Method, device and equipment for improving quality of low signal-to-noise ratio first arrival wave data and medium

Abstract

The present application belongs to the technical field of petroleum geophysical exploration data processing, and discloses a method, device, equipment and medium for improving the quality of low signal-to-noise ratio first arrival wave data. The method comprises the following steps: performing curvelet transform on the data in the first arrival wave time window of the forward single-shot data and the noisy forward single-shot data, and identifying the scale and angle corresponding to the curvelet coefficients not affected by noise; performing curvelet transform on the data in the first arrival wave time window of the actual single-shot data to obtain curvelet coefficients, keeping the scale and angle corresponding to the curvelet coefficients not affected by noise unchanged, reducing the values of the remaining curvelet coefficients of the actual single-shot data, and inversely transforming the curvelet coefficients after denoising the actual single-shot data, and combining zero-phase filtering to obtain the denoised shot gather data. The present application is suitable for improving the quality of low signal-to-noise ratio first arrival wave data, can accurately suppress noise, and can enhance the signal clarity and reliability of the first arrival wave data, thereby providing an accurate data processing scheme for seismic exploration.

Description

Technical Field

[0001] This invention belongs to the field of petroleum geophysical exploration data processing technology, and relates to a method, apparatus, equipment and medium for improving the quality of first arrival data with low signal-to-noise ratio. Background Technology

[0002] Pre-stack depth migration is essential for accurate imaging of complex structures, but it requires a high-precision near-surface velocity model, which in turn requires high-precision first-arrival times. Therefore, accurate first-arrival acquisition is crucial. Due to factors such as high environmental noise and complex surface structures in current oil and gas exploration areas, the signal-to-noise ratio of first-arrivals is low. Furthermore, the fast pace of exploration and large data volumes make accurate and complete first-arrival acquisition a significant challenge.

[0003] Traditional first-arrival picking methods mainly include instantaneous intensity ratio methods, neural network algorithms, and edge detection algorithms. However, these methods are not only poorly applicable and have low accuracy for first-arrival data in complex exploration areas, but also require a large amount of manual interactive modification. For low signal-to-noise ratio data, current methods mainly employ FX filtering, non-stationary predictive filtering, bandpass filtering, median filtering, and wavelet shaping to improve the quality of first-arrival data. For example, FX filtering can attenuate interference from direct waves, refracted waves, and regular noise, but its effect on suppressing random noise is poor; non-stationary predictive filtering can effectively suppress random noise, but its effect on suppressing coherent noise is poor; bandpass filtering loses much important information while filtering out noise; median filtering replaces the value of each point in the seismic data with the median of all values ​​in its neighborhood, leading to a loss of seismic signal details; and wavelet shaping may cause time shifts in the first-arrival wavelet.

[0004] Existing preprocessing techniques for low signal-to-noise ratio (SNR) data all have certain limitations. Therefore, adopting a new method to improve the quality of low SNR first-arrival data is of great significance for reducing noise, highlighting first-arrival characteristics, reducing manual input, and improving the quality and picking efficiency of low SNR first-arrival data. Summary of the Invention

[0005] The purpose of this invention is to provide a method for improving the quality of low signal-to-noise ratio first arrival data, which is used to improve the quality of low signal-to-noise ratio first arrival data in petroleum geophysical exploration.

[0006] Another object of the present invention is to provide an apparatus, device and medium for improving the quality of low signal-to-noise ratio first-arrival data.

[0007] To achieve the above objectives, the technical solution adopted by this invention is as follows:

[0008] A method for improving the quality of low signal-to-noise ratio first-arrival data includes the following steps:

[0009] Obtain forward modeling single-shot data and noisy forward modeling single-shot data; excite and collect / record actual single-shot data;

[0010] Select a seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data and actual single shot data respectively.

[0011] Curvature transformations were performed on the first arrival time window data of forward modeling single-shot data and the first arrival time window data of noisy forward modeling single-shot data to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

[0012] Curvature transformation is performed on the first arrival wave data within the time window of the actual single-shot data to obtain the curve wave coefficients of the actual single-shot data. The curve wave coefficients with the same scale and angle as scale γ and angle ω in the actual single-shot data are kept unchanged, and the values ​​of the remaining curve wave coefficients in the actual single-shot data are reduced. Combined with zero-phase filtering, the denoised shot gather data is obtained.

[0013] As a limitation, the obtained forward modeling single-shot data and noisy forward modeling single-shot data include:

[0014] Based on the collected preliminary geological survey and geophysical exploration data, a geological model of the target work area was constructed, and an observation system was set up. Forward modeling was carried out based on the geological model and the observation system to obtain forward modeling single-shot data.

[0015] Noise data is loaded onto forward modeling single-shot data to obtain noisy forward modeling single-shot data.

[0016] As a further limitation, the design parameters of the observation system include receiver line spacing, channel spacing, number of receiver channels per receiver line, number of sampling points per channel, and number of receiver lines;

[0017] Forward modeling single-shot data can be either three-dimensional or two-dimensional.

[0018] As a second constraint, a seed shot is selected in the target work area, and the first arrival time window of the seed shot is designed to obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data, and actual single shot data, including:

[0019] Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed in different regions.

[0020] Based on the first arrival time window of each area of ​​the seed cannon, the spatial interpolation method is used to determine the time window range of each first arrival wave of the cannon to be picked up in the target work area.

[0021] Based on the time window range of each first arrival wave of the shot to be picked up in the target work area, the first arrival wave time window data of the forward modeling single shot data, the first arrival wave time window data of the noisy forward modeling single shot data, and the first arrival wave time window data of the actual single shot data are obtained.

[0022] As a further limitation, based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed regionally, including:

[0023] Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target area. Using the firing point of the seed shot as the center point, the shot line as the vertical axis, and the seismic receiver line as the horizontal axis, the seismic gather data of each shot are divided into Z=2 segments in a rectangular coordinate system. k A set of regions, 0≤k≤4, sort the seismic traces in each region in ascending order of shot-receiver distance, and design the first arrival wave time window for each region.

[0024] As a further refinement, the seismic gather data for each shot are divided into Z=2 segments in a rectangular coordinate system. k When collecting sets of regions, it is done according to intervals. Divide the rectangular coordinate system into regions;

[0025] The first arrival time window length is 400–800 ms.

[0026] As a third limitation, curvelet transform is performed on the first-arrival time window data of forward modeling single-shot data and the first-arrival time window data of noisy forward modeling single-shot data respectively, to obtain the scale γ and angle ω corresponding to the curvelet coefficients unaffected by noise, including:

[0027] Curvature transforms were performed on the first arrival time window data of forward modeling single shot data and the first arrival time window data of noisy forward modeling single shot data to obtain the curve wave coefficients of forward modeling single shot data at each scale and angle, and the curve wave coefficients of noisy forward modeling single shot data at each scale and angle.

[0028] Sort the curve wave coefficients obtained from the forward modeling single-shot data from largest to smallest, and record the scale γ1 and angle ω1 contained in the first p% of the curve wave coefficients of the forward modeling single-shot data, 10≤p≤25;

[0029] The curvelet coefficients obtained from forward modeling single-shot data and those obtained from noisy forward modeling single-shot data are subtracted at the same scale and angle, respectively. The average of the absolute values ​​of the differences is calculated, and the scale γ2 and angle ω2 corresponding to the curvelet coefficients whose average value is less than or equal to τ are recorded. τ is the mean value of the curvelet coefficients obtained from forward modeling single-shot data at the same scale and angle mentioned above. 10≤t≤100;

[0030] Record the scale γ1 and angle ω1, scale γ2 and angle ω2 to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

[0031] As a further constraint, after sorting the curvesine coefficients obtained from the forward modeling single-shot data from largest to smallest, the smallest curvesine coefficient of q% and the largest curvesine coefficient of q% need to be removed respectively, 0.1≤q≤0.5. Then, the scale γ1 and angle ω1 contained in the curvesine coefficients of the first p% of the forward modeling single-shot data are recorded respectively.

[0032] As a fourth constraint, curvelet transform is performed on the first arrival time window data of the actual single-shot data to obtain the curvelet coefficients of the actual single-shot data. The curvelet coefficients with the same scale and angle as scale γ and angle ω in the actual single-shot data are kept unchanged, while the values ​​of the remaining curvelet coefficients in the actual single-shot data are reduced. Combined with zero-phase filtering, the denoised shot gather data is obtained, including:

[0033] Perform curvelet transform on the first arrival time window data of the actual single shot data to obtain the curvelet coefficients of the actual single shot data at each scale and angle. Keep the curvelet coefficients of the same scale and angle corresponding to the scale γ and angle ω of the curvelet coefficients obtained from the actual single shot data unchanged, and multiply the curvelet coefficients of the remaining scale and angle by ε to obtain new curvelet coefficients, 0.1≤ε<1.

[0034] Based on the curvesine coefficients of the same scale and angle corresponding to the scale γ and angle ω obtained from the actual single-shot data, and the curvesine coefficients of the remaining scale and angle multiplied by ε to obtain the new curvesine coefficients, the denoised curvesine coefficients of the actual single-shot data are obtained. The denoised curvesine coefficients of the actual single-shot data are then inversely transformed to obtain the denoised shot gather data.

[0035] Zero-phase filtering is applied to the denoised shot gather data to obtain the final denoised shot gather data.

[0036] This invention also provides an application of the above-mentioned method for improving the quality of low signal-to-noise ratio first arrival data in pre-stack depth migration and near-surface velocity models.

[0037] The present invention also provides an apparatus for improving the quality of low signal-to-noise ratio first-arrival data, used to implement the above-described method for improving the quality of low signal-to-noise ratio first-arrival data, comprising:

[0038] The single-shot data acquisition module is used to obtain forward modeling single-shot data and noisy forward modeling single-shot data; to excite and collect and record actual single-shot data;

[0039] The seed shot selection module is used to select the seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data and actual single shot data respectively.

[0040] The forward modeling single-shot data curve transform module is used to perform curve transform on the first arrival time window data of forward modeling single-shot data and the first arrival time window data of noisy forward modeling single-shot data respectively, to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

[0041] The shot gather denoising module is used to perform curvelet transform on the first arrival wave data within the time window of the actual single shot data to obtain the curvelet coefficients of the actual single shot data. It keeps the curvelet coefficients of the same scale and angle as the scale γ and angle ω in the actual single shot data unchanged, reduces the value of the remaining curvelet coefficients in the actual single shot data, and combines it with zero-phase filtering to obtain the denoised shot gather data.

[0042] The present invention also provides a computer device, the computer device including a processor and a memory, the memory being used to store at least one computer program, the at least one computer program being loaded by the processor and executed as described above regarding the method for improving the quality of low signal-to-noise ratio first arrival data.

[0043] The present invention also provides a storage medium for storing at least one computer program for executing the above-described method for improving the quality of low signal-to-noise ratio first-arrival data.

[0044] The present invention, by adopting the above-described technical solution, achieves the following technical advancements compared to existing technologies:

[0045] (1) This invention performs curvelet transform on the first arrival time window data of forward modeling single shot data and the first arrival time window data of noisy forward modeling single shot data respectively, so as to identify and maintain the scale and angle corresponding to the curvelet coefficients that are not affected by noise; by performing curvelet transform on the first arrival time window data of actual single shot data, the values ​​of the scale and angle curvelet coefficients corresponding to noise are reduced; by inverse transform and combined with zero phase filtering, noise can be accurately suppressed, and the signal clarity and reliability of the first arrival data can be enhanced.

[0046] (2) This invention can accurately suppress noise, enhance the signal-to-noise ratio of first arrival data, and provide basic data for near-surface velocity modeling.

[0047] In summary, this invention is applicable to improving the quality of first arrival data with low signal-to-noise ratio, accurately suppressing noise, enhancing the signal clarity and reliability of first arrival data, and providing a precise and efficient data processing solution for petroleum geophysical exploration. Attached Figure Description

[0048] Figure 1 The diagram shown is an overall flowchart of the method for improving the quality of low signal-to-noise ratio first-arrival data in Embodiment 1 of the present invention.

[0049] Figure 2The figure shown is a schematic diagram of the forward modeling single-shot data obtained in Embodiment 1 of the present invention;

[0050] Figure 3 The figure shown is a schematic diagram of the noisy forward modeling single-shot data obtained in Embodiment 1 of the present invention;

[0051] Figure 4 The diagram shown is a schematic diagram of the first arrival time window of the seismic trace regional design of the seed gun in Embodiment 1 of the present invention;

[0052] Figure 5 The figure shown is a schematic diagram of the forward modeling single-shot data after noise reduction according to Embodiment 1 of the present invention;

[0053] Figure 6 The diagram shown is a structural block diagram of the device for improving the quality of low signal-to-noise ratio first arrival wave data in Embodiment 2 of the present invention;

[0054] Figure 7 The diagram shown is a structural schematic of the computer device in Embodiment 2 of the present invention;

[0055] Figure 8 The diagram shown is a schematic diagram of the structure of the computer storage medium in Embodiment 2 of the present invention. Detailed Implementation

[0056] To better explain and facilitate understanding of the present invention, the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0057] Example 1

[0058] like Figure 1 As shown in the figure, this embodiment is a method for improving the quality of low signal-to-noise ratio first-arrival data. The method includes the following steps:

[0059] S1. Obtain forward modeling single-shot data and noisy forward modeling single-shot data; excite and collect / record actual single-shot data;

[0060] In practice, there are various methods for obtaining forward modeling single-shot data and noisy forward modeling single-shot data. The specific methods for obtaining forward modeling single-shot data and noisy forward modeling single-shot data given in this embodiment include:

[0061] Based on the collected preliminary geological survey and geophysical exploration data, a geological model of the target work area was constructed, and an observation system was set up. Forward modeling was carried out based on the geological model and the observation system to obtain forward modeling single-shot data.

[0062] Noise data collected from different areas of the target work area is loaded onto the forward modeling single-shot data of the corresponding area to obtain noisy forward modeling single-shot data.

[0063] In this embodiment, a geological model of the target work area is constructed based on the collected preliminary geological survey and geophysical exploration data. When setting up the observation system, the design parameters of the observation system include receiver line spacing, channel spacing, number of receiver channels per receiver line, number of sampling points per channel, and number of receiver lines. The design parameters of the observation system are consistent with the parameters of the expected data to be collected. The forward modeling single-shot data can be three-dimensional data or two-dimensional data, which is selected according to the parameters of the actual collected data.

[0064] In this specific implementation, the observation system parameters include a receiver line spacing of 200 meters, a channel spacing of 10 meters, 720 channels per receiver line, 3000 sampling points per channel, and 24 receiver lines. Forward modeling is performed based on the geological model and the observation system to obtain the following results: Figure 2 The diagram shows the forward modeling data for a single shot.

[0065] like Figure 3 The figure shows a schematic diagram of the obtained noisy forward modeling single-shot data. As can be seen from the figure, due to the influence of noise, the first arrival wave of the far-field gun-receiver is submerged by noise, and the signal-to-noise ratio of the first arrival wave data is low.

[0066] S2. Select a seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of the forward model single shot, the noisy forward model single shot data, and the actual single shot data respectively.

[0067] In specific implementation, there are various methods for selecting a seed shot in the target work area, setting the first arrival time window of the seed shot, and obtaining the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data, and actual single shot data, respectively. The method given in this embodiment specifically includes:

[0068] Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed in different regions.

[0069] Based on the first arrival time window of each area of ​​the seed cannon, the spatial interpolation method is used to determine the time window range of each first arrival wave of the cannon to be picked up in the target work area.

[0070] Based on the time window range of each first arrival wave of the shot to be picked up in the target work area, the first arrival wave time window data ANF[i][s][m][n] of the forward modeling single shot data, the first arrival wave time window data ASF[i][s][m][n] of the noisy forward modeling single shot data, and the first arrival wave time window data AF[j][s][m][n] of the actual single shot data are obtained; where i is the i-th shot in the simulated forward modeling, 1≤i≤I, and I is the total number of simulated shots; j is the j-th shot in the actual acquisition, 1≤j≤J, and J is the total number of actual acquisition shots; s is the s-th receiving line, 1≤s≤S, and S is the total number of receiving lines; m is the m-th receiving point on the s-th receiving line, 1≤m≤M, and M is the total number of receiving points on each receiving line; n is the number of sampling points collected by the n-th receiving point on the s-th receiving line, 1≤n≤N, and N is the total number of sampling points collected by the receiving points.

[0071] Among them, based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed in different regions. A more specific method is as follows:

[0072] Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target area. Using the firing point of the seed shot as the center point, the shot line as the vertical axis, and the seismic receiver line as the horizontal axis, the seismic gather data of each shot are divided into Z=2 segments in a rectangular coordinate system. k A set of regions, 0≤k≤4, sort the seismic traces in each region in ascending order of shot-receiver distance, and design the first arrival wave time window for each region.

[0073] In this step, the seismic gather data of each shot are divided into Z=2 segments in a rectangular coordinate system. k When collecting sets of regions, it is done according to intervals. The rectangular coordinate system is divided into regions; where the more complex the surface, the larger the value of k should be, and the more regions the seismic gather data is divided into. In this embodiment, k=2 is taken.

[0074] The first arrival time window length is 400-800 ms. When designing the first arrival time window for the seismic traces of the seed shot in different regions, the length of the first arrival time window is set according to the surface conditions. The greater the surface undulation, the longer the first arrival time window.

[0075] like Figure 4 The diagram shows the first arrival time window of the seismic trace design for seed guns. If the near-surface undulations are large, a larger first arrival time window needs to be selected. The length of this first arrival time window is 800ms.

[0076] S3. Perform curvelet transform on the first arrival time window data of forward modeling single shot data and the first arrival time window data of noisy forward modeling single shot data respectively to obtain the scale γ and angle ω corresponding to the curvelet coefficients that are not affected by noise.

[0077] The method described in this embodiment includes:

[0078] First, curvelet transform is performed on the first arrival time window data of forward modeling single shot data and the first arrival time window data of noisy forward modeling single shot data respectively to obtain the curvelet coefficients of forward modeling single shot data at each scale and angle, and the curvelet coefficients of noisy forward modeling single shot data at each scale and angle; wherein the curvelet transform adopts the USFFT or Wrapping method.

[0079] Then, the curve coefficients obtained from the forward modeling single-shot data are sorted from largest to smallest, and the scale γ1 and angle ω1 contained in the first p% of the curve coefficients of the forward modeling single-shot data are recorded respectively, 10≤p≤25; where 1≤γ1≤θ, θ is the total number of scales of the curve coefficients of the forward modeling single-shot data, and 1≤ω1≤ψ, ψ is the total number of angles of the curve coefficients of the forward modeling single-shot data.

[0080] In practice, for first-arrival data with a high signal-to-noise ratio, the value of p is larger, and for first-arrival data with a low signal-to-noise ratio, the value of p is smaller. In this embodiment, p = 15 is used.

[0081] In practice, after sorting the curvesine coefficients obtained from the forward modeling single-shot data from largest to smallest, it is necessary to remove the smallest curvesine coefficient and the largest curvesine coefficient of q% respectively, where 0.1≤q≤0.5. Then, record the scale γ1 and angle ω1 contained in the curvesine coefficients of the first p% of the forward modeling single-shot data. By removing the smallest and largest curvesine coefficients of q%, the main purpose is to remove the largest and smallest abnormal curvesine coefficients, so that the obtained curvesine coefficient values ​​are more reasonable. In this embodiment, q=1 is taken.

[0082] Finally, the curvelet coefficients obtained from the forward modeling single-shot data and the curvelet coefficients obtained from the noisy forward modeling single-shot data are subtracted at the same scale and angle, respectively, and the average of the absolute values ​​of the differences is calculated. The scale γ2 and angle ω2 corresponding to the curvelet coefficients whose average value is less than or equal to τ are recorded; τ is the mean value of the curvelet coefficients obtained from the forward modeling single-shot data at the same scale and angle mentioned above. 10≤t≤100, 1≤γ2≤θ, 1≤ω2≤ψ, and in this embodiment, t=30.

[0083] Record the scale γ1 and angle ω1, scale γ2 and angle ω2 to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

[0084] S4. Perform curvelet transform on the first arrival time window data of the actual single shot data to obtain the curvelet coefficients of the actual single shot data. Keep the curvelet coefficients of the same scale and angle as the scale γ and angle ω in the actual single shot data unchanged, reduce the value of the remaining curvelet coefficients of the actual single shot data, and combine with zero phase filtering to obtain the denoised shot gather data.

[0085] The method described in this embodiment includes:

[0086] Curvature transformation is performed on the first arrival wave data within the time window of the actual single-shot data to obtain the curve wave coefficients of the actual single-shot data at each scale and angle. The curve wave coefficients of the same scale and angle corresponding to the scale γ and angle ω in the curve wave coefficients obtained from the actual single-shot data are kept unchanged. The curve wave coefficients of the remaining scale and angle are multiplied by ε to obtain new curve wave coefficients, where 0.1≤ε<1, in order to reduce the value of the remaining curve wave coefficients of the actual single-shot data.

[0087] In practice, ε is the value of the noise curve coefficient. For first arrival data with a high signal-to-noise ratio, the value of ε can be larger, and for first arrival data with a low signal-to-noise ratio, the value of ε can be smaller. In this embodiment, ε is 0.001.

[0088] Based on the curvesine coefficients of the same scale and angle corresponding to the scale γ and angle ω obtained from the actual single-shot data, and the curvesine coefficients of the remaining scale and angle multiplied by ε to obtain the new curvesine coefficients, the denoised curvesine coefficients of the actual single-shot data are obtained. The denoised curvesine coefficients of the actual single-shot data are then inversely transformed to obtain the denoised shot gather data.

[0089] Zero-phase filtering is applied to the denoised shot gather data to obtain the final denoised shot gather data.

[0090] To verify this embodiment, this embodiment uses forward modeling single-shot data for simulation testing, and obtains the following results: Figure 5 The diagram shown is a denoised version of the forward model single-shot data. Figure 3 In comparison, the preprocessing process suppresses a large amount of random noise, enhances the first arrival characteristics, and makes the first arrivals of adjacent channels smoother and more continuous.

[0091] Example 2

[0092] This embodiment describes a device for improving the quality of low signal-to-noise ratio first-arrival data, such as... Figure 6 The diagram shown is a block diagram of an apparatus for improving the quality of low signal-to-noise ratio first-arrival data according to the method of Embodiment 1. The apparatus includes:

[0093] The single-shot data acquisition module is used to obtain forward modeling single-shot data and noisy forward modeling single-shot data; to excite and collect and record actual single-shot data;

[0094] The seed shot selection module is used to select the seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data and actual single shot data respectively.

[0095] The forward modeling single-shot data curve transform module is used to perform curve transform on the first arrival time window data of forward modeling single-shot data and the first arrival time window data of noisy forward modeling single-shot data respectively, to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

[0096] The shot gather denoising module is used to perform curvelet transform on the first arrival wave data within the time window of the actual single shot data to obtain the curvelet coefficients of the actual single shot data. It keeps the curvelet coefficients of the same scale and angle as the scale γ and angle ω in the actual single shot data unchanged, reduces the value of the remaining curvelet coefficients in the actual single shot data, and combines it with zero-phase filtering to obtain the denoised shot gather data.

[0097] In this embodiment, the device for improving the quality of low signal-to-noise ratio first-arrival data is illustrated by the above-mentioned division of functional modules. In actual applications, the above functions can be assigned to different functional modules as needed.

[0098] This embodiment also provides a method based on Embodiment 1 to improve the quality of low signal-to-noise ratio first arrival data, and obtains the application of denoised shot gather data in pre-stack depth migration and near-surface velocity models.

[0099] Based on the same inventive concept, such as Figure 7 As shown, this embodiment also provides a computer device, including: at least a processor and a memory, the memory being used to store at least one computer program, the at least one computer program being loaded by the processor and executed by the processor to improve the quality of low signal-to-noise ratio first arrival data according to Embodiment 1.

[0100] Based on the same inventive concept, such as Figure 8 As shown, this embodiment also provides a computer-readable storage medium for storing at least one computer program for executing the method for improving the quality of low signal-to-noise ratio first-arrival data of Embodiment 1.

[0101] Finally, it should be noted that those skilled in the art will understand that all or part of the processes in the above embodiments can be implemented by a computer program instructing related hardware. The program can be stored in a computer-readable storage medium, and when executed, it can include the processes of the embodiments of the above methods.

[0102] Furthermore, it should be understood that the computer-readable storage medium (e.g., memory) described herein may be volatile memory or non-volatile memory, or may include both volatile memory and non-volatile memory.

[0103] Those skilled in the art will also understand that the various exemplary logic blocks, modules, circuits, and algorithm steps described in conjunction with the disclosure herein can be implemented as electronic hardware, computer software, or a combination of both. To clearly illustrate this interchangeability between hardware and software, the functionality of various illustrative components, blocks, modules, circuits, and steps has been generally described. Whether this functionality is implemented as software or as hardware depends on the specific application and the design constraints imposed on the system as a whole. Those skilled in the art can implement the functionality in various ways for each specific application, but such implementation decisions should not be construed as departing from the scope of the embodiments disclosed herein.

[0104] It should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art can still modify the technical solutions described in the above embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. A method for improving the quality of low signal-to-noise ratio first-arrival data, characterized in that, Includes the following steps: Obtain forward modeling single-shot data and noisy forward modeling single-shot data; excite and collect / record actual single-shot data; Select a seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data and actual single shot data respectively. Curvature transformations were performed on the first arrival time window data of forward modeling single-shot data and the first arrival time window data of noisy forward modeling single-shot data to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise. Curvature transformation is performed on the first arrival wave data within the time window of the actual single-shot data to obtain the curve wave coefficients of the actual single-shot data. The curve wave coefficients with the same scale and angle as scale γ and angle ω in the actual single-shot data are kept unchanged, and the values ​​of the remaining curve wave coefficients in the actual single-shot data are reduced. Combined with zero-phase filtering, the denoised shot gather data is obtained.

2. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 1, characterized in that, Obtain forward modeling single-shot data and noisy forward modeling single-shot data, including: Based on the collected preliminary geological survey and geophysical exploration data, a geological model of the target work area was constructed, and an observation system was set up. Forward modeling was carried out based on the geological model and the observation system to obtain forward modeling single-shot data. Noise data is loaded onto forward modeling single-shot data to obtain noisy forward modeling single-shot data.

3. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 2, characterized in that, The design parameters of the observation system include receiver line spacing, channel spacing, number of receiver channels per receiver line, number of sampling points per channel, and number of receiver lines; Forward modeling single-shot data can be either three-dimensional or two-dimensional.

4. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 1, characterized in that, Select seed shots in the target work area, design the first arrival time window for the seed shots, and obtain the first arrival time window data for forward modeling single shots, noisy forward modeling single shots, and actual single shots, including: Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed in different regions. Based on the first arrival time window of each area of ​​the seed cannon, the spatial interpolation method is used to determine the time window range of each first arrival wave of the cannon to be picked up in the target work area. Based on the time window range of each first arrival wave of the shot to be picked up in the target work area, the first arrival wave time window data of the forward modeling single shot data, the first arrival wave time window data of the noisy forward modeling single shot data, and the first arrival wave time window data of the actual single shot data are obtained.

5. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 4, characterized in that, Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target work area, and the first arrival time windows of the seed shot seismic traces are designed regionally, including: Based on surface conditions and signal-to-noise ratio, seed shots are selected within the target area. Using the firing point of the seed shot as the center point, the shot line as the vertical axis, and the seismic receiver line as the horizontal axis, the seismic gather data of each shot are divided into Z=2 segments in a rectangular coordinate system. k A set of regions, 0≤k≤4, sort the seismic traces in each region in ascending order of shot-receiver distance, and design the first arrival wave time window for each region.

6. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 5, characterized in that, The seismic gather data for each shot are divided into Z=2 segments in a rectangular coordinate system. k When collecting sets of regions, it is done according to intervals. Divide the rectangular coordinate system into regions; The first arrival time window length is 400–800 ms.

7. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 1, characterized in that, Curvature transforms were performed on the first-arrival time-window data of forward modeling single-shot data and the first-arrival time-window data of noisy forward modeling single-shot data to obtain the scale γ and angle ω corresponding to the noise-independent curve coefficients, including: Curvature transforms were performed on the first arrival time window data of forward modeling single shot data and the first arrival time window data of noisy forward modeling single shot data to obtain the curve wave coefficients of forward modeling single shot data at each scale and angle, and the curve wave coefficients of noisy forward modeling single shot data at each scale and angle. Sort the curve wave coefficients obtained from the forward modeling single-shot data from largest to smallest, and record the scale γ1 and angle ω1 contained in the first p% of the curve wave coefficients of the forward modeling single-shot data, 10≤p≤25; The curvelet coefficients obtained from forward modeling single-shot data and those obtained from noisy forward modeling single-shot data are subtracted at the same scale and angle, respectively. The average of the absolute values ​​of the differences is calculated, and the scale γ2 and angle ω2 corresponding to the curvelet coefficients whose average value is less than or equal to τ are recorded. τ is the mean value of the curvelet coefficients obtained from forward modeling single-shot data at the same scale and angle mentioned above. Record the scale γ1 and angle ω1, scale γ2 and angle ω2 to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise.

8. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 7, characterized in that, After sorting the curvesine coefficients obtained from the forward modeling single-shot data from largest to smallest, it is necessary to remove the smallest curvesine coefficient and the largest curvesine coefficient of q% respectively, 0.1≤q≤0.

5. Then, record the scale γ1 and angle ω1 contained in the curvesine coefficients of the first p% of the forward modeling single-shot data.

9. The method for improving the quality of low signal-to-noise ratio first-arrival data according to claim 1, characterized in that, Curvature transform is performed on the first arrival time window data of the actual single-shot data to obtain the curvelet coefficients of the actual single-shot data. The curvelet coefficients at the same scale and angle as scale γ and angle ω in the actual single-shot data are kept unchanged, while the values ​​of the remaining curvelet coefficients in the actual single-shot data are reduced. Combined with zero-phase filtering, the denoised shot gather data is obtained, including: Perform curvelet transform on the first arrival time window data of the actual single shot data to obtain the curvelet coefficients of the actual single shot data at each scale and angle. Keep the curvelet coefficients of the same scale and angle corresponding to the scale γ and angle ω of the curvelet coefficients obtained from the actual single shot data unchanged, and multiply the curvelet coefficients of the remaining scale and angle by ε to obtain new curvelet coefficients, 0.1≤ε<1. Based on the curvesine coefficients of the same scale and angle corresponding to the scale γ and angle ω obtained from the actual single-shot data, and the curvesine coefficients of the remaining scale and angle multiplied by ε to obtain the new curvesine coefficients, the denoised curvesine coefficients of the actual single-shot data are obtained. The denoised curvesine coefficients of the actual single-shot data are then inversely transformed to obtain the denoised shot gather data. Zero-phase filtering is applied to the denoised shot gather data to obtain the final denoised shot gather data.

10. An application of a method for improving the quality of low signal-to-noise ratio first arrival data based on any one of claims 1 to 9 in pre-stack depth migration and near-surface velocity models.

11. An apparatus for improving the quality of low signal-to-noise ratio first-arrival data, used to implement the method for improving the quality of low signal-to-noise ratio first-arrival data as described in any one of claims 1 to 9, characterized in that, include: The single-shot data acquisition module is used to obtain forward modeling single-shot data and noisy forward modeling single-shot data; Excite and collect / record actual single-shot data; The seed shot selection module is used to select the seed shot in the target work area, set the first arrival time window of the seed shot, and obtain the first arrival time window data of forward modeling single shot data, noisy forward modeling single shot data and actual single shot data respectively. The forward modeling single-shot data curve transform module is used to perform curve transform on the first arrival time window data of forward modeling single-shot data and the first arrival time window data of noisy forward modeling single-shot data respectively, to obtain the scale γ and angle ω corresponding to the curve coefficients that are not affected by noise. The shot gather denoising module is used to perform curvelet transform on the first arrival wave data within the time window of the actual single shot data to obtain the curvelet coefficients of the actual single shot data. It keeps the curvelet coefficients of the same scale and angle as the scale γ and angle ω in the actual single shot data unchanged, reduces the value of the remaining curvelet coefficients in the actual single shot data, and combines it with zero-phase filtering to obtain the denoised shot gather data.

12. A computer device, characterized in that, The computer device includes a processor and a memory, the memory being used to store at least one computer program, the at least one computer program being loaded by the processor and executed as described in any one of claims 1 to 9 to improve the quality of low signal-to-noise ratio first arrival data.

13. A storage medium, characterized in that, The storage medium is used to store at least one computer program, which is used to execute the method for improving the quality of low signal-to-noise ratio first arrival data as described in any one of claims 1 to 9.

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