficient equation for deep coalbed methane reservoirs, represents the matrix composed of reservoir parameters, represents the covariance matrix of the noise, Indicates the Layers, represents the total number of strata, represents the covariance matrix, represents the adjustment matrix.

[0012] In a second aspect, the present invention provides a device for determining the fracture fluid indicator factor of a deep coalbed methane reservoir, comprising: an acquisition module for acquiring synthetic azimuth gather seismic data and logging data of a deep coalbed methane reservoir in a target work area; a first construction module for 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; 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 a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir under a 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; a solution module for solving the target 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.

[0013] In a third aspect, the present invention provides an electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, and when the processor executes the computer program, it implements the method for determining the fracture fluid indicator factor of the deep coalbed methane reservoir described in any one of the aforementioned embodiments.

[0014] In a fourth aspect, 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 indicator factor of a deep coalbed methane reservoir described in any one of the aforementioned embodiments.

[0015] The present invention provides 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 for the deep coalbed methane reservoir directly expressed by six reservoir parameters: wave impedance, longitudinal 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 using synthetic azimuth gather seismic data from the deep coalbed methane reservoir in a target work area. Finally, by solving the target functional, the fracture fluid indicator factor of the deep coalbed methane reservoir can be directly inverted. This method avoids the error accumulation problem that exists in indirect inversion of the fracture fluid indicator factor, and thus can effectively alleviate the technical problem of poor inversion accuracy of the inversion results that exists in existing methods for determining the fracture fluid indicator 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 briefly introduces the drawings required for use in the specific embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0017] Figure 1 A flow chart of a method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention;

[0018] Figure 2 A schematic diagram of an orthotropic medium provided by an embodiment of the present invention;

[0019] Figure 3 A schematic diagram of actual values ​​of reservoir parameters in a logging area provided by an embodiment of the present invention;

[0020] Figure 4 A schematic diagram of a 90° azimuth synthetic seismic record provided by an embodiment of the present invention;

[0021] Figure 5 A comparison diagram of inversion results between the method according to an embodiment of the present invention and the existing indirect inversion method for fracture fluid indicator factors;

[0022] Figure 6 A functional module diagram of a device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention;

[0023] Figure 7 A schematic diagram of an electronic device provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0024] To make the objectives, technical solutions, and advantages of the embodiments of the present invention more clear, the technical solutions of the embodiments of the present invention will be clearly and completely described below in conjunction with the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Generally, the components of the embodiments of the present invention described and shown in the drawings herein can be arranged and designed in various different configurations.

[0025] 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 invention as claimed, but rather merely represents selected embodiments of the present invention. All other embodiments derived by persons of ordinary skill in the art based on the embodiments of the present invention without creative effort shall fall within the scope of protection of the present invention.

[0026] The following embodiments of the present invention are described in detail with reference to the accompanying drawings. In the absence of conflict, the following embodiments and features in the embodiments may be combined with each other.

[0027] Example 1

[0028] Figure 1 A flow chart of a method for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention is shown as follows: Figure 1 As shown, the method specifically includes the following steps:

[0029] Step S102: Acquire synthetic azimuth gather seismic data and well logging data of the deep coalbed methane reservoir in the target work area.

[0030] Step S104: constructing an initial reservoir parameter model of the deep coalbed methane reservoir based on the well logging data.

[0031] Among them, reservoir parameters include: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor and fracture tangential weakness.

[0032] Specifically, the synthetic azimuth gather seismic data is data obtained after seismic exploration of the deep coalbed methane reservoir in the target work area using professional data acquisition equipment, and the well logging data is directly or indirectly calculated from the well logging curve obtained by logging the deep coalbed methane reservoir in the target work area. The embodiment of the present invention does not specifically limit the data type contained in the well logging data, as long as the above-mentioned reservoir parameters can be obtained directly or indirectly.

[0033] Regarding the fracture tangential weakness in the reservoir parameters, the existing ultrasonic logging imaging data confirms that deep coalbed methane reservoirs generally have continuous bedding and are accompanied by the development of vertical or near-vertical fractures. Under the assumption of long-wavelength seismic data, deep coalbed methane reservoirs can be approximated as follows: Figure 2 For the orthotropic medium shown in FIG, when the fractures contained in the medium are vertical or nearly vertical fractures, the vertical tangential weakness of the fractures is approximately equal to the horizontal tangential weakness of the fractures, which are collectively referred to as the fracture tangential weakness.

[0034] It is known that the reservoir parameters of the logging area can be calculated based on the logging data and recorded as the actual value of the reservoir parameters in the logging area. Figure 3 This is a schematic diagram of actual values ​​of reservoir parameters in a logging area provided by an embodiment of the present invention. Next, an initial reservoir parameter model of a deep coalbed methane reservoir can be constructed by interpolating or low-pass filtering the actual values ​​of reservoir parameters in the logging area.

[0035] Step S106: construct an approximate PP wave reflection coefficient equation for a deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0036] In order to avoid the error accumulation problem caused by indirect inversion of the fracture fluid indicator factor, the embodiment of the present invention performs a series of processing 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, anisotropic parameters, fracture fluid indicator factor and fracture tangential weakness.

[0037] Step S108, based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of 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.

[0038] The following relationship exists between earthquake observation data with known azimuth and forward modeling earthquake data: ,in, represents synthetic azimuth gather seismic data, , represents the forward modeling seismic data, represents the seismic wavelet, represents the approximate PP wave reflection coefficient equation for deep coalbed methane reservoirs, represents the matrix composed of reservoir parameters, represents the noise of azimuthal seismic observation data.

[0039] Therefore, after obtaining the approximate equation of the longitudinal wave reflection coefficient 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 simulation seismic data, under the Bayesian inversion framework, with the premise that the prior distribution of reservoir parameters obeys the Cauchy distribution and the goal of maximizing the posterior distribution of reservoir parameters, a target functional for inverting the reservoir parameters of deep coalbed methane reservoirs can be constructed.

[0040] Step S110 , under the constraints of the initial reservoir parameter model and logging data, solve the target functional to obtain the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0041] The present embodiment does not impose specific limitations on the method for solving the target functional. It suffices to use an initial reservoir parameter model as the initial data for the storage parameters, and ensure that the error between the reservoir parameters in the logging region in the inversion results and the actual values ​​of the reservoir parameters in the logging region calculated based on the logging data is less than a preset threshold. Alternatively, a generalized linear inversion method can be combined with an iterative reweighted least squares algorithm to solve the target functional.

[0042] By solving the target functional, we can obtain the target model of the reservoir parameters, namely: the target model of wave impedance, the target model of compressional wave velocity, the target model of shear modulus, the target model of anisotropy parameters, the target model of fracture fluid indicator factor and the target model of fracture tangential weakness. Finally, the target model of fracture fluid indicator factor is used as the inversion result of fracture fluid indicator factor.

[0043] An embodiment of the present invention provides a method for determining a fracture fluid indicator factor in 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: wave impedance, longitudinal 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 using synthetic azimuth gather seismic data from the deep coalbed methane reservoir in a target work area. Finally, by solving the target functional, the fracture fluid indicator factor of the deep coalbed methane reservoir can be directly inverted. This method avoids the error accumulation problem that exists in indirect inversion of the fracture fluid indicator factor, and thus can effectively alleviate the technical problem of poor inversion accuracy of inversion results that exists in existing methods for determining the fracture fluid indicator factor of deep coalbed methane reservoirs.

[0044] In an optional embodiment, the above step S106, constructing an approximate PP wave reflection coefficient equation of a deep coalbed methane reservoir expressed in terms of reservoir parameters, specifically includes the following steps:

[0045] Step S1061: Obtain the PP wave reflection coefficient equation of the orthotropic medium.

[0046] Specifically, the PP wave reflection coefficient equation of orthotropic media is expressed as: (Formula 1); where represents the azimuthal seismic reflection coefficient, represents the angle of incidence, represents the azimuth relative to the crack normal plane, represents the wave impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, It represents the velocity anisotropy parameter in different symmetry planes of orthotropic media, the symbol ￣ represents the average value of the parameters of the two adjacent layers above and below, and the symbol Indicates the difference between the parameters of two adjacent strata.

[0047] Step S1062: Substitute the relationship between the anisotropic parameter and the fracture weakness difference and the relationship 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 in terms of wave impedance, longitudinal wave velocity, shear modulus, anisotropic parameter, fracture tangential weakness, and fracture normal weakness.

[0048] Starting from the elastic stiffness matrix, according to the orthotropic parameters The definition of , the relationship between the anisotropy parameter and the crack weakness difference is: (Formula 2); where, It represents the anisotropic parameter of the transversely isotropic background medium. The medium after adding vertical cracks to the transversely isotropic background medium is an orthotropic medium. Indicates the vertical tangential weakness of the crack, Indicates the horizontal tangential weakness of the crack, Represents the normal weakness of the crack, both are dimensionless parameters.

[0049] When the cracks in the medium are vertical or nearly vertical, the vertical tangential weakness of the cracks is approximately equal to the horizontal tangential weakness of the cracks, which are collectively referred to as the tangential weakness of the cracks. , that is, , and then there is (Formula 3).

[0050] Substituting the above formulas 2 and 3 into formula 1, we can get the first PP wave reflection coefficient equation: (Formula 4); Obviously, Formula 4 is an expression for wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture tangential weakness and fracture normal weakness.

[0051] Step S1063 , sorting the first PP-wave reflection coefficient equation and removing its high-order terms to retain only the second-order angle terms, thereby obtaining the second PP-wave reflection coefficient equation.

[0052] The embodiment of the present invention uses the following trigonometric identities in the field of mathematics to organize the first PP wave reflection coefficient equation: , , , based on the above trigonometric identities, we can get formula 4: (Formula 5).

[0053] Next, ignore the fourth-order and higher terms (such as 、 etc.), retaining to the second-order angle term. The simplified second PP wave reflection coefficient equation is expressed as: (Formula 6). Obviously, the fracture weakness term and the main influencing terms are completely retained, which means that the simplified formula can still reflect the orthotropic characteristics of the medium.

[0054] Step S1064: Based on the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and the fracture normal weakness, the second PP wave reflection coefficient equation is replaced with parameters to obtain an approximate PP wave reflection coefficient equation for the deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0055] The above formula 6 can be regarded as the sum of the R term affected by the vertical crack and the R term not affected by the vertical crack, that is: (Formula 7), where , (Formula 8).

[0056] Next, Taking the logarithm we get: (Formula 9). Based on Euler's formula, we can get: , (Formula 10), Substituting Formula 10 into Formula 9 yields: (Formula 11).

[0057] Schoenberg and Sayers (1995) proposed It can be used to indicate fracture fluid. When the reservoir contains gas, its value is usually larger. In the embodiment of the present invention, the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and the fracture normal weakness is as follows: (Formula 12).

[0058] Rewrite Equation 12 as: (Formula 13), and Find the total differential, the result is: (Formula 14), where , , , dividing both sides of Formula 14 by the crack normal weakness, we can obtain: (Formula 15), Substituting Formula 15 into the above Formula 11, we can get: (Equation 16).

[0059] In order to highlight the functional relationship between the PP wave reflection coefficient equation and the reservoir parameters to be inverted, the abbreviated for , for , for , the approximate PP wave reflection coefficient equation of deep coalbed methane reservoir is expressed as: ;in, , , ; represents the angle of incidence, represents the azimuth relative to the crack normal plane, represents the wave impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, , Both represent the anisotropic parameters of the transversely isotropic background medium, Indicates the tangential weakness of the crack, represents the fracture fluid indicator factor, the symbol ￣ represents the average value of the parameters of the two adjacent formations above and below, and the symbol Indicates the difference between the parameters of two adjacent strata.

[0060] In an optional embodiment, step S108, based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir, constructs a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir in a Bayesian inversion framework, specifically comprising the following steps:

[0061] Step S1081, extracting seismic wavelets from synthetic azimuth gather seismic data.

[0062] Step S1082: constructing a forward modeling formula for seismic data based on the deep coalbed methane reservoir approximate PP wave reflection coefficient equation and seismic wavelet.

[0063] Specifically, the method of extracting seismic wavelets from synthetic azimuth gather seismic data is a well-known technique in the art and will not be described in detail in the present embodiment. According to the above description, the formula for forward modeling seismic data is: , represents the seismic wavelet, represents the approximate PP wave reflection coefficient equation for deep coalbed methane reservoirs, represents the matrix consisting of reservoir parameters.

[0064] Step S1083, under the Bayesian inversion framework, with the premise that the prior distribution of reservoir parameters obeys the Cauchy distribution and the goal of maximizing the posterior distribution of reservoir parameters, a target functional is constructed based on the formula of synthetic azimuth gather seismic data and forward simulation seismic data.

[0065] Posterior probability distribution of inverted parameters in prestack seismic inversion under the Bayesian framework It can be expressed as a prior probability and the likelihood function The joint distribution of , that is, (Formula 17), where It is hypothetical Satisfies the prior distribution, is the probability distribution of the observed data under this model, is the distribution of the observed data.

[0066] Assuming that the noise of seismic data is Gaussian distributed and independent, the noise of seismic data of synthetic azimuth gather is The distribution of can be written as follows: (Formula 18), where Indicates a preset constant, represents the covariance matrix of the noise, Represents the noise of synthetic azimuth gather seismic data.

[0067] It is known that there is the following relationship between synthetic azimuth gather seismic data and forward modeling seismic data: (Formula 19), Substituting Formula 19 into Formula 18, we can obtain the likelihood function: (Equation 20).

[0068] Based on formula 17, the expression of the posterior distribution of the reservoir parameters to be inverted can be obtained: (Formula 21), assuming that the prior distribution of reservoir parameters obeys the Cauchy distribution, that is, (Formula 22), where The covariance matrix of the reservoir parameters, also known as the covariance matrix, whose order is determined by the number of reservoir parameters, characterizes the statistical correlation between the reservoir parameters to be inverted. represents the adjustment matrix, so that Including the statistical correlation between reservoir parameters. Based on this, Equation 21 can be rewritten as follows: (Formula 23).

[0069] According to the maximum a posteriori probability estimation, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir in the embodiment of the present invention can be constructed, which is expressed as: ;in, represents synthetic azimuth gather seismic data, represents the forward modeling seismic data, , represents the seismic wavelet, represents the approximate PP wave reflection coefficient equation for deep coalbed methane reservoirs, represents the matrix composed of reservoir parameters, represents the covariance matrix of the noise, Indicates the Layers, represents the total number of strata, 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 target functional, The larger the posterior probability The smaller, on the contrary, The smaller the posterior probability The bigger.

[0070] In an optional embodiment, the above step S110, solving the target functional under the constraints of the initial reservoir parameter model and the well logging data, specifically includes the following steps:

[0071] Step S1101: determining a formula for the reservoir parameter disturbance based on the target functional.

[0072] Optionally, the target functional is processed using generalized linear inversion and iterative reweighted least squares algorithm. Specifically, first, a first-order Taylor expansion is performed on the target functional at the initial model of the reservoir parameters according to the generalized linear inversion theory to obtain the target function of the reservoir parameters. Then, the partial derivative of the target function of the reservoir parameters with respect to the reservoir parameter perturbation is calculated to obtain the partial derivative function. Next, the partial derivative function is set equal to 0 to obtain a solution expression for the reservoir parameter perturbation. Finally, the above solution expression is simplified according to the iterative reweighted least squares joint algorithm to obtain the formula for the reservoir parameter perturbation: ,in, It represents the variance of the noise in the synthetic azimuth gather seismic data.

[0073] Step S1102, based on the initial model of reservoir parameters, the formula for the reservoir parameter disturbance amount, and the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data, the first reservoir parameter subset is iteratively updated until a preset number of iterations is reached to obtain a target model of the first reservoir parameter subset; wherein the first reservoir parameter subset includes: wave impedance, longitudinal wave velocity, shear modulus, and anisotropy parameters.

[0074] Figure 4 A schematic diagram of a 90° azimuth synthetic seismic record provided by an embodiment of the present invention. According to the above expression of the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir, when the azimuth angle When the value is 90 degrees, =0, that is, the seismic data with an azimuth angle of 90° is not affected by the vertical fractures of the formation. Therefore, the embodiment of the present invention first uses the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data to invert the four reservoir parameters in the first reservoir parameter subset. The initial model of the known reservoir parameters (In this step, only the initial model of the first reservoir parameter subset is used), and the formula for the reservoir parameter perturbation , the reservoir parameter disturbance formula Substituting the seismic data with an azimuth angle of 90 degrees and iterating a specified number of times, the target model of the first reservoir parameter subset can be obtained.

[0075] Step S1103 , forward modeling seismic data with an azimuth angle of 90 degrees using the target model of the first reservoir parameter subset to obtain target forward modeled seismic data.

[0076] Next, based on the forward equation , using the target model of the first reservoir parameter subset to forward model the seismic data with an azimuth of 90 degrees, the target forward modeling seismic data is obtained ,in, Represents the matrix consisting of the first reservoir parameter subset.

[0077] Step S1104, calculating the difference between the seismic data with non-90-degree azimuth angles in the synthetic azimuth gather seismic data and the target forward modeling seismic data to obtain the target seismic data.

[0078] That is, the target seismic data is expressed as: .in, Indicates the seismic data with an azimuth angle of non-90 degrees in the synthetic azimuth gather seismic data. Represents the target seismic data.

[0079] Step S1105, based on the initial reservoir parameter model, the formula for the reservoir parameter disturbance amount and the target seismic data, the second reservoir parameter subset is iteratively updated until a preset number of iterations is reached to obtain a target model of the second reservoir parameter subset; wherein the second reservoir parameter subset includes: a fracture fluid indicator factor and a fracture tangential weakness.

[0080] According to the expression of the approximate PP wave reflection coefficient equation of deep coalbed methane reservoir, if the incident angle is the same, then If they are equal, then according to the distribution rate of convolution, the difference between the seismic data with non-90-degree azimuth angle in the synthetic azimuth gather seismic data and the seismic data with 90-degree azimuth angle obtained by forward modeling can eliminate the influence of The affected earthquake records. That is, the target earthquake data Is only Affected earthquake records.

[0081] In view of this, in the initial model with known reservoir parameters (In this step, only the initial model of the second reservoir parameter subset is used), and the formula for the reservoir parameter perturbation Based on the reservoir parameter disturbance formula, Substitute the target earthquake data , and iterate a specified number of times to obtain the target model of the second reservoir parameter subset.

[0082] Step S1106 , calculating the inversion error of the reservoir parameter target model based on the well logging data; wherein the reservoir parameter target model represents a set of the target model of the first reservoir parameter subset and the target model of the second reservoir parameter subset.

[0083] Step S1107 : When it is determined that the inversion error is greater than or equal to the first preset threshold, the reservoir parameter target model is continuously iteratively updated until the inversion error is less than the first preset threshold.

[0084] Step S1108 : When it is determined that the inversion error is less than the first preset threshold, the fracture fluid indicator factor in the reservoir parameter target model is used as the fracture fluid indicator factor inversion result.

[0085] Generally, when inverting reservoir parameters, a high number of iterations is required to obtain stable inversion results. However, practice has shown that after a certain number of iterations, the change in the inversion result gradually decreases, and subsequent large-scale iterative updates do not substantially improve the inversion result itself. Therefore, in an embodiment of the present invention, the actual values ​​of the reservoir parameters in the logging area calculated based on the logging data are used as reference data. The error between the inversion results and the actual values ​​of the reservoir parameters in the logging area obtained after a preset number of iterations (set based on experience) is calculated and recorded as the inversion error. This embodiment of the present invention does not specifically limit the calculation method of the inversion error; as long as it can reflect the numerical differences, it can be used. For example, the sum of the errors between the inversion results and the actual values ​​of each reservoir parameter at multiple sampling points can be calculated. Then, an error weight can be assigned to each reservoir parameter, and the inversion error can be calculated using this weighted method.

[0086] If the inversion error is greater than or equal to the first preset threshold, the inversion accuracy is insufficient and further iteration of the currently obtained target model is required. The iterations continue according to the operations in steps S1102-S1105 above, replacing the initial model of the reservoir parameters with the currently achieved target model. Optionally, the user can choose to recalculate the inversion error after a specified number of iterations (method one), or calculate the inversion error once per model iteration (method two). The specific method to be selected is determined based on the results of the previous inversion error calculation. If the difference between the inversion error and the first preset threshold is greater than a specified value, method one is selected; if the difference between the inversion error and the first preset threshold is less than or equal to a specified value, method two is selected.

[0087] After multiple iterations, if the inversion error is less than the first preset threshold, it means that the inversion accuracy meets the requirement, and the fracture fluid indicator factor in the reservoir parameter target model can be used as the fracture fluid indicator factor inversion result. Figure 5 This is a comparison chart of the inversion results of the embodiment of the present invention and the existing indirect inversion method of fracture fluid indicator factors. Figure 5 In the figure, 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 common 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. Figure 5 It can be seen that the fracture fluid indicator factor of deep coalbed methane reservoirs is significantly different from that of the surrounding rock. Compared with the indirect inversion method, the inversion results of the method provided by the embodiment of the present invention are more consistent with the actual values, that is, the method of the present invention is more effective and feasible.

[0088] The embodiment of the present invention is based on the method for solving the target functional provided above, which can effectively reduce the number of inversion iterations while ensuring the inversion accuracy of reservoir parameters, shorten the method running time, and thus improve the execution efficiency.

[0089] In an optional embodiment, 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:

[0090] When the fracture fluid indication factor is less than or equal to the second preset threshold, the fracture fluid filling type is determined to be liquid.

[0091] When the fracture fluid indication factor is greater than the second preset threshold, the fracture fluid filling type is determined to be gas.

[0092] That is, the numerical value of the fracture fluid indicator factor can be used to accurately identify the fluid filling type of deep coalbed methane reservoir fractures. 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.

[0093] Example 2

[0094] An embodiment of the present invention also provides a device for determining the fracture fluid indicator factor of a deep coalbed methane reservoir. The device is mainly used to execute the method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir provided in the above-mentioned embodiment 1. The following is a detailed introduction to the device for determining the fracture fluid indicator factor of a deep coalbed methane reservoir provided in an embodiment of the present invention.

[0095] Figure 6 A functional module diagram of a device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided by an embodiment of the present invention, such as Figure 6 As shown, the 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, wherein:

[0096] The acquisition module 10 is used to acquire synthetic azimuth gather seismic data and well logging data of the deep coalbed methane reservoir in the target work area.

[0097] The first construction module 20 is used to construct an initial reservoir parameter model of a deep coalbed methane reservoir based on logging data; wherein the reservoir parameters include: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor and fracture tangential weakness.

[0098] The second construction module 30 is used to construct an approximate PP wave reflection coefficient equation for a deep coalbed methane reservoir expressed in terms of reservoir parameters.

[0099] The third construction module 40 is used to construct a target functional for inverting reservoir parameters of deep coalbed methane reservoirs based on synthetic azimuth gather seismic data and approximate PP wave reflection coefficient equation of deep coalbed methane reservoirs in a Bayesian inversion framework.

[0100] The solving module 50 is used to solve the target functional under the constraints of the initial model of reservoir parameters and logging data to obtain the inversion result of the fracture fluid indicator factor of the deep coalbed methane reservoir.

[0101] An embodiment of the present invention provides a device for determining a fracture fluid indicator factor in 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: wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor, and fracture tangential weakness. The device then combines synthetic azimuth gather seismic data from the deep coalbed methane reservoir in a target work area to construct a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir. Finally, by solving the target functional, the fracture fluid indicator factor of the deep coalbed methane reservoir can be directly inverted. This device avoids the error accumulation problem that exists in indirect inversion of the fracture fluid indicator factor, and thus can effectively alleviate the technical problem of poor inversion accuracy of inversion results that exists in existing methods for determining the fracture fluid indicator factor of deep coalbed methane reservoirs.

[0102] Optionally, the second building module 30 is specifically configured to:

[0103] Obtain the PP wave reflection coefficient equation for orthotropic media.

[0104] The relationship between the anisotropy parameter and the difference in fracture weakness and the relationship that the vertical tangential weakness and the horizontal tangential weakness of the fracture are both equal to the tangential weakness of the fracture are substituted into the PP-wave reflection coefficient equation of the orthotropic medium. The first PP-wave reflection coefficient equation expressed in terms of wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture tangential weakness, and fracture normal weakness is obtained.

[0105] The first PP-wave reflection coefficient equation is reorganized and its high-order terms are eliminated to retain the second-order angle terms, thereby obtaining the second PP-wave reflection coefficient equation.

[0106] Based on the algebraic relationship between the fracture fluid indicator factor and the fracture tangential weakness and fracture normal weakness, the second PP wave reflection coefficient equation is replaced by parameters, and the approximate PP wave reflection coefficient equation of deep coalbed methane reservoir expressed by reservoir parameters is obtained.

[0107] Optionally, the third building block 40 is specifically configured to:

[0108] Extract seismic wavelets from synthetic azimuth gather seismic data.

[0109] Based on the approximate PP wave reflection coefficient equation of deep coalbed methane reservoir and seismic wavelet, a formula for forward modeling of seismic data is constructed.

[0110] In the Bayesian inversion framework, with the premise that the prior distribution of reservoir parameters obeys the Cauchy distribution and the goal of maximizing the posterior distribution of reservoir parameters, a target functional is constructed based on the formula of synthetic azimuth gather seismic data and forward simulation seismic data.

[0111] Optionally, the solution module 50 is specifically configured to:

[0112] Formula for determining reservoir parameter perturbation based on target functional.

[0113] Based on the initial reservoir parameter model, the formula for the reservoir parameter disturbance amount, and the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data, the first reservoir parameter subset is iteratively updated until a preset number of iterations is reached, thereby obtaining a target model of the first reservoir parameter subset; wherein the first reservoir parameter subset includes: wave impedance, compressional wave velocity, shear modulus, and anisotropy parameters.

[0114] The target model of the first reservoir parameter subset is used to forward model the seismic data with an azimuth angle of 90 degrees to obtain target forward modeling seismic data.

[0115] The difference between the seismic data with non-90-degree azimuth angles in the synthetic azimuth gather seismic data and the target forward modeling seismic data is calculated to obtain the target seismic data.

[0116] Based on the initial reservoir parameter model, the formula for the reservoir parameter disturbance amount, and the target seismic data, the second reservoir parameter subset is iteratively updated until a preset number of iterations is reached, thereby obtaining a target model of the second reservoir parameter subset; wherein the second reservoir parameter subset includes: a fracture fluid indicator factor and a fracture tangential weakness.

[0117] An inversion error of a reservoir parameter target model is calculated based on the well logging data; wherein the reservoir parameter target model represents a collection of a target model of a first reservoir parameter subset and a target model of a second reservoir parameter subset.

[0118] When it is determined that the inversion error is greater than or equal to the first preset threshold, the reservoir parameter target model is continuously iteratively updated until the inversion error is less than the first preset threshold.

[0119] When it is determined that the inversion error is less than the first preset threshold, the fracture fluid indicator factor in the reservoir parameter target model is used as the fracture fluid indicator factor inversion result.

[0120] Optionally, the device is further used to:

[0121] When the fracture fluid indication factor is less than or equal to the second preset threshold, the fracture fluid filling type is determined to be liquid.

[0122] When the fracture fluid indication factor is greater than the second preset threshold, the fracture fluid filling type is determined to be gas.

[0123] Alternatively, the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir is expressed as: ;in, , , ; represents the angle of incidence, represents the azimuth relative to the crack normal plane, represents the wave impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, , Both represent the anisotropic parameters of the transversely isotropic background medium, Indicates the tangential weakness of the crack, represents the fracture fluid indicator factor, the symbol ￣ represents the average value of the parameters of the two adjacent formations above and below, and the symbol Indicates the difference between the parameters of two adjacent strata.

[0124] Alternatively, the target functional for inverting the reservoir parameters of a deep coalbed methane reservoir is expressed as: ;in, represents synthetic azimuth gather seismic data, represents the forward modeling seismic data, , represents the seismic wavelet, represents the approximate PP wave reflection coefficient equation for deep coalbed methane reservoirs, represents the matrix composed of reservoir parameters, represents the covariance matrix of the noise, Indicates the Layers, represents the total number of strata, represents the covariance matrix, represents the adjustment matrix.

[0125] Example 3

[0126] See also 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, wherein the processor 60, the communication interface 63 and the memory 61 are connected via the bus 62; the processor 60 is used to execute an executable module stored in the memory 61, such as a computer program.

[0127] Memory 61 may include high-speed random access memory (RAM) and may also include non-volatile memory, such as at least one disk drive. Communication between the system network element and at least one other network element is achieved via at least one communication interface 63 (which may be wired or wireless), and may utilize the Internet, a wide area network, a local area network, a metropolitan area network, or the like.

[0128] The bus 62 may be an ISA bus, a PCI bus, or an EISA bus. The bus may be divided into an address bus, a data bus, a control bus, and the like. For ease of representation, Figure 7 Only one bidirectional arrow is used in the diagram, but this does not mean that there is only one bus or one type of bus.

[0129] Among them, the memory 61 is used to store programs, and the processor 60 executes the program after receiving the execution instruction. The method executed by the device defined by the process disclosed in any embodiment of the above-mentioned embodiment of the present invention can be applied to the processor 60 or implemented by the processor 60.

[0130] The processor 60 may be an integrated circuit chip with signal processing capabilities. During implementation, the steps of the above method may be performed by hardware integrated logic circuits or software instructions within the processor 60. The processor 60 may be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it may also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components. It may implement or execute the methods, steps, and logic block diagrams disclosed in the embodiments of the present invention. The general-purpose processor may be a microprocessor or any conventional processor. The steps of the methods disclosed in the embodiments of the present invention may be directly executed by a hardware decoding processor or by a combination of hardware and software modules within the decoding processor. The software modules may be located in storage media well-known in the art, such as random access memory, flash memory, read-only memory, programmable read-only memory, electrically erasable programmable memory, registers, or the like. The storage medium is located in the memory 61 , and the processor 60 reads the information in the memory 61 and completes the steps of the above method in combination with its hardware.

[0131] The computer program product of a method and apparatus for determining a fracture fluid indicator factor of a deep coalbed methane reservoir provided in an embodiment of the present invention includes a computer-readable storage medium storing a 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 previous method embodiment. For specific implementation, please refer to the method embodiment and will not be repeated here.

[0132] In addition, each functional unit in each embodiment of the present invention may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.

[0133] If the functions are implemented as software functional units and sold or used as independent products, they can be stored in a processor-executable, non-volatile, computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the portion that contributes to the prior art, or a portion of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present invention. The aforementioned storage media include various media capable of storing program code, such as USB flash drives, mobile hard drives, read-only memories (ROMs), random access memories (RAMs), magnetic disks, or optical disks.

[0134] It should be noted that similar reference numerals and letters denote similar items in the following drawings, and therefore, once an item is defined in one drawing, it does not need to be further defined or explained in subsequent drawings.

[0135] In the description of the present invention, it should be noted that the terms "center," "upper," "lower," "left," "right," "vertical," "horizontal," "inner," and "outer" and the like indicate positions or locations based on the positions shown in the accompanying drawings, or the positions or locations in which the inventive product is typically placed when in use. These terms are intended solely to facilitate the description of the present invention and to simplify the description, and are not intended to indicate or imply that the devices or components referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limitations on the present invention. Furthermore, the terms "first," "second," and "third," etc., are used solely to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0136] Furthermore, terms such as "horizontal," "vertical," and "overhanging" do not necessarily imply that a component must be absolutely horizontal or overhanging, but rather that it can be slightly tilted. For example, "horizontal" simply means that its direction is more horizontal than "vertical," and does not mean that the structure must be completely horizontal, but rather that it can be slightly tilted.

[0137] In the description of the present invention, it should also be noted that, unless otherwise expressly specified or limited, the terms "disposed," "installed," "connected," and "connected" should be understood in a broad sense. For example, they may refer to fixed connections, detachable connections, or integral connections; they may refer to mechanical connections or electrical connections; they may refer to direct connections or indirect connections through an intermediate medium; and they may refer to internal communication between two components. Those skilled in the art will understand the specific meanings of the above terms in the present invention based on the specific circumstances.

[0138] 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 it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or replace some or all of the technical features therein with equivalents. However, 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: include: Acquire synthetic azimuth gather seismic data and well logging data of deep coalbed methane reservoirs in the target work area; constructing an initial reservoir parameter model of the deep coalbed methane reservoir based on the well logging data; the reservoir parameters include: wave impedance, compressional wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor and fracture tangential weakness; Constructing an approximate PP wave reflection coefficient equation for a deep coalbed methane reservoir expressed using the reservoir parameters; Based on the synthetic azimuth gather seismic data and the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed under a Bayesian inversion framework; Determine a formula for a reservoir parameter disturbance based on the target functional; Iteratively updating a first reservoir parameter subset based on the reservoir parameter initial model, the reservoir parameter disturbance amount formula, and the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data until a preset number of iterations is reached to obtain a target model of the first reservoir parameter subset; the first reservoir parameter subset includes: wave impedance, compressional wave velocity, shear modulus, and anisotropy parameter; forward modeling seismic data with an azimuth angle of 90 degrees using the target model of the first reservoir parameter subset to obtain target forward modeled seismic data; Calculate the difference between the seismic data with an azimuth angle of non-90 degrees in the synthetic azimuth gather seismic data and the target forward modeling seismic data to obtain the target seismic data; Iteratively updating a second reservoir parameter subset based on the initial reservoir parameter model, the formula for the reservoir parameter disturbance amount, and the target seismic data until a preset number of iterations is reached to obtain a target model of the second reservoir parameter subset; the second reservoir parameter subset includes: a fracture fluid indicator factor and a fracture tangential weakness; Calculating an inversion error of a reservoir parameter target model based on the well logging data; the reservoir parameter target model represents a set of a target model of the first reservoir parameter subset and a target model of the second reservoir parameter subset; When it is determined that the inversion error is greater than or equal to a first preset threshold, continuing to iteratively update the reservoir parameter target model until the inversion error is less than the first preset threshold; When it is determined that the inversion error is less than the first preset threshold, the fracture fluid indicator factor in the reservoir parameter target model is used as the fracture fluid indicator factor inversion result 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 for a deep coalbed methane reservoir expressed using the reservoir parameters, including: Obtain the PP wave reflection coefficient equation for orthotropic media; Substituting the relationship between the anisotropy parameter and the difference in fracture weakness and the relationship that both the fracture vertical tangential weakness and the fracture horizontal tangential weakness are equal to the fracture tangential weakness into the PP wave reflection coefficient equation of the orthotropic medium, a first PP wave reflection coefficient equation expressed in terms of wave impedance, longitudinal wave velocity, shear modulus, anisotropy parameter, fracture tangential weakness, and fracture normal weakness is obtained; Arranging the first PP-wave reflection coefficient equation and removing its high-order terms to retain only the second-order angle terms, thereby obtaining 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, the second PP wave reflection coefficient equation is replaced with parameters to obtain an approximate PP wave reflection coefficient equation for 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 azimuth gather seismic data and the approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir, a target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is constructed under a Bayesian inversion framework, including: extracting seismic wavelets from the synthetic azimuth gather seismic data; Based on the deep coalbed methane reservoir approximate PP wave reflection coefficient equation and the seismic wavelet, constructing a formula for forward modeling seismic data; In the Bayesian inversion framework, with the premise that the prior distribution of the reservoir parameters obeys the Cauchy distribution and the goal of maximizing the posterior distribution of the reservoir parameters, the target functional is constructed based on the formula of the synthetic azimuth gather seismic data and the forward simulation seismic data.

4. 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 fracture fluid indicator factor inversion result of the deep coalbed methane reservoir, the method further includes: When the fracture fluid indicator factor is less than or equal to a second preset threshold, determining that the fracture fluid filling type is liquid; When the fracture fluid indication factor is greater than the second preset threshold, the fracture fluid filling type is determined to be gas.

5. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 1, characterized in that: The approximate PP wave reflection coefficient equation of the deep coalbed methane reservoir is expressed as: ;in, , , ; represents the angle of incidence, represents the azimuth relative to the crack normal plane, represents the wave impedance, represents the longitudinal wave velocity, , represents the shear wave velocity, represents the shear modulus, , Both represent the anisotropic parameters of the transversely isotropic background medium, Indicates the tangential weakness of the crack, represents the fracture fluid indicator factor, the symbol ￣ represents the average value of the parameters of the two adjacent formations above and below, and the symbol Indicates the difference between the parameters of two adjacent strata.

6. The method for determining the fracture fluid indicator factor of a deep coalbed methane reservoir according to claim 3, characterized in that: The target functional for inverting the reservoir parameters of the deep coalbed methane reservoir is expressed as: ;in, represents the synthetic azimuth gather seismic data, represents the forward modeling 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, Indicates the Layers, represents the total number of strata, represents the covariance matrix, represents the adjustment matrix.

7. A device for determining a fracture fluid indicator factor of a deep coalbed methane reservoir, characterized in that: include: Acquisition module, used to obtain synthetic azimuth gather seismic data and well logging data of deep coalbed methane reservoirs in the target work area; A first construction module is used to construct an initial reservoir parameter model of the deep coalbed methane reservoir based on the well logging data; the reservoir parameters include: wave impedance, compressional wave velocity, shear modulus, anisotropy parameter, fracture fluid indicator factor and fracture tangential weakness; The second construction module is used to construct an approximate PP wave reflection coefficient equation of a deep coalbed methane reservoir expressed by the reservoir parameters; A third construction module is configured to construct a target functional for inverting reservoir parameters of the deep coalbed methane reservoir under a 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; A solution module, configured to determine a formula for a reservoir parameter disturbance based on the target functional; Iteratively updating a first reservoir parameter subset based on the reservoir parameter initial model, the reservoir parameter disturbance amount formula, and the seismic data with an azimuth angle of 90 degrees in the synthetic azimuth gather seismic data until a preset number of iterations is reached to obtain a target model of the first reservoir parameter subset; the first reservoir parameter subset includes: wave impedance, compressional wave velocity, shear modulus, and anisotropy parameter; forward modeling seismic data with an azimuth angle of 90 degrees using the target model of the first reservoir parameter subset to obtain target forward modeled seismic data; Calculate the difference between the seismic data with an azimuth angle of non-90 degrees in the synthetic azimuth gather seismic data and the target forward modeling seismic data to obtain the target seismic data; Iteratively updating a second reservoir parameter subset based on the initial reservoir parameter model, the formula for the reservoir parameter disturbance amount, and the target seismic data until a preset number of iterations is reached to obtain a target model of the second reservoir parameter subset; the second reservoir parameter subset includes: a fracture fluid indicator factor and a fracture tangential weakness; Calculating an inversion error of a reservoir parameter target model based on the well logging data; the reservoir parameter target model represents a set of a target model of the first reservoir parameter subset and a target model of the second reservoir parameter subset; When it is determined that the inversion error is greater than or equal to a first preset threshold, continuing to iteratively update the reservoir parameter target model until the inversion error is less than the first preset threshold; When it is determined that the inversion error is less than the first preset threshold, the fracture fluid indicator factor in the reservoir parameter target model is used as the fracture fluid indicator factor inversion result of the deep coalbed methane reservoir.

8. An electronic device comprising a memory and a processor, wherein the memory stores a computer program that can be run on the processor, wherein: When the processor executes the computer program, the method for determining the fracture fluid indicator factor of the deep coalbed methane reservoir according to any one of claims 1 to 6 is implemented.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores computer instructions, and when the computer instructions are executed by a processor, the method for determining the fracture fluid indicator factor of the deep coalbed methane reservoir according to any one of claims 1 to 6 is implemented.

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