Method, device, terminal and storage medium for suppressing strong energy noise near shot point

Abstract

The embodiment of the present application discloses a method, device, terminal and storage medium for suppressing strong energy noise near a shot point, which belongs to the field of seismic exploration technology. The method includes: determining the noise time window corresponding to the strong energy noise based on the common shot point gather, wherein the strong energy noise exists in the surface wave area near the shot point, and the common shot point gather is a collection of seismic traces generated by the same shot point; filtering out the effective reflection wave data outside the noise time window from the seismic data; determining the amplitude compensation factor of each seismic trace in the common shot point gather based on the amplitude analysis result of the effective reflection wave data; performing amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensation data; and suppressing the strong energy noise based on the amplitude compensation data. By adopting the solution provided by the embodiment of the present application, the strong energy noise near the shot point can be effectively suppressed, thereby obtaining a high-quality gather.

Description

Technical Field

[0001] The embodiments of the present application relate to the technical field of seismic data processing, and in particular to a method, device, terminal, and storage medium for suppressing strong energy noise near a shot point. Background Art

[0002] During seismic exploration in loess source mountainous and desert areas, strong energy noise, namely "black triangle" noise, is prevalent in the near-track range due to the influence of the surface structure. In the collected single-shot trace gathers, the "black triangle" noise is distributed in a cone with the shot point position as the vertex in a three-dimensional situation, resulting in a low signal-to-noise ratio of the seismic record, which seriously interferes with the weak deep signals at near-offset distances.

[0003] Related technologies usually use the relationship between energy and shot detection moment to suppress the strong energy of near-shot points in the gather, calculate the energy difference between near-offset and far-offset in the gather, weaken the energy in time and space, and reduce the energy difference between different offsets in the gather to achieve the effect of noise suppression.

[0004] However, it is difficult to accurately separate the strong energy noise near the shot point in the recording, and the solutions provided by related technologies cannot effectively separate the noise, resulting in poor noise suppression effect. Summary of the Invention

[0005] The present invention provides a method, device, terminal, and storage medium for suppressing strong energy noise near a shot point. The solution is as follows:

[0006] On the one hand, an embodiment of the present application provides a method for suppressing strong energy noise near a shot point, the method comprising:

[0007] Determining a noise time window corresponding to strong energy noise based on a common shot gather, wherein the strong energy noise exists in a surface wave region near the shot, and the common shot gather is a collection of seismic traces generated by the same shot;

[0008] Filtering out effective reflected wave data outside the noise window from the seismic data;

[0009] determining an amplitude compensation factor for each of the seismic traces in the common shot gather based on an amplitude analysis result of the effective reflected wave data;

[0010] performing amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data;

[0011] The strong energy noise is suppressed based on the amplitude compensation data.

[0012] On the other hand, the present application provides a device for suppressing strong energy noise near a shot point, the device comprising:

[0013] a noise time window determination module for determining a noise time window corresponding to strong energy noise based on a common shot gather, wherein the strong energy noise exists in a surface wave region near a shot, and the common shot gather is a collection of seismic traces generated by a same shot;

[0014] A reflection wave data screening module is used to screen out effective reflection wave data outside the noise window from seismic data;

[0015] a compensation factor determination module, configured to determine an amplitude compensation factor for each of the seismic traces in the common shot gather based on an amplitude analysis result of the effective reflection wave data;

[0016] a compensation data acquisition module, configured to perform amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data;

[0017] A noise suppression module is used to suppress the strong energy noise based on the amplitude compensation data.

[0018] On the other hand, an embodiment of the present application provides a terminal, which includes a processor and a memory; the memory stores at least one instruction, and the at least one instruction is used to be executed by the processor to implement the method for suppressing strong energy noise near the shot point as described in the above aspect.

[0019] On the other hand, an embodiment of the present application provides a computer-readable storage medium, which stores at least one program code, and the program code is loaded and executed by a processor to implement the method for suppressing strong energy noise near the shot point as described in the above aspects.

[0020] In another aspect, embodiments of the present application provide a computer program product comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for suppressing near-shot high-energy noise provided in various optional implementations of the aforementioned aspects.

[0021] In the embodiment of the present application, the terminal determines the compensation factor of each seismic channel in the common shot point gather after performing amplitude analysis on the effective reflected wave outside the noise window, and then uses the compensation factor to compensate the seismic data to achieve balanced compensation of the effective reflected wave and excessive compensation of strong energy noise, which is beneficial for suppressing strong energy noise near the shot point and can effectively eliminate the energy difference of the gather caused by complex low-speed reduction belts. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] Figure 1 A schematic diagram of a single shot gather is shown;

[0023] Figure 2 A flow chart of a method for suppressing strong energy noise near a shot point provided by an exemplary embodiment of the present application is shown;

[0024] Figure 3 A schematic diagram showing a noise time window determined in a near shot gather provided by an exemplary embodiment of the present application is shown;

[0025] Figure 4 A schematic diagram showing frequency characteristics of seismic data provided by an exemplary embodiment of the present application is shown;

[0026] Figure 5 A schematic diagram illustrating a process of suppressing strong energy noise near a shot point provided by an exemplary embodiment of the present application is shown;

[0027] Figure 6 A single shot gather after noise suppression using the solution provided in an embodiment of the present application is shown;

[0028] Figure 7 A structural block diagram of a device for suppressing strong energy noise near a shot point provided by an exemplary embodiment of the present application is shown;

[0029] Figure 8 The figure shows a structural block diagram of a terminal provided by an exemplary embodiment of the present application. DETAILED DESCRIPTION

[0030] In order to make the objectives, technical solutions and advantages of this application clearer, the implementation methods of this application will be further described in detail below with reference to the accompanying drawings.

[0031] For ease of understanding, the nouns involved in the embodiments of this application are explained below.

[0032] Seismic exploration is a geophysical survey method that uses artificially excited elastic waves. By observing and analyzing the propagation patterns of these waves underground, researchers can infer the properties and morphology of subsurface rock formations by exploiting differences in elasticity and density between subsurface media. Seismic waves are artificially excited at the surface and received by geophones on the surface or in wells. The received seismic wave data is influenced by many factors, including the characteristics of the earthquake source, the location of the geophone points, and the structure of the subsurface rock formations. This exploration method offers high precision, enabling the analysis of rock structure, burial depth, and rock properties.

[0033] A gather is a collection of multiple seismic traces.

[0034] A common shot point gather refers to the gather formed by all seismic traces excited by the same shot point and received by different detection points.

[0035] Surface waves are seismic waves that propagate along the Earth's surface. They are highly energetic and widely present in seismic exploration. They are linearly distributed across a shot gather, exhibit low frequency and velocity, and last for a long time. These waves severely impact effective reflections from deep and mid-layer formations, significantly reducing the signal-to-noise ratio (SNR) of seismic data. The high-energy noise referred to in this application's examples refers to the surface wave region near the shot point.

[0036] Offset distance refers to the horizontal distance from the excitation point to the detection point in the vertical seismic profile.

[0037] Seismic exploration mainly includes three steps: seismic data acquisition, seismic data processing, and seismic data interpretation. The strong energy noise suppression method provided in the embodiment of the present application is applied before the seismic data processing step, which can effectively suppress the strong energy noise in the seismic data, thereby improving the quality of seismic data processing.

[0038] Strong energy noise near the shot point is a common problem in seismic exploration in desert regions. It is generally believed that this is caused by complex surface conditions and the interaction between the source and receivers and the complex surface medium. This generates waves propagating near the surface, hindering seismic imaging and resulting in strong energy noise. In three-dimensional scenarios, this strong energy noise is primarily distributed within a cone centered at the shot point. In some cases, the coverage area of ​​a single-shot gather obtained using controlled source excitation can reach half the total area of ​​the single-shot gather, severely impacting imaging quality.

[0039] Figure 1 A schematic diagram of a single-shot data set is shown, which is a time-space curve of the seismic wave, where the horizontal axis is the offset and the vertical axis is time. Strong energy noise is mainly distributed in the triangular area centered on the shot point, with strong linearity, strong amplitude, and low frequency and apparent velocity. Conventional suppression of strong energy noise near the shot point is usually based on the relationship between the change of seismic wave energy and offset distance. The energy difference between the near offset and far offset distance of the data set is statistically analyzed, and the energy in the time dimension and space dimension is weakened within a given threshold range. The purpose is to reduce the energy difference between the near offset and far offset distance in each data set, and ultimately achieve the effect of noise attenuation. However, since it is difficult to identify and separate strong energy noise in seismic data, the conventional method often has little effect, and does not take into account the impact of the nonlinear relationship between strong energy noise and offset distance caused by different propagation paths on the strong energy noise near the shot point.

[0040] In an embodiment of the present application, a method for suppressing strong energy noise near a shot point is provided. Taking into account the factors of the propagation path, amplitude equalization compensation is performed on the effective reflected wave through amplitude compensation, excessive amplitude compensation is performed on the strong energy noise, and the strong energy noise is suppressed, thereby achieving effective suppression of strong energy noise near a shot point.

[0041] Figure 2 A flowchart of a method for suppressing strong energy noise near a shot point provided by an exemplary embodiment of the present application is shown. The method includes:

[0042] Step 201: Determine the noise time window corresponding to the strong energy noise based on the common shot gather.

[0043] Strong energy noise exists in the surface wave region near the shot point. The common shot point gather is the collection of seismic traces generated by the same shot point.

[0044] During seismic exploration, necessary detection equipment and corresponding observation methods are used to obtain near-surface geophysical information to study the surface structure.

[0045] Shallow refraction and microseismic logging methods can be used to obtain near-surface survey data in P-wave and S-wave exploration. The terminal can determine the near-surface high-speed layer velocity based on this data. Using this velocity and recording time, the terminal can roughly analyze the spatial range of surface wave propagation, and then determine the noise time window corresponding to strong energy noise in the common shot gather.

[0046] The noise time window is a time-space window of the noise, and the range of the noise time window is defined from the two dimensions of space and time in the common shot point gather.

[0047] Step 202: Filter out effective reflection wave data outside the noise window from the seismic data.

[0048] Since the embodiment of the present application aims to utilize excessive compensation for strong energy noise to accurately suppress strong energy noise, when compensating for the amplitude, it is necessary to use the effective reflected wave energy as the basis for the degree of compensation. Therefore, after determining the noise time window, the terminal will cut off the strong energy noise from the seismic data and filter out the effective reflected wave data outside the noise time window.

[0049] The effective reflected wave data is used as the main object for subsequent analysis of the amplitude compensation factor.

[0050] Step 203: Determine the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude analysis result of the effective reflection wave data.

[0051] After the terminal filters out the effective reflected wave data, it is necessary to analyze the amplitude of the effective reflected wave. The process of amplitude analysis is also the process of energy statistics. The relationship between amplitude and offset distance needs to be obtained. Amplitude analysis can be performed using the root mean square amplitude statistical criterion, the mean absolute amplitude statistical criterion, or the autocorrelation amplitude statistical criterion.

[0052] Since the amplitude of each seismic channel is different, the terminal needs to obtain the amplitude compensation factor of each seismic channel. After obtaining the relationship between amplitude and offset, the amplitude analysis result can be used to calculate the amplitude compensation factor of each seismic channel.

[0053] Calculating the amplitude compensation factor of each seismic trace through the amplitude analysis results can solve the problem of poor noise suppression caused by energy differences between different shots due to different propagation paths.

[0054] Step 204 : Perform amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data.

[0055] After obtaining the amplitude compensation factor, the terminal performs amplitude compensation on all seismic data. Since the effective waves in the strong energy noise area in the seismic data are weak, and the amplitude compensation factor is calculated and determined by the amplitude analysis results of the effective reflection wave data outside the noise window, when performing amplitude compensation on the seismic data, the effective reflection wave energy in the strong energy noise area near the shot point will be compensated to the same amplitude energy level as that of the medium and long offset distances.

[0056] At the same time, the energy of the strong energy noise near the shot point will be further expanded, thereby achieving balanced compensation of the effective reflected wave and excessive compensation of the strong energy noise, making the strong energy noise near the shot point more prominent and turning into abnormal energy.

[0057] Step 205: Suppress the strong energy noise based on the amplitude compensation data.

[0058] The amplitude compensation data includes the balance compensation data of the effective reflected wave amplitude and the excess compensation data of the strong energy noise.

[0059] Optionally, the terminal suppresses the strong energy noise that becomes abnormal energy after amplitude compensation through a frequency-divided amplitude suppression method of multi-channel statistical single-channel suppression, which can achieve better strong energy noise suppression effect without damaging the effective reflected wave.

[0060] To summarize, in the embodiment of the present application, the terminal determines the compensation factor of each seismic channel in the common shot point gather after performing amplitude analysis on the effective reflected wave outside the noise window, and then uses the compensation factor to compensate the seismic data to achieve balanced compensation of the effective reflected wave and excessive compensation of strong energy noise, which is beneficial for suppressing strong energy noise near the shot point and can effectively eliminate the energy difference of the gather caused by complex low-speed reduction zones.

[0061] When determining the noise time window of strong energy noise near the shot point, the terminal divides the strong energy noise area near the shot point based on the surface wave velocity.

[0062] Figure 3 A schematic diagram of the noise time window determined in the near-shot gather provided by an embodiment of the present application is shown. The area enclosed by the broken line in the figure is the time window of strong energy noise in the common shot gather. The terminal determines the velocity threshold based on the surface wave velocity measured at different acquisition points in the near-shot surface wave area. The surface wave propagation velocity is slower than the seismic wave transmission velocity outside the surface wave area. The seismic wave transmission velocity within the surface wave area is not much different. Therefore, the maximum velocity collected in the surface wave area can be determined as the velocity threshold. For example, if the maximum velocity at the acquisition point in the surface wave area obtained by the terminal is 1200m / s, the velocity threshold is set to 1200m / s. Subsequently, the area in the common shot gather where the seismic wave velocity is less than or equal to the velocity threshold is determined as the noise time window corresponding to the strong energy noise.

[0063] In the embodiments of the present application, an amplitude compensation factor is determined by performing amplitude analysis on the effective reflection wave. This effective reflection wave data is obtained by removing a noise window from the seismic data. Strong energy noise radiates from the shot point, appearing as a black triangle near the shot point. Strong energy noise also persists at far offsets, existing within the effective reflection wave region of the common shot point gathers at other shot points. Therefore, when performing amplitude analysis, the effective reflection wave data must also be filtered to remove the strong energy noise. Specifically, the effective reflection wave data is subjected to frequency division filtering, filtering within the main frequency band of the effective reflection wave to remove energy noise and make the effective reflection wave more prominent.

[0064] Figure 4 A schematic diagram of the frequency characteristics of seismic data provided by an exemplary embodiment of the present application is shown, wherein the horizontal axis and the vertical axis represent frequency and amplitude, respectively, and the overall seismic data is a superposition of effective reflection wave data and strong energy noise. Specifically, before filtering, the terminal will first perform spectral analysis on the strong energy noise within the noise time window and the effective reflection wave data outside the noise time window, and determine the main frequency and bandwidth of the effective reflection wave and the main frequency and bandwidth of the strong energy noise, respectively. Among them, since the effective wave energy in the strong energy noise area is relatively weak compared to the noise, the main frequency and bandwidth of the seismic data within the noise time window are analyzed as the main frequency and bandwidth of the strong energy noise. In addition, since the frequency range of strong energy noise is relatively wide, strong energy noise may exist in both low and high frequency bands, and the seismic data needs to be frequency-divided and filtered. The terminal divides the frequency bands according to the main frequency and bandwidth of the effective reflection wave to obtain multiple analysis frequency bands, and then filters each analysis frequency band separately to obtain filtered data.

[0065] During the frequency division filtering process, the filters corresponding to different analysis frequency bands are determined based on the dominant noise frequency, noise bandwidth, dominant reflected wave frequency, and reflected wave bandwidth. The goal is to use the frequency band containing effective reflected waves as the filter's passband, thereby preserving the effective reflected waves after filtering, while simultaneously using the frequency band containing high-energy noise as the filter's stopband, thereby removing the high-energy noise. Filtering can be performed using adaptive infinite impulse response filters or least mean square adaptive filters.

[0066] Optionally, the terminal may filter the effective reflected wave dominant frequency band within a certain analysis time window according to the following formula: Where s(i) is the input seismic data, N is the number of sample points in the time window, j is the sequence number of the sample point in the time window, and i is a constant ranging from 1 to N.

[0067] After obtaining the filtered data, the terminal performs amplitude statistics to calculate the relationship between the amplitude energy and offset in several analysis frequency bands, and performs statistics on the filtered data according to methods such as the root mean square amplitude statistical criterion to form an amplitude offset function.

[0068] Optionally, the effective reflected waves within a certain analysis time window are statistically analyzed using the autocorrelation amplitude statistical criterion. Amplitude statistics are performed based on the filtering results of the filtering formula, and the amplitude offset function can be obtained as follows:

[0069]

[0070] Where A is the effective reflected wave amplitude, N is the number of sample points in the analysis time window, j is the sample point sequence number in the analysis time window, and NW is the number of autocorrelation sample points.

[0071] The main purpose of obtaining the amplitude offset function is to predict the effective wave energy within the near offset, and then determine the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude offset function.

[0072] In the process of determining the compensation factor based on the amplitude offset function, the terminal will perform iterative calculations based on the amplitude offset function to obtain the shot point amplitude component and the receiver point amplitude component of each seismic trace. ij It can be expressed as: A ij =S i ·R j ·G k ·D l , where S i is the shot point amplitude component, R j is the amplitude component of the detection point, G k is the structural component, D l is the offset component, amplitude A ijThe two main components of are the shot point amplitude component and the receiver point amplitude component. The embodiment of the present application does not consider the influence of the structural component and the offset component on the effective reflection wave amplitude.

[0073] The amplitude components of the shot point and the receiver point belong to the near-surface components and can be calculated by an iterative algorithm. After taking the logarithm of the amplitude expression, we can get: logA ij =logS i +logR j +logG k +logD l The energy error between the decomposed component and the original effective reflected wave can be expressed as, When i and j change, a series of equations can be obtained from the amplitude offset function. When the difference between the original effective wave amplitude energy and the decomposed amplitude energy is minimized, the series of equations of the amplitude offset function can be combined to perform the least squares solution, and the following can be obtained:

[0074]

[0075]

[0076]

[0077]

[0078] The above four equations together constitute the Gauss-Seidel iterative formula. Solving the equation can obtain the shot point amplitude component S of each seismic trace. i and the detection point amplitude component R j .

[0079] Then, the product of the amplitude component of the shot point and the amplitude component of the detection point is determined as the amplitude compensation factor of each seismic trace.

[0080] After determining the amplitude compensation factor for each seismic channel, the terminal multiplies the amplitude compensation factor by the seismic data to complete amplitude compensation of the seismic data and obtain amplitude-compensated data. Because amplitude analysis calculates the amplitude statistics of effective reflection wave energy at medium and long offsets, the amplitude compensation achieved is amplitude compensation for effective reflection wave energy. This overcompensates for strong energy noise near the shot point, further increasing the difference between strong energy noise near the shot point and effective reflection waves at medium and long offsets.

[0081] After compensating seismic data, the terminal needs to suppress the strong energy noise in the amplitude-compensated data. Using a multi-channel statistical single-channel suppression method, the terminal first performs amplitude processing on a group of adjacent seismic traces in both time and space to obtain the average amplitude value of the group. This average amplitude value is then processed to determine the suppression coefficient for the group. Finally, based on the suppression coefficient, strong energy noise is suppressed for each seismic trace in the group. The following describes the process of suppressing strong energy noise near a shot point using an exemplary embodiment.

[0082] Figure 5 A schematic diagram of a process for suppressing strong energy noise near a shot point provided by an exemplary embodiment of the present application is shown. The process includes:

[0083] Step 501 : performing amplitude processing on the trace group from the time and space dimensions to determine the average amplitude value corresponding to each sampling point in the trace group.

[0084] A trace group is a collection of X adjacent seismic traces, each containing multiple sampling points. The number of seismic traces in a trace group is user-defined. This embodiment uses a trace group with X seismic traces and T sampling points as an example. During amplitude processing, the terminal smoothes and filters the trace group based on a user-defined smoothing window length. The smoothing window length can optionally be set to 40 milliseconds.

[0085] First, the absolute value of the amplitude of each trace is taken to obtain the absolute amplitude value. The trace group is processed from the time dimension and smoothed according to the smoothing time window length. The smoothing filtering process is the process of sliding summing and averaging each sampling point according to the time window length. Its output can be recorded as: A(I,J),{I=1,T,J=1,X}, where X is the number of seismic traces in the trace group, T is the number of sampling points in the trace group, and A(I,J) is the output amplitude of the Jth seismic trace at the Ith sampling point after smoothing filtering.

[0086] When the smoothing time window is less than or equal to one sampling interval, no smoothing filtering is performed.

[0087] Subsequently, the output amplitude value A(I,J) is amplitude processed from the spatial dimension. When there are less than 3 seismic traces in a trace group, the average value of each sample point is taken as the average amplitude value at this moment. When there are more than 3 seismic traces in a trace group, the amplitudes of the X seismic traces at the same sampling point are arranged from small to large, and the amplitude average of the three adjacent sampling points with the median is taken as the average amplitude value at this sampling point, which can be recorded as B(I), {I=1,T}, where B(I) is the average amplitude value at the moment of the I-th sampling point.

[0088] Step 502: The product of the threshold coefficient and the average amplitude value is determined as the amplitude threshold value of each sample point in the trace group.

[0089] The amplitude threshold is used to determine whether a sample point needs to be amplitude suppressed. Generally, the amplitude threshold is a multiple of the average amplitude value, and this multiple is the threshold coefficient.

[0090] Generally, users consider that when the amplitude is higher than the average amplitude value threshold coefficient times, it is strong energy noise and needs to be suppressed. Therefore, the threshold coefficient is manually set by the user.

[0091] Step 503: When the amplitude value reaches the reference amplitude value, the suppression coefficient of each seismic trace in the trace group is determined based on the average amplitude value, the attenuation coefficient, and the amplitude value.

[0092] After obtaining the reference amplitude value, the terminal will judge the amplitude value of the sampling point to determine whether it needs to be noise suppressed. If the amplitude value of the sampling point is greater than the amplitude threshold value, the terminal determines that it needs to be suppressed. Otherwise, it does not need to be noise suppressed.

[0093] When the absolute amplitude of the input seismic trace exceeds the amplitude threshold, the terminal calculates the suppression coefficient as: Coef(I,J) = B(I){I = 1, T} × ALPA / A(I,J),{I = 1, T, J = 1, X}, where ALPA is the attenuation coefficient, which is used to limit the degree of suppression of strong energy noise. Coef(I,J) is the suppression coefficient for the Jth seismic trace at the Ith sample point. In the above formula, the average amplitude value is obtained by processing the amplitudes of multiple seismic traces in the trace group. Therefore, within this trace group, the average amplitude value is constant. Therefore, the suppression coefficient is negatively correlated with the amplitude value. That is, the larger the input amplitude value, the smaller the suppression coefficient.

[0094] When the average amplitude of the input seismic trace is 0 or less than the amplitude threshold, the suppression coefficient is 1.

[0095] Step 504: Smoothing the suppression coefficients of the plurality of track groups to obtain smoothed suppression coefficients.

[0096] After obtaining the suppression coefficients of multiple channel groups, in order to prevent the large difference in suppression coefficients between adjacent sampling points, which may lead to a sudden change in the amplitude after strong energy noise suppression, the terminal will smooth the suppression coefficient of each channel group before performing strong energy noise suppression. The obtained smoothed suppression coefficient is: Facot(I,J),{I=1,T,J=1,X}, where Facot is the smoothed suppression coefficient of the Jth channel at the Ith sampling point.

[0097] Optionally, the smoothing window may be set to 12 milliseconds. When the smoothing window is less than or equal to one sample point, the suppression coefficient is not smoothed.

[0098] Step 505: Suppress the strong energy noise of each seismic trace in the trace group based on the smoothing suppression coefficient.

[0099] After obtaining the smoothing suppression coefficient of the trace group, the terminal will weight the compensated amplitude of the input seismic trace according to the smoothing suppression coefficient of the trace group to which the input seismic trace belongs. That is, the compensated amplitude of each seismic trace is multiplied by the smoothing suppression coefficient to suppress the strong energy noise. The amplitude after strong energy noise suppression is obtained as follows: Trace(J) = Trace(J) × Factor(T, J), {I = 1, NT, J = 1, NX}, where Trace(J) is the amplitude after strong energy noise suppression.

[0100] By carrying out the above process for each trace group, the strong energy noise near the shot point can be suppressed.

[0101] In an embodiment of the present application, after the terminal performs amplitude processing on the amplitude compensation data, the average amplitude value at each sampling point of the channel group is obtained, and the suppression coefficient of each seismic channel is obtained by using the average amplitude value. Noise suppression is performed on each seismic channel according to the suppression coefficient to achieve the effect of noise attenuation. In addition, the suppression coefficient is smoothed, which can make the suppression coefficient change more smoothly, reduce the phenomenon of amplitude mutation in the seismic data after suppression, and output a higher quality channel set.

[0102] Figure 6 The figure shows a single shot gather after noise suppression using the solution provided in the embodiment of the present application. It can be clearly seen from the figure that the strong energy noise originally in the black triangle state is effectively suppressed. Figure 1 Compared with the strong energy noise near the shot point, the noise is significantly weakened, and the single-shot gather image after suppression is clearer, and there is no amplitude mutation phenomenon, which provides high-quality gathers for subsequent seismic data processing.

[0103] The following are device embodiments of the present application, which can be used to implement the method embodiments of the present application. For details not disclosed in the device embodiments of the present application, please refer to the method embodiments of the present application.

[0104] Figure 7 The following is a block diagram of a device for suppressing strong energy noise near a shot point, provided in an exemplary embodiment of the present application. The device may include:

[0105] A noise time window determination module 701 is configured to determine a noise time window corresponding to strong energy noise based on a common shot gather, wherein the strong energy noise exists in a surface wave region near a shot. The common shot gather is a collection of seismic traces generated by a single shot.

[0106] The reflection wave data screening module 702 is used to screen out the effective reflection wave data outside the noise window from the seismic data;

[0107] A compensation factor determination module 703 is configured to determine an amplitude compensation factor for each of the seismic traces in the common shot gather based on an amplitude analysis result of the effective reflection wave data;

[0108] A compensation data acquisition module 704 is configured to perform amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data;

[0109] The noise suppression module 705 is configured to suppress the high energy noise based on the amplitude compensation data.

[0110] Optionally, the compensation factor determination module 703 is configured to:

[0111] Performing frequency division filtering on the effective reflected wave data to obtain filtered data;

[0112] Statistically analyzing the relationship between the amplitude and the offset in the filtered data to obtain an amplitude-offset function, where the offset refers to the horizontal distance between the detection point and the shot point;

[0113] The amplitude compensation factor of each seismic trace in the common shot gather is determined based on the amplitude offset function.

[0114] Optionally, the compensation factor determination module 703 is configured to:

[0115] Performing iterative calculations based on the amplitude offset function to obtain the shot point amplitude component and the receiver point amplitude component of each seismic trace;

[0116] The product of the shot point amplitude component and the detection point amplitude component is determined as the amplitude compensation factor.

[0117] Optionally, the compensation factor determination module 703 is configured to:

[0118] Performing spectrum analysis on the strong energy noise data in the noise time window to determine the noise main frequency and noise bandwidth of the strong energy noise;

[0119] Performing spectrum analysis on the effective reflected wave data to determine the reflected wave main frequency and reflected wave bandwidth of the effective reflected wave;

[0120] dividing the effective reflected wave data according to the reflected wave main frequency and the reflected wave bandwidth to obtain an analysis frequency band;

[0121] Determining a filter corresponding to the analysis frequency band based on the main frequency of the noise, the bandwidth of the noise, the main frequency of the reflected wave, and the bandwidth of the reflected wave;

[0122] The effective reflected wave data is subjected to frequency division filtering by the filter to obtain the filtered data.

[0123] Optionally, the compensation data acquisition module 704 is configured to:

[0124] The product of the amplitude compensation factor and the seismic data is determined as the amplitude compensation data.

[0125] Optionally, the noise time window determination module 701 is configured to:

[0126] determining a velocity threshold based on the surface wave velocities at different acquisition points in the near-shot surface wave region;

[0127] An area in the common shot gather where the seismic wave velocity is less than or equal to the velocity threshold is determined as the noise time window corresponding to the strong energy noise.

[0128] Optionally, the noise suppression module 705 includes:

[0129] an amplitude processing unit, configured to perform amplitude processing on a trace group from both time and space dimensions to determine an average amplitude value corresponding to each sampling point in the trace group, wherein the trace group is a collection of X adjacent seismic traces and contains multiple sampling points;

[0130] a suppression coefficient calculation unit, configured to calculate a suppression coefficient of the track group based on the average amplitude value;

[0131] A noise suppression unit is configured to suppress the strong energy noise on each of the seismic traces in the trace group based on the suppression coefficient.

[0132] Optionally, the suppression coefficient calculation unit is used to:

[0133] The product of the threshold coefficient and the average amplitude value is determined as the amplitude threshold value of each sample point in the track group, wherein the amplitude threshold value is a threshold value used to determine whether the sample point needs to be amplitude suppressed;

[0134] When the amplitude value reaches the reference amplitude value, the suppression coefficient of each seismic trace in the trace group is determined based on the average amplitude value, the attenuation coefficient, and the amplitude value. The suppression coefficient is negatively correlated with the amplitude value, and the attenuation coefficient is used to limit the degree of suppression of the strong energy noise.

[0135] Optionally, the pressing unit is used to:

[0136] performing smoothing processing on the suppression coefficients of the plurality of track groups to obtain smoothed suppression coefficients;

[0137] Based on the smoothing suppression coefficient, the strong energy noise is suppressed for each of the seismic traces in the trace group.

[0138] Please refer to Figure 8 , which shows a block diagram of a terminal structure provided by an exemplary embodiment of the present application. The terminal 800 can be implemented as the terminal in each of the above embodiments. The terminal 800 may include one or more of the following components: a processor 810 and a memory 820.

[0139] The processor 810 may include one or more processing cores. The processor 810 uses various interfaces and lines to connect the various parts of the entire terminal 800, and executes various functions and processes data of the terminal 800 by running or executing instructions, programs, code sets or instruction sets stored in the memory 820, and calling data stored in the memory 820. Optionally, the processor 810 can be implemented in at least one hardware form of digital signal processing (DSP), field programmable gate array (FPGA), and programmable logic array (PLA). The processor 810 can integrate one or more combinations of a central processing unit (CPU), a graphics processing unit (GPU), a neural network processing unit (NPU), and a modem. Among them, the CPU mainly processes the operating system, user interface, and application programs; the GPU is responsible for rendering and drawing the content required to be displayed on the touch screen; the NPU is used to implement artificial intelligence (AI) functions; and the modem is used to handle wireless communication. It is understandable that the above-mentioned modem may not be integrated into the processor 810, but may be implemented by a separate chip.

[0140] The memory 820 may include a random access memory (RAM) or a read-only memory (ROM). Optionally, the memory 820 includes a non-transitory computer-readable storage medium. The memory 820 may be used to store instructions, programs, codes, code sets, or instruction sets. The memory 820 may include a program storage area and a data storage area, wherein the program storage area may store instructions for implementing an operating system, instructions for at least one function (such as a touch function, a sound playback function, an image playback function, etc.), instructions for implementing the following various method embodiments, etc.; the data storage area may store data created according to the use of the terminal 800 (such as audio data, a phone book), etc.

[0141] In addition, those skilled in the art will understand that the structure of the terminal 800 shown in the above drawings does not constitute a limitation of the terminal, and the terminal may include more or fewer components than shown, or combine certain components, or arrange the components differently. For example, the terminal 800 also includes a display screen, a camera assembly, a microphone, a speaker, a radio frequency circuit, an input unit, sensors (such as an accelerometer, an angular velocity sensor, a light sensor, etc.), an audio circuit, a WiFi module, a power supply, a Bluetooth module, and other components, which are not further described here.

[0142] An embodiment of the present application further provides a computer-readable storage medium storing at least one program code, which is loaded and executed by a processor to implement the method for suppressing strong energy noise near the shot point as described in the above embodiments.

[0143] An embodiment of the present application provides a computer program product comprising computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the method for suppressing near-shot high-energy noise provided in various optional implementations of the aforementioned aspects.

[0144] It should be understood that the "multiple" mentioned in this article refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B can represent three situations: A exists alone, A and B exist at the same time, and B exists alone. The character " / " generally indicates that the previous and subsequent associated objects are in an "or" relationship. In addition, the step numbers described in this article only illustrate a possible execution sequence between the steps. In some other embodiments, the above steps may not be executed in the order of the numbers, such as two steps with different numbers are executed at the same time, or two steps with different numbers are executed in the opposite order to the diagram. The embodiments of the present application do not limit this.

[0145] The above description is merely an optional embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent replacements, improvements, etc. made within the spirit and principles of the present application shall be included in the scope of protection of the present application.

Claims

1. A method for suppressing strong energy noise near a shot point, characterized in that: The method comprises: Determining a noise time window corresponding to strong energy noise based on a common shot gather, wherein the strong energy noise exists in a surface wave region near the shot, and the common shot gather is a collection of seismic traces generated by the same shot; Filtering out effective reflected wave data outside the noise window from the seismic data; determining an amplitude compensation factor for each of the seismic traces in the common shot gather based on an amplitude analysis result of the effective reflected wave data; performing amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data; Suppressing the strong energy noise based on the amplitude compensation data; The step of determining the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude analysis result of the effective reflection wave data includes: Performing frequency division filtering on the effective reflected wave data to obtain filtered data; Statistically analyzing the relationship between the amplitude and the offset in the filtered data to obtain an amplitude-offset function, where the offset refers to the horizontal distance between the detection point and the shot point; determining the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude offset function; Determining the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude offset function includes: Performing iterative calculations based on the amplitude offset function to obtain the shot point amplitude component and the receiver point amplitude component of each seismic trace; Determine the product of the shot point amplitude component and the detection point amplitude component as the amplitude compensation factor; The suppressing of the strong energy noise based on the amplitude compensation data includes: Performing amplitude processing on a trace group from both time and space dimensions to determine an average amplitude value corresponding to each sampling point in the trace group, wherein the trace group is a collection of X adjacent seismic traces and includes multiple sampling points; Calculating a suppression coefficient of the track group based on the average amplitude value; Based on the suppression coefficient, the strong energy noise is suppressed for each of the seismic traces in the trace group.

2. The method according to claim 1, characterized in that The performing frequency division filtering on the effective reflected wave data to obtain filtered data includes: Performing spectrum analysis on the strong energy noise data in the noise time window to determine the noise main frequency and noise bandwidth of the strong energy noise; Performing spectrum analysis on the effective reflected wave data to determine the reflected wave main frequency and reflected wave bandwidth of the effective reflected wave; dividing the effective reflected wave data according to the reflected wave main frequency and the reflected wave bandwidth to obtain an analysis frequency band; Determining a filter corresponding to the analysis frequency band based on the main frequency of the noise, the bandwidth of the noise, the main frequency of the reflected wave, and the bandwidth of the reflected wave; The effective reflected wave data is subjected to frequency division filtering by the filter to obtain the filtered data.

3. The method according to claim 1, characterized in that The step of performing amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data includes: The product of the amplitude compensation factor and the seismic data is determined as the amplitude compensation data.

4. The method according to claim 1, wherein The determining of the noise time window corresponding to the strong energy noise based on the common shot gathers includes: determining a velocity threshold based on the surface wave velocities at different acquisition points in the near-shot surface wave region; An area in the common shot gather where the seismic wave velocity is less than or equal to the velocity threshold is determined as the noise time window corresponding to the strong energy noise.

5. The method according to claim 1, wherein The step of calculating the suppression coefficient of the track group based on the average amplitude value includes: The product of the threshold coefficient and the average amplitude value is determined as the amplitude threshold value of each sample point in the track group, wherein the amplitude threshold value is a threshold value used to determine whether the sample point needs to be amplitude suppressed; When the amplitude value reaches the reference amplitude value, the suppression coefficient of each seismic trace in the trace group is determined based on the average amplitude value, the attenuation coefficient, and the amplitude value. The suppression coefficient is negatively correlated with the amplitude value, and the attenuation coefficient is used to limit the degree of suppression of the strong energy noise.

6. The method according to claim 1, characterized in that Suppressing the strong energy noise on each of the seismic traces in the trace group based on the suppression coefficient includes: performing smoothing processing on the suppression coefficients of the plurality of track groups to obtain smoothed suppression coefficients; Based on the smoothing suppression coefficient, the strong energy noise is suppressed for each of the seismic traces in the trace group.

7. A device for suppressing strong energy noise near the shot point, characterized in that: The device comprises: a noise time window determination module for determining a noise time window corresponding to strong energy noise based on a common shot gather, wherein the strong energy noise exists in a surface wave region near a shot, and the common shot gather is a collection of seismic traces generated by a same shot; A reflection wave data screening module is used to screen out effective reflection wave data outside the noise window from seismic data; a compensation factor determination module, configured to determine an amplitude compensation factor for each of the seismic traces in the common shot gather based on an amplitude analysis result of the effective reflection wave data; a compensation data acquisition module, configured to perform amplitude compensation on the seismic data using the amplitude compensation factor to obtain amplitude compensated data; a noise suppression module, configured to suppress the strong energy noise based on the amplitude compensation data; Wherein, the compensation factor determination module is used to: Performing frequency division filtering on the effective reflected wave data to obtain filtered data; Statistically analyzing the relationship between the amplitude and the offset in the filtered data to obtain an amplitude-offset function, where the offset refers to the horizontal distance between the detection point and the shot point; determining the amplitude compensation factor of each seismic trace in the common shot gather based on the amplitude offset function; Performing iterative calculations based on the amplitude offset function to obtain the shot point amplitude component and the receiver point amplitude component of each seismic trace; Determine the product of the shot point amplitude component and the detection point amplitude component as the amplitude compensation factor; The noise suppression module includes: an amplitude processing unit, configured to perform amplitude processing on a trace group from both time and space dimensions to determine an average amplitude value corresponding to each sampling point in the trace group, wherein the trace group is a collection of X adjacent seismic traces and contains multiple sampling points; a suppression coefficient calculation unit, configured to calculate a suppression coefficient of the track group based on the average amplitude value; A noise suppression unit is configured to suppress the strong energy noise on each of the seismic traces in the trace group based on the suppression coefficient.

8. A terminal, characterized in that: The terminal includes a processor and a memory; the memory stores at least one instruction, and the at least one instruction is used to be executed by the processor to implement the method for suppressing strong energy noise near the shot point according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that The computer-readable storage medium stores at least one program code, and the program code is loaded and executed by the processor to implement the method for suppressing strong energy noise near the shot point according to any one of claims 1 to 6.

10. A computer program product, characterized in that The computer program product includes computer instructions, which are stored in a computer-readable storage medium; a processor of a computer device reads the computer instructions from the computer-readable storage medium, and the processor executes the computer instructions, so that the computer device performs the method for suppressing near-shot point strong energy noise as described in any one of claims 1 to 6.

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