Method and apparatus for characterizing seismic geology of coal bed methane reservoirs with external water supply

Abstract

The application discloses a kind of coalbed gas reservoir exogenous water transmissive supply seismic geology's characterization method and equipment, it is related to coalbed gas development field, the method includes: using the poststack seismic data of research area to invert the aquifer thickness and aquifer proportion of research area;Based on OVT seismic data, the fracture density of research area is predicted;Equivalent conversion water level of research area is calculated;Further, the average water production of per 100m liquid level drop of research area is determined by the way of multiple regression analysis.The application considers static elements such as aquifer thickness, aquifer proportion, fracture density, and further considers dynamic elements such as equivalent conversion water level, determines exogenous water transmissive supply by multiple regression analysis, i.e.the average water production of per 100m liquid level drop, which can effectively exclude the water production of coalbed gas well caused by exogenous water, form effective pressure relief surface, and further ensure gas production, provide protection and technical support for high and stable production of coalbed gas well.

Description

Technical Field

[0001] This invention relates to the field of coalbed methane development, and in particular to a method and equipment for characterizing the seismic geology of external water recharge in coalbed methane reservoirs. Background Technology

[0002] Currently, the main method for extracting coalbed methane (CBM) is depressurization through drainage. Continuous drainage lowers the pressure in the coal reservoir until it falls below the critical desorption pressure of CBM. At this point, the gas desorbs from the coal surface, migrates, diffuses, and is eventually extracted to the surface through the wellbore. Generally, the more water drainage a CBM well produces, the better it is for depressurizing the coal reservoir and the better the gas production. However, in actual development, CBM wells with excessively high water production often have poor gas production, especially those that continuously produce large amounts of water, which commonly exhibit low or no gas production. Research shows that the produced water in CBM wells mainly comes from two sources: water within the coal reservoir and external water sources. Compared to the sandstone or limestone aquifers adjacent to the coal seam, the coal seam has weak water content and a low water cut. Excessive water production in CBM wells is often due to the removal of external water sources. Abnormally high water production makes it difficult to reduce the fluid content of coalbed methane wells and results in poor coalbed methane desorption. Excessive water production can easily damage the reservoir, leading to deterioration of physical properties. In addition, continuous fluid flushing of proppant or carrying coal dust can reduce permeability or even cause the failure of conductivity, resulting in inefficient coalbed methane development.

[0003] Patent document CN116681543A discloses a method for studying and finely characterizing the recharge sources of groundwater in coal seams. The method mainly includes the following steps: determining the sampling locations for surface water and groundwater; conducting experiments to obtain experimental data from the collected water samples; and plotting the Piper tri-line diagram, Scholler diagram, hydrogen and oxygen isotope correlation diagram with ions, isotope contour map, and δ¹⁸O diagram of the water samples in the study area. 11 B-value (a "fingerprint" in boron isotope geochemistry, used to measure the concentration of boron in a sample) 11 B / 10 The relationship between the relative levels of B (in‰) and B concentration is illustrated; the groundwater migration pathways are identified, and the possibility of cross-layer recharge is analyzed; a groundwater migration model for coal reservoirs in the study area is established; coal seam thickness and depth data are overlaid on the groundwater flow field migration model, and combined with gas content, coal petrographic composition data, and coal body structural characteristics, the recoverability of coalbed methane in different areas is comprehensively analyzed, and development blocks are optimized. However, this study only utilizes parameter well information and does not consider the heterogeneity of coal reservoirs, water conduction channels, or the energy of groundwater recharge.

[0004] Current research on high water production in coal reservoirs mainly considers the water content of the coal seam or the top and bottom plates, but rarely considers the communication between the coal reservoir and adjacent aquifers and the influence of the local hydrodynamic field caused by the relative altitude. It cannot effectively eliminate the water production of coalbed methane wells caused by external water sources, cannot form an effective pressure reduction surface, and thus cannot guarantee gas production. Summary of the Invention

[0005] The purpose of this invention is to provide a method and equipment for characterizing the seismic geology of external water recharge in coalbed methane reservoirs, which can effectively eliminate the water production of coalbed methane wells caused by external water, form an effective pressure reduction surface, and thus ensure gas production.

[0006] To achieve the above objectives, the present invention provides the following solution.

[0007] In a first aspect, a method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs is provided, the method comprising:

[0008] The thickness and proportion of aquifers in the study area were retrieved using post-stack seismic data of the study area.

[0009] Predict the crack density in the study area based on OVT (offset vector tile) seismic data;

[0010] Calculate the equivalent water level for the study area;

[0011] Based on the aquifer thickness, aquifer proportion, fracture density, and equivalent water level in the study area, the average water production per 100-meter drop in the liquid level was determined using multiple regression analysis.

[0012] Optionally, the aquifer thickness and aquifer percentage in the study area can be inverted using post-stack seismic data of the study area, specifically including:

[0013] Construct time-domain pseudo-gamma acoustic curves for the target layer segment in the study area;

[0014] The initial wave impedance is constructed by post-stack inversion based on the time-domain quasi-gamma acoustic wave curve.

[0015] Based on the initial wave impedance obtained by post-stack inversion, the wave impedance at different locations and depths in the study area is obtained by inversion iteration method, and the wave impedance distribution model of the study area is obtained.

[0016] Based on the wave impedance distribution model, the aquifer thickness and aquifer percentage in the study area are determined.

[0017] Optionally, construct the time-domain pseudo-gamma acoustic curves of the target layer segment in the study area, specifically including:

[0018] The time spectrum of seismic data for the target segment is calculated using the following formula;

[0019] ;

[0020] in, For time spectrum, and They represent time and frequency on the time spectrum, respectively. Indicates earthquake signal, Indicates the time on the seismic signal. Represents the Gaussian window function. This represents a time delay window function. Indicates the number of sampling points;

[0021] Based on the aforementioned time spectrum, determine the lower frequency limit of the seismic data frequency components. r and frequency limit Among them, the lower frequency limit and frequency limit The determination method is as follows: First, determine the maximum amplitude value in the time spectrum of the seismic data, and take the frequencies at 20% of the maximum amplitude value corresponding to the low-frequency end and the high-frequency band as the lower frequency limit and the upper frequency limit, respectively.

[0022] The high-frequency component of the gamma curve frequency spectrum and the low-frequency component of the acoustic logging curve frequency spectrum are extracted based on the lower frequency limit and the upper frequency limit; the frequency range of the high-frequency component is ( , The frequency range of the low-frequency component is: ( , );in, The highest frequency of the logging curve. The lowest frequency of the logging curve. This is the lower limit of frequency. This is the upper limit of frequency. This is the frequency overlap, typically taken as 5Hz;

[0023] By combining the high-frequency components of the gamma curve frequency spectrum and the low-frequency components of the sonic logging curve frequency spectrum, a pseudo-gamma sonic curve in the frequency domain is obtained.

[0024] The quasi-gamma sound wave curve in the frequency domain is subjected to an inverse Fourier transform to obtain the quasi-gamma sound wave curve in the time domain.

[0025] Optionally, the formula for obtaining the wave impedance at different locations and depths in the study area using the inversion iteration method based on the initial wave impedance obtained by post-stack inversion is as follows:

[0026] ;

[0027] in, This is the wave impedance correction amount. To invert the Hase matrix of the objective function, Let be the covariance matrix of the noise. This is the inverse of the covariance matrix of the wave impedance output by the inversion model. The superscript indicates the gradient of the inversion objective function. Indicates transpose. This represents the initial wave impedance after stacking inversion.

[0028] Optionally, the inversion objective function is the deviation between the seismic wave amplitude value corresponding to the wave impedance output by the inversion model and the seismic wave amplitude value in the actual seismic data.

[0029] Optionally, based on the wave impedance distribution model, the aquifer thickness and aquifer percentage in the study area are determined, specifically including:

[0030] The wave impedance range of aquifers was determined by conducting physical statistical analysis on rocks of different lithologies.

[0031] The aquifer distribution region in the wave impedance distribution model is determined based on the wave impedance range of the aquifer.

[0032] The aquifer thickness and aquifer percentage are calculated based on the aquifer distribution area.

[0033] Optionally, the formula for predicting the crack density in the study area based on OVT seismic data is:

[0034] ;

[0035] in, This represents the amplitude of P-wave reflections in OVT seismic data. It is the azimuth angle from the excitation point to the receiver point. It is the azimuth angle of the crack's direction. This represents a parameter reflecting the change in amplitude with the distance between guns. This represents a parameter reflecting the variation of amplitude with gun spacing and azimuth; among which, Used to characterize crack density.

[0036] Optionally, the formula for calculating the equivalent water level of the study area is:

[0037] ;

[0038] ;

[0039] in, For equivalent water level; This represents the absolute elevation of the bottom of the well in the study area; The absolute elevation of the reference surface for the study area; Formation pressure; To calculate the pressure; The relative density of groundwater with depth A changing function; This represents the relative density of fresh water.

[0040] Optionally, based on the aquifer thickness, aquifer proportion, fracture density, and equivalent water level in the study area, the formula for determining the average water production per 100-meter drop in the study area using multiple regression analysis is as follows:

[0041] ;

[0042] In the formula, This represents the average water production per 100-meter drop in the liquid level of the study area. , , and These are the fracture density, aquifer thickness, aquifer proportion, and equivalent water level of the study area, respectively. , , and These are the weighting coefficients for fracture density, aquifer thickness, aquifer proportion, and equivalent water level, respectively.

[0043] In a second aspect, a computer device is provided, comprising: a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the method described above.

[0044] According to specific embodiments provided by the present invention, the present invention discloses the following technical effects:

[0045] This invention provides a method and equipment for characterizing the seismic geology of external water recharge in coalbed methane reservoirs. The method includes: inverting the aquifer thickness and aquifer percentage in the study area using post-stack seismic data; predicting the fracture density in the study area based on OVT seismic data; calculating the equivalent water level in the study area; and determining the average water production per 100-meter drop in the study area using multiple regression analysis based on the aquifer thickness, aquifer percentage, fracture density, and equivalent water level. This invention, considering static factors such as aquifer thickness, aquifer percentage, and fracture density, further incorporates dynamic factors such as the equivalent water level. By using multiple regression analysis to determine the external water recharge, i.e., the average water production per 100-meter drop in the water level, it can effectively eliminate water production in coalbed methane wells caused by external water, forming an effective pressure reduction surface, thereby ensuring gas production and providing a guarantee and technical support for high and stable production of coalbed methane wells. Attached Figure Description

[0046] To more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0047] Figure 1 A flowchart illustrating a seismic geological characterization method for external water recharge in coalbed methane reservoirs, provided as an embodiment of the present invention;

[0048] Figure 2 A schematic diagram illustrating the relationship between the average water production per 100-meter drop in water level and aquifer thickness, aquifer proportion, fracture density, and equivalent water level, provided for embodiments of the present invention.

[0049] Figure 3 A schematic diagram of coal seam external water production risk based on the average water production value of the 100-meter liquid level drop, provided for embodiments of the present invention;

[0050] Figure 4 An internal structural diagram of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] The purpose of this invention is to provide a method and equipment for characterizing the seismic geology of external water recharge in coalbed methane reservoirs, which can effectively eliminate the water production of coalbed methane wells caused by external water, form an effective pressure reduction surface, and thus ensure gas production.

[0053] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0054] The water production capacity of coal seams is closely related to parameters such as fracture development in the aquifer strata, the proportion of aquifers, the thickness of the main aquifers, and the hydraulic head elevation. This invention uses geophysical methods to predict key characterization parameters, including roof lithology, aquifer thickness, and fracture development. Combined with hydrological analysis of energy parameters such as hydraulic head elevation, it comprehensively predicts the main controlling factors of overflow recharge. It proposes a quantitative index of water production capacity based on the unit liquid level drop, and uses multiple regression analysis to determine the main controlling factors of external water overflow recharge and assess water production risks, providing assurance and technical support for high and stable coalbed methane well production.

[0055] Example 1

[0056] like Figure 1 As shown in the figure, this embodiment provides a method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs. The method includes:

[0057] Step 101 involves using post-stack seismic data of the study area to invert the aquifer thickness and aquifer percentage of the study area, specifically including the following steps.

[0058] 1.1 Prediction of Lithology and Thickness of Coal-Bearing Strata. Given that the old age of coal-bearing strata results in small differences in elastic parameters between sandstone and mudstone, the sensitivity of gamma curves to lithology makes it easy to distinguish between sandstone and mudstone. Phase control inversion constrained by gamma-reconstructed pseudo-acoustic curves is used to predict the thickness and spatial distribution of aquifers.

[0059] 1.1.1 The specific implementation steps for reconstructing pseudo-gamma sonic logging curves are as follows.

[0060] a. First, use spectral analysis to calculate the time spectrum of the target layer and determine the effective frequency band of the seismic data, i.e., the lower frequency limit of the seismic data frequency components. and frequency limit .

[0061] The time spectrum calculation process is as follows: Assume Indicates earthquake signal, Describes the Gaussian window function (where, The signal sampling interval; The larger the value, the larger the window width, and vice versa. Then the time spectrum... It can be represented as:

[0062] (1)

[0063] in, For time spectrum, and They represent time and frequency on the time spectrum, respectively. Indicates earthquake signal, Indicates the time on the seismic signal. Represents the Gaussian window function. This represents a time delay window function. Indicates the number of sampling points.

[0064] b. Use Fourier transform to convert the gamma curve GR and the sonic logging curve AC to the frequency domain, respectively. The calculation formula is as follows:

[0065] , (2)

[0066] in, Indicates frequency, , Let represent the frequency spectra of the gamma curves GR and AC, respectively. The calculated frequency bands of the AC and GR curves are (C Hz - D Hz).

[0067] c. Based on the lower frequency limit determined in step a and frequency limit Based on the spectral results of the AC and GR curves calculated in step b, the frequency range of the low-frequency component of the AC curve is extracted as follows: , The frequency range of the high-frequency components of the GR curve is ( ) , The two are combined to obtain the pseudo-gamma sound wave curve in the frequency domain. :

[0068] (3)

[0069] in, This represents the low-frequency component of the AC curve. These are the high-frequency components of the GR curve.

[0070] The bandwidth of the reconstructed quasi-gamma acoustic waveform is: ~( ).

[0071] d. Transform the reconstructed frequency-domain quasi-gamma sound wave curve to the time domain using an inverse Fourier transform to obtain the time-domain quasi-gamma sound wave curve. The calculation formula is as follows:

[0072] (4)

[0073] The time-domain pseudo-gamma sonic curves were calculated, providing an initial model and well logging constraints for lithology and thickness seismic inversion.

[0074] 1.1.2 Predicting aquifer lithology and thickness using post-stack seismic inversion. The specific implementation steps are as follows:

[0075] a. Establish the initial model: Construct the initial model for post-stack inversion using the quasi-gamma acoustic wave curve reconstructed in the previous step, that is, establish the initial values ​​for inversion using the low-frequency components of the reconstructed curve.

[0076] b. Establish the inversion objective function based on the nonlinear inversion framework:

[0077] (5)

[0078] In the formula, z is the wave impedance, s is the model response, and d is the actual seismic record.

[0079] c. Establish the inversion iterative formula and termination condition.

[0080] Expanding equation (5) near a given initial wave impedance using Taylor series yields the following result.

[0081] (6)

[0082] In the formula, for The change in the inversion objective function at that point. , for The inversion objective function value at that point, for The inversion objective function value at that point, This represents the initial wave impedance after stacking inversion. For correction amount, for exist gradient, for exist The sea color matrix is ​​a symmetric positive definite matrix.

[0083] make If the first derivative is zero, then equation (6) can be rewritten as follows:

[0084] (7)

[0085] In the formula For matrix The generalized inverse matrix, The sea color matrix is ​​the inversion objective function.

[0086] To maintain the stability and high resolution of the inversion, an adaptive regularization constraint term consisting of model parameters and noise is added, resulting in the final inversion iterative formula as follows:

[0087] (8)

[0088] In the formula, This is the wave impedance correction amount. Let be the covariance matrix of the noise. This is the inverse of the covariance matrix of the wave impedance output by the inversion model. The superscript represents the gradient of the inversion objective function. This indicates transpose.

[0089] In the inversion process, an initial subsurface acoustic impedance model, i.e., a fixed-point model, is first established based on the well's acoustic impedance. Then, control parameters are calculated using the well's acoustic impedance and the seismic traces near the well, and the inversion is performed by extrapolating trace by trace. By setting iterative model parameters, the root mean square error between the synthetic data and the actual seismic data is calculated to be less than 10. -6 This is the termination condition for the iteration.

[0090] d. Rock physical statistical analysis of different lithologies: Typical exploration wells in the study area were selected, and detailed rock physical statistical analysis was carried out in combination with well logging data. Histograms were used to statistically analyze the distribution range of P-wave velocities of different lithologies, providing velocity cutoff values ​​for the prediction of aquifer lithology and thickness.

[0091] e. Extraction of aquifer proportion and thickness: On the inverted wave impedance profile, combined with the wave impedance range of the aquifer in the rock physics analysis, the wave impedance of the aquifer in the target section is multiplied by the wave impedance of the aquifer in the target section and the time sampling point to obtain the aquifer thickness. The aquifer thickness is then compared with the total formation thickness to obtain the aquifer proportion.

[0092] Step 102: Predict the crack density in the study area based on OVT seismic data.

[0093] In this embodiment of the invention, step 102 involves predicting fractures (water-conducting channels) in coal-bearing strata based on OVT seismic data. When the incident angle is small, the relationship between the P-wave reflection amplitude and fracture parameters (fracture azimuth, fracture dip angle, and fracture density) in anisotropic media can be expressed as:

[0094]

[0095] In the formula, Indicates the angle of incidence of seismic waves and the azimuth angle from the excitation point to the receiver point The corresponding P-wave reflection amplitude in the OVT seismic data, This represents the reflected amplitude when a longitudinal wave is incident perpendicularly. Indicates the azimuth angle from the excitation point to the receiver point. The total rate of change of amplitude under the following conditions; This is the rate of change of amplitude with offset distance, i.e., the isotropic gradient; This is the rate of change of amplitude with azimuth angle, i.e., the anisotropic gradient; It is the angle of incidence of the seismic wave; It is the azimuth angle from the excitation point to the receiver point; It is the azimuth angle of the crack's direction.

[0096] With a fixed incident angle, the above equation can be further simplified to:

[0097] (9)

[0098] in, This represents the amplitude of P-wave reflections in OVT seismic data. It is the azimuth angle from the excitation point to the receiver point. It is the azimuth angle of the crack's direction. This represents a parameter reflecting the change in amplitude with the distance between guns. This represents a parameter reflecting the variation of amplitude with gun spacing and azimuth; among which, Used to characterize crack density, it can reflect amplitude changes related to the shot-receiver distance. The amplitude variation with shot-receiver distance and azimuth can be considered as an anisotropy factor. The above formula can be used to inversely derive... , , These are three parameters related to the crack, namely the three parameters of the amplitude ellipse. This indicates the direction of the crack, while the amplitude ellipse... The ratio of the major axis to the minor axis can be used as a relative measure of crack density.

[0099] Step 103: Calculate the equivalent water level for the study area.

[0100] In this embodiment of the invention, step 103 calculates the equivalent converted water level to characterize the overflow recharge energy. By referencing the equivalent converted water level parameter from fracturing drainage data, the potential energy of groundwater fluids is quantitatively evaluated to reflect the characteristics of regional hydrodynamic conditions. The equivalent converted water level of the coal seam is calculated based on the reservoir pressure and elevation data of the coal seam well. The converted water level is a method of characterizing groundwater fluid potential energy by converting the total reservoir pressure into a head height based on the same benchmark. The direction of hydrodynamic runoff is closely related to the equivalent converted water level, i.e., it flows from a higher equivalent converted water level to a lower equivalent converted water level. Equivalent converted water level The calculation formula is:

[0101] (10)

[0102] in

[0103] (11)

[0104] In the formula: For equivalent water level, m; Let be the absolute elevation of the bottom of the well in the study area, in meters (m). Let be the absolute elevation of the reference surface of the study area, in meters (m). The formation pressure is expressed in Pa. For pressure calculation, Pa; The relative density of groundwater with depth A changing function; The relative density of fresh water is 1.

[0105] Step 104: Based on the aquifer thickness, aquifer proportion, fracture density, and equivalent water level in the study area, the average water production per 100-meter drop in the liquid level is determined using multiple regression analysis.

[0106] Step 104 of this embodiment of the invention is based on the risk assessment of external water overflow recharge using multiple regression analysis, and includes the following steps.

[0107] a. Based on the "100-meter liquid level drop - main control factors", a multiple linear regression calculation was performed. The 100-meter liquid level drop of multiple wells was compared with the main control factors of external water overflow recharge, including: fracture density, aquifer thickness, aquifer proportion, and equivalent water level. The weight coefficients of different factors were calculated.

[0108] (12)

[0109] In the formula, This represents the average water production per 100-meter drop in the liquid level of the study area. , , and These are the fracture density, aquifer thickness, aquifer proportion, and equivalent water level of the study area, respectively. , , and These are the weighting coefficients for fracture density, aquifer thickness, aquifer proportion, and equivalent water level, respectively.

[0110] b. Based on seismic geological calculations, the main controlling elements of external water overflow recharge of the target coal seam in the whole region are used to calculate the planar distribution characteristics of external water overflow recharge in the whole region using formula (12).

[0111] To illustrate the effectiveness of the method of the present invention, the following specific examples are provided in Embodiment 1 of the present invention.

[0112] In this example, four parameters were selected from a high-water-yielding coalbed methane block: fracture density between coal seam 8 and L4, thickness of the limestone aquifer, aquifer proportion, and equivalent water level. Multiple regression analysis was used to compare the differences in water production per unit liquid level drop and average water production per well as parameters characterizing water production risk. Coal seam 8 is one of the main mineable coal seams in the lower section of the Taiyuan Formation, with a stable thickness (average 2–4 m), making it a key focus for coalbed methane and mine water control. Limestone L4, located on the roof of coal seam 7, is 5–10 m thick, with a stable distribution throughout the area and moderate karst fissure development; it is one of the three main limestone aquifers in the Taiyuan Formation.

[0113] (1) Average water production per 100-meter drop in water level

[0114] The fitting relationship and correlation coefficient R between the average water production from the 100-meter drop in water level and the fracture density, equivalent water level, aquifer thickness, and aquifer proportion in the (8 coal seam to L4 limestone section) 2 like Figure 2 As shown in (a), (b), (c), and (d) in the figure.

[0115] The average water production from the 100-meter drop in liquid level is fitted with the following formula using the fracture density, total limestone thickness, and cumulative limestone-to-land ratio of the No. 8 coal seam-L4 limestone section:

[0116] The average water production per 100-meter drop in water level = -1611.879 + 34262.268 × (fracture density of coal seam 8 to L4 limestone section) - 7.340 × (thickness of aquifers L1 + L2 + L3 + L4) + 1442.872 × (thickness percentage of aquifers L1 to L4). Among these, L1, L2, L3, and L4 are four marine limestone marker layers in the lower section of the Taiyuan Formation, numbered sequentially from bottom to top.

[0117] The above-mentioned multiple regression fitting formula was used to calculate the 100-meter drop in liquid level across the entire area. The calculation results were normalized and used as a parameter for the external water overflow recharge intensity (water production risk coefficient) of coal seams 8 / 9 in the study area, and water production risk assessment was carried out in the three-dimensional area. The results are as follows: Figure 3 As shown, the southeastern to southern parts of the three-dimensional area have a relatively high risk of high water yield, while the central and northeastern parts of the study area have a relatively lower risk.

[0118] This invention is based on a comprehensive analysis of seismic inversion lithology, thickness and fracture prediction, hydrogeology, and development parameters. Under the guidance of the geological control factors of overflow recharge, it achieves the integration of seismic longitudinal and transverse spatial prediction with macro-geological analysis. Based on the control elements of overflow recharge capacity predicted by seismic geology, it uses multivariate regression analysis to obtain the evaluation of the overflow recharge capacity of external water sources in coal reservoirs. Compared with existing technical solutions that only qualitatively analyze the source of coal seam water production and rely solely on parameter wells, which cannot reflect the heterogeneity of longitudinal and transverse spaces, this invention achieves a quantitative evaluation of the risk of overflow recharge of external water sources in coal reservoirs through integrated seismic and geological methods and determines the bulk modulus of organic components in coal reservoirs. This provides a solid theoretical basis for the analysis and evaluation of coal reservoir water production and the design of water avoidance and control schemes.

[0119] Example 2

[0120] A computer device includes: a memory, a processor, and a computer program stored in the memory and executable on the processor, the processor executing the computer program to implement the method in Embodiment 1.

[0121] The computer device can be a database, and its internal structure diagram can be as follows: Figure 4As shown, the computer device includes a processor, memory, input / output (I / O) interfaces, and a communication interface. The processor, memory, and I / O interfaces are connected via a system bus, and the communication interface is also connected to the system bus via the I / O interfaces. The processor provides computing and control capabilities. The memory includes a non-volatile storage medium and internal memory. The non-volatile storage medium stores the operating system, computer programs, and a database. The internal memory provides an environment for the operation of the operating system and computer programs stored in the non-volatile storage medium. The database stores pending transactions. The I / O interfaces are used for exchanging information between the processor and external devices. The communication interface is used for communicating with external terminals via a network connection. When the computer program is executed by the processor, it implements the method in Embodiment 1.

[0122] Those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium. When executed, the computer program can include the processes of the embodiments described above. Any references to memory, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take many forms, such as Static Random Access Memory (SRAM) or Dynamic Random Access Memory (DRAM). The databases involved in the embodiments provided by this invention may include at least one type of relational database and non-relational database. Non-relational databases may include, but are not limited to, blockchain-based distributed databases. The processors involved in the embodiments provided by this invention may be general-purpose processors, central processing units, graphics processing units, digital signal processors, programmable logic devices, etc., and are not limited to these.

[0123] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0124] This document uses specific examples to illustrate the principles and implementation methods of the present invention. The descriptions of the above embodiments are only for the purpose of helping to understand the method and core ideas of the present invention. Furthermore, those skilled in the art will recognize that, based on the ideas of the present invention, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs, characterized in that, The method includes: The thickness and proportion of aquifers in the study area were retrieved using post-stack seismic data of the study area. Predicting fracture density in the study area based on OFT seismic data; Calculate the equivalent water level for the study area; Based on the aquifer thickness, aquifer proportion, fracture density and equivalent water level of the study area, the average water production per 100-meter drop in the study area was determined by multiple regression analysis. The formula for predicting crack density in the study area based on OFT seismic data is: ； in, This represents the amplitude of P-wave reflections in OVT seismic data. It is the azimuth angle from the excitation point to the receiver point. It is the azimuth angle of the crack's direction. This represents a parameter reflecting the change in amplitude with the distance between guns. This represents a parameter that reflects the variation of amplitude with gun spacing and azimuth; The formula for calculating the equivalent water level of the study area is: ； ； in, For equivalent water level; This represents the absolute elevation of the bottom of the well in the study area; The absolute elevation of the reference surface for the study area; Formation pressure; To calculate the pressure; The relative density of groundwater with depth A changing function; The relative density of freshwater; Based on the aquifer thickness, aquifer proportion, fracture density, and equivalent water level in the study area, the formula for determining the average water production per 100-meter drop in the study area using multiple regression analysis is as follows: ； In the formula, This represents the average water production per 100-meter drop in the liquid level of the study area. , , and These are the fracture density, aquifer thickness, aquifer proportion, and equivalent water level of the study area, respectively. , , and These are the weighting coefficients for fracture density, aquifer thickness, aquifer proportion, and equivalent water level, respectively.

2. The method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs according to claim 1, characterized in that, The thickness and proportion of aquifers in the study area were retrieved using post-stack seismic data, specifically including: Construct time-domain pseudo-gamma acoustic curves for the target layer segment in the study area; The initial wave impedance is constructed by post-stack inversion based on the time-domain quasi-gamma acoustic wave curve. Based on the initial wave impedance obtained by post-stack inversion, the wave impedance at different locations and depths in the study area is obtained by inversion iteration method, and the wave impedance distribution model of the study area is obtained. Based on the wave impedance distribution model, the aquifer thickness and aquifer percentage in the study area are determined.

3. The method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs according to claim 2, characterized in that, The time-domain pseudo-gamma acoustic curves of the target layer segments in the study area are constructed, specifically including: The time spectrum of seismic data for the target segment is calculated using the following formula; ； in, For time spectrum, and They represent time and frequency on the time spectrum, respectively. Indicates earthquake signal, Indicates the time on the seismic signal. Represents the Gaussian window function. This represents a time delay window function. Indicates the number of sampling points; Based on the aforementioned time-frequency spectrum, determine the lower and upper frequency limits of the seismic data frequency components; wherein, the lower frequency limit... and frequency limit The determination method is as follows: First, determine the maximum amplitude value in the time spectrum of the seismic data, and take the frequencies at 20% of the maximum amplitude value corresponding to the low-frequency end and the high-frequency band as the lower frequency limit and the upper frequency limit, respectively. The high-frequency component of the gamma curve frequency spectrum and the low-frequency component of the acoustic logging curve frequency spectrum are extracted based on the lower frequency limit and the upper frequency limit; the frequency range of the high-frequency component is ( , The frequency range of the low-frequency component is: ( , );in, The highest frequency of the logging curve. The lowest frequency of the logging curve. This is the lower limit of frequency. This is the upper limit of frequency. This refers to the frequency overlap. By combining the high-frequency components of the gamma curve frequency spectrum and the low-frequency components of the sonic logging curve frequency spectrum, a pseudo-gamma sonic curve in the frequency domain is obtained. The quasi-gamma sound wave curve in the frequency domain is subjected to an inverse Fourier transform to obtain the quasi-gamma sound wave curve in the time domain.

4. The method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs according to claim 2, characterized in that, The formula for obtaining the wave impedance at different locations and depths in the study area using the inversion iteration method based on the initial wave impedance obtained after stacking inversion is as follows: ； in, This is the wave impedance correction amount. To invert the Hase matrix of the objective function, Let be the covariance matrix of the noise. This is the inverse of the covariance matrix of the wave impedance output by the inversion model. The superscript indicates the gradient of the inversion objective function. Indicates transpose. The initial wave impedance after stacking inversion is represented by z, where z represents the wave impedance at different locations and depths within the study area.

5. The method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs according to claim 4, characterized in that, The inversion objective function is the deviation between the seismic wave amplitude value corresponding to the wave impedance output by the inversion model and the seismic wave amplitude value in the actual seismic data.

6. The method for characterizing the seismic geology of external water recharge in coalbed methane reservoirs according to claim 2, characterized in that, Based on the aforementioned wave impedance distribution model, the aquifer thickness and aquifer percentage in the study area are determined, specifically including: The wave impedance range of aquifers was determined by conducting physical statistical analysis on rocks of different lithologies. The aquifer distribution region in the wave impedance distribution model is determined based on the wave impedance range of the aquifer. The aquifer thickness and aquifer percentage are calculated based on the aquifer distribution area.

7. A computer device, comprising: A memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that the processor executes the computer program to implement the method of any one of claims 1-6.

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