Multi-step multi-domain combined noise suppression method for marine-land transition phase shale gas seismic data

Abstract

The present application relates to a kind of multi-step multi-domain joint sea-land transition phase shale gas seismic data noise suppression method, comprising input shale gas seismic data, load observation system;Multi-domain display analysis;Static correction calculation;Initial amplitude compensation;Abnormal amplitude suppression;Non-uniform sampling coherent noise suppression;Adaptive spectral editing;Abnormal amplitude suppression;Curve wave transform calculation;Robust surface consistency deconvolution processing, output shale gas seismic data.This method makes the attribute difference of effective signal and noise in multiple common gathers maximization, thereby targeted design filter combination;Overcome the problem that single denoising parameter is difficult to accurately control denoising intensity, leading to effective signal damage;Can be realized in full frequency band range to surface wave, waveguide, and various scattering interference and environmental interference, industrial interference and other multiple noise effective suppression, improve the signal-to-noise ratio of shale gas seismic data;Make seismic amplitude energy more balanced, and surface wave and waveguide have more obvious suppression effect.

Description

Technical Field

[0001] This invention belongs to the field of seismic exploration technology, specifically relating to a multi-step, multi-domain combined method for noise suppression of seismic data of marine-continental transitional shale gas. Background Technology

[0002] my country possesses abundant shale gas resources, and accelerating their exploration and development is of great significance for improving the energy structure and ensuring energy security. Actual shale gas reservoirs often exhibit characteristics such as low acoustic impedance, weak reflection, strong homogeneity, and strong anisotropy. In addition to the effective signal, seismic data acquired in the field typically includes surface waves, anomalous amplitude interference, multiple refractions, and background random noise, severely reducing the signal-to-noise ratio of the seismic data.

[0003] Studies have found that noise and effective signals are correlated in shale gas seismic data. Noise suppression algorithms that only address single-attribute differences are limited by their theoretical assumptions. During the suppression process, a single denoising parameter is difficult to precisely control the denoising intensity, which can cause some damage to the effective signal. For example, the FK filtering method, based on the low apparent velocity and low frequency characteristics of surface waves, can lead to mixing and spurious frequency problems while removing surface wave noise, resulting in distortion of the effective reflected wave. Furthermore, the nonlinear characteristics of the Random Transform can easily produce end-point effects during noise suppression. The KL Transform is an effective method for extracting the phase axis information of reflected waves, but its use in shale gas seismic data with steeply dipping structures can damage the effective signal.

[0004] Furthermore, shale gas seismic data suffers from significant issues such as roll wave noise, spatial aliasing, scattering interference, and environmental interference. Therefore, obtaining high-fidelity, high signal-to-noise ratio, and high-resolution shale gas seismic data using only a single conventional noise suppression method is challenging. It is necessary to develop a series of multi-step, multi-domain joint denoising methods based on different noise types and set appropriate parameters. Summary of the Invention

[0005] The purpose of this invention is to provide a multi-step, multi-domain combined noise suppression method for marine-continental transitional shale gas seismic data, in order to solve the problem that conventional noise suppression methods for shale gas seismic data have difficulty in accurately controlling the noise reduction intensity with a single noise reduction parameter, and are prone to causing damage to effective signals while suppressing noise.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A multi-step, multi-domain joint noise suppression method for seismic data of marine-continental transitional shale gas includes the following steps:

[0008] A. Input shale gas seismic data into the observation system and perform multi-domain gather display analysis by extracting gathers to maximize the difference in attributes between effective signal and noise;

[0009] B. In the common shot point concentration, the effects of terrain undulation, thickness variation of low and velocity reduction zones, and lateral velocity variation are eliminated through first arrival wave tomography static correction and residual static correction.

[0010] C. Amplitude level correction is performed through spherical diffusion compensation, near-surface Q compensation, and surface uniform amplitude compensation.

[0011] D. Suppressing high-energy noise and fixed mechanical interference through abnormal amplitude attenuation technology;

[0012] E. Rearrange the shale gas seismic data into a cross-shaped gather, suppress linear noise such as surface waves, guided waves and ground roll waves through non-uniform coherent noise suppression technology, and suppress low-frequency strong amplitude through adaptive spectrum editing method.

[0013] F. Extract common center point gathers and use abnormal amplitude suppression technology to suppress residual noise;

[0014] G. Rearrange the seismic data into common offset domain gathers and use curvelet transform techniques to suppress residual scattered surface waves and residual linear noise;

[0015] H. The data is processed using robust surface-consistent deconvolution techniques, and anomalous amplitude attenuation is performed within the common center point gather to output the processed shale gas seismic data.

[0016] Further, in step A, the multi-domain gather includes a common shot point domain gather, a common receiver point domain gather, a common offset domain gather, and a common center point domain gather.

[0017] Further, step E specifically includes the following steps;

[0018] E1. Calculate the non-uniform coherent noise model:

[0019]

[0020]

[0021] Where K0 is the wave number at the zero-crossing frequency, in formula (13), ω is the angular frequency, X is the distance between the shot point and the receiver point, N is the number of channels, K is the wave number, m is the number of reflected waves, and K m The wavenumber is the frequency that does not cross zero.

[0022]

[0023] Where N is the channel number, j is the number of filters, F0(ω, X) is the filter with zero-crossing frequency, and F j (ω, X) is a filter with a non-zero frequency, Z is the noise frequency coefficient, and A0(ω, X) and A j (ω, X) is the weighting function;

[0024] E2. Calculate the adaptive spectrum editing method model:

[0025]

[0026]

[0027] Where S represents M*N single-channel seismic data, and matching pursuit calculations are performed on the original data S in the common shot domain. MPD(η, f) represents the matching pursuit calculation result of the gather data, where η is the center position of the time window, f is the frequency, and Q... X (η, f) are adaptive factors, and S is the distance between the shot point and the receiver point;

[0028] Z = X (η, f), S> (17)

[0029] Noisy seismic data S and adaptive factor Q X By performing convolution on (η, f), data in the dominant frequency range is preserved, thereby effectively suppressing the influence of interference noise.

[0030] Compared with the prior art, the beneficial effects of the present invention are:

[0031] 1. The present invention provides a multi-step, multi-domain joint noise suppression method for shale gas seismic data in the marine-continental transitional phase. By analyzing shale gas seismic data through multi-channel display, the method maximizes the attribute differences between effective signals and noise in multiple channels, thereby enabling the targeted design of filter combinations.

[0032] 2. By combining seismic processing techniques and designing filters with multi-parameter control, the problem of difficulty in accurately controlling the denoising intensity with a single denoising parameter, which leads to damage to the effective signal, is overcome.

[0033] 3. Employing multi-step, multi-domain combined amplitude-preserving and fidelity-preserving pre-stack denoising techniques, we can effectively suppress various noises such as surface waves, guided waves, various scattering interferences, environmental interferences, and industrial interferences across the entire frequency band, thereby improving the signal-to-noise ratio of shale gas seismic data.

[0034] 4. Compared with the noise reduction methods for terrestrial shale gas seismic data, the noise suppression methods in the marine-continental transitional facies research block incorporate non-uniform coherent noise and robust surface-consistent deconvolution technology, resulting in more balanced seismic amplitude energy and a more significant suppression effect on surface waves and guided waves. Attached Figure Description​

[0035] To more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings used in the embodiments will be briefly introduced below. It should be understood that the following drawings only show some embodiments of the present invention and should not be regarded as a limitation on the scope. For those skilled in the art, other related drawings can be obtained based on these drawings without creative effort.

[0036] Figure 1 A schematic diagram of the noise suppression process for seismic data of marine-continental transitional shale gas.

[0037] Figure 2 For noise analysis of seismic data of marine-continental transitional shale gas, Figure 2 'a' represents surface wave noise analysis. Figure 2 b represents rolling waves, abnormal amplitude noise, and guided waves;

[0038] Figure 3 Comparison chart of abnormal amplitude suppression. Figure 3 'a' represents the state before suppression. Figure 3 b represents the result of suppression. Figure 3 c represents the differential profile;

[0039] Figure 4 Comparison of non-uniform correlated noise suppression. Figure 4 'a' represents the state before suppression. Figure 4 b represents the result of suppression. Figure 4 c represents the differential profile;

[0040] Figure 5 Comparison of adaptive spectral editing methods for suppressing low-frequency high-amplitude noise. Figure 5 'a' represents the state before suppression. Figure 5 b represents the result of suppression. Figure 5 c represents the differential profile;

[0041] Figure 6 Comparison of robust deconvolution processing results Figure 6 Before deconvolution, Figure 6 After b-deconvolution, Figure 6 c-spectrum comparison;

[0042] Figure 7 Comparison of single-shot data with multi-step, multi-domain joint denoising results. Figure 7 Before noise reduction, Figure 7 After denoising b Figure 7 c-difference profile. Detailed Implementation

[0043] The present invention will be further described below with reference to embodiments:

[0044] The present invention will now be described in further detail with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and not intended to limit it. Furthermore, it should be noted that, for ease of description, the accompanying drawings show only the parts relevant to the present invention, and not all of the structures.

[0045] It should be noted that similar reference numerals and letters in the following figures indicate similar items; therefore, once an item is defined in one figure, it does not need to be further defined and explained in subsequent figures. Furthermore, in the description of this invention, terms such as "first," "second," etc., are used only to distinguish descriptions and should not be construed as indicating or implying relative importance.

[0046] This invention presents a multi-step, multi-domain noise suppression method for shale gas seismic data in the marine-continental transitional facies. The study area is characterized by a marine-continental transitional facies. Based on the analysis of marine-continental transitional facies stratigraphic data, gather data from common shot point, common receiver point, common offset, and common center point domains are processed using static correction, amplitude compensation correction, and anomalous amplitude attenuation techniques before denoising. Subsequently, non-uniform coherent noise suppression, adaptive spectrum editing, anomalous amplitude suppression, curve transform, and robust surface consistency deconvolution noise suppression techniques are applied to the processed seismic data. The same multi-step, multi-domain denoising method was also used in the previous seismic data processing of the same stratum in this study area.

[0047] like Figure 1 As shown, the multi-step, multi-domain combined noise suppression method for seismic data of marine-continental transitional shale gas in this invention includes the following steps:

[0048] A. Input shale gas seismic data into the observation system, load the observation system, and perform multi-domain gather display analysis by extracting gathers to maximize the attribute difference between effective signal and noise; wherein, the multi-domain gathers include common shot point domain gathers, common receiver point domain gathers, common offset domain gathers, and common center point domain gathers, etc.

[0049] B. In the common shot point concentration, the effects of topographic undulations, variations in the thickness of low- and velocity-decreasing zones, and lateral velocity variations are eliminated by combining first-arrival tomographic static correction and residual static correction. The specific steps are as follows:

[0050] The first step is to calculate the static correction amount of the first-arrival tomography refractive layer:

[0051] T X =P*G (1)

[0052] G = (g1, g2, ..., g N ) T (2)

[0053]

[0054] Substitute formulas (2) and (3) into formula (1). Where T... X When the ray travels through the grid, X is the distance from the shot point to the receiver point, P is the M*N matrix of the tomographic ray segment, M is the grid dividing the tomographic ray segment, N represents rays in different directions, and G = (g1, g2, ..., g N ) T It is an N*1 slowness vector matrix.

[0055] The second step involves calculating the residual static correction based on the first arrival wave tomography static correction. The formula is as follows:

[0056] T S =P α +J β +G+D Δ +T Ω (4)

[0057] D Δ =QX 2 (5)

[0058] T Ω =S λ Y 2 (6)

[0059] In formula (4), T S P is the residual static correction amount. α and J β Let G be the residual static correction for the α-th shot point and the β-th receiver point, and D be the construction term. Δ For the remaining dynamic correction term, T Ω This is the time difference term caused by deviation from the survey line.

[0060] Substituting equations (5) and (6) into equation (4), in equation (5), Q is the residual dynamic correction factor, QX 2 This is the corresponding residual dynamic correction; in formula (6), S is the horizontal tilt factor, and SY is the horizontal tilt factor. 2 denoted as λ, representing the time difference between the λth CMP gather and the survey line.

[0061] C. Amplitude level correction is performed through spherical diffusion compensation, near-surface Q compensation, and surface uniform amplitude compensation. First, spherical diffusion compensation effectively eliminates the effects of dispersion; then, Q compensation effectively balances energy differences; finally, surface uniform amplitude compensation effectively balances energy differences. The specific steps are as follows:

[0062] Step 1, Expression for near-surface Q compensation factor:

[0063]

[0064] In formula (7), Q is the near-surface compensation factor, f m f is the center frequency of the stratum. k denoted as the center frequency after absorption by the formation, and T as the surface travel time.

[0065]

[0066] Substituting the Q value from equation (7) into equation (8), U(λ+Δλ, ω) is the attenuation coefficient after multiple iterations, λ is the energy value, Δλ is the energy surplus compensation value, and ω is the angular frequency value. h β is the center value of the angular frequency, and β is the angular frequency factor. For amplitude compensation, This is the phase correction term, and T is the surface travel time.

[0067] The second step is to define the function expression for the surface uniform amplitude model:

[0068]

[0069] In formula (9), X ij (t) represents the positions of the shot point and receiver point in a single seismic data stream, where i and j represent the positions of the shot point and receiver point, respectively. i (t) is the waveform component related to the shot point position i, Q j (t) is the waveform component related to the receiver position j. It is the offset distance Related waveform components, N(t) is the near-surface waveform pulse reflection value at the midpoint between the shot point and the receiver point, and N(t) is the waveform component excluding the shot point, receiver point, offset distance, and common center point gather.

[0070] D. Suppress high-energy noise and fixed mechanical interference through abnormal amplitude attenuation technology;

[0071]

[0072]

[0073] In formula (10), W f Let C be the attenuation coefficient at frequency f. f Z is the weighted median, and β is the filtering threshold. In formula (11), Z f The difference in horizontal amplitude decreases as the decay rate increases. S This is to attenuate the output result.

[0074] E. Rearrange the shale gas seismic data into a cross-shaped gather, suppress linear noise such as surface waves, guided waves and roll waves using non-uniform coherent noise suppression technology, and suppress low-frequency strong amplitude using adaptive spectrum editing method. The specific steps are as follows.

[0075] The first step is to calculate the non-uniform coherent noise model:

[0076]

[0077]

[0078] To ensure that the filter can attenuate non-uniform coherent noise, a zero-crossing frequency filter F0(ω, X) and a non-zero frequency filter F were designed. j (ω, X). In formula (12), K0 is the wave number at the zero-crossing frequency. In formula (13), ω is the angular frequency, X is the distance between the shot point and the receiver point, N is the number of channels, K is the wave number, m is the number of reflected waves, and K m The wave number is the frequency that is not zero-crossing.

[0079]

[0080] In formula (14), N is the channel number, j is the number of filters, F0(ω, X) is the zero-crossing frequency filter, and F j (ω, X) is a filter with a non-zero frequency, Z is the noise frequency coefficient, and A0(ω, X) and A j (ω, X) is the weighting function.

[0081] The second step is to calculate the adaptive spectrum editing method model:

[0082]

[0083]

[0084] In formula (15), S represents M*N single-channel seismic data. In formula (16), in the common shot domain, matching and tracking calculations are performed on the original data S. MPD(η, f) is the matching and tracking calculation result of the gather data, where η is the center position of the time window, f is the frequency, and Q... X (η, f) is the adaptive factor, and S is the distance between the shot point and the receiver point.

[0085] Z = X (η, f), S> (17)

[0086] In formula (17), the noisy seismic data S is compared with the adaptive factor Q. X By performing convolution on (η, f), data in the dominant frequency range is preserved, thereby effectively suppressing the influence of interference noise.​

[0087] F. Extract common center point gathers and use abnormal amplitude suppression technology to suppress residual noise;

[0088]

[0089] In formula (18), N is the number of channels, H is the number of sampling points in the time window, j is the sampling point, b(j) is the input threshold amplitude at point j, and E is the output amplitude value.

[0090] G. Rearrange the seismic data into common offset domain gathers and use curvelet transform techniques to suppress residual scattered surface waves and residual linear noise.

[0091] H. By employing robust surface-consistent deconvolution technology and performing anomalous amplitude attenuation processing within the common center point gather, high-fidelity, high signal-to-noise ratio, and high-resolution shale gas seismic data is output.

[0092] P(T)=P(i)*P(j)*P(CMP)*P(L)*Q (19)

[0093] In formula (19), T is the travel time of the reflected wave, i and j represent the different positions of the shot point and the receiver point, P(i) is the wavelet component of the shot point, P(j) is the wavelet component of the receiver point, P(CMP) is the wavelet component of the common center point gather, P(L) is the wavelet component of the offset distance, and Q is the robustness coefficient, which can change the impact of noise on the data.

[0094] Through cross-sectional comparison, it was found that the addition of non-uniform coherent noise technology and robust surface-consistent deconvolution technology to the marine-continental transitional strata in the study area resulted in a more balanced seismic amplitude energy, with particularly significant suppression effects on both surface waves and guided waves. Considering the all-around, high-density construction characteristics of the data, the differences in noise and effective signal between different gathers were analyzed. In the noise suppression work of marine-continental transitional shale gas seismic data, a multi-step, multi-domain combined amplitude-preserving and fidelity-preserving denoising technique was adopted to effectively suppress surface waves, guided waves, and various scattering interferences, environmental interferences, and industrial interferences while preserving fidelity. This approach aims to maintain signal strength across the entire frequency band, suppress noise, and improve the signal-to-noise ratio of shale gas seismic data.

[0095] Example 1

[0096] A multi-step, multi-domain joint noise suppression method for shale gas seismic data includes the following steps:

[0097] A. Taking the acquisition and processing of 3D seismic data in a certain work area as an example, this block is located at the junction of the southern slope of the depression and the uplift area. It is a superimposed basin of Mesozoic and Cenozoic sediments, with sedimentary facies divided into marine-continental transitional facies. The surface elevation of this area is 65-90m, with relatively small overall topographic relief, generally dipping from southwest to northwest. Shale gas seismic data was input into the observation system. The observation system parameters were set according to the construction scope and acquisition design requirements of the study area. A total of 13,325 shot points and 32,706 receiver points were completed. Square cells were established with a cell size of 20m*20m, and the coverage was 195 times (15 longitudinal times * 13 transverse times). Through OVT domain seismic data, gather processing was performed. The data volume after gather extraction was displayed and analyzed using multi-domain gathers (common shot point domain gathers, common receiver point domain gathers, common offset domain gathers, common center point domain gathers, etc.). Figure 2 As shown, the noise types in the data mainly include: surface waves, abnormal amplitude interference, multiple refractions, background random noise, ground roll waves, and severe spatial aliasing.

[0098] B. Perform first-arrival tomographic static correction and residual static correction on the seismic data of shale gas in the marine-continental transitional facies, which is divided into two steps:

[0099] The first step involves using the first-arrival tomographic static correction algorithm with an offset range of 50-2000m and 5 inversion layers to calculate the tomographic static correction parameters and establish a near-surface static correction model suitable for the study area.

[0100] The second step involves using a residual static correction algorithm with an offset range of 45-2000m and 5 inversion layers to calculate the residual static correction amount for medium and short wavelengths. The static correction processing parameters are set as shown in Tables 1 and 2. After two steps of static correction processing, the effects of terrain undulations, changes in the thickness of low and deceleration zones, and lateral changes in velocity can be effectively eliminated.

[0101] Table 1 shows the parameter tests for the first arrival chromatic correction.

[0102]

[0103] Table 2 Selection Table of Residual Static Correction Parameters

[0104]

[0105] C. Preliminary amplitude level correction is performed through spherical diffusion compensation, near-surface Q compensation, and surface consistency amplitude compensation to solve the problem of large amplitude differences between shots and traces in shale gas seismic data.

[0106] The first step is to set the thickness H of a single layer of the formation to be 5-10m and the dip angle θ to be 5°, and calculate the spherical diffusion compensation factor Q to be 87.

[0107] The second step is to set the center frequency to 30Hz and the fixed frequency to 25Hz, establish a near-surface model, and obtain a near-surface Q compensation factor of 90, which better distinguishes noise and signal.

[0108] The third step involves setting the common shot amplitude to 420, the common receiver amplitude to 400, the optimized long offset amplitude to 200, and calculating the surface consistency compensation factor to 82. Through the above three-step compensation process, the impact of amplitude variation on coherent noise is minimized, achieving the effect of spatial energy difference compensation.

[0109] D. In the gun domain gather data, the abnormal amplitude attenuation technique is used to suppress high-energy noise and fixed mechanical interference, such as... Figure 3 As shown, the attenuation factor is set to 1.2, the intermediate amplitude to 400, and the threshold amplitude to 300. When the intermediate amplitude value exceeds the threshold amplitude value, it is considered noise data. Noise data is removed, which can effectively reduce amplitude anomalies.

[0110] E. Rearrange the shale gas seismic data from the shot gathers into a cross-shaped arrangement, and use non-uniform coherent noise suppression techniques to suppress linear noise such as surface waves, guided waves, and ground roll waves, for example... Figure 4 As shown.

[0111] The first step is to set the noise frequency coefficient to 0.4, use the noise coefficient to predict the noise model, and then remove the noise, which significantly improves the signal-to-noise ratio.

[0112] The second step involves setting the dominant frequency band to 30-35Hz and using adaptive spectrum editing methods to suppress low-frequency strong amplitudes, resulting in a significant improvement in resolution. Figure 5 As shown.

[0113] F. Extract the common center point gather, set the threshold amplitude to 350, and use the abnormal amplitude suppression technique to suppress the residual noise.

[0114] G. The data is rearranged into a common offset domain gather, and the curvature factor is set to 2.3 and the threshold amplitude is set to 320, in order to use curvature transform technology to suppress residual scattered surface waves and residual linear noise.

[0115] H. The surface-consistent deconvolution technique was used, with a prediction step size of 4ms, an operator length of 200ms, and a noise figure of 0.01. The processing result is as follows: Figure 6 As shown, anomalous amplitude attenuation processing is performed within the common center point gather, which can effectively broaden the effective signal bandwidth and improve the resolution of shale gas seismic data. The final output is high-fidelity, high signal-to-noise ratio, and high-resolution shale gas seismic data. The denoising results of single-shot data are shown below. Figure 7 As shown.

[0116] In this embodiment, a noise suppression method for shale gas seismic data was used in a certain block of terrestrial strata. Through multi-collection display and comparative analysis, the multi-step multi-domain denoising method in this study area incorporated non-uniform coherent noise and robust surface-consistent deconvolution technology, which maximized the attribute differences between effective signals and noise in different collections, resulting in more balanced seismic amplitude energy and a more significant suppression effect on surface waves and guided waves. By combining classic seismic processing techniques and designing filters with multi-parameter control, signal loss was avoided during noise suppression across the entire frequency band, thereby improving the signal-to-noise ratio of shale gas seismic data.

[0117] Note that the above description is merely a preferred embodiment of the present invention and the technical principles employed. Those skilled in the art will understand that the present invention is not limited to the specific embodiments described herein, and various obvious changes, readjustments, and substitutions can be made without departing from the scope of protection of the present invention. Therefore, although the present invention has been described in detail through the above embodiments, the present invention is not limited to the above embodiments, and may include many other equivalent embodiments without departing from the concept of the present invention, the scope of which is determined by the scope of the appended claims.

Claims

1. A multi-step, multi-domain combined method for noise suppression of seismic data from marine-continental transitional shale gas fields, characterized in that, Includes the following steps: A. Input shale gas seismic data into the observation system and perform multi-domain gather display analysis through gather extraction to maximize the attribute differences between effective signal and noise; B. In the common shot point concentration, the effects of terrain undulation, thickness variation of low and velocity reduction zones, and lateral velocity variation are eliminated through first arrival wave tomography static correction and residual static correction. C. Amplitude correction is performed through spherical diffusion compensation, near-surface Q compensation, and surface uniform amplitude compensation. D. Suppressing high-energy noise and fixed mechanical interference through abnormal amplitude attenuation technology; E. Rearrange the shale gas seismic data into a cross-shaped gather, suppress linear noise using non-uniform coherent noise suppression technology, and suppress low-frequency strong amplitude using an adaptive spectral editing method. Calculate the non-uniform coherent noise model （12） （13） The wave number at the zero-crossing frequency, Angular frequency, The distance between the shot point and the receiver point. For the number of Tao, For wave number, For the number of reflected waves, The wavenumber is the frequency that does not cross zero. （14） As a Taoist name, This represents the number of filter arrangements. For zero-crossing frequency filters, For filters with non-zero frequencies, The noise frequency coefficient, , It is a weighted function; Computational adaptive spectral editing method model （15） （16） for Single-channel seismic data, in the common shot domain, for the raw data Perform matching and tracking calculations. The results of matching and tracking calculations for the gather data. The center position of the time window For frequency, As an adaptive factor; （17） Noisy seismic data With adaptive factor By performing convolution, data in the advantageous frequency range is preserved, thereby effectively suppressing the influence of interference noise; F. Extract common center point gathers and use abnormal amplitude suppression technology to suppress residual noise; （18） in, For the number of Tao, The number of sampling points in the time window. For sampling points, for The input threshold amplitude at the point, To output the amplitude value; G. Rearrange the seismic data into common offset domain gathers and use curvelet transform techniques to suppress residual scattered surface waves and residual linear noise; H. The data is processed using robust surface-consistent deconvolution techniques, and anomalous amplitude attenuation is performed within the common center point gather to output the processed shale gas seismic data.

2. The method for noise suppression of seismic data of marine-continental transitional shale gas as described in claim 1, characterized in that: Step A, the multi-domain gather includes common shot point domain gather, common receiver point domain gather, common offset domain gather and common center point domain gather.

Images