Bidirectional phase and amplitude method and device for improving quality of empirical green function

Abstract

The invention relates to the technical field of seismic exploration data processing methods, and particularly discloses a bidirectional phase and amplitude method and device for improving the quality of an empirical Green function, and the method comprises the steps: calculating the root mean square and the signal-to-noise ratio of a short-time cross function based on a seismic signal containing noise; updating a root mean square by using a root mean square ratio selection superposition method; performing iterative calculation by using a phase signal-to-noise ratio formula, and updating the signal-to-noise ratio; and utilizing the updated root mean square and the signal-to-noise ratio to recover the Green function, and calculating an effective seismic signal. According to the method, joint evaluation of the amplitude and the phase signal-to-noise ratio is introduced, so that the algorithm can be adaptively converged to an optimal set of short-time cross functions showing the highest signal consistency, test results of synthetic data and field data show that the method effectively eliminates interference of a non-static phase source, and the method has the advantages of being simple in structure and convenient to operate. And the capability of extracting a high-quality empirical Green function from more complex environmental noise is enhanced.

Description

Technical Field

[0001] This invention relates to the field of seismic exploration data processing methods, specifically to a method and apparatus for improving the quality of the empirical Green's function in both directions of phase and amplitude. Background Technology

[0002] Extracting reliable empirical Green's functions (ERFs) from environmental noise is crucial for various seismic applications, including imaging and monitoring subsurface velocity variations. A number of signal-to-noise ratio (SNR) stacking methods have been developed to improve the quality of ERFs. Among these methods, the root mean square ratio (RMS) selective stacking method effectively identifies short-time cross-correlation functions (SFCs) that contribute constructively to the recovery of the ERF. The core step of the RMS selective stacking method involves comparing the SNR of the ERF obtained after removing specific SFCs with the SNR of the ERF obtained from all SFCs, thereby suppressing interference from noise sources in non-static phase regions. However, when applied to complex environmental noise fields, such as traffic data, the RMS selective stacking method fails to adequately select sources within static phase regions, resulting in residual crosstalk in the ERF.

[0003] Based on this technical background, the present invention studies a method and apparatus for improving the bidirectional phase and amplitude of empirical Green's functions. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a method and apparatus for improving the quality of empirical Green's functions by considering both phase and amplitude. This method introduces a joint evaluation of amplitude and phase signal-to-noise ratio, enabling the algorithm to adaptively converge to the optimal set of short-time crossover functions that exhibit the highest signal consistency. Test results using synthetic and field data show that this method effectively eliminates interference from non-static phase sources and enhances the ability to extract high-quality empirical Green's functions from more complex environmental noise.

[0005] To achieve the above objectives, a first aspect of the present invention provides a method for improving the quality of a bidirectional phase and amplitude of an empirical Green's function, comprising:

[0006] Based on noisy seismic signals, the root mean square and signal-to-noise ratio of the short-time cross function are calculated;

[0007] The root mean square is updated using the root mean square ratio selection superposition method;

[0008] The signal-to-noise ratio is updated by iterative calculation using the phase signal-to-noise ratio formula.

[0009] The effective seismic signal is calculated by recovering the Green's function using the updated root mean square and signal-to-noise ratio.

[0010] A second aspect of the present invention provides an apparatus for improving the quality of the empirical Green's function in both directions of phase and amplitude, comprising:

[0011] The root mean square signal-to-noise ratio (RMSNR) calculation module is used to calculate the root mean square and signal-to-noise ratio of the short-time cross function based on noisy seismic signals.

[0012] The root mean square update module is used to update the root mean square using a root mean square ratio selection superposition method;

[0013] The signal-to-noise ratio (SNR) update module is used to perform iterative calculations using the phase SNR formula to update the SNR.

[0014] The Green's function recovery module is used to recover the Green's function using the updated root mean square and signal-to-noise ratio to calculate the effective seismic signal.

[0015] A third aspect of the present invention provides an electronic device, the electronic device comprising:

[0016] Memory, which stores executable instructions;

[0017] A processor that executes the executable instructions in the memory to implement the method for improving the quality of the empirical Green's function in both directions of phase and amplitude as described in the first aspect.

[0018] A fourth aspect of the present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the method for improving the quality of the empirical Green's function by bidirectional phase and amplitude as described in the first aspect.

[0019] The beneficial effects of this invention include:

[0020] (1) The method for improving the quality of empirical Green's function by bidirectional phase and amplitude proposed in this invention introduces the signal-to-noise ratio as an evaluation standard, which together with the amplitude signal-to-noise ratio enhances the coherence of empirical Green's function. By gradually increasing the evaluation threshold, the short-time cross-correlation function is iteratively selected, so that the algorithm can adaptively generate the best set of short-time cross-correlation functions, which can effectively recover high-quality empirical Green's function from complex environmental noise fields.

[0021] (2) The bidirectional phase and amplitude method for improving the quality of empirical Green's function proposed in this invention introduces a joint evaluation of amplitude and phase signal-to-noise ratio, enabling the algorithm to adaptively converge to the optimal set of short-time cross functions that exhibit the highest signal consistency. Test results of synthetic data and field data show that this method effectively eliminates interference from non-static phase sources and enhances the ability to extract high-quality empirical Green's functions from more complex environmental noise.

[0022] Other features and advantages of the present invention will be described in detail in the following detailed description section. Attached Figure Description

[0023] The above and other objects, features and advantages of the present invention will become more apparent from the more detailed description of exemplary embodiments of the invention in conjunction with the accompanying drawings.

[0024] Figure 1 This is a flowchart illustrating the method for improving the quality of the empirical Green's function in both directions of phase and amplitude, as proposed in this invention.

[0025] Figure 2 This is a flowchart illustrating a specific implementation of the method for improving the quality of the empirical Green's function in two-way phase and amplitude proposed in this invention. Detailed Implementation

[0026] Preferred embodiments of the invention will now be described in more detail. While preferred embodiments of the invention are described below, it should be understood that the invention can be implemented in various forms and should not be limited to the embodiments set forth herein.

[0027] This invention provides a method for improving the quality of the empirical Green's function in both directions of phase and amplitude, such as... Figure 1 As shown, it includes:

[0028] Based on noisy seismic signals, the root mean square and signal-to-noise ratio of the short-time cross function are calculated;

[0029] The root mean square (RMS) is updated using the RMS ratio selection superposition method.

[0030] The signal-to-noise ratio is updated by iterative calculation using the phase signal-to-noise ratio formula.

[0031] The effective seismic signal is calculated by recovering the Green's function using the updated root mean square and signal-to-noise ratio.

[0032] In this invention, the signal-to-noise ratio (SNR) is introduced as an evaluation criterion, which, together with the amplitude SNR, enhances the coherence of the empirical Green's function. By gradually increasing the evaluation threshold, the short-time cross-correlation function is iteratively selected, enabling the algorithm to adaptively generate the optimal set of short-time cross-correlation functions. This effectively recovers high-quality empirical Green's functions from complex environmental noise fields.

[0033] According to the present invention, the root mean square ratio is used to select and superimpose a method to update the root mean square for improving the amplitude within the effective surface wave velocity range.

[0034] According to the present invention, the phase signal-to-noise ratio formula is used for iterative calculation to update the signal-to-noise ratio in order to improve phase consistency within the effective surface wave velocity range.

[0035] According to the present invention, the expression for the phase signal-to-noise ratio formula is as follows:

[0036]

[0037] Where M is the number of short-time cross-correlation functions, rms is the root mean square, φ(t) is the instantaneous phase, ts is the signal within the velocity range, tn is the noise window, and PSNR is the phase signal-to-noise ratio.

[0038] According to the present invention, the root mean square ratio selection superposition method performs a short-time cross-correlation function selection based on the root mean square amplitude signal-to-noise ratio of all short-time cross-correlation functions.

[0039] Preferably, the phase signal-to-noise ratio formula performs multiple short-time cross-correlation function selections on the root mean square amplitude signal-to-noise ratio of all short-time cross-correlation functions.

[0040] According to the present invention, the updated root mean square and signal-to-noise ratio Green's function are used to improve the signal consistency of short-time cross function sets.

[0041] In this invention, a joint evaluation of amplitude and phase signal-to-noise ratio is introduced, enabling the algorithm to adaptively converge to the optimal set of short-time crossover functions that exhibit the highest signal consistency. Test results of synthetic and field data show that this method effectively eliminates interference from non-static phase sources and enhances the ability to extract high-quality empirical Green's functions from more complex environmental noise.

[0042] The present invention will be described in more detail below through embodiments.

[0043] Example 1:

[0044] like Figure 2 As shown, this embodiment proposes a method for improving the quality of the empirical Green's function by considering both phase and amplitude. It introduces the signal-to-noise ratio (SNR) as an evaluation criterion, which, together with the amplitude SNR, enhances the coherence of the empirical Green's function. By gradually increasing the evaluation threshold, it iteratively selects the short-time cross-correlation function, enabling the algorithm to adaptively generate the optimal set of short-time cross-correlation functions.

[0045] This method is an iterative bidirectional phase and amplitude method, as detailed below:

[0046] The root mean square ratio (RMS) superposition method emphasizes that the signal recovered by the empirical Green's function from a sufficient number of short-time cross-correlation functions should have a high amplitude within the effective surface wave velocity range. It is important to note that the signal within this velocity range should also have higher phase consistency. Therefore, a signal-to-noise ratio (SNR) method specifically measuring phase consistency is introduced, evaluating the contribution of the short-time cross-correlation function to the quality of the empirical Green's function by combining amplitude and phase SNR. Inspired by the phase-weighted superposition method, the formula for phase SNR is defined as follows:

[0047]

[0048] Where M is the number of short-time cross-correlation functions, rms represents the root mean square, φ(t) represents the instantaneous phase, ts is the signal within the velocity range, and tn is the noise window;

[0049] The root mean square ratio (RMS) selection superposition method can help select noise sources within the static phase region. In this method, short-time cross-correlation function (SCRC) selection is performed only once based on the RMS amplitude signal-to-noise ratio of all short-time cross-correlation functions. However, when the selected SCRC functions are more consistent, a higher SNR value can be generated. By replacing the previous standard with this new SNR and performing the next round of selection, the signal consistency of the short-time cross-correlation function set can be further improved.

[0050] The method proposed in this embodiment effectively eliminates interference from non-static phase sources and enhances the ability to extract high-quality empirical Green functions from more complex environmental noise.

[0051] Example 2:

[0052] This embodiment provides a method for improving the quality of the empirical Green's function in both directions of phase and amplitude, such as... Figure 1 As shown, it includes:

[0053] Based on noisy seismic signals, the root mean square and signal-to-noise ratio of the short-time cross function are calculated;

[0054] The root mean square (RMS) is updated using the RMS ratio selection superposition method.

[0055] The signal-to-noise ratio is updated by iterative calculation using the phase signal-to-noise ratio formula.

[0056] The effective seismic signal is calculated by recovering the Green's function using the updated root mean square and signal-to-noise ratio.

[0057] In this embodiment, the root mean square ratio is used to select and superimpose the method to update the root mean square in order to improve the amplitude within the effective surface wave velocity range.

[0058] In this embodiment, the phase signal-to-noise ratio formula is used for iterative calculation, and the signal-to-noise ratio is updated to improve the phase consistency within the effective surface wave velocity range.

[0059] In this embodiment, the expression for the phase signal-to-noise ratio formula is:

[0060]

[0061] Where M is the number of short-time cross-correlation functions, rms is the root mean square, φ(t) is the instantaneous phase, ts is the signal within the velocity range, tn is the noise window, and PSNR is the phase signal-to-noise ratio;

[0062] In this embodiment, the root mean square ratio selection superposition method performs a short-time crossover correlation function selection based on the root mean square amplitude signal-to-noise ratio of all short-time crossover functions;

[0063] In this embodiment, the phase signal-to-noise ratio formula performs multiple short-time crossover correlation function selections on the root mean square amplitude signal-to-noise ratio of all short-time crossover functions;

[0064] In this embodiment, the updated root mean square and signal-to-noise ratio recovery Green's function are used to improve the signal consistency of the short-time crossover function set.

[0065] Example 3:

[0066] This embodiment provides a device for improving the quality of the empirical Green's function by alternating phase and amplitude, comprising:

[0067] The root mean square signal-to-noise ratio (RMSNR) calculation module is used to calculate the root mean square and signal-to-noise ratio of the short-time cross function based on noisy seismic signals.

[0068] The root mean square update module is used to update the root mean square by selecting the superposition method based on the root mean square ratio.

[0069] The signal-to-noise ratio (SNR) update module is used to iteratively calculate and update the SNR using the phase SNR formula.

[0070] The Green's function recovery module is used to recover the Green's function using the updated root mean square and signal-to-noise ratio, and to calculate the effective seismic signal.

[0071] In this embodiment, the root mean square ratio is used to select and superimpose the method to update the root mean square in order to improve the amplitude within the effective surface wave velocity range.

[0072] In this embodiment, the phase signal-to-noise ratio formula is used for iterative calculation, and the signal-to-noise ratio is updated to improve the phase consistency within the effective surface wave velocity range.

[0073] In this embodiment, the expression for the phase signal-to-noise ratio formula is:

[0074]

[0075] Where M is the number of short-time cross-correlation functions, rms is the root mean square, φ(t) is the instantaneous phase, ts is the signal within the velocity range, tn is the noise window, and PSNR is the phase signal-to-noise ratio;

[0076] In this embodiment, the root mean square ratio selection superposition method performs a short-time crossover correlation function selection based on the root mean square amplitude signal-to-noise ratio of all short-time crossover functions;

[0077] In this embodiment, the phase signal-to-noise ratio formula performs multiple short-time crossover correlation function selections on the root mean square amplitude signal-to-noise ratio of all short-time crossover functions;

[0078] In this embodiment, the updated root mean square and signal-to-noise ratio recovery Green's function are used to improve the signal consistency of the short-time crossover function set.

[0079] Example 4:

[0080] This invention provides an electronic device including a memory and a processor, comprising:

[0081] Memory, which stores executable instructions;

[0082] A processor executes executable instructions in memory to implement methods for improving the quality of the empirical Green's function in both directions of phase and amplitude.

[0083] This memory is used to store non-transitory computer-readable instructions. Specifically, the memory may include one or more computer program products, which may include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM) and / or cache memory. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0084] The processor may be a central processing unit (CPU) or other form of processing unit with data processing capabilities and / or instruction execution capabilities, and may control other components in the electronic device to perform desired functions. In one embodiment of the invention, the processor is used to execute computer-readable instructions stored in the memory.

[0085] Those skilled in the art should understand that, in order to solve the technical problem of how to achieve a good user experience, this embodiment may also include well-known structures such as communication buses and interfaces, and these well-known structures should also be included within the protection scope of this invention.

[0086] For a detailed description of this embodiment, please refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0087] Example 5:

[0088] This invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements a method for improving the quality of a bidirectional phase and amplitude of an empirical Green's function.

[0089] A computer-readable storage medium according to embodiments of the present invention stores non-transitory computer-readable instructions. When these non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the methods described in the foregoing embodiments of the present invention are performed.

[0090] The aforementioned computer-readable storage media include, but are not limited to: optical storage media (e.g., CD-ROM and DVD), magneto-optical storage media (e.g., MO), magnetic storage media (e.g., magnetic tape or portable hard drive), media with built-in rewritable non-volatile memory (e.g., memory card), and media with built-in ROM (e.g., ROM cartridge).

[0091] The bidirectional phase and amplitude method for improving the quality of empirical Green's functions proposed in the embodiments of the present invention introduces a joint evaluation of amplitude and phase signal-to-noise ratio, enabling the algorithm to adaptively converge to the optimal set of short-time cross functions that exhibit the highest signal consistency. Test results of synthetic data and field data show that the method effectively eliminates interference from non-static phase sources and enhances the ability to extract high-quality empirical Green's functions from more complex environmental noise.

[0092] The various embodiments of the present invention have been described above. These descriptions are exemplary and not exhaustive, nor are they limited to the disclosed embodiments. Many modifications and variations will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method of improving the quality of the Green's function experience of the bidirectional phase and amplitude, characterized by, The method comprises the following steps: Based on the noisy seismic signal, the root mean square and signal-to-noise ratio of the short-time cross function are calculated; The root mean square is updated by using the root mean square ratio selection stacking method; The signal-to-noise ratio is updated by using the phase signal-to-noise ratio formula for iterative calculation; The effective seismic signal is calculated by using the updated root mean square and signal-to-noise ratio to recover the Green function.

2. The method of claim 1, wherein, The root mean square is updated by using the root mean square ratio selection stacking method to improve the amplitude in the effective surface wave velocity range.

3. The method of claim 1, wherein, The signal-to-noise ratio is updated by using the phase signal-to-noise ratio formula for iterative calculation to improve the phase consistency in the effective surface wave velocity range.

4. The method of claim 1, wherein, The expression of the phase signal-to-noise ratio formula is: Wherein, M is the number of short-time cross correlation function, rms is the root mean square, φ(t) is the instantaneous phase, ts is the signal in the velocity range, tn is the noise window, and PSNR is the phase signal-to-noise ratio.

5. The method of claim 1, wherein, The root mean square ratio selection stacking method performs a short-time cross correlation function selection for the root mean square amplitude signal-to-noise ratio of all short-time cross functions.

6. The method of claim 1, wherein, The phase signal-to-noise ratio formula performs multiple short-time cross correlation function selections for the root mean square amplitude signal-to-noise ratio of all short-time cross functions.

7. The method of claim 1, wherein, The Green function is recovered by using the updated root mean square and signal-to-noise ratio to improve the signal consistency of the short-time cross function set.

8. An apparatus for improving the quality of a Green's function by bi-directional phase and amplitude, characterized by, The method comprises the following steps: The root mean square signal-to-noise ratio calculation module is used to calculate the root mean square and signal-to-noise ratio of the short-time cross function based on the noisy seismic signal; The root mean square updating module is used to update the root mean square by using the root mean square ratio selection stacking method; The signal-to-noise ratio updating module is used to update the signal-to-noise ratio by using the phase signal-to-noise ratio formula for iterative calculation; The Green function recovery module is used to recover the Green function by using the updated root mean square and signal-to-noise ratio to calculate the effective seismic signal.

9. An electronic device, comprising: The electronic device comprises: A memory storing executable instructions; A processor running the executable instructions in the memory to implement the method for improving the bidirectional phase and amplitude of the quality of the empirical Green function according to any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer readable storage medium stores a computer program, which is executed by the processor to implement the method for improving the bidirectional phase and amplitude of the quality of the empirical Green function according to any one of claims 1-7.

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