Coal rock formation pressure prediction method and device, electronic equipment and storage medium

Abstract

The invention discloses a coal rock formation pressure prediction method and device, electronic equipment and a storage medium. The method comprises the following steps: determining target seismic data of a target coal rock stratum; based on the target seismic data, target shear wave velocity information corresponding to different offset ranges is determined, and Lame parameters corresponding to the target coal rock stratum are determined based on the target shear wave velocity information; determining reference elastic impedance corresponding to different offset ranges based on the Lame parameter, performing inversion based on the target seismic data, the Lame parameter and the reference elastic impedance, and determining a target Lame parameter of the target coal rock stratum; and determining skeleton effective stress corresponding to the target coal rock stratum based on the target Lame parameter, determining overlying stratum pressure of the overlying stratum, and determining target pressure of the target coal rock stratum based on the skeleton effective stress and the overlying stratum pressure. According to the embodiment of the invention, the problem that the pressure of the deep coal rock formation is difficult to predict is solved, and accurate prediction of the pressure of the deep coal rock formation is realized.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration and development technology, and in particular to a method, apparatus, electronic device and storage medium for predicting coal and rock formation pressure. Background Technology

[0002] Formation pressure prediction plays a crucial role in the exploration and development of coal and rock formations. Firstly, it helps assess the commercial value of coal gas extraction. Deep coal gas reservoirs are typically buried at great depths with high formation pressures, which directly affect the occurrence and production capacity of coal gas. Therefore, pressure prediction for deep coal gas reservoirs is extremely important.

[0003] Conventional methods for predicting formation pressure are based on undercompaction theory. These methods utilize empirical models, models fitting effective stress to normal compaction trend lines, and models relating rock physical parameters to stress. They also incorporate the influence of formation pressure on seismic wave velocity to construct pressure-sensitive parameters for prediction. These methods include the equivalent depth method, the Eaton method, and the Bowers model method. However, methods based on undercompaction theory require the application of normal compaction background trends. The acquisition of normal compaction background trends is generally based on assumptions such as relatively stable lithological combinations, minimal tectonic activity, and weak heterogeneity, making accurate establishment difficult in practical applications. This poses challenges for deep formation pressure prediction. Summary of the Invention

[0004] This invention provides a method, apparatus, electronic device, and storage medium for predicting pressure in coal and rock formations, in order to solve the problem of difficulty in predicting pressure in deep coal and rock formations and achieve accurate prediction of pressure in deep coal and rock formations.

[0005] According to one aspect of the present invention, a method for predicting coal and rock formation pressure is provided, the method comprising:

[0006] Determine the target seismic data for the target coal and rock formation; the target coal and rock formation is obtained by tracing along the seismic reflection phase axis, and the target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distance ranges;

[0007] Based on the target seismic data, target shear wave velocity information corresponding to different shot-receiver distances is determined, and Lamé parameters corresponding to the target coal and rock formation are determined based on the target shear wave velocity information; the target seismic data and the shear wave velocity information corresponding to different shot-receiver distances have a first correlation relationship, and the target shear wave velocity information and the Lamé parameters have a second correlation relationship; the Lamé parameters are used to describe the isotropic linear elasticity of the target coal and rock formation.

[0008] Based on the Lamé parameters, the reference elastic impedance corresponding to different shot-receiver distance ranges is determined. Based on the target seismic data, the Lamé parameters, and the reference elastic impedance, the target Lamé parameters of the target coal and rock formation are determined by inversion.

[0009] The effective stress of the skeleton corresponding to the target coal and rock formation is determined based on the target Lamé parameters, and the overlying stratum pressure is determined based on the overlying stratum. The target pressure of the target coal and rock formation is determined based on the effective stress of the skeleton and the overlying stratum pressure. The overlying stratum is the stratum between the surface and the target coal and rock formation.

[0010] According to another aspect of the present invention, a coal and rock formation pressure prediction device is provided, the device comprising:

[0011] The data determination module is used to determine the target seismic data of the target coal and rock formation; the target coal and rock formation is obtained by tracing along the seismic reflection phase axis, and the target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distance ranges;

[0012] The parameter determination module is used to determine the target shear wave velocity information corresponding to different shot-receiver distance ranges based on the target seismic data, and to determine the Lamé parameters corresponding to the target coal and rock formation based on the target shear wave velocity information; the target seismic data and the shear wave velocity information corresponding to different shot-receiver distance ranges have a first correlation relationship, the target shear wave velocity information and the Lamé parameters have a second correlation relationship, and the Lamé parameters are used to describe the isotropic linear elasticity of the target coal and rock formation;

[0013] The inversion module is used to determine the reference elastic impedance corresponding to different shot-receiver distance ranges based on the Lamé parameters, and to perform inversion based on the target seismic data, the Lamé parameters and the reference elastic impedance to determine the target Lamé parameters of the target coal and rock strata.

[0014] The pressure determination module is used to determine the effective stress of the skeleton corresponding to the target coal and rock formation based on the target Lamé parameters, and to determine the overlying stratum pressure of the overlying stratum. The target pressure of the target coal and rock formation is determined based on the effective stress of the skeleton and the overlying stratum pressure. The overlying stratum is the stratum between the ground surface and the target coal and rock formation.

[0015] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0016] At least one processor; and

[0017] A memory communicatively connected to the at least one processor; wherein,

[0018] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the coal and rock formation pressure prediction method according to any embodiment of the present invention.

[0019] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the coal and rock formation pressure prediction method according to any embodiment of the present invention.

[0020] The technical solution of this invention is to determine the target seismic data of the target coal and rock strata; the target coal and rock strata are obtained by tracing along the seismic reflection phase axis to ensure the accurate determination of the target coal and rock strata; the target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distance ranges to ensure the accuracy and usability of the data. Based on target seismic data, target shear wave velocity information corresponding to different shot-receiver distances is determined. The target seismic data and the shear wave velocity information corresponding to different shot-receiver distances have a primary correlation. After determining the target seismic data, accurate target shear wave velocity information can be obtained accurately based on this primary correlation. Further, density information of the target coal and rock formations corresponding to different shot-receiver distances is acquired. Based on the target shear wave velocity and density information, Lamé parameters corresponding to the target coal and rock formations are determined, facilitating the accurate determination of reference elastic impedance corresponding to different shot-receiver distances based on the Lamé parameters and density information. Further, based on the target seismic data, Lamé parameters, density information, and reference elastic impedance, an inversion is performed to determine the target Lamé parameters and target density information of the target coal and rock formations. This inversion method is more stable, and the inversion results have higher accuracy. Finally, based on the target Lamé parameters, the effective stress of the skeleton corresponding to the target coal and rock formations is determined. Based on the target density information, the overlying stratum pressure is determined. Based on the effective stress of the skeleton and the overlying stratum pressure, the target pressure of the target coal and rock formations is determined, solving the problem of difficult prediction of pressure in deep coal and rock formations and achieving accurate prediction of pressure in deep coal and rock formations.

[0021] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0022] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying 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.

[0023] Figure 1 This is a flowchart of a method for predicting coal and rock formation pressure according to an embodiment of the present invention;

[0024] Figure 2 This is a schematic cross-sectional view of post-stack seismic data according to an embodiment of the present invention;

[0025] Figure 3 This is a schematic diagram of the well vibration calibration results according to an embodiment of the present invention;

[0026] Figure 4 This is a schematic diagram of the longitudinal wave velocity, transverse wave velocity, density, and Lamé parameter curves according to an embodiment of the present invention;

[0027] Figure 5 This is a schematic diagram of a pre-stack CRP gather according to an embodiment of the present invention;

[0028] Figure 6a This is a schematic cross-sectional view of the target Lamé first parameter obtained by inversion according to an embodiment of the present invention;

[0029] Figure 6b This is a schematic cross-sectional view of the target Lamé second parameter obtained by inversion according to an embodiment of the present invention;

[0030] Figure 6c This is a schematic cross-sectional view of the target density obtained by inversion according to an embodiment of the present invention;

[0031] Figure 7 This is a cross-sectional view of the overlying formation pressure according to an embodiment of the present invention;

[0032] Figure 8 This is a cross-sectional view of the target pressure in the target coal and rock formation according to an embodiment of the present invention;

[0033] Figure 9 This is a schematic diagram of a coal and rock formation pressure prediction device according to an embodiment of the present invention;

[0034] Figure 10 This is a schematic diagram of the structure of an electronic device for implementing the coal and rock formation pressure prediction method of the present invention, according to an embodiment of the present invention. Detailed Implementation

[0035] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. 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 should fall within the scope of protection of the present invention.

[0036] It should be noted that the terms "first," "second," "target," etc., used in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0037] Example 1

[0038] Figure 1 This is a flowchart of a method for predicting pressure in coal and rock formations according to an embodiment of the present invention. This embodiment is applicable to the prediction of pressure in deep coal and rock formations. The method can be executed by a coal and rock formation pressure prediction device, which can be implemented in hardware and / or software. The coal and rock formation pressure prediction device can be configured in any electronic device with network communication function.

[0039] like Figure 1 As shown, the coal and rock formation pressure prediction method of the present invention includes the following process:

[0040] S110. Determine the target seismic data of the target coal and rock strata. Based on the target seismic data, determine the target shear wave velocity information corresponding to different shot-receiver distances. The target coal and rock strata are obtained by tracing along the seismic reflection phase axis. The target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distances. The target seismic data and the shear wave velocity information corresponding to different shot-receiver distances have a first correlation relationship.

[0041] In seismic exploration, pre-stack CRP gathers are obtained by processing seismic records and arranging seismic traces from different shot points and receivers according to the location of common reflection points. The principle is based on the propagation characteristics of seismic waves in the subsurface medium. By performing dynamic corrections and other processing on the seismic records, seismic waves from the same reflection point are aligned in time, thus forming CRP gathers.

[0042] Specifically, determining the target seismic data for the target coal and rock strata includes: acquiring seismic data corresponding to different shot-receiver offsets; preprocessing the seismic data to obtain processed seismic data corresponding to different shot-receiver offsets; the seismic data is the data corresponding to the target coal and rock strata, and the preprocessing includes at least filtering, deconvolution, and migration imaging; determining a preset number of target shot-receiver offset ranges, and using the processed seismic data corresponding to the target shot-receiver offset ranges as the pre-stack CRP gathers corresponding to the target shot-receiver offset ranges; optimizing each pre-stack CRP gather to obtain the target seismic data; the optimization includes denoising, demultiplexing, and frequency compensation.

[0043] Furthermore, based on the target seismic data, determining the target shear wave velocity information corresponding to different shot-receiver distances may include: determining a deep coal-rock gas rock physics model, which is used to describe the correlation between seismic data and shear wave velocity information of coal-rock strata; and further inputting the target seismic data into the deep coal-rock gas rock physics model to obtain the target shear wave velocity information corresponding to different shot-receiver distances.

[0044] Optionally, determining the deep coal and gas rock physics model may include: obtaining the seismic records and characteristic parameters corresponding to the coal and strata, including mineral composition curves, TOC content curves, porosity curves, water saturation curves, acoustic velocity curves, and density curves; and characteristic parameters including the mineral composition of deep coal and gas such as clay, quartz, and organic matter, reservoir space such as fractures and dissolution pores, and anisotropic characteristics of the coal and strata; and further constructing the deep coal and gas rock physics model based on the seismic records, characteristic parameters, and depth corresponding to the coal and strata.

[0045] S120. Obtain the density information of the target coal and rock formation corresponding to different shot-receiver distances. Determine the Lamé parameters corresponding to the target coal and rock formation based on the target shear wave velocity information and density information. Determine the reference elastic impedance corresponding to different shot-receiver distances based on the density information and Lamé parameters. The Lamé parameters are used to describe the isotropic linear elasticity of the target coal and rock formation.

[0046] Among them, the Lamé parameter is used to describe the isotropic linear elasticity of the target coal and rock formation.

[0047] Furthermore, determining the Lamé parameters corresponding to the target coal and rock formation based on the target shear wave velocity and density information includes: the target coal and rock formation has a certain thickness, therefore, the target coal and rock formation corresponds to a certain depth range, which can be divided into preset layers. Each layer corresponds to a set of target shear wave velocity and density information for different shot-receiver distance ranges. The target shear wave velocity and density information have a second correlation with the Lamé parameters. Therefore, based on the target shear wave velocity, density information and second correlation corresponding to the preset layers, the Lamé parameters corresponding to different shot-receiver distance ranges for each layer are determined.

[0048] As an optional implementation, the Lamé parameters include a first Lamé parameter and a second Lamé parameter. The first Lamé parameter reflects the elastic properties of the target coal-rock formation under volume changes, while the second Lamé parameter describes the elastic properties of the target coal-rock formation under shape changes. Accordingly, the Lamé parameters corresponding to the target coal-rock formation are determined based on the target shear wave velocity and density information, including steps A1-A3:

[0049] Step A1: Determine the target P-wave velocity information corresponding to different shot-receiver distance ranges.

[0050] Specifically, the target P-wave velocity information can be determined based on the well logging data corresponding to the target coal and rock formation.

[0051] Step A2: Determine the first parameter of Lamé based on the target P-wave velocity information, target S-wave velocity information, and density information.

[0052] Specifically, based on the target P-wave velocity information, target S-wave velocity information, and target density information, the Lamé first parameter can be determined using the following formula:

[0053]

[0054] Among them, V P It is the target longitudinal wave velocity information, V S ρ represents the target shear wave velocity information, and ρ represents the density information.

[0055] Step A3: Determine the second parameter of Lamé based on the target shear wave velocity information and the target density information.

[0056] Specifically, based on the target shear wave velocity and density information, the Lamé second parameter can be determined using the following formula:

[0057]

[0058] Among them, V S ρ represents the target shear wave velocity information, and ρ represents the density information.

[0059] In this embodiment, after determining the target P-wave velocity information corresponding to different shot-receiver distance ranges, the first Lamé parameter is determined based on the target P-wave velocity information, target S-wave velocity information, and density information. The second Lamé parameter is determined based on the target S-wave velocity information and density information, thus achieving accurate determination of the Lamé parameters to ensure the accuracy of the data used in the subsequent inversion process.

[0060] Furthermore, based on the Lamé parameters, the reference elastic impedance corresponding to different shot-receiver distance ranges is determined, including:

[0061]

[0062] Where λ is the first Lamé parameter, μ is the second Lamé parameter, λ0 is the normalized value of the first Lamé parameter, μ0 is the normalized value of the second Lamé parameter, and ρ0 is the normalized value of the density. θ is the P-wave incident angle corresponding to different shot-receiver distance ranges.

[0063] S130. Based on the target seismic data, Lamé parameters, density information and reference elastic impedance, inversion is performed to determine the target Lamé parameters and target density information of the target coal and rock strata.

[0064] Specifically, a Bayesian-based objective function is constructed. Based on the objective function, target seismic data, Lamé parameters, density information, and reference elastic impedance, inversion is performed to determine the target elastic impedance corresponding to different shot-receiver distance ranges. Based on the target elastic impedance, the target Lamé parameters and target density information of the target coal and rock strata are determined.

[0065] Determining the target Lamé parameters of the target coal and rock formation based on the target elastic impedance can include: linearizing both sides of the formula corresponding to the target elastic impedance by taking the logarithm, thereby expressing the target elastic impedance corresponding to different shot-receiver distance ranges as the product of the target Lamé parameters of the coefficient matrix and the target density information, which can be expressed in the form of the following formula. Solving the following formula will yield the target Lamé parameters and target density information of the target coal and rock formation:

[0066]

[0067] Where EI0 represents the normalized value of the elastic impedance, and θ1, θ2 and θ3 represent the P-wave incident angles corresponding to different source-receiver distance ranges.

[0068] S140. Determine the effective stress of the skeleton corresponding to the target coal and rock formation based on the target Lamé parameters, determine the overlying stratum pressure based on the target density information, and determine the target pressure of the target coal and rock formation based on the effective stress of the skeleton and the overlying stratum pressure; the overlying stratum is the stratum between the surface and the target coal and rock formation.

[0069] Specifically, determining the effective skeleton stress corresponding to the target coal and rock formation based on the target Lamé parameters can include: determining the effective skeleton stress corresponding to the target coal and rock formation based on the first Lamé parameter and the second Lamé parameter, which can be expressed by the following formula:

[0070]

[0071] Where: ΔH / H is the deformation per unit thickness. For the target coal and rock formation, ΔH / H can be considered a constant. λ is the first parameter of Lamé, and μ is the second parameter of Lamé.

[0072] Meanwhile, the overlying formation pressure can be expressed by the following formula:

[0073]

[0074] Where ρ represents the target density information, g represents the gravitational acceleration, and H represents the formation depth.

[0075] Furthermore, since the overlying stratum pressure is the sum of the effective stress of the skeleton and the target pressure of the target coal and rock strata, the target pressure is the difference between the overlying stratum pressure and the effective stress of the skeleton.

[0076] Optionally, the target pressure of the target coal and rock formation is determined based on the effective stress of the skeleton and the overlying strata pressure, including: determining the corresponding Biot coefficient of the target coal and rock formation, and determining the target pressure of the target coal and rock formation based on the Biot coefficient, the effective stress of the skeleton, and the overlying strata pressure; the target pressure of the target coal and rock formation can be expressed by the following formula:

[0077] P f =P ov -αP e ;

[0078] Among them, P f Target pressure, P ov Overlying formation pressure, P e Effective stress of the skeleton, where α is the Biot coefficient.

[0079] The technical solution of this invention is to determine the target seismic data of the target coal and rock strata; the target coal and rock strata are obtained by tracing along the seismic reflection phase axis to ensure the accurate determination of the target coal and rock strata; the target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distance ranges to ensure the accuracy and usability of the data. Based on target seismic data, target shear wave velocity information corresponding to different shot-receiver distances is determined. The target seismic data and the shear wave velocity information corresponding to different shot-receiver distances have a primary correlation. After determining the target seismic data, accurate target shear wave velocity information can be obtained accurately based on this primary correlation. Further, density information of the target coal and rock formations corresponding to different shot-receiver distances is acquired. Based on the target shear wave velocity and density information, Lamé parameters corresponding to the target coal and rock formations are determined, facilitating the accurate determination of reference elastic impedance corresponding to different shot-receiver distances based on the Lamé parameters and density information. Further, based on the target seismic data, Lamé parameters, density information, and reference elastic impedance, an inversion is performed to determine the target Lamé parameters and target density information of the target coal and rock formations. This inversion method is more stable, and the inversion results have higher accuracy. Finally, based on the target Lamé parameters, the effective stress of the skeleton corresponding to the target coal and rock formations is determined. Based on the target density information, the overlying stratum pressure is determined. Based on the effective stress of the skeleton and the overlying stratum pressure, the target pressure of the target coal and rock formations is determined, solving the problem of difficult prediction of pressure in deep coal and rock formations and achieving accurate prediction of pressure in deep coal and rock formations.

[0080] Example 2

[0081] The technical solution in this embodiment is based on the examples described in the above embodiments, and is elaborated in detail using actual data of deep coal and rock strata in a certain region.

[0082] 1) Obtain seismic data corresponding to different shot-receiver offsets in deep coal and rock formations, and preprocess and optimize the seismic data to obtain target seismic data. Specifically, the process involves filtering, deconvolution, and migration imaging of seismic shot records acquired in the field from deep coal and rock formations to obtain pre-stack time-migrated common reflection point (CRP) gathers. Since pre-stack CRP gathers typically contain random noise, multiples, and have low resolution, further optimization processing such as denoising, multiple removal, and frequency compensation is required to obtain target seismic data with high fidelity, high resolution, and high signal-to-noise ratio, providing a data foundation for predicting formation pressure in deep coal and rock gas.

[0083] like Figure 5 As shown in the figure, the black line represents the interpretation results of the target stratigraphic level in the coal and rock formation. The optimized gather has good quality, high signal-to-noise ratio, and high resolution. The phase axis of the target layer is relatively flat, which can meet the requirements of pre-stack elastic impedance inversion.

[0084] Furthermore, filtering, deconvolution, and migration imaging of seismic shot records acquired in the field from deep coal and rock strata can yield post-stack time-migrated seismic data (referred to as "post-stack seismic data"). Figure 2 As shown, the cyan interpretation layer between 1750ms and 1800ms represents the bottom interpretation result of the actual coal and rock strata, indicating that the coal and rock reservoir structure is relatively gentle and the development characteristics are relatively stable.

[0085] 2) Determination of time-depth relationship for well-seismic calibration: The well logging data in the study area is processed by removing outliers and standardizing. The wave impedance curve is calculated using the sonic curve and density curve. The reflection coefficient curve is calculated according to equation (1). The seismic wavelet is extracted from the post-stack seismic data obtained in step 1). The above reflection coefficient and seismic wavelet are used to convolve to obtain the synthetic seismic record. The synthetic seismic record is compared with the post-stack seismic data near the well. The synthetic seismic record is drifted and locally stretched according to the wave impedance relationship between the two to align the synthetic seismic record with the main waveform characteristics of the seismic trace near the well. If the correlation coefficient between the two reaches the preset threshold, the time-depth curve is the well-seismic calibration result. If the correlation coefficient does not reach the preset threshold, the seismic wavelet needs to be adjusted and iterated until the requirements are met. The time-depth relationship at this time is the final calibration result. Figure 3 As shown.

[0086]

[0087] Among them: Z i+1 and Z i These are the impedances above and below the reflecting interface, which are the product of velocity and density.

[0088] 3) Determination of target coal and rock strata: Deep coal and rock strata are characterized by low-amplitude tectonic features, thin thickness, and interbedded rock. It is necessary to combine existing sedimentary and tectonic geological knowledge, utilize the time-depth relationship established in step 2), and use the seismic data reflection phase axis as a lateral constraint to accurately interpret the top and bottom plates of the coal and rock reservoir. At the same time, based on the seismic response characteristics, the lateral distribution characteristics of the interbedded rock layers should be accurately determined to provide a reliable basis for seismic inversion modeling, that is, the target coal and rock strata are obtained by tracing along the seismic reflection phase axis.

[0089] 4) Determination of target shear wave velocity information and Lamé parameters for different shot-receiver distance ranges: Considering the mineral components of deep coal and gas such as argillaceous, quartz, and organic matter, as well as its reservoir space such as fractures and dissolution pores, and taking into account the anisotropic characteristics of the reservoir, a deep coal and gas rock physics model is constructed based on mineral composition curves, TOC content curves, porosity curves, water saturation curves, acoustic velocity curves, and density curves to predict target shear wave velocity information and calculate the first Lamé parameter λ and the second Lamé parameter μ.

[0090]

[0091] Where: V P It is the target longitudinal wave velocity information, V S ρ represents the target shear wave velocity information, and ρ represents the density information.

[0092] like Figure 4 As shown in the figure, the blue curve is the head velocity curve calculated using the acoustic transit time curve, the brown curve is the density information, the red curve is the target shear wave velocity information predicted by the rock physics modeling results, and the pink and cyan curves are the Lamé first parameter λ and the Lamé second parameter μ calculated using the target P-wave velocity information, target shear wave velocity information and density information. It can be seen from the figure that the shear wave velocity and Lamé parameters are similar in characteristics to the P-wave velocity and density curves, which can effectively reflect the basic characteristics of coal and rock formations.

[0093] 5) Initial elastic impedance models corresponding to different gun-receiver distance ranges (which can be near, medium, and far gun-receiver distance ranges); using the Lamé first parameter λ, Lamé second parameter μ, and target density information obtained in step 4) to calculate the reference elastic impedance of the near, medium, and far gathers according to equation (4), and perform lateral interpolation in the three-dimensional data volume space to finally obtain the initial elastic impedance models corresponding to the near, medium, and far gun-receiver distance ranges.

[0094]

[0095] Wherein, λ is the first Lamé parameter, μ is the second Lamé parameter, ρ is the density information, λ0 is the normalized value of the first Lamé parameter, μ0 is the normalized value of the second Lamé parameter, ρ0 is the normalized value of the density information, and θ is the P-wave incident angle corresponding to different source-receiver distance ranges.

[0096] 6) Inversion process: Using the initial elastic impedance models corresponding to the near, medium, and far gun-receiver distances obtained in step 5), construct objective functions based on Bayesian theory respectively, and perform inversion based on the objective functions to obtain the target elastic impedances of the near, medium, and far gun-receiver distances. Take the logarithm of both sides of equation (4) for linearization, and express the elastic impedances of the target elastic impedances of the near, medium, and far gun-receiver distances as the product of the target Lamé parameters of the coefficient matrix and the target density information, as shown in equation (5). Solve equation (5) to obtain the target Lamé parameters and target density information of the target coal and rock strata, such as... Figure 6a , Figure 6b and Figure 6c .

[0097]

[0098] Where EI0 represents the normalized value of the elastic impedance, and θ1, θ2, and θ3 represent the longitudinal wave incident angles corresponding to the near, medium, and far gun-receiver distance ranges, respectively.

[0099] Figure 6a This is a schematic cross-sectional view of the target Lamé first parameter obtained by inversion according to an embodiment of the present invention; Figure 6b This is a schematic cross-sectional view of the target Lamé second parameter obtained by inversion according to an embodiment of the present invention; Figure 6c This is a schematic cross-sectional view of the target density obtained by inversion according to an embodiment of the present invention. Figure 6a , Figure 6b and Figure 6c This indicates that the inversion resolution is high and the inversion results are in good agreement with known information.

[0100] 7) Determination of effective stress of the skeleton: Based on Hooke's quantitation and the relationship between Young's modulus, effective stress of the skeleton, and elastic strain, the effective stress P of the skeleton is calculated using the general elastic modulus and strain. e .

[0101]

[0102] Where: ΔH / H is the deformation per unit thickness. For the target coal and rock formation, ΔH / H can be considered a constant. λ is the first parameter of Lamé, and μ is the second parameter of Lamé.

[0103] 8) Determination of Overburden Pressure: The overburden pressure is the pressure generated by the weight of the overburden strata above the deep coal and rock formations. Combined with the velocity field, the overburden pressure P is obtained by integration using the target density information obtained in step 6). ov This can be expressed using the following formula:

[0104]

[0105] Where ρ represents the target density information, g represents the gravitational acceleration, and H represents the formation depth.

[0106] Figure 7 This is a cross-sectional diagram of the overlying strata pressure, which shows that the overlying strata pressure at the bottom of the formation is higher than that in the shallower strata.

[0107] 9) Determination of the target pressure of the target coal and rock formation: Since the overlying strata pressure is the sum of the effective stress of the skeleton and the target pressure of the target coal and rock formation, the target pressure is the difference between the overlying strata pressure and the effective stress of the skeleton. Considering the influence of the Biot coefficient α, the target pressure P can be obtained. f The calculation formula is as follows:

[0108] P f =P ov -αP e (8)

[0109] Among them, P f Target pressure, P ov Overlying formation pressure, P e Effective stress of the skeleton, where α is the Biot coefficient.

[0110] Figure 7 The cross-sectional diagram of the target pressure in the target coal and rock formation shows that the pressure in the coal and rock formation is relatively high, reflecting the high sealing properties of the coal and rock, which further illustrates the effectiveness and applicability of the method.

[0111] The technical solution of this invention combines pre-stack CRP gathers, deep coal and rock gas petrophysical models, and elastic impedance initial models corresponding to different shot-receiver distances to accurately determine the target Lamé parameters and target density information of the target coal and rock formation. The operation is simple and the inversion is stable. Furthermore, based on the target Lamé parameters, the effective stress of the skeleton corresponding to the target coal and rock formation is determined; based on the target density information, the overlying strata pressure is determined; and based on the effective stress of the skeleton and the overlying strata pressure, the target pressure of the target coal and rock formation is determined. This solves the problem of difficulty in predicting the pressure of deep coal and rock formations and achieves accurate prediction of the pressure of deep coal and rock formations.

[0112] Example 3

[0113] Figure 9 This is a schematic diagram of a coal and rock formation pressure prediction device provided in an embodiment of the present invention. This embodiment is applicable to the prediction of pressure in deep coal and rock formations. The coal and rock formation pressure prediction device can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 9 As shown, the coal and rock formation pressure prediction device of the present invention includes:

[0114] Information determination module 210 is used to determine target seismic data of target coal and rock formations, and based on the target seismic data, determine target shear wave velocity information corresponding to different shot-receiver distance ranges; the target coal and rock formations are obtained by tracking along the seismic reflection phase axis, the target seismic data includes pre-stack CRP gathers corresponding to different shot-receiver distance ranges, and the target seismic data and the shear wave velocity information corresponding to different shot-receiver distance ranges have a first correlation relationship.

[0115] The parameter determination module 220 is used to acquire the density information of the target coal and rock formation corresponding to different shot-receiver distance ranges, determine the Lamé parameters corresponding to the target coal and rock formation based on the target shear wave velocity information and the density information, and determine the reference elastic impedance corresponding to different shot-receiver distance ranges based on the density information and the Lamé parameters; the Lamé parameters are used to describe the isotropic linear elasticity of the target coal and rock formation.

[0116] The inversion module 230 is used to perform inversion based on the target seismic data, the Lamé parameters, the density information and the reference elastic impedance to determine the target Lamé parameters and target density information of the target coal and rock formation;

[0117] The pressure prediction module 240 is used to determine the effective stress of the skeleton corresponding to the target coal and rock formation based on the target Lamé parameters, determine the overlying stratum pressure based on the target density information, and determine the target pressure of the target coal and rock formation based on the effective stress of the skeleton and the overlying stratum pressure; the overlying stratum is the stratum between the ground surface and the target coal and rock formation.

[0118] Based on the above embodiments, optionally, the Lamé parameters include a first Lamé parameter and a second Lamé parameter; the first Lamé parameter is used to reflect the elastic properties of the target coal and rock formation when the volume changes; the second Lamé parameter is used to describe the elastic properties of the target coal and rock formation when the shape changes.

[0119] Based on the above embodiments, optionally, the parameter determination module includes a Lamé parameter determination unit, which is used to: determine the target P-wave velocity information corresponding to different shot-receiver distance ranges; determine a first Lamé parameter based on the target P-wave velocity information, the target S-wave velocity information and the density information; and determine a second Lamé parameter based on the target S-wave velocity information and the density information.

[0120] Based on the above embodiments, optionally, the inversion module includes a reference elastic impedance determination unit, which is used to determine the reference elastic impedance using the following formula:

[0121]

[0122] Where λ is the first Lamé parameter, μ is the second Lamé parameter, λ0 is the normalized value of the first Lamé parameter, μ0 is the normalized value of the second Lamé parameter, and ρ0 is the normalized value of the density. θ is the P-wave incident angle corresponding to different shot-receiver distance ranges.

[0123] Based on the above embodiments, optionally, the inversion module is used to: construct an objective function based on Bayesian theory; perform inversion based on the objective function, the target seismic data, the Lamé parameters, the density information, and the reference elastic impedance to determine the target elastic impedance corresponding to different shot-receiver distance ranges; and determine the target Lamé parameters and target density information of the target coal and rock strata based on the target elastic impedance.

[0124] Based on the above embodiments, optionally, the pressure determination module is used to: determine the corresponding Biot coefficient of the target coal and rock formation, and determine the target pressure of the target coal and rock formation based on the Biot coefficient, the effective stress of the skeleton and the pressure of the overlying strata;

[0125] Accordingly, determining the target pressure of the target coal and rock formation based on the Biot coefficient, the effective stress of the skeleton, and the overlying formation pressure includes:

[0126] P f =P ov -αP e ;

[0127] Among them, P f Target pressure, P ov The effective stress of the skeleton, P e The overlying formation pressure, where α is the Biot coefficient.

[0128] Based on the above embodiments, optionally, the data determination module is used for:

[0129] Seismic data corresponding to different shot-receiver distances are acquired, and the seismic data is preprocessed to obtain processed seismic data corresponding to different shot-receiver distances; the seismic data is data corresponding to the target coal and rock strata, and the preprocessing includes at least filtering, deconvolution, and migration imaging.

[0130] Determine a preset target shot-receiver distance range, and use the processed seismic data corresponding to the target shot-receiver distance range in the processed seismic data as the pre-stack CRP gather corresponding to the target shot-receiver distance range;

[0131] The target seismic data is obtained by optimizing each of the pre-stack CRP gathers; the optimization process includes denoising, demultiplexing, and frequency compensation.

[0132] The coal and rock formation pressure prediction device provided in the embodiments of the present invention can execute the coal and rock formation pressure prediction method provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0133] Example 4

[0134] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0135] Figure 10A schematic diagram of an electronic device that can be used to implement the coal and rock formation pressure prediction method of embodiments of the present invention is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workbenches, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (such as helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0136] like Figure 10 As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0137] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0138] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as coal and rock formation pressure prediction methods.

[0139] In some embodiments, the coal and rock formation pressure prediction method may be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program may be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the coal and rock formation pressure prediction method described above may be performed. Alternatively, in other embodiments, processor 11 may be configured to perform the coal and rock formation pressure prediction method by any other suitable means (e.g., by means of firmware).

[0140] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0141] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0142] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0143] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0144] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0145] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0146] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0147] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A method of predicting pressure in a coal and rock formation, characterized by, The method comprises: determining target seismic data of a target coal rock formation, determining target S-wave velocity information corresponding to different offset ranges based on the target seismic data, the target coal rock formation being obtained by seismic reflection event tracking, the target seismic data comprising pre-stack CRP gathers corresponding to different offset ranges, and the target seismic data and S-wave velocity information corresponding to different offset ranges having a first correlation relationship; obtaining density information of the target coal rock formation corresponding to different offset ranges, determining Lame parameters corresponding to the target coal rock formation based on the target S-wave velocity information and the density information, and determining reference elastic impedances corresponding to different offset ranges based on the density information and the Lame parameters, wherein the Lame parameters are used to describe isotropic linear elasticity of the target coal rock formation; performing inversion based on the target seismic data, the Lame parameters, the density information and the reference elastic impedances to determine target Lame parameters and target density information of the target coal rock formation; determining skeleton effective stress of the target coal rock formation based on the target Lame parameters, determining overburden pressure of an overburden formation based on the target density information, and determining target pressure of the target coal rock formation based on the skeleton effective stress and the overburden pressure, wherein the overburden formation is a formation between the ground and the target coal rock formation.

2. The method of claim 1, wherein, The Lame parameters comprise a first Lame parameter and a second Lame parameter, the first Lame parameter is used to reflect elastic properties of the target coal rock formation when the volume changes, and the second Lame parameter is used to describe elastic properties of the target coal rock formation when the shape changes.

3. The method of claim 2, wherein, Determining Lame parameters corresponding to the target coal rock formation based on the target S-wave velocity information and the density information comprises: determining target P-wave velocity information corresponding to different offset ranges; determining the first Lame parameter based on the target P-wave velocity information, the target S-wave velocity information and the density information; determining the second Lame parameter based on the target S-wave velocity information and the density information.

4. The method of claim 3, wherein, Determining reference elastic impedances corresponding to different offset ranges based on the density information and the Lame parameters comprises: wherein λ is the first Lame parameter, μ is the second Lame parameter, ρ is the density information, λ0 is a normalized quantity of the first Lame parameter, μ0 is a normalized quantity of the second Lame parameter, ρ0 is a normalized quantity of the density information, and θ is a P-wave incidence angle corresponding to different offset ranges, 5. The method of claim 1, wherein, Performing inversion based on the target seismic data, the Lame parameters, the density information and the reference elastic impedances to determine target Lame parameters and target density information of the target coal rock formation comprises: constructing a target function based on Bayesian theory, performing inversion based on the target function, the target seismic data, the Lame parameters, the density information and the reference elastic impedances to determine target elastic impedances corresponding to different offset ranges; and determining the target Lame parameters and the target density information of the target coal rock formation based on the target elastic impedances.

6. The method of claim 1, wherein, Determining target pressure of the target coal rock formation based on the skeleton effective stress and the overburden pressure comprises: determining a Biot coefficient corresponding to the target coal rock formation, and determining the target pressure of the target coal rock formation based on the Biot coefficient, the skeleton effective stress and the overburden pressure.

7. The method of claim 1, wherein, Determining target seismic data of a target coal rock formation comprises: Acquire seismic data corresponding to different offsets, preprocess the seismic data to obtain processed seismic data corresponding to different offsets; the seismic data is data corresponding to a target coal rock formation, and the preprocessing includes at least filtering, deconvolution and migration imaging; Determine a preset target offset range, and take processed seismic data corresponding to the target offset range in the processed seismic data as a prestack CRP gather corresponding to the target offset range; Optimize each prestack CRP gather to obtain target seismic data; the optimization includes denoising, multiple wave removal and frequency compensation.

8. A coal formation pressure prediction apparatus, characterized by comprising: The device comprises: An information determination module configured to determine target seismic data of a target coal rock formation, and determine target S-wave velocity information corresponding to different offset ranges based on the target seismic data; the target coal rock formation is obtained by tracing seismic reflection events, the target seismic data includes prestack CRP gathers corresponding to different offset ranges, and the target seismic data has a first correlation relationship with S-wave velocity information corresponding to different offset ranges; A parameter determination module configured to acquire density information of the target coal rock formation corresponding to different offset ranges, determine a Lame parameter corresponding to the target coal rock formation based on the target S-wave velocity information and the density information, and determine reference elastic impedance corresponding to different offset ranges based on the density information and the Lame parameter; the Lame parameter is used to describe isotropic linear elasticity of the target coal rock formation; An inversion module configured to perform inversion based on the target seismic data, the Lame parameter, the density information and the reference elastic impedance, and determine a target Lame parameter and target density information of the target coal rock formation; A pressure prediction module configured to determine a skeleton effective stress corresponding to the target coal rock formation based on the target Lame parameter, determine an overburden pressure of an overburden formation based on the target density information, and determine a target pressure of the target coal rock formation based on the skeleton effective stress and the overburden pressure; the overburden formation is a formation between the ground and the target coal rock formation.

9. An electronic device, comprising: The electronic device comprises: At least one processor; and A memory connected to the at least one processor in communication; wherein The memory stores a computer program executable by the at least one processor, and the computer program is executed by the at least one processor to enable the at least one processor to execute the coal rock formation pressure prediction method in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions for enabling the processor to execute the coal rock formation pressure prediction method in any one of claims 1-7 when executed.

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