A seismic data noise suppression method, device, equipment, medium and program

Abstract

This disclosure relates to the field of seismic exploration data processing technology, and particularly to a method, apparatus, device, storage medium, and computer program for suppressing seismic data noise. The method includes: acquiring seismic interference traces and normal seismic traces; suppressing the seismic interference traces to obtain suppressed seismic interference traces; determining whether the scaling factor in the suppressed seismic interference traces is greater than a preset threshold value; if the scaling factor in the suppressed seismic interference traces is less than or equal to the preset threshold value, then determining that the seismic interference trace has been suppressed; if the scaling factor in the suppressed seismic interference traces is greater than the preset threshold value, then marking the seismic interference trace as a bad trace; interpolating the bad trace using the normal seismic trace to obtain an interpolation result; and replacing the corresponding seismic interference trace with the interpolation result. This invention can be adapted to surge noise suppression.

Description

Technical Field

[0001] This disclosure relates to the field of seismic exploration data processing technology, and in particular to a method, apparatus, device, storage medium, and computer program for suppressing noise in seismic data. Background Technology

[0002] When towed cables collect data at sea, they are affected by ocean currents, causing the cables to undulate and vibrate vertically. This results in vertically striped swell noise appearing on the seismic profile. Swell noise is a common type of noise in marine seismic data, especially when the towed cable is shallow, where the noise is more intense. Swell noise is characterized by strong amplitude, low frequency, and narrow bandwidth. In seismic records, the overall background noise is particularly noticeable. Because it decays very slowly, the amplitude of the noise hardly decreases over time in single-shot records, making subsequent data processing quite difficult.

[0003] Currently, amplitude attenuation methods for suppressing strong energy noise in marine seismic data can effectively suppress surge noise. The basic principle of amplitude attenuation is to use the characteristics of surge noise, such as strong amplitude, low frequency, narrow bandwidth, long duration, and almost no attenuation, to suppress surge noise. However, after processing marine seismic data using amplitude attenuation, although most of the surge noise is suppressed, there are still some differences between it and the surrounding effective signals, which is not conducive to further analysis and processing of the data. Summary of the Invention

[0004] This disclosure provides a method, apparatus, device, storage medium, and program for suppressing noise in seismic data.

[0005] Firstly, this disclosure provides a method for suppressing noise in seismic data, including:

[0006] Obtain earthquake interference traces and normal earthquake traces;

[0007] The seismic interference trace is suppressed to obtain the suppressed seismic interference trace;

[0008] Determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value;

[0009] If the scaling factor in the suppressed seismic interference trace is less than or equal to a preset threshold value, then the seismic interference trace is determined to have been suppressed.

[0010] If the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value, the seismic interference trace is marked as a bad trace.

[0011] The bad trace is interpolated using the normal seismic trace to obtain the interpolation result;

[0012] Replace the corresponding seismic interference trace with the interpolation result.

[0013] In this embodiment of the invention, the process of suppressing the seismic interference trace to obtain a suppressed seismic interference trace includes:

[0014] The earthquake interference channel is divided into multiple windows according to a preset number of windows;

[0015] The amplitude of each window is calculated individually to obtain the amplitude of the window;

[0016] Determine whether the amplitude of the window is abnormal;

[0017] If the amplitude of the window is greater than or equal to a preset threshold, it is determined that the window does not have surge noise;

[0018] If the amplitude of the window is less than a preset threshold, then noise suppression is applied to the window to obtain a suppressed window.

[0019] The suppressed seismic interference trace is generated by combining the window without surge noise and the suppressed window.

[0020] In this embodiment of the invention, determining whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value includes:

[0021] Calculate the number of suppressed windows in the suppressed seismic interference trace;

[0022] The ratio of the number of suppressed windows to the preset number of windows is used as a scaling factor;

[0023] The scaling factor is compared with a preset threshold value. If the scaling factor minus the preset threshold value is greater than zero, it means that the scaling factor is greater than the preset threshold value.

[0024] If the scaling factor minus the preset threshold value is less than or equal to zero, it means that the scaling factor is less than or equal to the preset threshold value.

[0025] In this embodiment of the invention, the step of interpolating the bad trace using the normal seismic trace to obtain the interpolation result includes:

[0026] Select a predetermined number of normal seismic traces that are adjacent to the bad traces in the normal seismic traces;

[0027] Interpolation calculations are performed on the bad traces based on the selected normal seismic traces to obtain the interpolation calculation results;

[0028] The interpolation processing result is generated based on the interpolation calculation result.

[0029] In this embodiment of the invention, the step of interpolating the bad trace based on the selected normal seismic trace to obtain the interpolation result includes:

[0030] The bad traces and the selected normal seismic traces are combined to form the seismic data to be processed;

[0031] The seismic data to be processed is subjected to seismic trace flattening to obtain flattened seismic data to be processed;

[0032] Interpolation calculations are performed on the flattened seismic data to be processed to obtain the interpolation results.

[0033] In this embodiment of the invention, replacing the corresponding seismic interference trace with the interpolation result includes:

[0034] The interpolation calculation results are subjected to seismic trace restoration processing to obtain the restoration result;

[0035] Determine the location of the suppressed seismic interference trace;

[0036] The recovery result replaces the corresponding seismic interference trace according to the location of the suppressed seismic interference trace.

[0037] Secondly, this disclosure provides a seismic data noise suppression device, comprising:

[0038] The acquisition module is used to acquire seismic interference traces and normal seismic traces;

[0039] The suppression processing module is used to suppress the seismic interference trace to obtain a suppressed seismic interference trace.

[0040] The judgment module is used to determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value;

[0041] An interpolation processing module is used to interpolate the bad trace using the normal seismic trace to obtain the interpolation processing result.

[0042] The replacement module is used to replace the corresponding seismic interference trace with the interpolation result.

[0043] Thirdly, this disclosure provides a computer device including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the seismic data noise suppression method described above.

[0044] Fourthly, this disclosure provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the steps of the seismic data noise suppression method described above.

[0045] Fifthly, this disclosure provides a computer program product, including a computer program / instructions, which, when executed by a processor, implements the steps of the seismic data noise suppression method described above.

[0046] This disclosure provides a method, apparatus, device, storage medium, and computer program for suppressing seismic data noise. By suppressing seismic interference channels through amplitude attenuation and interpolation processing, the amplitude of seismic signals can be enhanced, facilitating more accurate location, orientation, and morphology of geological structures. Suppression of seismic interference channels removes noise that does not contribute to the target data, improving the signal-to-noise ratio and reducing the false identification rate. This suppression process plays a significant role in subsequent seismic data processing. Furthermore, by comparing the scale factors of different seismic interference channels, the impact of different interference signal types on seismic data can be better understood. This method provides a reference and basis for seismic data analysis and processing. By replacing the seismic interference trace data with the interpolation results, the influence of interference signals (such as surge noise) on the seismic signal can be removed, thereby effectively improving the quality of seismic survey data and reducing the deviation and error of the survey results. After replacing the seismic interference trace data, the structure and location parameters of underground rock strata can be calculated more accurately. At the same time, surge noise is suppressed, and further interpolation replacement is performed on traces that are not completely processed after suppression. This allows surge noise to be processed better and more thoroughly, while restoring the effective signal of the seismic data and improving the signal-to-noise ratio of the seismic data. This method is highly targeted. Attached Figure Description

[0047] The present disclosure will be described in more detail below based on embodiments and with reference to the accompanying drawings:

[0048] Figure 1 This is a flowchart illustrating a method for suppressing noise in seismic data, as provided in Embodiment 1 of this disclosure.

[0049] Figure 2 This is a functional block diagram of a seismic data noise suppression device provided in Embodiment 3 of this disclosure.

[0050] Figure 3 This is a flowchart illustrating a seismic data noise suppression method provided in Embodiment 1 of this disclosure.

[0051] Figure 4 The original seismic atlas of actual marine seismic data surge noise provided in Embodiment 1 of this disclosure.

[0052] Figure 5 The seismic atlas provided in Embodiment 1 of this disclosure after suppressing surge noise using the amplitude attenuation method.

[0053] Figure 6This is a seismic gather map after surge noise suppression using a seismic data noise suppression method, provided as an embodiment of this disclosure.

[0054] Figure 7 An enlarged view of the original seismic gather showing the effect of suppressing surge noise from actual marine seismic data provided in Embodiment 1 of this disclosure.

[0055] Figure 8 This is an enlarged image of the seismic gather after suppressing surge noise using the amplitude attenuation method, as provided in Embodiment 1 of this disclosure.

[0056] Figure 9 This is a seismic gather map after surge noise suppression using a seismic data noise suppression method, provided as an embodiment of this disclosure.

[0057] Figure 10 This is a schematic diagram of the electronic device used in the seismic data noise suppression method provided in Embodiment 4 of this disclosure.

[0058] In the accompanying drawings, the same parts are referred to by the same reference numerals, and the drawings are not drawn to scale. Detailed Implementation

[0059] To enable those skilled in the art to better understand the technical solutions of this disclosure, and to fully understand and implement the process of how this disclosure applies technical means to solve technical problems and achieve corresponding technical effects, the technical solutions in the embodiments of this disclosure will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this disclosure, not all embodiments. The embodiments of this disclosure and the various features within them can be combined with each other without conflict, and the resulting technical solutions are all within the protection scope of this disclosure. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without creative effort should fall within the protection scope of this disclosure.

[0060] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this disclosure are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this disclosure described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0061] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0062] Example 1

[0063] Figure 1 This is a schematic flowchart illustrating a method for suppressing seismic data noise according to an embodiment of this disclosure. Figure 1 As shown, a method for suppressing noise in seismic data includes:

[0064] S1. Obtain the seismic interference trace and the seismic normal trace.

[0065] In this embodiment of the invention, "acquiring" refers to collecting earthquake data that needs to be studied.

[0066] Specifically, seismic interference channels refer to interference signals in seismic records that do not conform to the morphological characteristics of seismic waves. These interference signals can come from various factors, such as interference from input signals and sensor noise. These interference signals can affect the accuracy and reliability of seismic data and may affect the results of seismic processing and interpretation. On the other hand, seismic normal channels refer to signals with seismic wave characteristics collected through seismic experiments, measurements, and other means. These signals can reflect the underground structure and the propagation of seismic waves.

[0067] S2. The seismic interference trace is suppressed to obtain the suppressed seismic interference trace.

[0068] In this embodiment of the invention, the suppression process refers to adjusting the amplitude of the seismic signal in the seismic data to gradually reduce the amplitude of the frequency band occupied by surge noise.

[0069] Specifically, when performing amplitude attenuation processing, the seismic interference trace needs to be divided into multiple windows, the amplitude of each window needs to be calculated, and then it needs to be determined whether there are any abnormalities in the amplitude of the window. For the windows with abnormalities, the amplitude of the surge noise needs to be reduced to an acceptable range, thereby achieving the effect of suppression.

[0070] In this embodiment of the invention, the process of suppressing the seismic interference trace to obtain a suppressed seismic interference trace includes:

[0071] The earthquake interference channel is divided into multiple windows according to a preset number of windows;

[0072] The amplitude of each window is calculated individually to obtain the amplitude of the window;

[0073] Determine whether the amplitude of the window is abnormal;

[0074] If the amplitude of the window is greater than or equal to a preset threshold, it is determined that the window does not have surge noise;

[0075] If the amplitude of the window is less than a preset threshold, then noise suppression is applied to the window to obtain a suppressed window.

[0076] The suppressed seismic interference trace is generated by combining the window without surge noise and the suppressed window.

[0077] In this embodiment of the invention, the division refers to dividing the seismic interference traces according to the number of windows determined by the requirements; the amplitude calculation refers to calculating the time-direction amplitude, mean amplitude, and median amplitude of the divided windows; the judgment refers to accurately locating the windows with amplitude anomalies based on the calculated mean amplitude and median amplitude; and the noise suppression refers to performing noise attenuation processing on the windows with surge noise.

[0078] Specifically, each input seismic data trace is divided into multiple windows from top to bottom according to a preset number of windows. The second step is noise detection. First, the time-direction amplitude is calculated. For all input seismic data traces, the amplitude of each window from top to bottom is calculated. The calculation functions include root mean square amplitude, average amplitude, and maximum amplitude. The formula for calculating the root mean square amplitude is:

[0079]

[0080] Where P rms P is the root mean square amplitude, n is the number of time windows, and P is the root mean square amplitude. i Let be the sampling amplitude value of the i-th statistical time window.

[0081] The formula for calculating the average amplitude is:

[0082]

[0083] Where P mean The average amplitude is given by P, where n is the number of time windows. i Let be the sampling amplitude value of the i-th statistical time window.

[0084] The formula for calculating the maximum amplitude is:

[0085] P max =max{P1,P2,...,P n}

[0086] Where P max The maximum amplitude is given by n, the number of time windows, and P. n This represents the sampling amplitude value for the nth statistical time window.

[0087] Next, spatial amplitude calculations are performed, calculating the amplitude for each window at the same time position for each trace. The calculation functions include mean amplitude and median amplitude. The formula for calculating the mean amplitude is:

[0088]

[0089] in Let be the mean amplitude of the wn window, and m be the number of shot collections calculated from the spatial amplitude. Let be the time amplitude of the wn window of the i-th gun set.

[0090] The formula for calculating the median amplitude is:

[0091]

[0092] in represents the median amplitude of the wn window, and m is the shot number calculated from the spatial amplitude. Let wn be the time amplitude of the m-th shot set;

[0093] The calculated mean and median amplitudes are used to pinpoint the windows where amplitude anomalies exist, which are the windows where surge noise exists.

[0094] In detail, noise attenuation is finally required. After accurately locating the window with abnormal amplitude, if the calculated spatial amplitude is less than a preset threshold, noise attenuation is applied to that window to suppress abnormal noise. The processing functions include percentage, exponential, and corrected exponential suppression. The formula for percentage suppression is:

[0095]

[0096] Where P is the original amplitude and N is the percentage (0-100);

[0097] The formula for calculating index suppression is:

[0098] P = P N

[0099] Where P is the original amplitude and N is the exponent;

[0100] The formula for calculating the corrected index suppression is:

[0101]

[0102] Where P is the original amplitude, P min The minimum amplitude is N, and the exponent is N.

[0103] In this embodiment of the invention, dividing the signal into multiple windows allows for a more precise determination of its exact location and time, avoiding erroneous judgments of overall anomalies due to interference from the amplitude of the entire seismic interference trace. Individual processing and positioning of each window enables a more accurate grasp of the location, extent, and impact of the anomaly. Simultaneously, amplitude anomaly detection can eliminate interference caused by these factors through amplitude calculation for each window, quickly excluding non-seismic interference. Furthermore, window-based amplitude calculation improves data analysis efficiency, enabling rapid and accurate screening of anomalous signals.

[0104] In this embodiment of the invention, after processing seismic interference channels, some inexplicable interference can be removed, which will help observe the details of underground geological structures. Suppression of seismic interference channels can enhance the amplitude of seismic signals, helping to more accurately locate the position, direction, and morphology of geological structures; it can also remove noise that does not contribute to the target data, improving the signal-to-noise ratio of the seismic data and reducing the false identification rate; and it plays a significant role in subsequent seismic data processing. While the influence of seismic interference channels on seismic data is difficult to completely remove, suppression can reduce the number of iterations in the current seismic data processing, thereby increasing the processing speed. Furthermore, after suppressing seismic interference channels, the results of the suppressed interference can be obtained directly without further processing of the interference during data processing. This shortens data processing time and improves work efficiency.

[0105] S3. Determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value.

[0106] In this embodiment of the invention, the judgment refers to the judgment made by comparing the scale factor in the suppressed seismic interference trace with a preset threshold value.

[0107] Typically, the threshold value is set according to the specific application scenario. For example, if the threshold value is low, the scale factor in the suppressed seismic interference traces will be small, indicating that the interference has been well suppressed; if the threshold value is high, the scale factor in the suppressed seismic interference traces will be large, indicating that there is still some interference that needs further processing.

[0108] In this embodiment of the invention, determining whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value includes:

[0109] Calculate the number of suppressed windows in the suppressed seismic interference trace;

[0110] The ratio of the number of suppressed windows to the preset number of windows is used as a scaling factor;

[0111] The scaling factor is compared with a preset threshold value. If the scaling factor minus the preset threshold value is greater than zero, then the scaling factor is greater than the preset threshold value.

[0112] If the scaling factor minus the preset threshold value is less than or equal to zero, then the scaling factor is less than or equal to the preset threshold value.

[0113] In this embodiment of the invention, the calculation refers to the number of windows defined according to the suppression window during the process of obtaining the suppressed seismic interference trace, and the comparison refers to the comparison of the value of the scaling factor and the threshold value.

[0114] Specifically, the seismic interference trace is divided into multiple windows. The amplitude of each window is calculated and compared with a pre-set threshold to determine whether the window needs to be suppressed. For windows that need to be suppressed, seismic signal suppression processing is performed to cover them as all-zero windows to reduce the impact of seismic interference on other windows. The number of suppressed windows is counted. Usually, all-zero windows are considered as suppressed windows because the original amplitude information in the window has been completely lost after seismic signal suppression processing. Subsequent processing and analysis are then carried out based on the suppressed seismic interference trace.

[0115] In detail, the scaling factor is an important indicator for measuring the intensity of seismic interference and the effectiveness of suppression processing. The value of the scaling factor will vary depending on the type of seismic data and the degree of interference. The ratio between the number of windows to be suppressed and the preset number of windows is considered the scaling factor; the larger the scaling factor, the more severe the seismic interference, and the more stringent the suppression processing needs to be.

[0116] In this embodiment of the invention, by comparing the ratio of the number of suppressed windows to the preset number of windows, the suppression effect can be accurately evaluated, and the degree of interference in the seismic data can be measured. The smaller the scaling factor, the smaller the degree of interference in the seismic data, and the less interference to the data. By calculating the scaling factor, different post-processing methods can be selected according to different data and degrees of interference, further optimizing the efficiency of data analysis and processing, and effectively controlling data quality. This not only improves the quality of the data but also avoids introducing interference information in subsequent analyses.

[0117] In this embodiment of the invention, researchers need to employ a series of algorithms and methods when analyzing and processing seismic data. Especially in practical applications such as seismic phase picking, velocity model construction, and source location, they are severely affected by interference noise. Therefore, determining the presence of severe interference signals through a scaling factor can avoid the impact of interference signals on subsequent processing. The scaling factor is the ratio of the energy of the interference signal to the energy of the seismic signal in the seismic record, reflecting the strength of the interference signal. By comparing the scaling factors of different seismic interference traces, the impact of different interference signal types on seismic data can be better understood, providing reference and basis for seismic data analysis and processing.

[0118] S4. If the scaling factor in the suppressed seismic interference trace is less than or equal to a preset threshold value, then it is determined that the seismic interference trace has been suppressed.

[0119] In this embodiment of the invention, "determining" means that the seismic interference, including surge noise, has been suppressed after amplitude attenuation processing.

[0120] Specifically, if the scaling factor in the suppressed seismic interference trace is less than or equal to a preset threshold value, it means that the intensity of the seismic interference trace has been significantly reduced and no longer has a significant impact on the seismic data. Therefore, determining that the seismic interference trace has been suppressed means that the denoising methods in data processing have demonstrated sufficient suppression capabilities, reducing the noise interference to the seismic data to a relatively acceptable level.

[0121] S5. If the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value, the seismic interference trace is marked as a bad trace.

[0122] Specifically, for suppressed seismic interference traces, if their scaling factor is greater than the preset threshold value, it indicates that they still have a strong interference effect on seismic data and should be processed or removed separately. For example, when extracting and analyzing seismic information, these data marked as bad traces can be removed to improve the accuracy and precision of the processing results.

[0123] S6. Interpolate the bad trace using the normal seismic trace to obtain the interpolation result.

[0124] In this embodiment of the invention, the interpolation process refers to using a specific interpolation algorithm to calculate and reconstruct the missing data on the bad track, thereby obtaining a complete set of seismic records.

[0125] Specifically, the bad track is interpolated using the normal seismic trace that does not include surge noise. This means using the data from the normal trace to perform linear interpolation or other interpolation methods on the data from the bad track, so that the data from the bad track can be recovered and supplemented, thereby obtaining a complete and reliable set of seismic records.

[0126] It's important to note that different interpolation algorithms can be used depending on the specific characteristics and requirements of the data. Commonly used interpolation methods include linear interpolation, bilinear interpolation, and cubic spline interpolation. Among these, linear interpolation is one of the simplest and most widely used methods, suitable for simple reconstruction and supplementation of bad sector data. Other interpolation algorithms, however, can achieve better results when processing complex data.

[0127] In this embodiment of the invention, the step of interpolating the bad trace using the normal seismic trace to obtain the interpolation result includes:

[0128] Select a predetermined number of normal seismic traces that are adjacent to the bad traces in the normal seismic traces;

[0129] Interpolation calculations are performed on the bad traces based on the selected normal seismic traces to obtain the interpolation calculation results;

[0130] The interpolation processing result is generated based on the interpolation calculation result.

[0131] In this embodiment of the invention, the selection refers to selecting a preset number of normal seismic channels adjacent to the bad channel from the normal seismic channels that do not include surge noise, and the interpolation calculation refers to fitting the missing data points on the bad channel based on the relevant information of the preset number of normal seismic channels adjacent to the bad channel.

[0132] Specifically, the location of bad traces with missing data is first determined, usually by manual or semi-automatic methods. After the location of the bad trace is determined, the adjacent normal data points are extracted to obtain a finite trace set. Specifically, the bad trace and a predetermined number of normal traces to its left and right are combined into a trace set. The extracted normal data points are interpolated or fitted to estimate the missing data points at the location of the bad trace, thereby obtaining a continuous seismic data.

[0133] In detail, interpolation calculations are performed at the locations of missing data points for the extracted data. Interpolation methods can include linear interpolation, piecewise interpolation, cubic spline interpolation, radial basis function interpolation, and Kriging-based interpolation. After interpolation, the results are usually smoothed to eliminate noise that may have occurred during the calculation. Smoothing methods can include mean smoothing, median smoothing, and weighted smoothing. After the interpolation calculation is completed, the interpolated results need to be merged with the original signal to reconstruct the original seismic record. The merging process requires weighted averaging or interpolation compensation methods between the interpolated results and the original signal.

[0134] Specifically, the number of windows needs to be set first. The number of windows defines how many adjacent normal seismic traces are selected near the bad trace for interpolation calculation. The number of windows should be adjusted according to specific circumstances. Generally, a trial run can be conducted first, and the appropriate window number can be determined based on the interpolation results, and adjustments can be made accordingly. A larger window number allows for the selection of more adjacent normal seismic traces, providing more information and thus improving interpolation accuracy. However, the computational load also gradually increases with the increase in the number of windows, reducing computational efficiency. If the number of windows is too small, too few adjacent normal seismic traces will be selected, and interpolation accuracy cannot be well guaranteed.

[0135] In this embodiment of the invention, the step of interpolating the bad trace based on the selected normal seismic trace to obtain the interpolation result includes:

[0136] The bad traces and the selected normal seismic traces are combined to form the seismic data to be processed;

[0137] The seismic data to be processed is subjected to seismic trace flattening to obtain flattened seismic data to be processed;

[0138] Interpolation calculations are performed on the flattened seismic data to be processed to obtain the interpolation results.

[0139] In this embodiment of the invention, the flattening process refers to the operation of translation and stretching of each time window data in the seismic record. The interpolation calculation refers to transforming the seismic data from the original time domain coordinate system to the frequency domain coordinate system and performing data compensation processing in the frequency domain to obtain seismic records that do not actually exist within a certain time window.

[0140] Specifically, seismic flattening refers to performing NMO processing on the seismic data to be processed. To perform NMO processing, an appropriate stacking velocity needs to be selected, and the data needs to be grouped. In this step, a known velocity model from seismic exploration can be used, or it can be determined through data analysis. After selecting the stacking velocity, the data needs to be divided according to the stacking velocity, assigning the data to the corresponding velocity layers. For each trace, its NMO time interval needs to be calculated. When calculating the time interval, the influence of subsurface velocity variations on the seismic record needs to be considered. The NMO time interval is determined by calculating the relationship between arrival time and offset distance. After obtaining the NMO time interval for each trace, NMO correction is performed. The data for each trace is shifted according to its NMO time interval, subtracting the velocity influence of the subsurface medium on the seismic record. After completing the NMO correction, the velocity-grouped data needs to be sorted according to the original traces and reorganized into the original seismic data sequence.

[0141] Furthermore, after NMO processing, if there are missing seismic records due to picking errors, stratigraphic deformation, or other reasons, interpolation is required to fill in the missing records and ensure a continuous sequence. An interpolation method is chosen; commonly used methods include linear interpolation, cubic spline interpolation, and Kriging interpolation. The appropriate interpolation method is selected based on the characteristics and requirements of the data. After selecting the method, the spatial resolution and interpolation step size of the interpolation grid need to be determined. Based on the spatial resolution of the acquired data, the size and resolution of the interpolation grid are determined to ensure that the interpolated seismic data meets the analysis requirements. Interpolation calculations are then performed on the data according to the selected interpolation method and grid. During interpolation, the sampling interval can be used to obtain a continuous sequence of seismic records.

[0142] It is important to note that if a bad trace is located in the middle part of the seismic data, traces at the same position of several adjacent shots will be extracted according to the user settings. If there are traces marked as bad traces, they will be ignored and other traces will be used to interpolate the bad traces. If a bad trace is located at either end of the seismic data, and the number of shots before or after it is less than half of the number of shots set by the user, special handling is required. If there are several adjacent shots, those adjacent shots will be used, and the bad traces among them will be ignored. Other traces will be used to interpolate the bad traces at both ends of the shot set.

[0143] In this embodiment of the invention, interpolation is performed using a preset number of normal seismic traces adjacent to the bad traces. This minimizes the differences between the bad and normal traces, reduces interpolation errors, and improves imaging results. Furthermore, adjacent normal seismic traces have a certain degree of similarity, and selecting adjacent normal seismic traces for interpolation can better maintain data continuity and consistency between adjacent traces, which is more in line with reality. At the same time, it can reduce interference from geological events or structural factors, retain more geological information, and thus better interpret seismic data.

[0144] In this embodiment of the invention, since surge noise has a significant impact on seismic data, and normal traces typically do not include surge noise, interpolation using normal traces can reduce the impact of noise and improve the quality and reliability of seismic data. The data in normal traces is the raw, unprocessed data, and the interpolation results reflect the original information at the bad traces, making it more accurate and reliable. By interpolating bad traces using normal seismic traces that do not include surge noise, the quality and reliability of seismic data can be improved, making subsequent seismic data analysis and processing more accurate and effective.

[0145] S7. Replace the corresponding seismic interference trace with the interpolation result.

[0146] In this embodiment of the invention, the replacement refers to replacing the original bad track data with the interpolation calculation results of a predetermined number of adjacent normal seismic traces on the bad track.

[0147] Specifically, by interpolating the bad trace with the normal traces adjacent to it on the left and right, and replacing the corresponding seismic interference trace with the interpolation result, seismic interference noise can be successfully suppressed, improving the quality and reliability of seismic data. At the same time, the same method is also needed for interpolation suppression processing for other traces that are related to the seismic interference trace, such as common center point traces (CMP traces), common migration traces (CDP traces), or local common migration traces (LMO traces).

[0148] In this embodiment of the invention, replacing the corresponding seismic interference trace with the interpolation result includes:

[0149] The interpolation calculation results are subjected to seismic trace restoration processing to obtain the restoration result;

[0150] Determine the location of the suppressed seismic interference trace;

[0151] The recovery result replaces the corresponding seismic interference trace according to the location of the suppressed seismic interference trace.

[0152] In this embodiment of the invention, the recovery process refers to performing INMO processing on the seismic data after NMO processing, and then recovering the flattened data. The determination refers to finding the location of the suppressed seismic interference traces. The replacement refers to directly replacing the suppressed seismic interference trace data with the recovery result.

[0153] Specifically, seismic trace restoration processing refers to INMO processing. Before INMO processing, sampling parameters need to be determined, including sampling interval and number of sampling points. These parameters are determined based on the characteristics of the seismic record and the analysis requirements. Choosing an appropriate window function can reduce spectral leakage and contamination, improving the effectiveness of INMO processing. Commonly used window functions include the Hanning window, Blackman window, and Hamming window. The interpolated seismic data undergoes a Fourier transform to calculate its spectrum. For each frequency value, weighted processing is performed according to the selected window function to obtain a weighted spectrum. Based on the velocity model, the INMO time interval for each trace is calculated. The INMO time interval needs to be calculated based on the frequency values ​​to consider the influence of subsurface medium velocity on the frequency response. The INMO time interval is used to perform phase adjustment on the spectrum, restoring the initial time of the seismic record and reducing the influence of subsurface medium velocity. When calculating the INMO time interval, an appropriate calculation method needs to be selected, such as the stacking velocity analysis method or the fully self-walking method.

[0154] In detail, during data processing, the locations of seismic interference traces that need to be suppressed can be determined by analyzing the characteristics and quality of the seismic records. Once determined, these traces need to be kept in correspondence with other aspects of the record path. The seismic records before and after suppression are compared, and the corresponding seismic interference traces in the original data are replaced with the restored seismic records based on the locations of the suppressed seismic interference traces. All seismic interference traces are replaced according to their suppressed locations.

[0155] Furthermore, check whether the suppressed seismic interference trace data meets the data quality requirements. If it does not meet the requirements, further processing and adjustments are needed to ensure the accuracy and reliability of the data.

[0156] In this embodiment of the invention, these noises can be effectively suppressed through interpolation and inverse transformation operations, thereby improving the accuracy and reliability of the data. By generating seismic interference trace data with suppressed surge noise, the quality of data interpretation can be optimized, improving the accuracy and credibility of the survey results. By optimizing data quality, misinterpretation and invalid surveys can be reduced, thereby lowering costs and waste. High-quality seismic data can provide strong support for fields such as oil and gas exploration, earthquake disaster assessment, and geological exploration, expanding the application scope of seismic data.

[0157] In this embodiment of the invention, by replacing the seismic interference trace data with the interpolation processing results, the influence of interference signals (such as surge noise) on the seismic signal can be removed, thereby effectively improving the quality of seismic survey data and reducing the deviation and error of the survey results. After replacing the seismic interference trace data, the structure and location parameters of the underground rock strata can be calculated more accurately. At the same time, surge noise is suppressed, and further interpolation replacement is performed on traces that are not thoroughly processed after suppression. This allows surge noise to be processed better and more thoroughly, while restoring the effective signal of the seismic data and improving the signal-to-noise ratio of the seismic data. This method is highly targeted.

[0158] Example 2

[0159] To better understand the present invention, a second embodiment is provided below to further explain how the present invention interpolates the bad trace using the normal seismic trace to obtain the interpolation result.

[0160] In this embodiment of the invention, firstly, the position of a bad channel is read. If the bad channel is located in the middle part of the shot set, the channels at the same position of several adjacent shots are extracted according to the user setting. If there is channel data marked as bad channel in step two, it is ignored and other channel data are used to perform sinc interpolation (digital signal processing method) on the bad channel. If the bad channel is located at both ends of the shot set, and the number of shots before or after is less than half of the number of shots set by the user, special processing is required. If there are several adjacent shots, the adjacent shots are used, and the bad channels in them are ignored. Other channels are used to perform sinc interpolation on the bad channels at both ends of the shot set.

[0161] Example 3

[0162] like Figure 2 The diagram shown is a functional block diagram of the seismic data noise suppression device provided in this embodiment.

[0163] The seismic data noise suppression device 100 described in this embodiment can be installed in an electronic device. Depending on the functions implemented, the seismic data noise suppression device 100 may include an acquisition module 101, a suppression processing module 102, a judgment module 103, an interpolation processing module 104, and a replacement module 105. The module described in this invention can also be called a unit, which refers to a series of computer program segments that can be executed by the processor of an electronic device and can perform a fixed function, and which are stored in the memory of the electronic device.

[0164] In this embodiment, the functions of each module / unit are as follows:

[0165] The acquisition module is used to acquire seismic interference traces and normal seismic traces;

[0166] The suppression processing module is used to suppress the seismic interference trace to obtain a suppressed seismic interference trace.

[0167] The judgment module is used to determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value;

[0168] An interpolation processing module is used to interpolate the bad trace using the normal seismic trace to obtain the interpolation processing result.

[0169] The replacement module is used to replace the corresponding seismic interference trace with the interpolation result.

[0170] Example 4

[0171] like Figure 10 As shown, this embodiment also provides a computer device, which may include a processor 10, a memory 11, a communication bus 12 and a communication interface 13, and may also include a computer program stored in the memory 11 and executable on the processor 10, such as a multi-scale stratigraphic division program.

[0172] In some embodiments, the processor 10 may be composed of integrated circuits, such as a single packaged integrated circuit or multiple integrated circuits with the same or different functions, including combinations of one or more central processing units (CPUs), microprocessors, digital processing chips, graphics processors, and various control chips. The processor 10 is the control unit of the electronic device, connecting various components of the entire electronic device through various interfaces and lines. It executes programs or modules stored in the memory 11 (e.g., executing multi-scale stratigraphic division programs) and calls data stored in the memory 11 to perform various functions of the electronic device and process data.

[0173] The memory 11 includes at least one type of readable storage medium, including flash memory, portable hard drive, multimedia card, card-type memory (e.g., SD or DX memory), magnetic memory, magnetic disk, optical disk, etc. In some embodiments, the memory 11 can be an internal storage unit of an electronic device, such as a portable hard drive. In other embodiments, the memory 11 can be an external storage device of the electronic device, such as a plug-in portable hard drive, Smart Media Card (SMC), Secure Digital (SD) card, Flash Card, etc. Furthermore, the memory 11 can include both internal and external storage units of the electronic device. The memory 11 can be used not only to store application software and various types of data installed on the electronic device, such as the code of a multi-scale stratigraphic division program, but also to temporarily store data that has been output or will be output.

[0174] The communication bus 12 can be a peripheral component interconnect (PCI) bus or an extended industry standard architecture (EISA) bus, etc. This bus can be divided into an address bus, a data bus, a control bus, etc. The bus is configured to enable communication between the memory 11 and at least one processor 10, etc.

[0175] The communication interface 13 is used for communication between the aforementioned electronic device and other devices, including a network interface and a user interface. Optionally, the network interface may include a wired interface and / or a wireless interface (such as a Wi-Fi interface, Bluetooth interface, etc.), typically used to establish communication connections between the electronic device and other electronic devices. The user interface may be a display, an input unit (such as a keyboard), or, optionally, a standard wired or wireless interface. Optionally, in some embodiments, the display may be an LED display, a liquid crystal display, a touch-sensitive liquid crystal display, or an OLED (Organic Light-Emitting Diode) touchscreen, etc. The display may also be appropriately referred to as a screen or display unit, used to display information processed in the electronic device and to display a visual user interface.

[0176] The figure only shows an electronic device with components. Those skilled in the art will understand that the structure shown in the figure does not constitute a limitation on the electronic device and may include fewer or more components than shown, or combine certain components, or have different component arrangements.

[0177] For example, although not shown, the electronic device may also include a power supply (such as a battery) to power the various components. Preferably, the power supply can be logically connected to the at least one processor 10 through a power management device, thereby enabling functions such as charging management, discharging management, and power consumption management. The power supply may also include one or more DC or AC power supplies, recharging devices, power fault detection circuits, power converters or inverters, power status indicators, and other arbitrary components. The electronic device may also include various sensors, Bluetooth modules, Wi-Fi modules, etc., which will not be described in detail here.

[0178] It should be understood that the embodiments described are for illustrative purposes only and are not limited to this structure in the scope of the patent application.

[0179] The multi-scale stratigraphic division program stored in the memory 11 of the electronic device is a combination of multiple instructions, which, when run in the processor 10, can achieve the following:

[0180] Obtain earthquake interference traces and normal earthquake traces;

[0181] The seismic interference trace is suppressed to obtain the suppressed seismic interference trace;

[0182] Determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value;

[0183] If the scaling factor in the suppressed seismic interference trace is less than or equal to a preset threshold value, then the seismic interference trace is determined to have been suppressed.

[0184] If the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value, the seismic interference trace is marked as a bad trace.

[0185] The bad trace is interpolated using the normal seismic trace to obtain the interpolation result;

[0186] Replace the corresponding seismic interference trace with the interpolation result.

[0187] Specifically, the specific implementation method of the processor 10 for the above instructions can be referred to the description of the relevant steps in the corresponding embodiment of the accompanying drawings, and will not be repeated here.

[0188] Furthermore, if the modules / units integrated into the electronic device are implemented as software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium. The computer-readable storage medium can be volatile or non-volatile. For example, the computer-readable medium may include: any entity or device capable of carrying the computer program code, a recording medium, a USB flash drive, a portable hard drive, a magnetic disk, an optical disk, a computer memory, or a read-only memory (ROM).

[0189] Example 5

[0190] Based on the above embodiments, this embodiment provides a computer device, including a memory, a processor, and a computer program stored in the memory. The processor executes the computer program to implement the steps of the seismic data noise suppression method described in the above embodiments.

[0191] In some embodiments of this example, a computer-readable storage medium is provided, on which a computer program is stored, characterized in that the computer program, when executed by a processor, implements the steps of the seismic data noise suppression method described in the above embodiments.

[0192] In some embodiments of this example, a computer program product is provided, including a computer program / instruction, characterized in that, when the computer program is executed by a processor, it implements the steps of the seismic data noise suppression method described in the above embodiments.

[0193] The processor may include, but is not limited to, one or more processors or microprocessors. Each processor may be implemented as an Application Specific Integrated Circuit (ASIC), Digital Signal Processor (DSP), Digital Signal Processing Device (DSPD), Programmable Logic Device (PLD), Field Programmable Gate Array (FPGA), controller, microcontroller, microprocessor, or other electronic component, for executing the methods in the above embodiments.

[0194] Computer-readable storage media can be implemented by any type of volatile or non-volatile storage device or a combination thereof. Computer-readable storage media may include, but are not limited to, random access memory (RAM), read-only memory (ROM), flash memory, EPROM memory, EEPROM memory, registers, and computer storage media (e.g., hard disks, floppy disks, solid-state drives, removable disks, CD-ROMs, DVD-ROMs, Blu-ray discs, etc.).

[0195] Computer-readable storage media may also store at least one computer-executable program / instruction, such as computer-readable instructions. Computer-readable storage media include, but are not limited to, volatile memory and / or non-volatile memory. Volatile memory may include, for example, random access memory (RAM) and / or cache memory. Computer-readable storage media may include, for example, read-only memory (ROM), hard disk, flash memory, etc. For example, a non-transitory computer-readable storage medium may be connected to a computing device such as a computer, and then, when the computing device executes the computer-readable instructions stored on the computer-readable storage medium, the various methods described above can be performed.

[0196] In addition, the computer device may include (but is not limited to) a data bus, an input / output (I / O) bus, a display, and input / output devices (e.g., keyboard, mouse, speakers, etc.).

[0197] The processor can communicate with external devices via the I / O bus through wired or wireless networks.

[0198] In one embodiment, the at least one computer-executable instruction may also be compiled into or comprise a software product / computer program product, wherein one or more computer-executable instructions are executed by a processor to perform the steps of the various functions and / or methods in the embodiments described herein.

[0199] In the embodiments provided in this disclosure, it should be understood that the disclosed apparatus and methods can also be implemented in other ways. The apparatus embodiments described above are merely illustrative; for example, the flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of apparatus, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. Furthermore, in some alternative implementations, the functions marked in the blocks may occur in a different order than those marked in the drawings. For example, two consecutive blocks may actually be executed substantially in parallel, or they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram and / or flowchart, and combinations of blocks in block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or action, or can be implemented using a combination of dedicated hardware and computer instructions.

[0200] It should be noted that, in this disclosure, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitation, an element limited by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0201] Although the embodiments disclosed in this disclosure are as described above, the above content is only for the purpose of facilitating understanding of this disclosure and is not intended to limit this disclosure. Those skilled in the art to which this disclosure pertains may make any modifications and changes in the form and details of the implementation without departing from the spirit and scope disclosed in this disclosure, but the scope of patent protection of this disclosure shall still be determined by the scope defined in the appended claims.

Claims

1. A method for suppressing noise in seismic data, characterized in that, include: Obtain earthquake interference traces and normal earthquake traces; The seismic interference trace is suppressed to obtain the suppressed seismic interference trace; Determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value; If the scaling factor in the suppressed seismic interference trace is less than or equal to a preset threshold value, then the seismic interference trace is determined to have been suppressed. If the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value, the seismic interference trace is marked as a bad trace. The bad trace is interpolated using the normal seismic trace to obtain the interpolation result; Replace the corresponding seismic interference trace with the interpolation result.

2. The seismic data noise suppression method according to claim 1, characterized in that, The process of suppressing the seismic interference trace to obtain the suppressed seismic interference trace includes: The earthquake interference channel is divided into multiple windows according to a preset number of windows; The amplitude of each window is calculated individually to obtain the amplitude of the window; Determine whether the amplitude of the window is abnormal; If the amplitude of the window is greater than or equal to a preset threshold, it is determined that the window does not have surge noise; If the amplitude of the window is less than a preset threshold, then noise suppression is applied to the window to obtain a suppressed window. The suppressed seismic interference trace is generated by combining the window without surge noise and the suppressed window.

3. The seismic data noise suppression method according to claim 1, characterized in that, The step of determining whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value includes: Calculate the number of suppressed windows in the suppressed seismic interference trace; The ratio of the number of suppressed windows to the preset number of windows is used as a scaling factor; The scaling factor is compared with a preset threshold value. If the scaling factor minus the preset threshold value is greater than zero, then the scaling factor is greater than the preset threshold value. If the scaling factor minus the preset threshold value is less than or equal to zero, then the scaling factor is less than or equal to the preset threshold value.

4. The seismic data noise suppression method according to claim 1, characterized in that, The process of interpolating the bad trace using the normal seismic trace to obtain the interpolation result includes: Select a predetermined number of normal seismic traces that are adjacent to the bad traces in the normal seismic traces; Interpolation calculations are performed on the bad traces based on the selected normal seismic traces to obtain the interpolation calculation results; The interpolation processing result is generated based on the interpolation calculation result.

5. The seismic data noise suppression method according to claim 4, characterized in that, The step of interpolating the bad trace based on the selected normal seismic trace to obtain the interpolation result includes: The bad traces and the selected normal seismic traces are combined to form the seismic data to be processed; The seismic data to be processed is subjected to seismic trace flattening to obtain flattened seismic data to be processed; Interpolation calculations are performed on the flattened seismic data to be processed to obtain the interpolation results.

6. The seismic data noise suppression method according to claim 1, characterized in that, The step of replacing the corresponding seismic interference trace with the interpolation result includes: The interpolation calculation results are subjected to seismic trace restoration processing to obtain the restoration result; Determine the location of the suppressed seismic interference trace; The recovery result replaces the corresponding seismic interference trace according to the location of the suppressed seismic interference trace.

7. A seismic data noise suppression device, characterized in that, The device includes: The acquisition module is used to acquire seismic interference traces and normal seismic traces; The suppression processing module is used to suppress the seismic interference trace to obtain a suppressed seismic interference trace. The judgment module is used to determine whether the scaling factor in the suppressed seismic interference trace is greater than a preset threshold value; An interpolation processing module is used to interpolate the bad trace using the normal seismic trace to obtain the interpolation processing result. The replacement module is used to replace the corresponding seismic interference trace with the interpolation result.

8. A computer device, comprising a memory, a processor, and a computer program stored in the memory, characterized in that, The processor executes the computer program to implement the steps of the seismic data noise suppression method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by a processor, the computer program implements the steps of the seismic data noise suppression method according to any one of claims 1 to 6.

10. A computer program product comprising a computer program / instructions, characterized in that, When executed by a processor, the computer program implements the steps of the seismic data noise suppression method according to any one of claims 1 to 6.

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