A wavelet-consistent time-varying correction method, device, equipment and related system

Abstract

The application discloses a kind of wavelet consistency time-varying correction method, device, equipment and related system, the method can include: after acquiring seismic data is carried out frequency domain denoising, to extract seismic wavelet;In frequency domain compression seismic wavelet, to determine zero phase seismic data;Zero phase seismic data is carried out frequency band energy equalization processing, to obtain full-band seismic data;Based on Yu's wavelet time-varying correction is carried out to full-band seismic data.Through the denoising processing of seismic data in frequency domain, the factor of reducing the influence of wavelet extraction quality is further improved, and then the consistency of zero phase seismic data is improved;Then frequency band energy equalization processing is carried out to seismic data, and then energy tends to be consistent, amplitude consistency is obviously improved;Finally, after Yu's wavelet time-varying correction, wavelet is further compressed, sidelobe is weakened, amplitude spectrum smooth continuity is enhanced, longitudinal resolution is significantly improved, and spectrum is further widened.

Description

Technical Field

[0001] This invention relates to the field of geophysical seismic exploration technology, and in particular to a wavelet consistency time-varying correction method, apparatus, equipment and related system. Background Technology

[0002] As exploration and development deepen, the focus of oil and gas exploration is shifting towards three directions: unconventional, deep, and lithological trap oil and gas reservoirs. The difficulty of oil and gas exploration is increasing day by day. This requires continuous improvement in exploration and construction technology, as well as continuous improvement in data processing technology, to ensure high resolution, high fidelity, and high signal-to-noise ratio of the data.

[0003] Currently, in geophysical exploration, pre-stack seismic reservoir prediction technology is a key technology for unconventional oil and gas and lithologic trap oil and gas exploration. While it has been effective in improving the lateral resolution of reservoir prediction, it cannot significantly improve the vertical resolution, and its prediction accuracy is also limited by the vertical resolution of seismic data. Therefore, seeking effective seismic data processing methods to improve seismic data resolution before predicting reservoirs is a core step in providing valuable information for reservoir prediction.

[0004] A seismic wavelet is a component of a seismic record convolution model, typically referring to a seismic pulse consisting of two to three or more phases. More precisely, a seismic wavelet is the far-field time-domain response of the mass velocity (land-based detector) or pressure (sea-based detector) recorded by a receiver, which is the propagation of seismic energy from the source through a complex underground path.

[0005] Wavelet is the main factor affecting the resolution of seismic records. To improve the resolution of seismic data, the wavelet needs to be adjusted to increase its consistency. Summary of the Invention

[0006] The inventors discovered that existing methods for adjusting wavelet consistency over time primarily involve addressing seismic record consistency issues before implementation, either by adjusting the seismic records in terms of time or amplitude. Some methods simultaneously adjust both the amplitude and phase of the seismic data, which improves processing accuracy to some extent. However, further improvements are needed in efficiently unifying wavelets, improving seismic record resolution, and broadening the spectrum while adjusting seismic record consistency during processing without compromising data fidelity.

[0007] In view of the above problems, the present invention is proposed to provide a wavelet consistency time-varying correction method, apparatus, device and related system that overcomes or at least partially solves the above problems.

[0008] In a first aspect, embodiments of the present invention provide a wavelet consistency time-varying correction method, which may include:

[0009] After frequency domain denoising of the acquired seismic data, seismic wavelets are extracted.

[0010] The seismic wavelet is compressed in the frequency domain to determine the zero-phase seismic data;

[0011] The zero-phase seismic data is subjected to frequency band capability equalization processing to obtain full-band seismic data.

[0012] Time-varying correction is performed on the full-band seismic data based on the Yu wavelet.

[0013] Optionally, the extraction of the seismic wavelet may include the following steps:

[0014] First arrival waves are removed from earthquake data;

[0015] Determine the autocorrelation value of the seismic trace with the highest signal-to-noise ratio and / or above a preset threshold in the seismic data after removing the first arrival wave;

[0016] A convolutional model is constructed based on the autocorrelation value to extract the seismic wavelet.

[0017] Optionally, compressing the seismic wavelet in the frequency domain to determine the zero-phase seismic data may include:

[0018] The seismic wavelet is zero-phased and compressed in the frequency domain to determine the compression operator.

[0019] Based on the compression operator, the seismic data after removing the first arrival wave and converting it to zero phase are determined.

[0020] Optionally, performing frequency band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data may include:

[0021] The seismic data after removing the first arrival wave and making it zero-phase is processed into frequency bands to obtain seismic data in several frequency bands.

[0022] Based on the energy compensation curve of the seismic data in each frequency band, energy equalization processing is performed on the seismic data in time-division windows to ensure the consistency of the seismic data amplitude.

[0023] The seismic data after energy equalization processing is reconstructed to obtain full-band seismic data.

[0024] Optionally, it may also include: determining the size of the processing window below the initial arrival time based on the balanced window length, time, and high-frequency and low-frequency information.

[0025] Optionally, the frequency domain denoising of the acquired seismic data may include:

[0026] Based on the filter operator length, lowest frequency, and highest frequency, the bandwidth of the suppressor band and the passband are determined to obtain the filter expression;

[0027] The seismic data is subjected to amplitude filtering based on the aforementioned filtering expression;

[0028] The amplitude-filtered seismic data is then denoised in the frequency domain to suppress seismic trace noise.

[0029] Optionally, the time-varying correction of the full-band seismic data based on the Yu wavelet may include:

[0030] Based on wavelet length, high-frequency information, and low-frequency information, the Yu wavelet expression is determined;

[0031] Based on the Yu wavelet expression, the sample values ​​of the sampling points of the full-band seismic data are time-varyingly corrected point by point.

[0032] Optionally, the method may further include:

[0033] The acquired seismic data is preprocessed, and the preprocessing includes at least one of the following methods: static correction, signal-to-noise ratio denoising, and energy compensation.

[0034] Secondly, embodiments of the present invention provide a seismic data stitching method, which may include:

[0035] According to the wavelet consistency time-varying correction method described in the first aspect of the claim, consistency time-varying correction is performed on seismic data;

[0036] The seismic data is stitched together based on the consistent time-varying correction.

[0037] Thirdly, embodiments of the present invention provide a wavelet consistency time-varying correction device, which may include:

[0038] The acquisition module is used to acquire earthquake data;

[0039] The denoising module is used to perform frequency domain denoising on the acquired seismic data;

[0040] The extraction module is used to extract seismic wavelets;

[0041] A compression module is used to compress the seismic wavelet in the frequency domain to determine the zero-phase seismic data;

[0042] The processing module is used to perform frequency band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data.

[0043] The correction module is used to perform time-varying correction on the full-band seismic data based on the Yu wavelet.

[0044] Optionally, the device may also include:

[0045] The preprocessing module is used to preprocess the acquired seismic data, and the preprocessing includes at least one of the following methods: static correction, signal-to-noise ratio denoising, and energy compensation.

[0046] Fourthly, embodiments of the present invention provide a seismic data stitching device, which may include: a stitching module;

[0047] The stitching module is used to stitch together the time-varying seismic data obtained by the wavelet consistency time-varying correction method described in the first aspect.

[0048] Fifthly, embodiments of the present invention provide a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the wavelet consistency time-varying correction method described in the first aspect, or the seismic data stitching method described in the second aspect.

[0049] In a sixth aspect, embodiments of the present invention provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the wavelet consistency time-varying correction method described in the first aspect, or the seismic data stitching method described in the second aspect.

[0050] In a seventh aspect, embodiments of the present invention provide an earthquake data processing system, which may include: a data correction device and a data stitching device;

[0051] The data correction device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the wavelet consistency time-varying correction method described in the first aspect to perform consistency time-varying correction on the acquired seismic data.

[0052] The stitching device includes a processor and a computer program stored in a memory and capable of running on the processor. When the processor executes the program, it stitches the seismic data to perform stitching processing on the seismic data after consistency time-varying correction.

[0053] The beneficial effects of the above-described technical solutions provided in the embodiments of the present invention include at least the following:

[0054] This invention provides a wavelet consistency time-varying correction method, apparatus, device, and related system. The method includes: denoising acquired seismic data in the frequency domain to extract seismic wavelets; compressing the seismic wavelets in the frequency domain to determine zero-phase seismic data; performing frequency-band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data; and performing time-varying correction on the full-band seismic data based on the Yu wavelet. By denoising the seismic data in the frequency domain, factors affecting the quality of wavelet extraction are reduced, thereby improving the consistency of the zero-phase seismic data; then, frequency-band energy equalization processing of the seismic data is performed to achieve energy uniformity, significantly improving amplitude consistency; finally, after Yu wavelet time-varying correction, the wavelet is further compressed, sidelobes are weakened, the amplitude spectrum smoothness and continuity are enhanced, the longitudinal resolution is significantly improved, and the spectrum is further broadened.

[0055] Other features and advantages of the invention will be set forth in the following description, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the written description and the accompanying drawings.

[0056] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0057] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0058] Figure 1 This is a flowchart illustrating the wavelet consistency time-varying correction method provided in Embodiment 1 of the present invention;

[0059] Figure 2 This is a schematic diagram of the specific process of frequency domain denoising provided in Embodiment 1 of the present invention;

[0060] Figure 3 This is a schematic diagram of the process for extracting seismic wavelets provided in Embodiment 1 of the present invention;

[0061] Figure 4 This is a schematic diagram of the specific process of step S12;

[0062] Figure 5 This is a schematic diagram of the specific process for step S13;

[0063] Figure 6 Here is a detailed flowchart of step S14;

[0064] Figure 7This is a schematic diagram of the specific process of the wavelet consistency time-varying correction method provided in Embodiment 1 of the present invention;

[0065] Figure 8 This refers to the preprocessed seismic data acquired in Embodiment 1 of the present invention.

[0066] Figure 9 This is the superimposed profile obtained after acquisition and preprocessing, as provided in Embodiment 1 of the present invention;

[0067] Figure 10 This refers to the preprocessed seismic data spectrum provided in Embodiment 1 of the present invention.

[0068] Figure 11 The corrected seismic data provided in Embodiment 1 of the present invention;

[0069] Figure 12 This is the corrected superimposed profile provided in Embodiment 1 of the present invention;

[0070] Figure 13 This refers to the corrected seismic data spectrum provided in Embodiment 1 of the present invention;

[0071] Figure 14 This is a schematic diagram of the wavelet consistency time-varying correction device provided in Embodiment 1 of the present invention;

[0072] Figure 15 This is a schematic diagram of the structure of the earthquake data processing system provided in Embodiment 2 of the present invention. Detailed Implementation

[0073] Exemplary embodiments of the present disclosure will now be described in more detail with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be implemented in various forms and should not be limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art.

[0074] Example 1

[0075] Embodiment 1 of the present invention provides a wavelet consistency time-varying correction method, referring to... Figure 1 As shown, the method may include the following steps:

[0076] Step S11: After denoising the acquired seismic data in the frequency domain, extract the seismic wavelet.

[0077] Step S12: Compress the seismic wavelet in the frequency domain to determine the zero-phase seismic data.

[0078] Step S13: Perform frequency band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data.

[0079] Step S14: Perform time-varying correction on the full-band seismic data based on the Yu wavelet.

[0080] The method provided in this embodiment of the invention reduces factors affecting the quality of wavelet extraction by denoising the seismic data in the frequency domain, thereby improving the consistency of zero-phase seismic data; then, it performs energy equalization processing on the seismic data in frequency bands to achieve energy uniformity and significantly improve amplitude uniformity; finally, after Yu's wavelet time-varying correction, the wavelet is further compressed, the sidelobes are weakened, the amplitude spectrum is smoother and more continuous, the longitudinal resolution is significantly improved, and the spectrum is further broadened.

[0081] In an optional embodiment, after acquiring the seismic data, the process may further include:

[0082] The acquired seismic data is preprocessed, including at least one of the following methods: static correction, signal-to-noise ratio denoising, and energy compensation.

[0083] Static correction can include elevation static correction and residual static correction. Elevation static correction reduces errors caused by variations in surface elevation. In seismic data processing for detailed structural interpretation and reservoir property description, residual static correction is a key technique affecting the signal-to-noise ratio and resolution of seismic profiles. The main purpose of residual static correction is to eliminate residual errors from base-level static correction and adjust the stacking phase of common-center gathers to achieve in-phase stacking. For example, a method of multiple iterations of velocity analysis and residual static correction can be used for data processing, resulting in a significant improvement in both the signal-to-noise ratio and data quality after residual static correction.

[0084] The above signal-to-noise ratio denoising refers to the general denoising process, which is different from the frequency domain denoising described below. This signal-to-noise ratio denoising can use conventional techniques to improve the signal-to-noise ratio, and when processing seismic data, noise is no longer included in the calculation.

[0085] The aforementioned energy compensation makes the energy of seismic data more uniform, resulting in higher imaging accuracy.

[0086] In another alternative embodiment, refer to Figure 2 As shown, the frequency domain denoising of the acquired seismic data in step S11 above may include the following steps:

[0087] Step S21: Based on the filter operator length, the lowest frequency, and the highest frequency, determine the bandwidth of the suppression band and the passband to obtain the filter expression.

[0088] In this embodiment of the invention, a pure amplitude filter is used for filtering. The bandwidth of the suppression band and the passband are calculated based on the given filter operator length, lowest frequency and highest frequency. The filtering expression is then determined based on the above parameters and applied to the filter for filtering.

[0089] Step S22: Perform amplitude filtering on the seismic data based on the filtering expression. In this step, amplitude filtering can improve the lateral resolution.

[0090] Step S23: Perform frequency domain denoising on the amplitude-filtered seismic data to suppress seismic trace noise. In this step, after denoising in the frequency domain, the noise in the seismic data is suppressed, thereby improving both the lateral and longitudinal resolutions of the seismic data, and thus enhancing the overall signal-to-noise ratio of the seismic data.

[0091] In another alternative embodiment, refer to Figure 3 As shown, the extraction of seismic wavelets in step S11 above may include the following steps:

[0092] Step S31: Remove the first arrival wave from the seismic data.

[0093] The first arrival wave, as mentioned above, is the wavefront of a seismic wave that first arrives at a certain observation point, at which point the particles of the medium begin to vibrate, and is recorded as the first arrival wave, or the first arrival (time) of the wave. In this step, for seismic data undergoing wavelet consistency correction, the inventors remove the first arrival wave to specifically calculate the reflected wave, thereby improving the accuracy of wavelet extraction. It should be noted that in this embodiment of the invention, when removing the first arrival wave, the first arrival wave must first be determined. However, the method of determining the first arrival wave is not the inventive point of this embodiment of the invention; that is, the first arrival wave can be determined by any method or any technical means that can achieve removal, and this embodiment of the invention does not specifically limit this.

[0094] Step S32: Determine the autocorrelation value of the seismic trace with the highest signal-to-noise ratio and / or above a preset threshold in the seismic data after removing the first arrival wave. In this embodiment of the invention, the autocorrelation value (sample value of the wavelet at each sample point) of the seismic trace in the above seismic data can be determined by a more advanced autocorrelation algorithm (an iterative accumulation process).

[0095] Step S33: Construct a convolution model based on autocorrelation values ​​to extract seismic wavelets.

[0096] In this embodiment of the invention, by removing the first arrival wave and determining the autocorrelation value of the seismic trace based on the signal-to-noise ratio, a convolution model is constructed, ultimately achieving the goal of extracting the seismic wavelet.

[0097] In another alternative embodiment, refer to Figure 4As shown, step S12 above, which involves compressing the seismic wavelet in the frequency domain to determine the zero-phase seismic data, may specifically include the following steps:

[0098] Step S41: Zero-phase the seismic wavelet. This step can be performed using any zero-phase technique. The purpose is to obtain zero-phase seismic data and to make the wavelet shape more consistent, thereby correcting the wavelet phase.

[0099] Step S42: Compress the seismic wavelet in the frequency domain to determine the compression operator. This step compresses the aforementioned seismic wavelet in the frequency domain, for example, from 250ms to 200ms, thus determining its compression operator.

[0100] Step S43: Based on the compression operator, determine the zero-phase seismic data after removing the first arrival wave. In this step, the compression operator obtained in step S42 is applied to all sampling points in the seismic data to obtain zero-phase seismic data. The wavelet morphology of the seismic data tends to be consistent, improving the longitudinal and lateral resolution of the seismic data.

[0101] In another alternative embodiment, refer to Figure 5 As shown, step S13 above performs frequency band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data, which may specifically include the following steps:

[0102] Step S51: Perform frequency band processing on the seismic data after removing the first arrival wave and zeroing the phase to obtain seismic data in several frequency bands.

[0103] In this step, the seismic data is divided into frequency bands in the frequency domain, for example, into multiple frequency bands such as 1–15 Hz, 10–25 Hz, and 20–35 Hz. The inventors perform overlapping frequency band division on the above-mentioned seismic data to improve the accuracy of the seismic data.

[0104] Step S52: Based on the balanced time window length, time, and high-frequency and low-frequency information, determine the size of the processing time window to be removed below the initial arrival time.

[0105] This step involves dividing the seismic data into several equally divided processing windows. This allows for better alignment with localized variations during data processing, resulting in more balanced data energy processing.

[0106] Step S53: Energy compensation curve based on seismic data within each frequency band. This step can determine the aforementioned energy compensation curve using a fitting algorithm.

[0107] It should be noted that the execution of steps S52 and S53 is not in any particular order. Step S52 can be executed first and then step S53, or step S53 can be executed first and then step S52, or steps S52 and S53 can be executed simultaneously. This embodiment of the invention does not impose any specific limitations on this.

[0108] Step S54: Perform energy equalization processing on the seismic data across time windows to ensure consistency in seismic data amplitude. This step involves calculating the equalization value for each time window, i.e., optimizing the amplitude of the seismic data.

[0109] Step S55: Reconstruct the energy-equalized seismic data to obtain full-band seismic data. This step uses time-division windowing to optimize the amplitude of the above seismic data to obtain full-band seismic data.

[0110] This embodiment, through the above-described processing of seismic data, achieves higher amplitude consistency, thereby further improving the matching degree of the seismic data. For example, it further improves the matching degree when stitching seismic data, or enhances the matching degree with actual geological bodies and structures.

[0111] In another alternative embodiment, refer to Figure 6 As shown, step S14 above performs time-varying correction on the full-band seismic data based on the Yu wavelet, which may specifically include the following steps:

[0112] Step S61: Determine the Yu wavelet expression based on wavelet length, high-frequency information, and low-frequency information. This step involves fitting the wavelet's shape with existing Yu wavelet expressions to determine the matching process required to achieve the desired Yu wavelet shape. In other words, it involves constraining the wavelet and determining the expression describing the wavelet's characteristics to achieve the Yu wavelet's shape.

[0113] Step S62: Perform time-varying correction on the sample values ​​of the full-band seismic data point by point based on the Yu wavelet expression. This step determines the operator for each sample point in the seismic data according to the time variation, so as to use the wavelet to correct the seismic data and ensure the consistency of the seismic data.

[0114] The inventors used Yu's wavelet, which has high resolution, no excessive sidelobe interference, and does not introduce unnecessary noise. The resolution of the processed seismic traces is improved, and the spectrum is further broadened.

[0115] In one specific embodiment, refer to Figure 7 As shown, the above-mentioned wavelet consistency time-varying correction method may specifically include the following steps:

[0116] Step S71: Preprocess the acquired seismic data. (Refer to...) Figure 8As shown, this is preprocessed seismic data; the longitudinal resolution of the seismic traces is low. (Refer to...) Figure 9 As shown, this is a preprocessed overlay profile. It can be seen that the resolution of the overlay profile in the above image is slightly low, and the geological bodies or inter-layer boundaries are not clear. (Refer to...) Figure 10 The image shows the spectrum of preprocessed seismic data after acquisition.

[0117] Step S72: Frequency domain noise reduction.

[0118] Step S73: Extract seismic wavelet.

[0119] Step S74: Zero-phase seismic wavelet.

[0120] Step S75: Compress the seismic wavelet to determine the compression operator.

[0121] Step S76: Zero-phase seismic data.

[0122] Step S77: Frequency band capability equalization processing.

[0123] Step S78: Frequency band energy equalization processing to obtain full-band seismic data.

[0124] Step S79: Perform time-varying correction on the full-band seismic data based on the Yu wavelet.

[0125] The specific description of the steps in the embodiments of the present invention can be found in the description of the other embodiments described above, and will not be repeated here.

[0126] Reference Figure 11 , Figure 12 and Figure 13 As shown, Figure 11 The vertical resolution in Figure 8 The vertical resolution is significantly improved, and each vertical boundary is clearer. Figure 12 and Figure 9 In comparison, geological bodies or interfaces between strata are more clearly defined, for example... Figure 12 The boundaries of the strata in the CMP (Common Centroid) region between 2400 and 2500 are more clearly shown in traces 1490-1530. Figure 13 and Figure 10 In comparison, the amplitude resolution is improved, for example, the amplitude of useful high-frequency signals between 50 and 70 is increased, and the original abnormal frequencies are attenuated, for example, abnormal noise displayed at 150 Hz is attenuated.

[0127] Based on the same inventive concept, this invention also provides a wavelet consistency time-varying correction device, referring to... Figure 14As shown, the device may include: an acquisition module 141, a noise reduction module 142, an extraction module 143, a compression module 144, a processing module 145, and a correction module 146, and its working principle is as follows:

[0128] Module 141 is used to acquire seismic data;

[0129] The denoising module 142 is used to perform frequency domain denoising on the acquired seismic data;

[0130] Extraction module 143 is used to extract seismic wavelets;

[0131] Compression module 144 is used to compress seismic wavelets in the frequency domain to determine zero-phase seismic data;

[0132] The processing module 145 is used to perform frequency band energy equalization processing on the zero-phase seismic data to obtain full-band seismic data;

[0133] The correction module 146 is used to perform time-varying correction on full-band seismic data based on the Yu wavelet.

[0134] In an optional embodiment, refer to Figure 14 As shown, it may also include a preprocessing module 147, which is used to preprocess the acquired seismic data. The preprocessing includes at least one of the following methods: static correction, signal-to-noise ratio denoising, and energy compensation.

[0135] In another optional embodiment, the extraction module 143 is specifically used to: remove the first arrival wave from the seismic data; determine the autocorrelation value of the seismic trace with the highest signal-to-noise ratio and / or higher than a preset threshold in the seismic data after removing the first arrival wave; and construct a convolution model based on the autocorrelation value to extract the seismic wavelet.

[0136] In another optional embodiment, the compression module 144 is specifically used to: zero-phase the seismic wavelet, compress the seismic wavelet in the frequency domain to determine a compression operator; and based on the compression operator, determine the seismic data after removing the first arrival wave and zero-phase conversion.

[0137] In another optional embodiment, the processing module 145 is specifically used to: perform frequency band processing on the seismic data after removing the first arrival wave and making it zero-phase, so as to obtain seismic data in several frequency bands; perform energy equalization processing on the seismic data in time windows based on the energy compensation curve of the seismic data in each frequency band, so as to make the amplitude of the seismic data consistent; and reconstruct the seismic data after energy equalization processing to obtain full-band seismic data.

[0138] In another optional embodiment, the processing module 145 may further be used to: determine the size of the processing window to be removed below the initial arrival time based on the equalization window length, time, and high-frequency and low-frequency information.

[0139] In another optional embodiment, the correction module 146 is specifically used to: determine the Yu wavelet expression based on the wavelet length, high-frequency information and low-frequency information; and perform time-varying correction on the sample values ​​of the sampling points of the full-band seismic data point by point based on the Yu wavelet expression.

[0140] In another optional embodiment, the denoising module 142 is specifically used to: determine the bandwidth of the suppression band and the passband based on the filter operator length, the lowest frequency, and the highest frequency to obtain a filtering expression; perform amplitude filtering processing on the seismic data based on the filtering expression; and perform frequency domain denoising on the amplitude-filtered seismic data to suppress seismic trace noise.

[0141] Based on the same inventive concept, this embodiment of the invention also provides a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the above-described wavelet consistency time-varying correction method.

[0142] Based on the same inventive concept, this embodiment of the invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the above-described wavelet consistency time-varying correction method.

[0143] The principles by which the above-mentioned devices, media, and related equipment in the embodiments of the present invention solve the problem are similar to those of the aforementioned methods. Therefore, their implementation can refer to the implementation of the aforementioned methods, and repeated details will not be repeated.

[0144] Example 2

[0145] To balance long-term sustainability and cost reduction, modern seismic exploration often involves processing seismic records with significant wavelet differences. Due to the particularly complex surface environment in my country, various excitation and reception devices are used in seismic exploration to adapt to surface factors, resulting in differences in wavelet timing, amplitude, and phase between seismic records. Furthermore, significant variations in acquisition parameters, data quality, and field processing methods across different periods of seismic records also contribute to substantial differences in wavelets. These wavelet differences severely impact the quality of seismic record processing, posing challenges to interpretation, reservoir prediction, and even oil and gas exploration.

[0146] To fully utilize existing seismic data and reduce seismic exploration costs without compromising data accuracy, appropriate data processing methods are needed to mitigate the negative impact of seismic wavelet variations on reflected signals. Currently, data splicing and consistency issues are mainly addressed through time-shifting, adjusted deconvolution, and matched filtering. Time-shifting focuses solely on time difference correction, offering simplicity but failing to balance the adjustment and matching of shallow and deep data, and may also increase noise, exacerbating data inconsistencies. Adjusted deconvolution is challenging in terms of parameter selection, difficult to implement, and prone to reducing the signal-to-noise ratio.

[0147] The most widely used and effective method is matched filtering, which can be divided into wavelet shaping, seismic wavelet processing based on wavelet transform, direct matched filtering, and matched filtering based on wavelet transform.

[0148] Traditional wavelet shaping, based on the Toplitz equation and Wiener filtering, requires high signal-to-noise ratios at the splicing points of seismic records with different wavelets, and also needs to extract high-quality seismic wavelets. However, the effectiveness of this method decreases when the wavelet varies with time and space. Direct matched filtering, based on the Toplitz equation, calculates the filtering operators for two types of seismic records separately and averages them. The matched filtering operator is then applied to the seismic record with one wavelet to make it approximate the record with the other wavelet. This averaging method has generally low accuracy and is more suitable for seismic records with two wavelets. When there are many types of wavelets in the seismic record, the calculation becomes cumbersome and there is a high degree of ambiguity. Wavelet transform-based matched filtering (wavelet domain matched filtering) decomposes the seismic record into the wavelet domain and achieves matching in different ranges. This method adapts well to the time-varying characteristics of the data, but its drawbacks include cumbersome calculation, susceptibility to errors, and difficulty in improving frequency consistency.

[0149] Based on the same inventive concept, this embodiment of the invention also provides a seismic data stitching method, which may include: performing time-varying consistency correction on seismic data using the wavelet consistency time-varying correction method in embodiment 1; and performing stitching processing on the seismic data after consistency time-varying correction.

[0150] The splicing method provided in this embodiment of the invention reduces wavelet differences by performing time-varying consistency correction on the wavelets. This efficient unification of wavelets not only improves the resolution and broadens the spectrum of seismic records but also enhances the data quality of contiguous processing during seismic data splicing, providing support for seismic interpretation, reservoir prediction, and even oil and gas exploration. Other beneficial effects and related descriptions in this embodiment of the invention can be found in the relevant content of Embodiment 1, and will not be repeated here.

[0151] Based on the same inventive concept, this embodiment of the invention also provides a seismic data stitching device, which may include: a stitching module; the stitching module is used to stitch together the seismic data after time-varying correction based on the wavelet consistency time-varying correction method described in Embodiment 1.

[0152] Based on the same inventive concept, this embodiment of the invention also provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described seismic data stitching method.

[0153] Based on the same inventive concept, this embodiment of the invention also provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described seismic data stitching method.

[0154] Based on the same inventive concept, an earthquake data processing system is also provided in the embodiments of the present invention, referring to... Figure 15 As shown, the system may include: a data correction device 151 and a data splicing device 152;

[0155] The data correction device 151 includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the wavelet consistency time-varying correction method described in Embodiment 1 to perform consistency time-varying correction on the acquired seismic data.

[0156] The stitching device 152 includes a processor and a computer program stored in a memory and capable of running on the processor. When the processor executes the program, it implements the above-described seismic data stitching method to stitch together the seismic data after consistency time-varying correction.

[0157] The principles by which the above-described apparatus, medium, related equipment, and system in the embodiments of the present invention solve the problem are similar to those of the aforementioned methods. Therefore, their implementation can refer to the implementation of the aforementioned methods, and repeated details will not be repeated.

[0158] Those skilled in the art will understand that embodiments of the present invention can be provided as methods, systems, or computer program products. Therefore, the present invention can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, the present invention can take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0159] This invention is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations and / or block diagrams. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0160] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0161] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 One or more processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0162] Obviously, those skilled in the art can make various modifications and variations to this invention without departing from its spirit and scope. Therefore, if these modifications and variations fall within the scope of the claims of this invention and their equivalents, this invention also intends to include these modifications and variations.

Claims

1. A wavelet uniformity time-varying correction method, characterized in that, include: After frequency domain denoising of the acquired seismic data, seismic wavelets are extracted. The seismic wavelet is zero-phased and compressed in the frequency domain to determine the compression operator. Based on the compression operator, the seismic data after removing the first arrival wave and converting it to zero phase is determined; The seismic data after removing the first arrival wave and zeroing the phase are processed into frequency bands to obtain seismic data in several frequency bands. Based on the energy compensation curve of the seismic data in each frequency band, energy equalization processing is performed on the seismic data in time-division windows to ensure the consistency of the seismic data amplitude. The seismic data after energy equalization processing is reconstructed to obtain full-band seismic data; Time-varying correction is performed on the full-band seismic data based on the Yu wavelet.

2. The method according to claim 1, characterized in that, The extraction of the seismic wavelet includes the following steps: First arrival waves are removed from earthquake data; Determine the autocorrelation value of the seismic trace with the highest signal-to-noise ratio and / or above a preset threshold in the seismic data after removing the first arrival wave; A convolutional model is constructed based on the autocorrelation value to extract the seismic wavelet.

3. The method according to claim 1, characterized in that, Also includes: Based on the balanced window length, time, and high-frequency and low-frequency information, the size of the processing window below the initial arrival time is determined.

4. The method according to claim 1, characterized in that, The frequency domain denoising of the acquired seismic data includes: Based on the filter operator length, lowest frequency, and highest frequency, the bandwidth of the suppressor band and the passband are determined to obtain the filter expression; The seismic data is subjected to amplitude filtering based on the aforementioned filtering expression; The amplitude-filtered seismic data is then denoised in the frequency domain to suppress seismic trace noise.

5. The method according to claim 1, characterized in that, The time-varying correction of the full-band seismic data based on the Yu wavelet includes: Based on wavelet length, high-frequency information, and low-frequency information, the Yu wavelet expression is determined; Based on the Yu wavelet expression, the sample values ​​of the sampling points of the full-band seismic data are time-varyingly corrected point by point.

6. The method according to any one of claims 1 to 5, characterized in that, Also includes: The acquired seismic data is preprocessed, and the preprocessing includes at least one of the following methods: static correction, noise reduction, and energy compensation.

7. A method for stitching seismic data, characterized in that, include: The wavelet consistency time-varying correction method according to any one of claims 1 to 6 is used to perform consistency time-varying correction on seismic data; The seismic data is stitched together based on the consistent time-varying correction.

8. A wavelet uniformity time-varying correction device, characterized in that, include: The acquisition module is used to acquire earthquake data; The denoising module is used to perform frequency domain denoising on the acquired seismic data; The extraction module is used to extract seismic wavelets; A compression module is used to zero-phase the seismic wavelet and compress the seismic wavelet in the frequency domain to determine the compression operator. Based on the compression operator, the seismic data after removing the first arrival wave and converting it to zero phase is determined; The processing module is used to perform frequency band processing on the seismic data after removing the first arrival wave and making it zero-phase, so as to obtain seismic data in several frequency bands. Based on the energy compensation curve of the seismic data in each frequency band, energy equalization processing is performed on the seismic data in time-division windows to ensure the consistency of the seismic data amplitude; the energy-equalized seismic data is then reconstructed to obtain full-band seismic data. The correction module is used to perform time-varying correction on the full-band seismic data based on the Yu wavelet.

9. The apparatus according to claim 8, characterized in that, Also includes: The preprocessing module is used to preprocess the acquired seismic data, and the preprocessing includes at least one of the following methods: static correction, noise reduction, and energy compensation.

10. A seismic data stitching device, characterized in that, include: splicing modules; The stitching module is used to stitch together the seismic data after time-varying correction based on the wavelet consistency time-varying correction method according to any one of claims 1 to 6.

11. A computer-readable storage medium having a computer program stored thereon, characterized in that, When executed by the processor, the program implements the wavelet consistency time-varying correction method as described in any one of claims 1 to 6, or the seismic data stitching method as described in claim 7.

12. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the wavelet consistency time-varying correction method as described in any one of claims 1 to 6, or the seismic data stitching method as described in claim 7.

13. A seismic data processing system, characterized in that, include: Data correction equipment and data splicing equipment; The data correction device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, it implements the wavelet consistency time-varying correction method as described in any one of claims 1 to 6 to perform consistency time-varying correction on the acquired seismic data. The stitching device includes a processor and a computer program stored in a memory and capable of running on the processor. When the processor executes the program, it stitches the seismic data to perform stitching processing on the seismic data after consistency time-varying correction.

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