Methods, apparatus, equipment and media for comparative analysis of seismic acquisition data quality

Abstract

This disclosure provides a method, apparatus, equipment, and medium for comparative analysis of seismic acquisition data quality. The method includes: acquiring seismic geological characteristic information corresponding to multiple single-shot seismic acquisition data to be compared and analyzed; dividing the multiple single-shot seismic acquisition data into one or more groups based on the similarity of the seismic geological characteristic information; performing waveform identification on each single-shot seismic acquisition data within each group to determine the signal energy analysis time window covering refracted wave signals and the noise energy analysis time window covering reflected waves from the target layer within each group; calculating the equivalent signal-to-noise ratio (SNR) of a single shot based on the signal data within the aforementioned signal energy analysis time window and the noise energy analysis time window; and performing comparative analysis based on the equivalent SNR of a single shot within the same group to obtain the quality analysis results of the multiple single-shot seismic acquisition data. This method can improve the accuracy of single-shot comparative analysis results and is applicable to low SNR areas or other geological exploration areas.

Description

Technical Field

[0001] This disclosure relates to the field of geophysical exploration technology, and in particular to a method, apparatus, equipment and medium for comparative analysis of the quality of seismic acquisition data. Background Technology

[0002] In the process of seismic exploration, the quality of seismic acquisition data is of great significance for subsequent seismic data processing to obtain geological structures or to conduct oil and gas exploration.

[0003] Seismic raw shot comparison analysis is a key technique for ensuring the effectiveness of seismic data acquisition. In seismic exploration, the signal-to-noise ratio (SNR) is typically defined as the ratio of the average energy of the effective signal to the average energy of the interference, and it is a crucial indicator for raw shot comparison analysis. As seismic exploration progresses, it is gradually extending to more complex areas, with low SNR regions such as loess plateaus, thick gravel deposits in piedmont areas, and large deserts becoming key areas for onshore exploration.

[0004] However, for these low signal-to-noise ratio regions, current single-shot comparative analysis methods generally suffer from the problems of high difficulty in single-shot comparative analysis and inaccurate comparative analysis results. Summary of the Invention

[0005] To solve the above-mentioned technical problems, or at least partially solve them, embodiments of this disclosure provide a method, apparatus, equipment, and medium for comparative analysis of the quality of seismic acquisition data.

[0006] In a first aspect, embodiments of this disclosure provide a method for comparative analysis of the quality of seismic acquisition data. The method includes: acquiring seismic geological characteristic information corresponding to multiple single-shot seismic acquisition data to be compared and analyzed; dividing the multiple single-shot seismic acquisition data into one or more groups based on the similarity of the seismic geological characteristic information; performing waveform identification on each single-shot seismic acquisition data within each group to determine a signal energy analysis window covering refracted wave signals and a noise energy analysis window covering reflected waves from the target layer within each group; calculating the equivalent signal-to-noise ratio (SNR) of a single shot based on the signal data within the signal energy analysis window and the noise energy analysis window; and performing comparative analysis based on the equivalent SNR of a single shot within the same group to obtain the quality analysis results of the multiple single-shot seismic acquisition data.

[0007] According to embodiments of this disclosure, the seismic single-shot acquisition data within the same group use a consistent signal energy analysis time window and a consistent noise energy analysis time window; the consistency includes: the number of channels and time length covered by the aforementioned signal energy analysis time window corresponding to the seismic single-shot acquisition data within the same group are consistent; the number of channels and time length covered by the aforementioned noise energy analysis time window corresponding to the seismic single-shot acquisition data within the same group are consistent.

[0008] According to embodiments of this disclosure, waveform identification is performed on each seismic single-shot acquisition data within each group after grouping, determining the signal energy analysis window covering refracted wave signals and the noise energy analysis window covering target layer reflected waves within each group. This includes: for each seismic single-shot acquisition data within each group, identifying the refracted wave signal region and the target layer reflected wave signal region in the current seismic single-shot acquisition data; identifying target refracted wave signal segments within the refracted wave signal regions whose waveform feature sharpness exceeds the minimum sharpness requirement and whose waveform lateral variation is less than a preset threshold; and selecting the aforementioned segments within a preset statistical channel range to cover the lateral direction. The first time window number of the target refracted wave signal segment is determined, and the first time window length for covering a complete waveform of the target refracted wave signal segment in the longitudinal direction is determined. The signal energy analysis time window is an axial time window defined by the first time window number and the first time window length. The noise energy analysis time window for covering the target layer reflected wave signal region is determined. The noise energy analysis time window is a hyperbolic time window defined by the second time window number and the second time window length. The second time window number is equal to the total number of channels corresponding to a single receiving line, and the second time window length is the second time window length for covering the target layer reflected wave signal region.

[0009] According to embodiments of this disclosure, waveform identification is performed on the seismic single-shot acquisition data within each group after grouping, and the signal energy analysis time window covering refracted wave signals and the noise energy analysis time window covering target layer reflected waves within each group are determined. This includes: receiving first setting data for the signal energy analysis time window and second setting data for the noise energy analysis time window from a user; the first setting data includes a first time window channel number setting value and a first time window length setting value; the second setting data includes a second time window channel number setting value and a second time window length setting value; the first time window channel number setting value is within a preset statistical channel number range; and a defined area is delineated based on the first and second setting data, and the ground within the defined area is analyzed. Waveform identification is performed on the data collected by a single seismic shot to obtain first waveform matching data for the aforementioned signal energy analysis time window and second waveform matching data for the aforementioned noise energy analysis time window. The first waveform matching data is verified based on the minimum sharpness requirements of the waveform features and a preset threshold for the lateral variation of the waveform. The defined area corresponding to the verified first waveform matching data is used as a unified signal energy analysis time window within the same group. The second waveform matching data is verified based on whether it covers the target layer reflected wave signal region. The defined area corresponding to the verified second waveform matching data is used as a unified noise energy analysis time window within the same group.

[0010] According to embodiments of this disclosure, the method further includes: automatically generating a signal energy analysis window when no first waveform matching data passes verification; and automatically generating a noise energy analysis window when no second waveform matching data passes verification. The automatic generation of the signal energy analysis window includes: identifying refracted wave signal regions in the seismic single-shot acquisition data; determining target refracted wave signal segments within the refracted wave signal regions whose waveform feature sharpness exceeds a minimum sharpness requirement and whose lateral waveform variation is less than a preset threshold; selecting a first time window channel number within a preset statistical channel number range to cover the target refracted wave signal segments in the lateral direction; and determining a first time window length for covering a complete waveform of the target refracted wave signal segments in the longitudinal direction. The signal energy analysis window is an axial time window defined by the first time window channel number and the first time window length. The aforementioned automatic generation of noise energy analysis time window includes: identifying the target layer reflected wave signal region in the aforementioned single-shot seismic acquisition data; determining a noise energy analysis time window to cover the aforementioned target layer reflected wave signal region, wherein the noise energy analysis time window is a hyperbolic time window defined by the second time window channel number and the second time window length, wherein the second time window channel number is equal to the total number of channels corresponding to a single receiver line, and the second time window length is the length of the second time window covering the aforementioned target layer reflected wave signal region.

[0011] According to embodiments of this disclosure, the equivalent signal-to-noise ratio (SNR) of a single shot is calculated based on the signal data within the aforementioned signal energy analysis window and the aforementioned noise energy analysis window. This includes: calculating the root mean square amplitude value corresponding to the signal data within the aforementioned signal energy analysis window to obtain the equivalent energy of the refracted wave; calculating the root mean square amplitude value corresponding to the signal data within the aforementioned noise energy analysis window to obtain the equivalent noise energy; and performing a quotient operation between the equivalent energy of the refracted wave and the equivalent noise energy to obtain the equivalent SNR of a single shot.

[0012] According to embodiments of this disclosure, the aforementioned seismic geological characteristic information includes: surface structure information corresponding to the respective locations of the multiple seismic single-shot acquisition data, and target layer reflected wave T0 time information, wherein the T0 time information is the intersection of the reflected wave time-distance curve and the time axis. Based on the similarity of the aforementioned seismic geological characteristic information, the multiple seismic single-shot acquisition data are divided into one or more groups, including: determining a first similarity between the surface structure information corresponding to the multiple seismic single-shot acquisition data; determining a second similarity between the target layer reflected wave T0 time information corresponding to the multiple seismic single-shot acquisition data; grouping seismic single-shot acquisition data with the first similarity below a first threshold and the second similarity below a second threshold into the same group; and grouping seismic single-shot acquisition data with the first similarity above the first threshold or the second similarity above the second threshold into different groups.

[0013] According to embodiments of this disclosure, a comparative analysis is performed based on the equivalent signal-to-noise ratio of a single shot within the same group to obtain the quality analysis results of the aforementioned multiple seismic single-shot acquisition data. This includes: sorting the seismic single-shot acquisition data within the same group according to the equivalent signal-to-noise ratio of a single shot; and performing one or more of the following operations based on the sorted seismic single-shot acquisition data: determining the acquisition parameters corresponding to one or more of the top-ranked seismic single-shot acquisition data as the target acquisition parameters for subsequent construction; or, analyzing and processing the construction quality of one or more of the bottom-ranked seismic single-shot acquisition data based on the sorted seismic single-shot acquisition data to obtain construction quality analysis and recommendation results.

[0014] Secondly, embodiments of this disclosure provide an apparatus for comparative analysis of the quality of seismic acquisition data. The apparatus includes: an information acquisition module, a grouping module, a dual-time-window determination module, a calculation module, and a comparative analysis module. The information acquisition module acquires seismic geological characteristic information corresponding to multiple single-shot seismic acquisition data to be compared and analyzed. The grouping module divides the multiple single-shot seismic acquisition data into one or more groups based on the similarity of the seismic geological characteristic information. The dual-time-window determination module performs waveform identification on each single-shot seismic acquisition data within each group, determining the signal energy analysis time window covering refracted wave signals and the noise energy analysis time window covering reflected waves from the target layer within each group. The calculation module calculates the equivalent signal-to-noise ratio (SNR) of a single shot based on the signal data within the signal energy analysis time window and the noise energy analysis time window. The comparative analysis module performs comparative analysis based on the equivalent SNR of a single shot within the same group to obtain the quality analysis results of the multiple single-shot seismic acquisition data.

[0015] Thirdly, embodiments of this disclosure provide an electronic device. The electronic device includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, communication interface, and memory communicate with each other via the communication bus; the memory stores computer programs; and the processor, when executing the program stored in the memory, implements the method for comparative analysis of seismic acquisition data quality as described above.

[0016] Fourthly, embodiments of this disclosure provide a computer-readable storage medium. The computer-readable storage medium stores a computer program, which, when executed by a processor, implements the method for comparative analysis of seismic acquisition data quality as described above.

[0017] The technical solutions provided in the embodiments of this disclosure have some or all of the following advantages:

[0018] By grouping and evaluating seismic data based on differences in seismic geological conditions at excitation locations, the uniqueness of lateral comparison conditions is improved, eliminating differences in single-shot waveforms caused by variations in geological conditions and ensuring the accuracy of quality analysis results for multiple seismic single-shot acquisitions. A dual-time-window single-shot equivalent signal-to-noise ratio (SNR) partitioning comparison method is employed to compare and analyze the quality of single-shot data. This method utilizes refracted waves to obtain equivalent signal energy, leveraging their stability, immunity to interference, and ease of identification and extraction. This results in purer and more reliable energy, improving the accuracy of SNR estimation and thus ensuring the accuracy of single-shot comparison analysis results. This method eliminates the need for other signal-to-noise separation techniques, directly obtaining the necessary information for SNR estimation, simplifying the data analysis process. The obtained noise includes all noise types, effectively addressing the problem of poor accuracy in seismic data quality analysis in low SNR regions with well-developed correlation noise compared to other methods. Attached Figure Description

[0019] The accompanying drawings, which are incorporated in and form a part of this specification, illustrate embodiments consistent with this disclosure and, together with the description, serve to explain the principles of this disclosure.

[0020] To more clearly illustrate the technical solutions in the embodiments of this disclosure or the prior art, the accompanying drawings used in the description of the embodiments or related technologies will be briefly introduced below. Obviously, those skilled in the art can obtain other drawings based on these drawings without creative effort.

[0021] Figure 1 A flowchart illustrating a method for comparative analysis of seismic acquisition data quality according to an embodiment of the present disclosure is shown schematically.

[0022] Figure 2 A detailed implementation flowchart of step S130 of an embodiment of the present disclosure is shown schematically;

[0023] Figure 3 The diagram illustrates the signal energy analysis time windows of typical seismic single-shot acquisition data selected from (a) the first group and (b) the second group, respectively, according to an embodiment of this disclosure.

[0024] Figure 4 The diagram illustrates a noise energy analysis time window of typical seismic single-shot acquisition data selected from (a) the first group and (b) the second group, respectively, according to an embodiment of this disclosure.

[0025] Figure 5 A detailed implementation flowchart of step S130 of another embodiment of this disclosure is shown schematically;

[0026] Figure 6The diagram illustrates a comparison of single-shot bandpass filtering results of seismic single-shot acquisition data in the second group of embodiments of this disclosure, wherein (a) is the result of single shot 4, (b) is the result of single shot 5, and (c) is the result of single shot 6.

[0027] Figure 7 An apparatus for comparative analysis of seismic acquisition data quality according to an embodiment of the present disclosure is schematically illustrated; and

[0028] Figure 8 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown. Detailed Implementation

[0029] Optimizing acquisition parameters through acquisition method experiments and monitoring construction quality are two crucial foundational tasks for ensuring the quality of seismic acquisition data. The results of raw single-shot comparative analysis are important criteria for judging the quality of construction parameters and assessing whether there are any quality issues in the acquisition process.

[0030] Current methods for single-shot comparative analysis typically involve selecting data at the location of the reflected wave from the target layer using rectangular or axial time windows, and then estimating the signal-to-noise ratio (SNR) using algorithms such as superposition, singular value decomposition (SVD) in the time domain, statistical averaging, correlation, and cross-correlation. Most of these methods assume noise is random, considering the correlated signal as the effective signal. They then utilize the difference in correlation between the effective signal and random interference to calculate the signal and noise energy separately, thereby estimating the SNR.

[0031] However, in actual single-shot systems, not only is there random noise, but also a significant amount of correlated noise. The aforementioned method mistakenly identifies correlated interference in a single shot as valid signal, thus including the energy of the correlated interference in the valid signal calculation, leading to inaccurate signal-to-noise ratio (SNR) estimation results.

[0032] Some methods first use FK filtering to separate correlated interference, then use correlation time-shifting to estimate the energy of the remaining effective signal, and finally estimate the signal-to-noise ratio (SNR) by the ratio of the energy of the effective signal to that of all interference (including correlated and random interference). However, the accuracy of this method is limited by the effectiveness of correlated interference separation. If the correlated noise is not completely separated, the accuracy of the SNR estimation will be greatly reduced, especially for exploration in low SNR areas. The results of single-shot comparison analysis are not accurate enough, particularly in low SNR areas with severe correlated interference, which cannot accurately estimate the SNR and cannot meet the requirements of actual exploration.

[0033] In view of this, embodiments of the present disclosure provide a method for comparative analysis of the quality of seismic acquisition data. By employing a dual-time-window equivalent signal-to-noise ratio (SNR) partitioning comparison method, the quality of single shots can be compared and analyzed. During the analysis process, this method does not require the use of other signal-to-noise separation techniques and directly obtains the necessary information for SNR estimation, simplifying the data analysis process. The obtained noise includes all noise types. Compared with existing methods, it is better adapted to low SNR areas with well-developed related noise and can effectively solve the problem of inaccurate single-shot comparative analysis results in 2D and 3D seismic exploration of low SNR areas on land.

[0034] To make the objectives, technical solutions, and advantages of the embodiments of this disclosure clearer, the technical solutions of 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, not all, of the embodiments of this disclosure. Based on the embodiments of this disclosure, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this disclosure.

[0035] The first exemplary embodiment of this disclosure provides a method for comparative analysis of the quality of seismic acquisition data. This method can be performed by an electronic device with computing capabilities.

[0036] Figure 1 A flowchart illustrating a method for comparative analysis of seismic acquisition data quality according to an embodiment of the present disclosure is shown.

[0037] Reference Figure 1 As shown, the method for comparative analysis of seismic acquisition data quality provided in this embodiment includes the following steps: S110, S120, S130, S140 and S150.

[0038] In step S110, the seismic geological characteristics information corresponding to the multiple seismic single-shot acquisition data to be compared and analyzed is obtained.

[0039] In the embodiments of this disclosure, it is necessary to compare and analyze multiple (≥2) seismic single-shot acquisition data for the same exploration area. In some embodiments, the individual seismic single-shot acquisition data may differ due to variations in acquisition parameters, construction quality, and other human control factors; in other embodiments, the sampling locations corresponding to the aforementioned seismic single-shot acquisition data are located at different locations within the exploration area, and there may also be differences due to lateral variations in the geological structure of the exploration area.

[0040] In the implementation concept of this disclosure, by grouping and evaluating the quality based on the differences in seismic geological conditions (i.e., seismic geological characteristic information) at the excitation location, the uniformity of the horizontal comparison conditions is improved, the differences in single-shot waveforms caused by differences in geological conditions are eliminated, and the accuracy of the results of the quality difference analysis of seismic single-shot acquisition data within the same group is ensured. That is, the results of the quality analysis of multiple seismic single-shot acquisition data are due to human control factors such as acquisition parameters and construction quality, and the advantages and disadvantages of acquisition parameters, construction quality and other factors are analyzed.

[0041] In some embodiments, geophysical data such as surface structure survey results and profiles of previous seismic exploration results in the exploration area are collected and analyzed to obtain seismic geological characteristic information corresponding to multiple seismic single-shot acquisition data that need to be compared and analyzed. The aforementioned seismic geological characteristic information is used to reflect seismic geological conditions, including information such as geological structure and detection characteristics (such as reflection wave characteristics, refraction wave characteristics, etc.) corresponding to each sampling location of the seismic single-shot acquisition data.

[0042] For example, the aforementioned seismic geological characteristics information includes: surface structure information corresponding to the location of each of the above-mentioned single-shot seismic data acquisitions, and T0 time information of the target layer reflection wave, wherein the aforementioned T0 time information is the intersection of the reflection wave time-distance curve and the time axis.

[0043] In step S120, based on the similarity of the above-mentioned seismic geological characteristic information, the above-mentioned multiple seismic single-shot acquisition data are divided into one or more groups.

[0044] According to an embodiment of this disclosure, in step S120 above, the multiple seismic single-shot acquisition data are divided into one or more groups based on the similarity of the seismic geological characteristic information, including: determining a first similarity between the surface structure information corresponding to the multiple seismic single-shot acquisition data; determining a second similarity between the target layer reflected wave T0 time information corresponding to the multiple seismic single-shot acquisition data; grouping the seismic single-shot acquisition data with the first similarity lower than a first threshold and the second similarity lower than a second threshold into the same group; and grouping the seismic single-shot acquisition data with the first similarity greater than the first threshold or the second similarity greater than the second threshold into different groups.

[0045] Because surface and subsurface geological conditions within a seismic exploration area typically differ laterally, these differences can lead to variations in the quality of single-shot acquisitions at different locations. The primary purpose of single-shot comparative analysis is to determine the quality of construction parameters and monitor the quality of data acquisition. Only comparative analysis results obtained after excluding the influence of seismic geological conditions on single-shot quality can better guide the optimization of construction parameters and the evaluation of construction quality issues. Based on the similarity of seismic geological characteristics, multiple single-shot acquisition data sets to be analyzed and compared can be divided into one or more groups. This ensures that the seismic geological conditions at all single-shot acquisition locations within a group are similar, effectively avoiding the influence of seismic geological conditions on single-shot quality, improving the singularity of comparative factors, and thus enhancing the accuracy of the comparative analysis results. In other words, by grouping highly similar single-shot acquisition data sets according to the similarity of the aforementioned seismic geological characteristics, the seismic geological characteristics corresponding to the single-shot acquisition data within the same group are considered consistent. Only by analyzing the differences in the single-shot acquisition data within the group is it possible to determine the quality of human-controlled factors such as acquisition parameters and construction quality.

[0046] In step S130, waveform identification is performed on the single-shot seismic data acquired in each group after grouping, and the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the reflected wave of the target layer are determined in each group.

[0047] Seismic waves generated by an earthquake propagate upwards directly to the ground, forming direct waves, surface waves, and scattered waves. Others are reflected and refracted downwards through underground geological interfaces and return to the ground, forming refracted waves and reflected waves.

[0048] Refracted waves and reflected waves are both seismic waves that propagate downwards after being excited by an earthquake and then return to the surface after encountering an underground interface. The energy relationship between them can be expressed as:

[0049] E R =K×E S (1)

[0050] Among them, E R E represents the energy of the refracted wave. S The energy of the reflected wave is represented by K, which is the energy relationship coefficient between the refracted and reflected waves and is related to the seismic geological conditions.

[0051] According to the definition of signal-to-noise ratio, noise energy is expressed as E. N The signal-to-noise ratio (SNR) estimated when the reflected wave energy is used as the signal energy is:

[0052] SN=E S / E N (2)

[0053] Wherein, SN represents the signal-to-noise ratio estimated when the reflected wave energy is used as the signal energy.

[0054] The signal-to-noise ratio (hereinafter referred to as the equivalent signal-to-noise ratio) estimated when using the refracted wave energy as the signal energy is:

[0055] ESN=E R / E N (3)

[0056] Wherein, ESN represents the equivalent signal-to-noise ratio estimated when the refracted wave energy is used as the signal energy.

[0057] According to the previous formula (1), the equivalent signal-to-noise ratio and the signal-to-noise ratio have the following relationship:

[0058] ESN = K × SN. (4)

[0059] When performing single-gun comparisons, if the total number of guns to be compared is n, and the signal-to-noise ratio of each gun is SN... i Let i = 1, 2, 3...n, and the equivalent signal-to-noise ratio per shot be ESN. i i = 1, 2, 3...n, or, the equivalent signal-to-noise ratio per shot can be expressed as K × SN i , i = 1, 2, 3...n.

[0060] After grouping according to seismic geological conditions, the energy relationship coefficient K between the refracted and reflected waves of each single shot within the group is a fixed value. Using SN... i To compare quality and utilize K×SN i When comparing the quality of shots between shots, the ranking results are the same, which means that the equivalent signal-to-noise ratio and the signal-to-noise ratio are equally effective in measuring the differences between individual shots.

[0061] In seismic single-shot records, refracted waves appear as the first wave, which has advantages such as stability, immunity to interference from other sources, and ease of identification and separation. Its energy value can be accurately obtained without relying on other signal-to-noise separation techniques. Using its energy to estimate the signal-to-noise ratio can yield more realistic and reliable results, which is beneficial to improving the accuracy of single-shot comparative analysis results.

[0062] Therefore, based on the above analysis and considerations, in the embodiments of this disclosure, by using the refracted wave signal as the signal analysis source and the analysis time window covering the refracted wave signal as the signal energy analysis time window, the advantages of refracted waves being stable, unaffected by interference, and easy to identify and extract are utilized, making the obtained energy purer and more reliable, improving the accuracy of signal-to-noise ratio estimation, and thus ensuring the accuracy of single-shot comparative analysis results.

[0063] According to embodiments of this disclosure, the seismic single-shot acquisition data within the same group use a consistent signal energy analysis time window and a consistent noise energy analysis time window; the consistency includes: the number of channels and time length covered by the aforementioned signal energy analysis time window corresponding to the seismic single-shot acquisition data within the same group are consistent; the number of channels and time length covered by the aforementioned noise energy analysis time window corresponding to the seismic single-shot acquisition data within the same group are consistent.

[0064] In step S140, the equivalent signal-to-noise ratio of a single gun is calculated based on the signal energy analysis time window and the signal data within the noise energy analysis time window.

[0065] By calculating the signal data within the signal energy analysis window and the noise energy analysis window, the equivalent energy of the signal within the signal energy analysis window (which corresponds to the equivalent energy of the refracted wave) is obtained, and the equivalent energy of the noise within the noise energy analysis window is obtained. The equivalent energy of the signal and the equivalent energy of the noise are then divided, and the equivalent signal-to-noise ratio of a single shot is obtained by referring to the formula (3) above.

[0066] For example, in one embodiment, the equivalent signal-to-noise ratio (SNR) of a single shot is calculated based on the signal data within the aforementioned signal energy analysis window and the aforementioned noise energy analysis window. This includes: calculating the root mean square amplitude value corresponding to the signal data within the aforementioned signal energy analysis window to obtain the equivalent energy of the refracted wave; calculating the root mean square amplitude value corresponding to the signal data within the aforementioned noise energy analysis window to obtain the equivalent noise energy; and performing a quotient operation between the equivalent energy of the refracted wave and the equivalent noise energy to obtain the equivalent SNR of a single shot.

[0067] For example, the equivalent energy of a refracted wave can be expressed as the following expression:

[0068]

[0069] Among them, E Rrms The refracted wave represents the equivalent energy, and its value is the root mean square amplitude value corresponding to the signal data within the signal energy analysis window; P represents the total number of sampling points within the signal energy analysis window; A i This represents the amplitude value of the i-th sampling point within the time window for signal energy analysis.

[0070] The noise equivalent energy can be expressed as the following expression:

[0071]

[0072] Among them, E Nrms The noise equivalent energy is represented by the root mean square amplitude value corresponding to the signal data within the noise energy analysis window; Q represents the total number of sampling points within the signal energy analysis window; A jThis represents the amplitude value of the j-th sampling point within the time window for signal energy analysis.

[0073] In step S150, a comparative analysis is performed based on the equivalent signal-to-noise ratio of a single shot within the same group to obtain the quality analysis results of the aforementioned multiple seismic single-shot acquisition data.

[0074] By comparing and analyzing the equivalent signal-to-noise ratios of multiple seismic single-shot acquisition data within the same group, we can obtain the relative levels of the equivalent signal-to-noise ratios of each single shot, and thus the relative quality of the multiple seismic single-shot acquisition data.

[0075] In some implementation scenarios, the relative quality of acquisition parameters and construction quality of each seismic single-shot acquisition data can be determined based on the relative level of the equivalent signal-to-noise ratio of a single shot or the relative quality of the seismic single-shot acquisition data.

[0076] For example, according to an embodiment of this disclosure, in step S150 above, a comparative analysis is performed based on the equivalent signal-to-noise ratio of a single shot within the same group to obtain the quality analysis results of the multiple seismic single-shot acquisition data, including:

[0077] For seismic single-shot acquisition data within the same group, sort them according to the equivalent signal-to-noise ratio of the single shot;

[0078] Based on the sorted seismic single-shot acquisition data, perform one or more of the following operations:

[0079] The acquisition parameters corresponding to one or more of the top-ranked seismic single-row acquisition data are determined as the target acquisition parameters for subsequent construction; or...

[0080] Based on the sorted seismic single-row acquisition data, the construction quality of one or more seismic single-row acquisition data at the bottom of the sort is analyzed and processed to obtain construction quality analysis and recommendations.

[0081] In the embodiments including steps S110 to S150 above, the quality evaluation is grouped according to the differences in seismic geological conditions at the excitation location, which improves the uniformity of the lateral comparison conditions, eliminates the difference factors of single-shot waveforms caused by differences in geological conditions, and ensures the accuracy of the results of quality analysis of multiple seismic single-shot acquisition data; the method of comparing and analyzing the quality of single shots by using dual-time-window single-shot equivalent signal-to-noise ratio partitioning comparison is adopted. Among them, refracted waves are used to obtain equivalent signal energy, which takes advantage of the stability, lack of interference, and ease of identification and extraction of refracted waves, making the obtained energy purer and more reliable, improving the accuracy of signal-to-noise ratio estimation, and thus ensuring the accuracy of single-shot comparison analysis results; the above method does not require the use of other signal-to-noise separation techniques, directly obtains the necessary information for signal-to-noise ratio estimation, simplifies the data analysis process, and the obtained noise includes all noise types. Compared with the methods in the correlation techniques, it can effectively solve the problem of poor accuracy of seismic data quality analysis corresponding to low signal-to-noise ratio areas with developed correlation noise.

[0082] It should be noted that although the above methods can effectively solve the problem of poor accuracy in seismic data quality analysis in low signal-to-noise ratio areas in related technologies, it does not mean that the application scenarios of the above methods are limited to low signal-to-noise ratio areas. The above methods are applicable to exploration scenarios of any geological structure.

[0083] In the embodiments of this disclosure, two implementation methods for determining the signal energy analysis window and the noise energy analysis window are proposed. One implementation method is to automatically select the window by the electronic device based on preset characteristics and waveform recognition. The other implementation method is to determine the window by human-computer interaction. The electronic device receives the user's set parameters for the window, judges the rationality of the window based on preset conditions, and selects a reasonable window as the analysis window. If the human-set parameters are unreasonable and a reasonable window cannot be obtained, an alternative solution is executed: the electronic device automatically selects the window by waveform recognition based on preset characteristics, thus ensuring that a reasonable and relatively accurate analysis window can be obtained. In the two embodiments described above, the first method requires pre-determining and optimizing preset features to ensure the accuracy of the waveform automatic identification and selection of the time window by the electronic device. This method has the advantages of being efficient and convenient for automatic selection of the time window. The second method provides a manual option for setting the time window, which has a user-friendly interface for some technicians and is convenient for experienced technicians to set the analysis time window. At the same time, for some scenarios where the time window settings are not perfect, the corresponding matching of signal data can be performed through the setting parameters of the time window to obtain a reasonable and accurate analysis time window as much as possible. When no matching result can be obtained, the analysis time window is automatically picked up according to preset features. While being compatible with the flexibility of user settings, it also effectively ensures the reasonable availability and accuracy of the analysis time window.

[0084] The following reference Figures 2-5 The two implementation methods described above will be introduced separately.

[0085] Figure 2 A detailed implementation flowchart of step S130 of an embodiment of the present disclosure is shown schematically.

[0086] According to one embodiment of this disclosure, referring to Figure 2 As shown, in step S130 above, waveform identification is performed on the single-shot seismic data acquired in each group after grouping, and the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the reflected wave of the target layer in each group are determined. This includes the following steps: S210, S220, S230 and S240.

[0087] In step S210, for each seismic single-shot acquisition data in the above groups, the refracted wave signal region and the target layer reflected wave signal region in the current seismic single-shot acquisition data are identified.

[0088] In step S220, a target refracted wave signal segment is determined in the above-mentioned refracted wave signal region where the waveform feature sharpness exceeds the minimum sharpness requirement and the waveform lateral change is less than a preset threshold.

[0089] The aforementioned minimum resolution requirement is used to define the minimum resolution of the bands that can be used for signal analysis sources, which facilitates waveform identification and ensures the accuracy of energy estimation within the selected analysis window.

[0090] The aforementioned waveform characteristics include the waveform characteristics of the first arrival signal and the refracted wave. For example, the target refracted wave signal segment is defined as the segment in the refracted wave signal region where the waveform characteristics of the first arrival signal (the location where the signal energy in the seismic record begins to appear is defined as the first arrival signal) and the refracted wave are relatively clear (judged using the minimum resolution requirement) and laterally stable (limited by lateral variation being less than a preset threshold).

[0091] In step S230, within a preset range of statistical channels, a first time window channel number is selected to cover the target refracted wave signal segment in the lateral direction, and a first time window length is determined to cover a complete waveform of the target refracted wave signal segment in the longitudinal direction. The signal energy analysis time window is an axial time window defined by the first time window channel number and the first time window length.

[0092] The preset statistical channel count range is, for example, 10 to 20 channels, and the specific range is set reasonably according to the waveform characteristics of different exploration areas. This preset statistical channel count serves two purposes: firstly, it ensures that the selected channel count range has a statistical effect, avoiding excessive deviation in signal data due to an insufficient number, thus failing to reflect the overall trend; secondly, it avoids selecting too many channels, which would include signal data with significant deviations in the lateral range, leading to lateral waveform instability and inaccurate calculations of the equivalent signal-to-noise ratio per shot. By limiting the number of channels in the first time window to the preset statistical channel count range, both a certain statistical effect and lateral stability of the waveform within the time window are ensured.

[0093] Figure 3 The diagram illustrates a typical signal energy analysis time window of seismic single-shot acquisition data selected from (a) the first group and (b) the second group, respectively, according to an embodiment of this disclosure.

[0094] For example, in step S120, multiple seismic single-shot acquisition data are divided into two groups, and the signal energy analysis time windows selected from these two groups are displayed in... Figure 3 In (a) and (b), the field file ID (FFID) for the seismic single-shot acquisition data in the first group is 59, and the FFID for the seismic single-shot acquisition data in the second group is 100. (Refer to...) Figure 3 In Figures (a) and (b), the signal energy analysis window 310 and the second signal energy analysis window 320 are shown respectively. The first signal energy analysis window 310 is the signal energy analysis window corresponding to the single-shot seismic acquisition data of file 59, and the second signal energy analysis window 320 is the signal energy analysis window corresponding to the single-shot seismic acquisition data of file 100. The above-mentioned signal energy analysis window 310 and the second signal energy analysis window 320 are marked with three border lines. The central axis represents the central axis of the window, and the range enclosed by the upper and lower border lines represents the range corresponding to the signal energy analysis window.

[0095] By employing an axial time window, a segment of refracted wave with a clear first arrival, distinct wave group characteristics, and minimal lateral variation is selected as the source data for signal energy analysis. The length of the first time window contains one complete waveform. For example, referring to... Figure 3 The first time window length shown in (a) and (b) is 100ms.

[0096] The number of channels in the first time window should ideally be between 10 and 20. This ensures both a certain statistical effect and lateral stability of the waveforms within each channel within the time window; for example, in Figure 3 In example (a), with a first time window of 14 channels, the covered channel number (CHAN) ranges from 200 to 213. Figure 3In example (b), the first time window has 19 channels, covering the channel number range of 128-146.

[0097] In step S240, a noise energy analysis time window for covering the target layer reflected wave signal region is determined. The noise energy analysis time window is a hyperbolic time window defined by the second time window channel number and the second time window length. The second time window channel number is equal to the total number of channels corresponding to a single receiving line, and the second time window length is the second time window length for covering the target layer reflected wave signal region.

[0098] Figure 4 The diagram illustrates a noise energy analysis time window of typical seismic single-shot acquisition data selected from (a) the first group and (b) the second group, respectively, according to an embodiment of this disclosure.

[0099] In step S120, multiple seismic single-shot acquisition data are divided into two groups, and the noise energy analysis time windows selected from these two groups are displayed. Figure 4 In (a) and (b), the field file ID (FFID) for the seismic single-shot acquisition data in the first group is 59, and the FFID for the seismic single-shot acquisition data in the second group is 100. (Refer to...) Figure 4 As shown in (a) and (b), based on the obtained T0 time information of the target layer reflected wave, a hyperbolic time window can be used to pick out noise energy analysis source data in the seismic single-shot acquisition data. The length of the second time window in the vertical direction is based on the principle of covering the reflected wave of the target layer segment. Generally, it is selected with the T0 time of the target layer reflected wave as the central axis, varying up and down by 500ms to 1000ms as the time window range. The number of channels in the second time window is equal to the total number of channels of a single receiver line. For example, in Figure 4 The first noise energy analysis window 410, shown in (a), is the noise energy analysis window corresponding to the seismic single-shot acquisition data of file 59. Figure 4 The second noise energy analysis window 420 shown in Figure (b) is the noise energy analysis window corresponding to the single-shot seismic acquisition data of file 100. Both the first noise energy analysis window 410 and the second noise energy analysis window 420 are hyperbolic windows. The target layer reflection wave T0 time corresponding to the central axis of the first noise energy analysis window 410 and the second noise energy analysis window 420 is 3500ms, and the corresponding two border lines are 3000ms and 4000ms.

[0100] In embodiments including steps S210 to S240 above, the electronic device automatically identifies and selects the time window for waveform recognition. This requires pre-determining and optimizing preset features to ensure the accuracy of the electronic device in automatically identifying and selecting the time window for waveform recognition. This method has the advantages of being efficient and convenient for automatically selecting the time window.

[0101] Figure 5 A detailed implementation flowchart of step S130 of another embodiment of this disclosure is shown schematically.

[0102] According to another embodiment of this disclosure, referring to Figure 5 As shown, in step S130 above, waveform identification is performed on the single-shot seismic data acquired in each group after grouping, and the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the reflected wave of the target layer in each group are determined. This includes the following steps: S510, S520, S531, S541a, S532 and S542a.

[0103] In step S510, the user receives first setting data for the signal energy analysis window and second setting data for the noise energy analysis window.

[0104] The first set data mentioned above includes a first time window channel number setting value and a first time window length setting value. The second set data mentioned above includes a second time window channel number setting value and a second time window length setting value. The first time window channel number setting value is within the preset statistical channel number range.

[0105] In step S520, the defined area is divided according to the first set data and the second set data, and the waveform identification is performed on the seismic single-shot acquisition data within the defined area to obtain the first waveform matching data and the second waveform matching data for the signal energy analysis time window.

[0106] Based on the user's settings for the signal energy analysis window and noise energy analysis window, one or more defined regions can be obtained from the seismic single-shot acquisition data. By identifying the waveforms within these one or more defined regions, the data containing refracted wave waveforms within the defined regions are determined as the first waveform matching data, and the data containing reflected wave waveforms within the defined regions are determined as the second waveform matching data.

[0107] In step S531, the first waveform matching data is verified according to the minimum clarity requirement of the waveform features and the preset threshold for the lateral variation of the waveform.

[0108] The aforementioned minimum resolution requirement is used to define the minimum resolution of the bands that can be used for signal analysis sources, which facilitates waveform identification and ensures the accuracy of energy estimation within the selected analysis window.

[0109] The aforementioned waveform characteristics include the waveform characteristics of the first arrival signal and the refracted wave. For example, the target refracted wave signal segment is defined as the segment in the refracted wave signal region where the waveform characteristics of the first arrival signal (the location where the signal energy in the seismic record begins to appear is defined as the first arrival signal) and the refracted wave are relatively clear (judged using the minimum resolution requirement) and laterally stable (limited by lateral variation being less than a preset threshold).

[0110] If the clarity requirement of the first waveform matching data exceeds the minimum clarity requirement and the horizontal change of the waveform is less than the preset threshold, the first waveform matching data is considered to have passed the verification.

[0111] In step S541a, the defined region corresponding to the first waveform matching data that has passed the verification is used as the unified signal energy analysis time window within the same group.

[0112] In step S532, the second waveform matching data is verified based on whether the second waveform matching data covers the data of the target layer reflected wave signal region.

[0113] In one embodiment, the target layer reflected wave signal region can be determined by acquiring the target layer reflected wave T0 time information, and then time window verification can be performed based on whether the second waveform matching data covers the data of the target layer reflected wave signal region. If the second waveform matching data covers the data of the target layer reflected wave signal region, the second waveform matching data verification is considered successful.

[0114] In step S542a, the defined region corresponding to the verified second waveform matching data is used as the unified noise energy analysis window within the same group.

[0115] In some scenarios, if the user-defined parameters are reasonable, steps S541a and S542a can usually be executed, such as... Figure 5 The diagram is shown below, with a single dotted line indicating the block.

[0116] In other scenarios, if the user's parameters are set incorrectly, causing waveform matching data across one or more defined regions to fail verification, then... (Refer to...) Figure 5 The block diagram shown in the double-dotted line diagram includes, in addition to S510, S520, S531 and S532, S541b and S542b in the above-mentioned step S130.

[0117] It is understandable that, for a set of set data, the above step S130 includes: S510, S520, S531, S541a, S532 and S542a, or includes S510, S520, S531, S541b, S532 and S542b. For the execution process of multiple sets of set data, there may be cases where both S541a and S541b, and both S542a and S542b are present.

[0118] In step S541b, if there is no first waveform matching data that has passed verification, a signal energy analysis time window is automatically generated.

[0119] In some embodiments, steps S541b and S542b described above can be implemented by steps S410 to S440 as described in the above embodiments.

[0120] For example, the automatically generated signal energy analysis window mentioned above includes:

[0121] Identify the refracted wave signal regions in the above-mentioned single-shot seismic data;

[0122] In the aforementioned refracted wave signal region, a target refracted wave signal segment is identified where the waveform feature sharpness exceeds the minimum sharpness requirement and the lateral waveform variation is less than a preset threshold.

[0123] Within a preset range of statistical channels, a first time window channel number is selected to cover the target refracted wave signal segment in the lateral direction, and a first time window length is determined to cover a complete waveform of the target refracted wave signal segment in the longitudinal direction. The signal energy analysis time window is an axis-bound time window defined by the first time window channel number and the first time window length.

[0124] In step S542b, if there is no verified second waveform matching data, a noise energy analysis window is automatically generated.

[0125] For example, the automatically generated noise energy analysis window mentioned above includes:

[0126] Identify the target layer reflected wave signal region in the above-mentioned single-shot seismic data;

[0127] A noise energy analysis time window is determined for covering the reflected wave signal region of the target layer. The noise energy analysis time window is a hyperbolic time window defined by the number of second time window channels and the length of the second time window. The number of second time window channels is equal to the total number of channels corresponding to a single receiving line, and the length of the second time window is the length of the second time window covering the reflected wave signal region of the target layer.

[0128] In embodiments including steps {S510, S520, S531, S532, S541a, S542a} or {S510, S520, S531, S532, S541b, S542b}, a human-computer interaction method is used to determine the time window. The electronic device receives the user's set parameters for the time window, judges the rationality of the time window based on preset conditions, and selects a reasonable time window as the analysis time window. If the human-set parameters are unreasonable and a reasonable time window cannot be obtained, an alternative solution is executed: the electronic device automatically identifies the waveform and selects the time window according to preset characteristics, ultimately ensuring that a reasonable and relatively accurate analysis time window can be obtained. This solution offers the option to manually set the time window, providing a user-friendly interface for experienced technicians and facilitating the configuration of analysis windows. Furthermore, for scenarios where time window settings are incomplete, it allows for matching and selection of corresponding signal data through the time window parameters, aiming to obtain a reasonable and accurate analysis window. In cases where a match cannot be found, it automatically selects an analysis window based on preset characteristics. This approach combines the flexibility of user settings with the effective guarantee of the reasonable availability and accuracy of the analysis window.

[0129] To verify the effectiveness of the method provided in this disclosure, in a real-world scenario in the Kedong Loess Plateau region of the Tarim Basin, where the surface is covered by a thick layer of loess, the original seismic single-shot data contains a large amount of high-energy surface waves, refracted and multiple-refracted waves, near-surface scattered waves, and other related noise. The reflected waves are completely submerged under the noise, resulting in an extremely low signal-to-noise ratio for the original single-shot data. By comparing and analyzing the data acquired by multiple seismic single-shot data with different excitation parameters in the aforementioned region using the method provided in this disclosure, objective and accurate evaluation results were obtained.

[0130] The specific implementation process is as follows:

[0131] Step 1: Collect data to obtain information on the seismic geological conditions at the single-shot firing locations. Collect micrologging data and previously acquired 2D profiles from the locations of the six single shots. Analysis revealed that the low-velocity layer thickness at shot points 1-3 was approximately 125m, and the T0 time of the target layer reflection wave was 3.5s. The low-velocity layer thickness at shot points 4-6 was approximately 285m, and the T0 time of the target layer reflection wave was also 3.5s.

[0132] Step 2: Group the shots to be analyzed according to the seismic geological conditions at the excitation locations. Using the surface structure and target layer reflection wave T0 time information obtained from the six single shot excitation locations, the shot points are divided into groups based on the principle of similar surface structure characteristics and similar target layer reflection wave T0 times, resulting in two groups: shot points 1-3 are assigned to group 1, and shot points 4-6 are assigned to group 2.

[0133] Step 3: Determine the signal energy analysis time window. Analyze the first group of single shots, identify the refracted waves of the left and right branches. Based on the lateral variation characteristics of the refracted wave waveform, select a segment of refracted waves with a length of 100ms along the axis in channels 200-213. This segment should have a crisp first arrival (clear) waveform, clear waveform characteristics, and minimal lateral variation as the source data for signal energy analysis. Refer to... Figure 3 As shown in (a). Analyzing the second group of single shots, the refracted waves of the left and right arms were identified. Based on the lateral variation characteristics of the refracted wave waveforms, a segment of refracted waves with a 100ms along-axis time window was selected from channels 128-146. This segment exhibited a crisp (clear) first arrival of the wave group, clear wave group characteristics, and minimal lateral variation, serving as the source data for signal energy analysis. Figure 3 As shown in (b).

[0134] Step 4: Determine the noise energy analysis time window. Based on the obtained target layer reflection T0 time, use a hyperbolic time window to pick up noise energy analysis source data on the first group of single shots. The time window length is 1000ms, and the center point time of the time window is the same as the T0 time, which is 3500ms. Figure 4 As shown in (a); on the second group of single shots, a hyperbolic time window was used to pick up noise energy analysis source data. The time window length was 1000 ms, and the time of the center point of the time window was the same as the time T0, which was 3500 ms. Figure 4 As shown in (b).

[0135] Step 5: Calculate the root mean square amplitude (RMS) of the signal data within the selected time window. Using the signal data within the signal energy analysis time window determined in Step 3, calculate the RMS amplitude of the signal to obtain the equivalent energy of the refracted wave (i.e., the equivalent signal energy). Using the signal data within the noise energy analysis time window determined in Step 4, calculate the RMS amplitude of the noise to obtain the equivalent noise energy. Then, divide the equivalent signal energy by the equivalent noise energy to obtain the equivalent signal-to-noise ratio (SNR) per shot.

[0136] Table 1 below lists the equivalent signal energy, noise energy, and equivalent signal-to-noise ratio of each individual gun within the two groups.

[0137]

[0138] Step 6: Compare the calculated equivalent signal-to-noise ratio values ​​of a single shot within the group. The order of single shot quality from highest to lowest in Group 1 is 3, 2, and 1. The order of single shot quality from highest to lowest in Group 2 is 6, 5, and 4.

[0139] Figure 6 The diagram illustrates a comparison of single-shot bandpass filtering results of seismic single-shot acquisition data in the second group of embodiments of this disclosure, wherein (a) is the result of single shot 4, (b) is the result of single shot 5, and (c) is the result of single shot 6.

[0140] Reference Figure 6 As shown in (a) to (c), qualitative analysis of the bandpass filtering results of single shots 4-6 reveals that shot 6 exhibits the highest continuity of reflected wave, followed by shot 5, with shot 4 showing the worst continuity. This is consistent with the quality results of single shots 4-6 obtained using the method provided in this embodiment (the order of single shot quality from highest to lowest is shot 6, 5, and 4). Therefore, the order of single shot quality obtained using the method provided in this embodiment is consistent with the findings of the qualitative analysis, confirming the accuracy of the method provided in this embodiment.

[0141] A second exemplary embodiment of this disclosure provides an apparatus for comparative analysis of the quality of seismic acquisition data.

[0142] Figure 7 An apparatus for comparing and analyzing the quality of seismic acquisition data according to an embodiment of the present disclosure is illustrated schematically.

[0143] Reference Figure 7 As shown, the seismic acquisition data quality comparison and analysis apparatus 700 provided in this embodiment includes: an information acquisition module 701, a grouping module 702, a dual time window determination module 703, a calculation module 704, and a comparison and analysis module 705.

[0144] The aforementioned information acquisition module 701 is used to acquire seismic geological characteristic information corresponding to multiple seismic single-shot acquisition data to be compared and analyzed.

[0145] The aforementioned grouping module 702 is used to divide the aforementioned multiple seismic single-shot acquisition data into one or more groups based on the similarity of the aforementioned seismic geological characteristic information.

[0146] The aforementioned dual-time-window determination module 703 is used to identify the waveform of each seismic single-shot acquisition data in each group after grouping, and to determine the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the target layer reflected wave in each group.

[0147] The aforementioned calculation module 704 is used to calculate the equivalent signal-to-noise ratio of a single shot based on the signal energy analysis time window and the signal data within the aforementioned noise energy analysis time window.

[0148] The aforementioned comparative analysis module 705 is used to perform comparative analysis based on the equivalent signal-to-noise ratio of a single shot within the same group, and to obtain the quality analysis results of the aforementioned multiple seismic single-shot acquisition data.

[0149] The specific implementation details of each of the above modules, or the implementation steps that may be further included, can be referred to the description of the first embodiment, and will not be repeated here.

[0150] Any plurality of the functional modules included in the aforementioned device 700 may be combined into one module, or any one of the modules may be split into multiple modules. Alternatively, at least a portion of the functionality of one or more of these modules may be combined with at least a portion of the functionality of other modules and implemented in one module. At least one of the functional modules included in the aforementioned device 700 may be at least partially implemented as hardware circuitry, such as a Field Programmable Gate Array (FPGA), a Programmable Logic Array (PLA), a System-on-Chip, a System-on-Substrate, a System-on-Package, an Application-Specific Integrated Circuit (ASIC), or implemented in hardware or firmware by any other reasonable means of integrating or packaging circuitry, or implemented in software, hardware, or firmware, or in any appropriate combination of any of these three implementation methods. Alternatively, at least one of the functional modules included in the aforementioned device 700 may be at least partially implemented as a computer program module, which, when run, can perform corresponding functions.

[0151] A third exemplary embodiment of this disclosure provides an electronic device.

[0152] Figure 8 A schematic block diagram of an electronic device provided in an embodiment of the present disclosure is shown.

[0153] Reference Figure 8 As shown, the electronic device 800 provided in this embodiment includes a processor 801, a communication interface 802, a memory 803, and a communication bus 804. The processor 801, the communication interface 802, and the memory 803 communicate with each other through the communication bus 804. The memory 803 is used to store computer programs. When the processor 801 executes the program stored in the memory, it implements the method for comparing and analyzing the quality of seismic acquisition data as described above.

[0154] A fourth exemplary embodiment of this disclosure also provides a computer-readable storage medium. The computer-readable storage medium stores a computer program that, when executed by a processor, implements the method for comparative analysis of seismic acquisition data quality as described above.

[0155] The computer-readable storage medium may be included in the device / apparatus described in the above embodiments; or it may exist independently and not assembled into the device / apparatus. The computer-readable storage medium carries one or more programs that, when executed, implement the method according to the embodiments of this disclosure.

[0156] According to embodiments of this disclosure, the computer-readable storage medium can be a non-volatile computer-readable storage medium, such as including, but not limited to: portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof. In this disclosure, the computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

[0157] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, 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 limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0158] The above description is merely a specific embodiment of this disclosure, enabling those skilled in the art to understand or implement it. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the general principles defined herein may be implemented in other embodiments without departing from the spirit or scope of this disclosure. Therefore, this disclosure is not to be limited to the embodiments shown herein, but is to be accorded the widest scope consistent with the principles and novel features claimed herein.

Claims

1. A method for comparative analysis of the quality of seismic acquisition data, characterized in that, include: Obtain seismic geological characteristic information corresponding to multiple single-shot seismic acquisition data to be compared and analyzed; The seismic geological characteristic information includes: surface structure information corresponding to the location of each of the multiple seismic single-shot acquisition data, and T0 time information of the target layer reflected wave, wherein the T0 time information is the intersection of the reflected wave time-distance curve and the time axis; Based on the similarity of the earthquake geological characteristic information, the multiple seismic single-shot acquisition data are divided into one or more groups, including: determining a first similarity between the surface structure information corresponding to the multiple seismic single-shot acquisition data; determining a second similarity between the target layer reflected wave T0 time information corresponding to the multiple seismic single-shot acquisition data; grouping the seismic single-shot acquisition data with the first similarity below a first threshold and the second similarity below a second threshold into the same group; and grouping the seismic single-shot acquisition data with the first similarity above the first threshold or the second similarity above the second threshold into different groups. Waveform identification was performed on the single-shot seismic data within each group after grouping, and the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the reflected wave of the target layer were determined within each group; The equivalent signal-to-noise ratio of a single shot is calculated based on the signal data within the signal energy analysis window and the noise energy analysis window. The quality analysis results of the multiple seismic single-shot acquisition data are obtained by comparing and analyzing the equivalent signal-to-noise ratio of single shots within the same group.

2. The method according to claim 1, characterized in that, The same signal energy analysis time window and the same noise energy analysis time window were used for all single-shot seismic data within the same group; The consistency includes: The number of channels and the duration of the signal energy analysis window covered by each seismic single-shot acquisition number within the same group are consistent; The number of channels and the duration of the noise energy analysis window are consistent for each seismic single-shot acquisition number within the same group.

3. The method according to claim 1, characterized in that, Waveform identification was performed on the single-shot seismic data within each group after grouping to determine the signal energy analysis window covering refracted wave signals and the noise energy analysis window covering reflected waves from the target layer within each group, including: For each seismic single-shot acquisition data in each group, identify the refracted wave signal region and the target layer reflected wave signal region in the current seismic single-shot acquisition data; In the refracted wave signal region, a target refracted wave signal segment is identified where the waveform feature sharpness exceeds the minimum sharpness requirement and the lateral waveform variation is less than a preset threshold. Within a preset range of statistical channels, a first time window channel number is selected to cover the target refracted wave signal segment in the lateral direction, and a first time window length is determined to cover a complete waveform of the target refracted wave signal segment in the longitudinal direction. The signal energy analysis time window is an axial time window defined by the first time window channel number and the first time window length. A noise energy analysis time window is determined for covering the reflected wave signal region of the target layer. The noise energy analysis time window is a hyperbolic time window defined by a second time window channel number and a second time window length. The second time window channel number is equal to the total number of channels corresponding to a single receiving line, and the second time window length is the length of the second time window covering the reflected wave signal region of the target layer.

4. The method according to claim 1, characterized in that, Waveform identification was performed on the single-shot seismic data within each group after grouping to determine the signal energy analysis window covering refracted wave signals and the noise energy analysis window covering reflected waves from the target layer within each group, including: The system receives first setting data for the signal energy analysis time window and second setting data for the noise energy analysis time window from the user; the first setting data includes a first time window channel number setting value and a first time window length setting value; the second setting data includes a second time window channel number setting value and a second time window length setting value; the first time window channel number setting value is within a preset statistical channel number range; The region is defined based on the first set data and the second set data. Waveform identification is performed on the seismic single-shot acquisition data within the defined region to obtain the first waveform matching data and the second waveform matching data for the signal energy analysis time window. The first waveform matching data is verified based on the minimum clarity requirement of the waveform features and the preset threshold for the lateral variation of the waveform. The defined region corresponding to the first waveform matching data that passes the verification is used as the unified signal energy analysis time window within the same group; The second waveform matching data is verified based on whether it covers the data of the target layer reflected wave signal region. The defined region corresponding to the second waveform matching data that passed the verification was used as the unified noise energy analysis time window within the same group.

5. The method according to claim 4, characterized in that, Also includes: In the absence of first waveform matching data that has passed verification, a signal energy analysis time window is automatically generated; In the absence of valid second waveform matching data, a noise energy analysis window is automatically generated. The automatically generated signal energy analysis window includes: Identify the refracted wave signal region in the earthquake single-shot acquisition data; In the refracted wave signal region, a target refracted wave signal segment is identified where the waveform feature sharpness exceeds the minimum sharpness requirement and the lateral waveform variation is less than a preset threshold. Within a preset range of statistical channels, a first time window channel number is selected to cover the target refracted wave signal segment in the lateral direction, and a first time window length is determined to cover a complete waveform of the target refracted wave signal segment in the longitudinal direction. The signal energy analysis time window is an axial time window defined by the first time window channel number and the first time window length. The automatically generated noise energy analysis window includes: Identify the target layer reflected wave signal region in the earthquake single-shot acquisition data; A noise energy analysis time window is determined for covering the reflected wave signal region of the target layer. The noise energy analysis time window is a hyperbolic time window defined by a second time window channel number and a second time window length. The second time window channel number is equal to the total number of channels corresponding to a single receiving line, and the second time window length is the length of the second time window covering the reflected wave signal region of the target layer.

6. The method according to claim 1, characterized in that, The equivalent signal-to-noise ratio per gun is calculated based on the signal data within the signal energy analysis window and the noise energy analysis window, including: Calculate the root mean square amplitude value corresponding to the signal data within the signal energy analysis window to obtain the equivalent energy of the refracted wave. Calculate the root mean square amplitude value corresponding to the signal data within the noise energy analysis window to obtain the noise equivalent energy. The equivalent signal-to-noise ratio of a single shot is obtained by quotienting the equivalent energy of the refracted wave with the equivalent energy of the noise.

7. The method according to claim 1, characterized in that, Based on a comparative analysis of the equivalent signal-to-noise ratio of individual shots within the same group, the quality analysis results of the multiple seismic single-shot acquisition data are obtained, including: For seismic single-shot acquisition data within the same group, sort them according to the equivalent signal-to-noise ratio of the single shot; Based on the sorted seismic single-shot acquisition data, perform one or more of the following operations: The acquisition parameters corresponding to one or more of the top-ranked seismic single-row acquisition data are determined as the target acquisition parameters for subsequent construction; or... Based on the sorted seismic single-row acquisition data, the construction quality of one or more seismic single-row acquisition data at the bottom of the sort is analyzed and processed to obtain construction quality analysis and recommendations.

8. A device for comparing and analyzing the quality of seismic acquisition data, characterized in that, include: The information acquisition module is used to acquire seismic geological characteristic information corresponding to multiple seismic single-shot acquisition data to be compared and analyzed; The seismic geological characteristic information includes: surface structure information corresponding to the location of each of the multiple seismic single-shot acquisition data, and T0 time information of the target layer reflected wave, wherein the T0 time information is the intersection of the reflected wave time-distance curve and the time axis; The grouping module is used to divide the multiple seismic single-shot acquisition data into one or more groups based on the similarity of the seismic geological characteristic information, including: determining a first similarity between the surface structure information corresponding to the multiple seismic single-shot acquisition data; determining a second similarity between the target layer reflected wave T0 time information corresponding to the multiple seismic single-shot acquisition data; grouping the seismic single-shot acquisition data with the first similarity lower than a first threshold and the second similarity lower than a second threshold into the same group; and grouping the seismic single-shot acquisition data with the first similarity greater than the first threshold or the second similarity greater than the second threshold into different groups. The dual-time-window determination module is used to identify the waveform of each seismic single-shot acquisition data in each group after grouping, and to determine the signal energy analysis time window covering the refracted wave signal and the noise energy analysis time window covering the reflected wave of the target layer in each group; The calculation module is used to calculate the equivalent signal-to-noise ratio of a single shot based on the signal data within the signal energy analysis window and the noise energy analysis window. The comparative analysis module is used to perform comparative analysis based on the equivalent signal-to-noise ratio of a single shot within the same group, and to obtain the quality analysis results of the multiple seismic single-shot acquisition data.

9. An electronic device, characterized in that, It includes a processor, a communication interface, a memory, and a communication bus, wherein the processor, the communication interface, and the memory communicate with each other through the communication bus; Memory, used to store computer programs; A processor, when executing a program stored in memory, implements the method of any one of claims 1-7.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, it implements the method of any one of claims 1-7.

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