Earthquake spread spectrum processing method and device based on expected wavelets

Abstract

The invention discloses a seismic spread spectrum processing method and device based on expected wavelets, and relates to the technical field of geophysical exploration, and the main points of the technical scheme are that spread spectrum processing is carried out on original wavelets to obtain expected wavelets with better anti-interference capability so as to reduce the influence of subsequent operation on data quality. And then calculating seismic imaging results after the reflection coefficients are respectively convoluted with the original wavelets and the expected wavelets, obtaining amplitude spectrums of the two seismic imaging results, performing spectrum balance processing on the amplitude spectrums corresponding to the original wavelets by taking the amplitude spectrums corresponding to the expected wavelets as standards, eliminating possible distortion and noise in the seismic imaging results, and obtaining the seismic imaging results. And the seismic imaging result quality is improved. The method does not need to be established on the basis of a white spectrum hypothesis, and under the condition that the reflection coefficient does not completely conform to the white spectrum hypothesis, the characteristics of the underground structure can be reflected more accurately.

Description

Technical Field

[0001] The present invention relates to the field of geophysical exploration technology, and more particularly to a seismic spread spectrum processing method and device based on expected wavelet. Background Art

[0002] The concept of seismic resolution plays a crucial role in different stages of seismic exploration, including data acquisition, wave imaging processing, and geological interpretation.

[0003] We know that seismic resolution can be attributed to the resolution of the imaging wavelet on the imaging profile. According to the theory of seismic wave inversion imaging, the resolution of seismic waves mainly depends on the overall shape of the imaging wavelet, and this shape can be characterized by a row of the Hessian matrix. The closer the Hessian matrix is ​​to a diagonal matrix, that is, the closer the imaging wavelet is to the pulse, the higher the resolution of the prestack seismic imaging results. Each row of the Hessian matrix represents a seismic wavelet at a different point in the underground medium. However, in actual seismic processing, it is often difficult to accurately extract seismic wavelets due to the influence of complex surface and environmental factors, resulting in a certain degree of distortion in the imaging results relative to the real object, such as blurring and degradation.

[0004] Currently, using spectral whitening, a common method for directly improving the resolution of seismic data under the white spectrum assumption, is to flatten the amplitude spectrum within the effective frequency band of each signal in the frequency domain to compensate for high-frequency components, thereby improving resolution. Due to its simplicity, this method has been widely used in practice.

[0005] However, in practical applications, the frequency characteristics of underground media may be affected by a variety of factors, such as geological structure and medium heterogeneity, resulting in reflection coefficients that often do not fully conform to the white spectrum assumption. In this case, spectral whitening may make the processed data misleading and difficult to accurately reflect the characteristics of the underground structure. At the same time, actual seismic acquisition data is band-limited and may have low data resolution. Both data band-limitation and low resolution may reduce data quality. In this case, although spectral whitening can improve data resolution, the data after spectral whitening may be distorted, have enhanced noise, or introduce false features, further reducing data quality.

[0006] Based on the above reasons, the field of geophysical exploration technology is currently in urgent need of developing a spread spectrum processing method and device to improve the reliability of the spread spectrum results of resolution-band-limited seismic observation data, while being applicable to complex and changeable geological exploration environments. Summary of the Invention

[0007] In view of the shortcomings of the existing technology, the present invention provides the following technical solutions: a seismic spread spectrum processing method based on expected wavelet, comprising the following steps:

[0008] S1. Obtain the convolution result of the reflection coefficient and the original wavelet as the original seismic imaging result, perform Fourier transform on the original seismic imaging result, and obtain the original amplitude spectrum.

[0009] S2. Given a desired frequency range, perform spectrum spreading on the original wavelet to obtain a desired wavelet, where the frequency range of the desired wavelet is the desired frequency range; calculate the convolution result of the reflection coefficient and the desired wavelet as the desired seismic imaging result.

[0010] S3. Perform Fourier transform on the expected seismic imaging result to obtain the expected amplitude spectrum.

[0011] S4. Perform spectrum balancing processing on the original amplitude spectrum based on the expected amplitude spectrum.

[0012] S5. Perform inverse Fourier transform based on the result of spectrum balancing processing and output the spread spectrum seismic imaging result.

[0013] The present invention is further configured as follows: the expected frequency range is a dominant frequency band of the original amplitude spectrum, and the dominant frequency band is a frequency range where the amplitude density is concentrated in the amplitude spectrum determined by peak detection or clustering algorithm.

[0014] The present invention is further configured to: given a target geological depth A and a resolution B, obtain a wavelet C capable of interpreting the structure at a geological depth of A meters with a resolution of B meters, wherein the frequency range of the wavelet C is the desired frequency range.

[0015] The present invention is further configured such that: the resolution B is greater than or equal to 10m.

[0016] The present invention is further configured as follows: the spectrum balancing processing steps are as follows:

[0017] S41 , performing statistics on the original amplitude spectrum and the expected amplitude spectrum respectively to obtain a mapping parameter for each amplitude value in the original amplitude spectrum and a mapping parameter for each amplitude value in the expected amplitude spectrum, wherein the mapping parameter is a cumulative frequency or probability.

[0018] S42 : Map each amplitude value in the original amplitude spectrum to an amplitude value in the expected amplitude spectrum that is closest to its mapping parameter, and output a spectrum balancing result of the original amplitude spectrum.

[0019] The present invention further comprises performing a Fourier transform on the spread spectrum seismic imaging results to obtain a spread spectrum amplitude spectrum. Statistics are then collected on the spread spectrum amplitude spectrum to obtain mapping parameters for each amplitude value in the spread spectrum amplitude spectrum. Mapping parameter distribution graphs are then plotted for the original amplitude spectrum, the desired amplitude spectrum, and the spread spectrum amplitude spectrum, respectively, with the mapping parameters as the ordinate and the amplitude values ​​as the abscissa.

[0020] The present invention is further configured such that: the mapping parameter distribution diagram is a histogram, the number of groups in each histogram is the same, and the group spacing between each group is the same.

[0021] The present invention is further configured as follows: two different colors are selected as low mapping parameter colors and high mapping parameter colors, the groups in the histogram are numbered from small to large according to the amplitude, each number corresponds to a different color, the rectangle of the group with the smallest number is the low mapping parameter color, the rectangle of the group with the largest number is the high mapping parameter color, and the rectangles of the remaining groups are gradually changed from the low mapping parameter color to the high mapping parameter color according to the number from small to large, and each rectangle is a solid color.

[0022] The present invention is further configured as follows: the low mapping parameter color is white, the high mapping parameter color is black, the color of each rectangle corresponds to a grayscale value, and each histogram is converted into a line graph with the grayscale value as the horizontal coordinate and the mapping parameter as the vertical coordinate.

[0023] The present invention is further configured such that the number of groups in each histogram is 256.

[0024] The present invention is further configured such that: the mapping parameter is the cumulative frequency.

[0025] The present invention is further configured such that: the original wavelet is a Ricker wavelet.

[0026] The present invention is further configured such that: the original seismic imaging result is obtained based on SEGY format data or SU format data.

[0027] The present invention is further configured such that: the spread spectrum seismic imaging result is output in SEGY format or SU format.

[0028] The present invention is further configured as follows: the original seismic imaging result is a convolution result of the reflection coefficient and the original wavelet through the Marmousi model; the expected seismic imaging result is a convolution result of the reflection coefficient and the expected wavelet through the Marmousi model.

[0029] The present invention also provides a seismic spread spectrum processing device based on a desired wavelet, comprising a storage medium and a processor, wherein the storage medium stores a computer program. The processor is configured to implement the above-mentioned seismic spread spectrum processing method based on a desired wavelet when executing the computer program.

[0030] In summary, the present invention has the following beneficial effects compared to the prior art: the present invention first performs spread spectrum processing on the original wavelet to obtain a desired wavelet with better anti-interference ability, thereby reducing the impact of subsequent operations on data quality. Then, the seismic imaging results after the reflection coefficient is convolved with the original wavelet and the desired wavelet are calculated, and the amplitude spectra of the two seismic imaging results are obtained. The amplitude spectrum corresponding to the desired wavelet is used as the standard, and the amplitude spectrum corresponding to the original wavelet is spectrally balanced to eliminate possible distortion and noise in the seismic imaging results, thereby improving the quality of the seismic imaging results. The present invention does not need to be based on the white spectrum assumption. When the reflection coefficient does not fully conform to the white spectrum assumption, it can more accurately reflect the characteristics of the underground structure. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 Schematic diagram of the flow of the seismic spread spectrum processing method based on the expected wavelet in this embodiment.

[0032] Figure 2 is the original seismic imaging result in this embodiment.

[0033] Figure 3 It is a line graph of the original amplitude spectrum in this embodiment.

[0034] Figure 4 is the expected seismic imaging result in this embodiment.

[0035] Figure 5 It is a line graph of the expected amplitude spectrum in this embodiment.

[0036] Figure 6 This is the result of spread spectrum seismic imaging in this embodiment.

[0037] Figure 7 It is a line graph of the spread spectrum amplitude spectrum in this embodiment. DETAILED DESCRIPTION

[0038] The technical solution of the present invention will be clearly described below in conjunction with the accompanying drawings. Obviously, the described embodiments are not all embodiments of the present invention. All other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the invention.

[0039] Example

[0040] like Figure 1 As shown, a preferred embodiment of the present invention provides a seismic spread spectrum processing method based on expected wavelet, which includes the following steps:

[0041] S1. Obtain the convolution result of the reflection coefficient and the original wavelet as the original seismic imaging result, such as Figure 2As shown, the original seismic imaging result in this embodiment is the convolution result of the reflection coefficient and the original wavelet obtained by the marmousi model. The original seismic imaging result is subjected to Fourier transform to obtain the original amplitude spectrum.

[0042] S2. Given the expected frequency range, perform spectrum spreading on the original wavelet to obtain the expected wavelet, where the frequency range of the expected wavelet is the expected frequency range; calculate the convolution result of the reflection coefficient and the expected wavelet as the expected seismic imaging result, such as Figure 4 As shown, the expected seismic imaging result in this embodiment is the convolution result of the reflection coefficient and the expected wavelet obtained through the Marmousi model.

[0043] S3. Perform Fourier transform on the expected seismic imaging result to obtain the expected amplitude spectrum.

[0044] S4. Perform spectrum balancing processing on the original amplitude spectrum based on the expected amplitude spectrum.

[0045] S5. Perform inverse Fourier transform based on the result of spectrum balance processing and output the spread spectrum seismic imaging result, such as Figure 6 shown.

[0046] This method first performs spread spectrum processing on the original wavelet to obtain the desired wavelet with better anti-interference capabilities, reducing the impact of subsequent operations on data quality. It then calculates the seismic imaging results after convolving the reflection coefficient with the original and desired wavelets, obtaining the amplitude spectra of the two seismic imaging results. Using the amplitude spectrum corresponding to the desired wavelet as a standard, it performs spectral balancing on the amplitude spectrum corresponding to the original wavelet, eliminating potential distortion and noise in the seismic imaging results and improving their quality. This method does not require the white spectrum assumption and can more accurately reflect the characteristics of underground structures even when the reflection coefficient does not fully conform to the white spectrum assumption.

[0047] It should be noted that the original wavelet is any wavelet that can be used for seismic imaging, such as Ricker wavelet, Klauder wavelet, Ormsby wavelet, Butterworth wavelet, etc. In this embodiment, the original wavelet is the Ricker wavelet.

[0048] Furthermore, given a target geological depth A and a resolution B, a wavelet C is obtained that can interpret the structure at a geological depth of A meters at a resolution of B meters. The frequency range of wavelet C is the desired frequency range. The resolution B is greater than or equal to 10 meters. In this embodiment, the resolution is 10 meters. The geological depth is the true depth vertically downward from the surface to the target point. In this embodiment, the target geological depth A is 6000 meters.

[0049] It should be noted that the expected frequency range may also be set to a dominant frequency band of the original amplitude spectrum, where the dominant frequency band is a frequency range where the amplitude density is concentrated in the amplitude spectrum determined by peak detection or clustering algorithm.

[0050] The spectrum balancing processing steps in this embodiment are as follows:

[0051] S41. Statistically analyze the original amplitude spectrum and the expected amplitude spectrum to obtain a mapping parameter for each amplitude value in the original amplitude spectrum and a mapping parameter for each amplitude value in the expected amplitude spectrum. The mapping parameter is a cumulative frequency or probability. In this embodiment, the mapping parameter is a cumulative frequency.

[0052] S42 : Map each amplitude value in the original amplitude spectrum to an amplitude value in the expected amplitude spectrum that is closest to its mapping parameter, and output a spectrum balancing result of the original amplitude spectrum.

[0053] In the above-mentioned spectrum balancing process, there may be multiple original amplitude values ​​that have similar mapping parameters to a certain amplitude value in the expected amplitude spectrum, resulting in all of these original amplitude values ​​being mapped to that amplitude value, thereby increasing the frequency information of the seismic imaging results and, to a certain extent, eliminating the distortion and noise caused by data band limitation or low resolution.

[0054] This embodiment also performs a Fourier transform on the spread-spectrum seismic imaging results to obtain a spread-spectrum amplitude spectrum. After statistical analysis of the spread-spectrum amplitude spectrum, mapping parameters for each amplitude value in the spread-spectrum amplitude spectrum are obtained. Mapping parameter distribution diagrams are plotted for the original amplitude spectrum, the expected amplitude spectrum, and the spread-spectrum amplitude spectrum, with the mapping parameters as the ordinate and the amplitude values ​​as the abscissa. This visually demonstrates the degree of matching among the original, expected, and spread-spectrum amplitude spectra.

[0055] In this embodiment, the mapping parameter distribution diagram is a histogram, and each histogram has the same number of groups and the same group spacing.

[0056] Furthermore, two different colors are selected as low-mapping parameter colors and high-mapping parameter colors. The groups in the histogram are numbered from smallest to largest according to amplitude, with each number corresponding to a different color. The rectangle in the smallest numbered group is the low-mapping parameter color, and the rectangle in the largest numbered group is the high-mapping parameter color. The rectangles in the remaining groups are numbered in ascending order, gradually transitioning from the low-mapping parameter color to the high-mapping parameter color, with each rectangle being a solid color. This color comparison provides a more intuitive representation of the degree of match between the original amplitude spectrum, the desired amplitude spectrum, and the spread spectrum amplitude spectrum.

[0057] In this embodiment, the low mapping parameter color is white, the high mapping parameter color is black, the color of each rectangle corresponds to a grayscale value, and the grayscale value is used as the horizontal coordinate and the mapping parameter is used as the vertical coordinate. Each histogram is converted into a line graph, as shown in FIG. Figure 3 、5 , 7. The line graph can more clearly reflect the trend matching degree of the original amplitude spectrum, the expected amplitude spectrum and the spread spectrum amplitude spectrum.

[0058] In this embodiment, the original seismic imaging result is obtained based on SEGY format data or SU format data, and the spread spectrum seismic imaging result is output in SEGY format or SU format.

[0059] This embodiment further provides a seismic spread spectrum processing device based on a desired wavelet, comprising a storage medium and a processor, wherein the storage medium stores a computer program. The processor is configured to implement the aforementioned seismic spread spectrum processing method based on a desired wavelet when executing the computer program.

[0060] In summary, this embodiment first performs spread spectrum processing on the original wavelet to obtain the desired wavelet with better anti-interference ability, thereby reducing the impact of subsequent operations on data quality. Then, the seismic imaging results after the reflection coefficient is convolved with the original wavelet and the desired wavelet are calculated, and the amplitude spectra of the two seismic imaging results are obtained. The amplitude spectrum corresponding to the desired wavelet is used as the standard, and the amplitude spectrum corresponding to the original wavelet is spectrally balanced to eliminate the distortion and noise that may exist in the seismic imaging results, thereby improving the quality of the seismic imaging results. The method proposed in this embodiment does not need to be based on the white spectrum assumption. When the reflection coefficient does not fully conform to the white spectrum assumption, it can more accurately reflect the characteristics of the underground structure.

[0061] The foregoing description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Those skilled in the art will readily appreciate that various modifications and variations of the present invention are possible. Any modifications, equivalent substitutions, or improvements made within the spirit and principles of the present invention are intended to be within the scope of protection of the present invention.

Claims

1. A seismic spread spectrum processing method based on expected wavelet, characterized by: The steps include: S1. Obtain the convolution result of the reflection coefficient and the original wavelet as the original seismic imaging result, perform Fourier transform on the original seismic imaging result, and obtain the original amplitude spectrum; S2. Given a desired frequency range, perform spectrum spreading on the original wavelet to obtain a desired wavelet, where the frequency range of the desired wavelet is the desired frequency range; calculate the convolution result of the reflection coefficient and the desired wavelet as the desired seismic imaging result; S3. Perform Fourier transform on the expected seismic imaging result to obtain the expected amplitude spectrum; S4, performing spectrum balancing processing on the original amplitude spectrum based on the expected amplitude spectrum; S5. Perform inverse Fourier transform based on the result of spectrum balancing processing and output the spread spectrum seismic imaging result.

2. The method for earthquake spread spectrum processing based on expected wavelet according to claim 1, characterized in that: The expected frequency range is a dominant frequency band of the original amplitude spectrum, and the dominant frequency band is a frequency range where the amplitude density is concentrated in the amplitude spectrum determined by peak detection or clustering algorithm.

3. The method for earthquake spread spectrum processing based on expected wavelet according to claim 1, characterized in that: Given a target geological depth A and a resolution B, a wavelet C is obtained that can interpret the structure at a geological depth of A meters with a resolution of B meters. The frequency range of the wavelet C is the desired frequency range.

4. The method for earthquake spread spectrum processing based on expected wavelet according to claim 3, characterized in that: The resolution B is greater than or equal to 10m.

5. A seismic spread spectrum processing method based on desired wavelet according to any one of claims 1 to 4, characterized in that: The spectrum balancing process steps are as follows: S41. Perform statistics on the original amplitude spectrum and the expected amplitude spectrum respectively to obtain a mapping parameter for each amplitude value in the original amplitude spectrum and a mapping parameter for each amplitude value in the expected amplitude spectrum, wherein the mapping parameter is a cumulative frequency or probability; S42 : Map each amplitude value in the original amplitude spectrum to an amplitude value in the expected amplitude spectrum that is closest to its mapping parameter, and output a spectrum balancing result of the original amplitude spectrum.

6. The method for earthquake spread spectrum processing based on expected wavelet according to claim 5, characterized in that: Performing Fourier transform on the spread spectrum seismic imaging results to obtain the spread spectrum amplitude spectrum; performing statistics on the spread spectrum amplitude spectrum to obtain the mapping parameters of each amplitude value in the spread spectrum amplitude spectrum; With the mapping parameter as the ordinate and the amplitude value as the abscissa, the mapping parameter distribution diagrams of the original amplitude spectrum, the expected amplitude spectrum, and the spread spectrum amplitude spectrum are plotted respectively.

7. The method for earthquake spread spectrum processing based on expected wavelet according to claim 6, characterized in that: The mapping parameter distribution diagram is a histogram, and the number of groups in each histogram is the same, and the group spacing of each group is the same.

8. The method for earthquake spread spectrum processing based on expected wavelet according to claim 7, characterized in that: Select two different colors as low mapping parameter color and high mapping parameter color, and number the groups in the histogram from small to large according to the amplitude. Each number corresponds to a different color. The rectangle of the group with the smallest number is the low mapping parameter color, and the rectangle of the group with the largest number is the high mapping parameter color. The rectangles of the remaining groups are gradually changed from low mapping parameter color to high mapping parameter color according to the number from small to large, and each rectangle is a solid color.

9. The method for earthquake spread spectrum processing based on expected wavelet according to claim 8, characterized in that: The low mapping parameter color is white, the high mapping parameter color is black, the color of each rectangle corresponds to a grayscale value, and each histogram is converted into a line graph with the grayscale value as the horizontal coordinate and the mapping parameter as the vertical coordinate.

10. The method for seismic spread spectrum processing based on expected wavelet according to claim 9, characterized in that: The number of groups in each histogram is 256.

11. The method for earthquake spread spectrum processing based on expected wavelet according to claim 5, characterized in that: The mapping parameter is the cumulative frequency.

12. A seismic spread spectrum processing method based on desired wavelet according to any one of claims 1 to 4, characterized in that: The original wavelet is a Ricker wavelet.

13. The method for earthquake spread spectrum processing based on expected wavelet according to claim 1, characterized in that: The original seismic imaging results are obtained based on SEGY format data or SU format data.

14. A seismic spread spectrum processing method based on desired wavelet according to claim 1 or 13, characterized in that: The spread spectrum seismic imaging results are output in SEGY format or SU format.

15. A seismic spread spectrum processing method based on desired wavelet according to any one of claims 1 to 4, characterized in that: The original seismic imaging result is a convolution result of the reflection coefficient and the original wavelet through the Marmousi model, and the expected seismic imaging result is a convolution result of the reflection coefficient and the expected wavelet through the Marmousi model.

16. A seismic spread spectrum processing device based on expected wavelet, characterized by: The method comprises a storage medium and a processor, wherein the storage medium stores a computer program; the processor is configured to implement a seismic spread spectrum processing method based on an expected wavelet as claimed in any one of claims 1 to 15 when executing the computer program.

Images