Space-time variation seismic wavelet solving method and device, electronic equipment and storage medium

Abstract

The invention provides a space-time variation seismic wavelet solving method and device, electronic equipment and a storage medium. The invention relates to a space-time variation seismic wavelet solving method, which comprises the following steps of: windowing on a seismic record by adopting a plurality of space channels and a plurality of time points; a corresponding wavelet is solved for each sampling point, and the wavelet of the point is weighted and optimized according to information of multiple channels of wavelets in the window. According to the method provided by the invention, the optimized wavelets can be obtained, and the reflection coefficient is calculated by using the optimized wavelets, so that the seismic data resolution is greatly improved, the frequency band is widened, and the structure is well implemented.

Description

Technical Field

[0001] The present invention belongs to the field of digital signal processing such as seismic exploration data processing, and specifically relates to a method and device for obtaining spatio-temporal variable seismic wavelets, an electronic device, and a storage medium. Background Art

[0002] Deep exploration, oil and gas prediction, and high-resolution processing have always been key areas in oil and gas exploration.

[0003] Severe absorption attenuation and low resolution of seismic data are prominent problems in oil and gas exploration in complex exploration areas in China. Conventional high-resolution processing methods based on convolution theory usually cannot guarantee the fidelity and signal-to-noise ratio after processing. Therefore, it is very important to develop a method that can effectively improve the resolution of pre-stack and post-stack data while protecting the amplitude characteristics and signal-to-noise ratio, which can provide high-quality basic data for high-resolution seismic imaging and fine reservoir interpretation.

[0004] All along, the extraction of seismic wavelets has been a difficult problem in seismic signal processing, mainly due to the complexity and uncertainty of the underground medium.

[0005] A spatio-temporal variable seismic wavelet obtaining method proposed by the present invention can obtain spatio-temporal variable seismic wavelets, which are closer to more real seismic wavelets. Using this wavelet to deconvolve seismic records can improve the resolution of seismic signals and provide high-quality seismic data for high-resolution exploration. Summary of the Invention

[0006] The purpose of the present invention is to improve the resolution of seismic data. A spatio-temporal variable seismic wavelet obtaining method is proposed, which can obtain spatio-temporal variable seismic wavelets, which are closer to more real seismic wavelets. Using this wavelet to deconvolve seismic records can improve the resolution of seismic signals and achieve better processing effects.

[0007] To achieve the above object, the present invention provides a method for obtaining spatio-temporal variable seismic wavelets, including:

[0008] On a seismic record, take multiple spatial channels and multiple time points to open a window;

[0009] Obtain a corresponding wavelet for each sample point, and optimize the wavelet at this point by weighting according to the multi-channel wavelet information within the window.

[0010] Further, the formula used for weighted optimization is:

[0011]

[0012] where c(t) is the weighting factor calculated for each window, is the average value of the signals within the window, w is the wavelet, t is the time, and τ is the delay time.

[0013] Further, it also includes deconvolving the seismic record with the optimized wavelet to obtain the reflection coefficient.

[0014] Further, convolving the obtained reflection coefficient with the seismic wavelet to improve the resolution of the seismic signal:

[0015] s(t) = w(t) * r(t) (1)

[0016] Wherein, s(t) is the seismic record, w(t) is the seismic wavelet, and r(t) is the reflection coefficient sequence.

[0017] According to another aspect of the present invention, there is provided a device for obtaining a spatio-temporal variable seismic wavelet, including:

[0018] A windowing module, which takes multiple spatial channels and multiple time points on a seismic record to perform windowing;

[0019] A weighting module, which obtains a corresponding wavelet for each sample point and weights and optimizes the wavelet at this point according to the multi-channel wavelet information within the window.

[0020] According to another aspect of the present invention, there is provided an electronic device, and the electronic device includes:

[0021] A memory, which stores executable instructions;

[0022] A processor, and the processor runs the executable instructions in the memory to implement the method for obtaining a spatio-temporal variable seismic wavelet as described above.

[0023] According to another aspect of the present invention, there is provided a non-transitory computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, it implements the method for obtaining a spatio-temporal variable seismic wavelet as described above.

[0024] Using the method of the present invention, an optimized wavelet can be obtained, and the reflection coefficient is calculated using the optimized wavelet, so that the resolution of seismic data is greatly improved, the frequency band is broadened, and the structure is better implemented. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] By describing the exemplary embodiments of the present invention in more detail in conjunction with the drawings, the above and other objects, features, and advantages of the present invention will become more obvious. Among them, in the exemplary embodiments of the present invention, the same reference numerals generally represent the same components.

[0026] Figure 1 It is a flowchart of the method for obtaining a spatio-temporal variable seismic wavelet according to the present invention.

[0027] Figure 2Schematic diagram of a sliding window according to an embodiment of the present invention.

[0028] Figure 3 This is a diagram of the original data of a certain area after stacking according to an embodiment of the present invention.

[0029] Figure 4 This is a data diagram showing improved resolution of a certain area after stacking according to an embodiment of the present invention.

[0030] Figure 5 This is a diagram of the original data of a certain area after stacking according to an embodiment of the present invention.

[0031] Figure 6 This is a data diagram showing improved resolution of a certain area after stacking according to an embodiment of the present invention.

[0032] Figure 7 A comparison diagram of amplitude spectra before and after improving the resolution according to an embodiment of the present invention. DETAILED DESCRIPTION

[0033] The preferred embodiments of the present invention will be described in more detail below. Although the preferred embodiments of the present invention are described below, it should be understood that the present invention can be implemented in various forms and should not be limited by the embodiments set forth herein. On the contrary, these embodiments are provided to make the present invention more thorough and complete, and to fully convey the scope of the present invention to those skilled in the art.

[0034] The present invention is further described below in conjunction with the accompanying drawings and specific embodiments, but is not intended to be limiting of the present invention. It should be noted that the embodiments and features in the embodiments of the present invention may be combined with each other without conflict.

[0035] Embodiment 1

[0036] The source signal propagates underground and encounters a reflective layer. The signal is reflected back to the detector and recorded as data. The data is filtered by the earth, the frequency becomes lower, and it is inevitably introduced with noise. This is a convolution process. If you want to obtain information about the underground reflective layer, this is a deconvolution process. The main function of this process is to eliminate the filtering effect of the earth as much as possible, obtain the real seismic wavelet more accurately, and then compress the seismic wavelet to make the actual data closer to the real underground reflection sequence, thereby improving the resolution of seismic data and widening the frequency band.

[0037] like Figure 1 As shown, this embodiment provides a method for obtaining a time-space varying seismic wavelet, comprising:

[0038] On a seismic record, multiple channels in space and multiple points in time are used to open windows;

[0039] For each sample point, a corresponding wavelet is obtained, and based on the multi-channel wavelet information within this window, the wavelet at this point is weighted and optimized.

[0040] Without considering noise, according to the convolution model, the seismic record s(t) can be written as the convolution of the seismic wavelet w(t) and the reflection coefficient sequence r(t), that is

[0041] s(t) = w(t) * r(t) (1)

[0042] It is usually assumed that the reflection coefficient is a random sequence. At this time, the autocorrelation of the seismic record can be approximated as the autocorrelation of the seismic wavelet. According to the properties of the Fourier transform, convolution in the time domain is equivalent to multiplication in the frequency domain, so there is

[0043] S(t) = W(t) * R(t) (2)

[0044] Deconvolution is to multiply the seismic record by the compressed wavelet to obtain the reflection coefficient, thereby improving the resolution of the seismic record.

[0045] The resolution of the seismic record is determined by the continuation length of the seismic signal (seismic wavelet) w(t) and the distance between the reflection coefficients r(t). The shorter the continuation length of w(t) and the greater the distance between r(t), the higher the resolution; conversely, the lower the resolution.

[0046] Conventional wavelet extraction techniques obtain wavelets for a single trace. In the present invention, on a seismic record, spatial multi-traces and multiple points in time are used to open a window. For each sample point, a corresponding wavelet is obtained. Within this window, based on the multi-channel wavelet information, the wavelet at this point is weighted and optimized. In this way, the spatio-temporal variable deconvolution operator for each sample point of each trace is obtained. It achieves complete spatio-temporal variation and is thus particularly suitable for the case where the seismic wavelet has spatio-temporal variations.

[0047] The formula used for weighted optimization is:

[0048]

[0049] where c(t) is the weighting factor calculated for each window, which can be the average value of the signal within the window, w is the wavelet, t is time, and τ is the delay time.

[0050] After sliding the window, a mixed-phase deconvolution operator designed for each sample point can be realized, thus being closer to the real seismic wavelet, and further maximizing the compression of the wavelet to improve the resolution.

[0051] Generally, the window slides from shallow to deep. The window size can vary, can overlap, can not overlap, can be equally divided, or can be unequally divided, and can be adjusted arbitrarily according to the profile situation.

[0052] If the data noise is severe, the effect of conventional deconvolution is poor and shows instability. By sliding window equalization, the problem of abnormal energy of the output data of deconvolution is solved. This achieves full spatio-temporal variation and is thus particularly applicable to the case where the seismic wavelet has spatio-temporal variations. Therefore, the method of the present invention can better adapt to the characteristics of actual data.

[0053] Furthermore, it also includes performing deconvolution on the seismic record with the optimized wavelet to obtain the reflection coefficient. By convolving the obtained reflection coefficient with the seismic wavelet, the resolution of the seismic signal is improved:

[0054] s(t) = w(t) * r(t) (1)

[0055] where s(t) is the seismic record, w(t) is the seismic wavelet, and r(t) is the reflection coefficient sequence.

[0056] Embodiment 2

[0057] Refer to Figures 3 - 7 As shown, in this embodiment, taking the actual seismic data of a certain area as an example, the actual application of the method for obtaining spatio-temporal variable seismic wavelets of the present invention is described.

[0058] Figure 3 is the post-stack original data map of a certain area according to the embodiment of the present invention, Figure 4 is the post-stack data map with improved resolution of a certain area according to the embodiment of the present invention. Figure 5 is the post-stack original data map of a certain area according to the embodiment of the present invention, Figure 6 is the post-stack data map with improved resolution of a certain area according to the embodiment of the present invention.

[0059] Figure 7 is the amplitude spectrum comparison map before and after improving the resolution according to the embodiment of the present invention. It can be seen from the comparison that the resolution of the seismic data is greatly improved. Therefore, the method of the present invention can better adapt to the characteristics of actual data.

[0060] As shown in the figure, the structural amplitude in this area is large, the signal resolution is low, and the structure is difficult to determine. After using the method of the present invention to improve the resolution, it can be seen that the data resolution is greatly improved, the frequency band is broadened, and the structure is better determined.

[0061] Embodiment 3

[0062] This embodiment provides a device for obtaining spatio-temporal variable seismic wavelets, including:

[0063] A windowing module, which takes multiple spatial channels and multiple time points on a seismic record to perform windowing;

[0064] A weighting module, which obtains a corresponding wavelet for each sample point and weights and optimizes the wavelet at this point according to the multi-channel wavelet information within this window.

[0065] Example 4

[0066] This embodiment provides an electronic device, which includes:

[0067] A memory storing executable instructions;

[0068] A processor that runs the executable instructions in the memory to implement the spatio-temporal variable seismic wavelet extraction method, which includes:

[0069] On a seismic record, take multiple spatial channels and multiple time points to open a window;

[0070] For each sample point, obtain a corresponding wavelet, and optimize the wavelet at this point by weighting according to the multi-channel wavelet information within this window.

[0071] Example 5

[0072] This embodiment provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the spatio-temporal variable seismic wavelet extraction method, which includes:

[0073] On a seismic record, take multiple spatial channels and multiple time points to open a window;

[0074] For each sample point, obtain a corresponding wavelet, and optimize the wavelet at this point by weighting according to the multi-channel wavelet information within this window.

[0075] The above computer-readable storage medium includes but is not limited to: optical storage media (such as CD-ROM and DVD), magneto-optical storage media (such as MO), magnetic storage media (such as magnetic tapes or external hard drives), media with built-in rewritable non-volatile memory (such as memory cards), and media with built-in ROM (such as ROM cartridges).

[0076] In summary, the spatio-temporal variable seismic wavelet extraction method of the present invention can accurately obtain the true seismic wavelet, and then compress the seismic wavelet, making the actual data closer to the true underground reflection sequence, thereby improving the resolution and broadening the frequency band of seismic data, achieving a good processing effect.

[0077] The embodiments of the present invention have been described above. The above description is exemplary and not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those of ordinary skill in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for obtaining spatio-temporal variable seismic wavelets, characterized in that, it includes: On a seismic record, take multiple spatial channels and multiple time points to open a window; For each sample point, obtain a corresponding wavelet, and optimize the wavelet at this point by weighting according to the multi-channel wavelet information within this window.

2. The method for obtaining spatio-temporal variable seismic wavelets according to claim 1, characterized in that, the formula used for weighted optimization is: where c(t) is the weighting factor calculated for each window, is the average value of the signal within the window, w is the wavelet, t is time, and τ is the delay time.

3. The method for obtaining spatio-temporal variable seismic wavelets according to claim 2, characterized in that, it further includes deconvolving the seismic record with the optimized wavelet to obtain the reflection coefficient.

4. The method for obtaining spatio-temporal variable seismic wavelets according to claim 3, characterized in that, convolve the obtained reflection coefficient with the seismic wavelet to improve the resolution of the seismic signal: s(t) = w(t)) * r(t)(1) where s(t) is the seismic record, w(t) is the seismic wavelet, and r(t) is the reflection coefficient sequence.

5. A device for obtaining spatio-temporal variable seismic wavelets, characterized in that, it includes: A window-opening module, which takes multiple spatial channels and multiple time points on a seismic record to open a window; A weighting module, which obtains a corresponding wavelet for each sample point and optimizes the wavelet at this point by weighting according to the multi-channel wavelet information within this window.

6. The device for obtaining spatio-temporal variable seismic wavelets according to claim 5, characterized in that, the formula used for weighted optimization is: where c(t) is the weighting factor calculated for each window, is the average value of the signal within the window, w is the wavelet, t is time, and τ is the delay time.

7. The device for obtaining spatio-temporal variable seismic wavelets according to claim 6, characterized in that, it further includes deconvolving the seismic record with the optimized wavelet to obtain the reflection coefficient.

8. The device for obtaining spatio-temporal variable seismic wavelets according to claim 7, characterized in that, convolve the obtained reflection coefficient with the seismic wavelet to improve the resolution of the seismic signal: s(t) = w(t)) * r(t)(1) where s(t) is the seismic record, w(t) is the seismic wavelet, and r(t) is the reflection coefficient sequence.

9. An electronic device, characterized in that, the electronic device includes: A memory, which stores executable instructions; A processor, which runs the executable instructions in the memory to implement the method for obtaining spatio-temporal variable seismic wavelets according to any one of claims 1-4.

10. A non-transitory computer-readable storage medium, on which a computer program is stored, characterized in that, when the computer program is executed by a processor, it implements the method for obtaining spatio-temporal variable seismic wavelets according to any one of claims 1-4.

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