Passive source surface wave data processing method based on wave field separation

Abstract

The present application relates to the field of surface wave exploration, and discloses a passive source surface wave data processing method based on wave field separation, which comprises the following steps: preprocessing the obtained original noise data; removing near wave field interference, i.e. selecting target segment signals in the preprocessed original noise data; performing wave field separation on the target segment signals to obtain noise signals in a single propagation direction; and performing deconvolution and mutual coherence interference processing on the noise signals in the single propagation direction to obtain surface wave signals with high signal-to-noise ratio. The present application can extract surface wave signals with high precision and high signal-to-noise ratio from passive source noise records in a relatively short time, thereby reducing the data processing workload and data acquisition cost to a certain extent. Furthermore, the present application improves the process of extracting surface wave signals from passive source noise signals through wave field separation processing, can reduce the influence of complex wave field on the interference process, and thereby improves the signal-to-noise ratio of the interference result.

Description

Technical Field

[0001] This invention relates to the field of surface wave exploration, specifically to a passive source surface wave data processing method based on wavefield separation, a passive source surface wave data processing device based on wavefield separation, an electronic device, and a computer-readable storage medium. Background Technology

[0002] Surface wave exploration is a rapidly developing shallow surface exploration method in recent years. This technology boasts advantages such as high detection accuracy, strong stratification capability, and low economic cost. Surface wave exploration can be divided into active source surface wave exploration and passive source surface wave exploration. With the development of surface wave exploration, the theory of seismic wave fields in shallow surface media with arbitrary source (using passive source noise imaging) has also developed rapidly. The application of passive source surface wave exploration is becoming increasingly widespread, and research on passive source noise imaging methods is also increasing.

[0003] Passive source noise records are a typical type of seismic data. They are seismic signals excited by sources generated by the natural environment and unintentionally by human activity. Because they typically contain strong surface wave energy and are easily obtained, passive source noise signals are also a very important type of seismic data. With the development of passive source surface wave exploration, research on extracting effective surface wave data from passive source noise records has rapidly progressed. The process of extracting surface wave signals from passive source noise data is generally achieved using three methods: cross-correlation interferometry, deconvolution interferometry, and mutual coherence interferometry.

[0004] Currently, many scholars have conducted in-depth research on passive source noise data processing. A typical noise processing workflow includes: 1. Instrument response removal (filtering); 2. Data segmentation, dividing long recordings into segments ranging from tens of seconds to one minute; 3. Seismic interferometry processing of each segment; 4. Superimposing the processed interferometric data to ultimately obtain the surface wave signal.

[0005] However, in traditional research methods, the wavefield information in environmental noise recordings is complex, resulting in low signal-to-noise ratios and severe noise interference. Conventional methods require long periods of data recording to extract effective surface wave signals from noise; typically, several hours or even longer of interferometric superposition of recorded data are needed to obtain surface wave signals with high signal-to-noise ratios. Traditional methods are not only time-consuming and labor-intensive, producing relatively low surface wave signal-to-noise ratios, but also have relatively high data acquisition costs. Summary of the Invention

[0006] The purpose of this invention is to provide a passive source surface wave data processing method based on wavefield separation, which solves the problems of traditional methods being time-consuming and labor-intensive in the processing process, having relatively low signal-to-noise ratios of the extracted surface waves, and having relatively high data acquisition costs.

[0007] To achieve the above-mentioned objectives, the technical solution adopted by this invention is: a passive source surface wave data processing method based on wavefield separation, the method comprising:

[0008] The acquired raw noise data is preprocessed;

[0009] Select the target segment signal from the preprocessed original noise data;

[0010] Wavefield separation is performed on the target segment signal to obtain a noise signal with a single propagation direction;

[0011] By interferometric processing of noise signals propagating in a single direction, a surface wave signal with a high signal-to-noise ratio can be obtained.

[0012] Preferably, the preprocessing includes at least one of filtering, resampling, and bad sector removal.

[0013] Preferably, wavefield separation is performed on the target segment signal to obtain a noise signal with a single propagation direction, including:

[0014] The target segment signal is transformed from the time-space domain to the frequency-wavenumber domain to obtain the frequency-wavenumber domain data of the target segment signal;

[0015] Remove unfavorable signals from the frequency-wavenumber domain data of the target segment signal and retain favorable signals;

[0016] The favorable signal is transformed from the frequency-wavenumber domain to the time-space domain to obtain a noise signal with a single propagation direction.

[0017] Preferably, the calculation formula for transforming the target segment signal from the time-space domain to the frequency-wavenumber domain is as follows:

[0018] ;

[0019] In the formula, f For frequency, k For wave number, t For time, x For the number of earthquake traces, i The imaginary unit, m For the time-space domain data of the target segment signal, M This is the frequency-wavenumber domain data of the target segment signal.

[0020] Preferably, the formula for transforming the advantageous signal from the frequency-wavenumber domain to the time-space domain is as follows:

[0021] ;

[0022] In the formula, m ′ represents the time-space domain data of the noise signal. M′ represents the frequency-wavenumber domain data of the favorable signal. f For frequency, k For wave number, t For time, x For the number of earthquake traces, i It is the imaginary unit.

[0023] Preferably, the noise signal propagating in a single direction is subjected to interference processing to obtain a surface wave signal with a high signal-to-noise ratio, including:

[0024] Calculate the noise signal in a single propagation direction between two detectors;

[0025] By processing the noise signal in a single propagation direction between two detectors based on interferometry, a surface wave signal with a high signal-to-noise ratio is obtained.

[0026] The present invention also provides a passive source surface wave data processing device based on wavefield separation, the device being used to implement the above-described passive source surface wave data processing method based on wavefield separation, the device comprising:

[0027] The processing module is used to preprocess the acquired raw noise data;

[0028] The selection module is used to extract the target segment signal from the preprocessed raw noise data;

[0029] The separation module is used to separate the wave field of the target segment signal to obtain a noise signal with a single propagation direction;

[0030] The interference module is used to perform interference processing on noise signals propagating in a single direction to obtain surface wave signals.

[0031] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described passive source surface wave data processing method based on wavefield separation.

[0032] The present invention also provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described passive source surface wave data processing method based on wavefield separation.

[0033] The beneficial effects of this invention are mainly reflected in:

[0034] 1. This invention can extract high-precision, high signal-to-noise ratio surface wave signals from passive source noise records of a relatively short time, thereby reducing the workload of data processing and the cost of data acquisition to a certain extent.

[0035] 2. This invention improves the process of extracting surface wave signals from passive source noise signals through wave field separation processing, which can reduce the influence of complex wave fields on the interference process, thereby improving the signal-to-noise ratio of the interference results. Attached Figure Description

[0036] Figure 1 This is a flowchart of a passive source surface wave data processing method based on wavefield separation provided by one embodiment of the present invention;

[0037] Figure 2 This is a flowchart of wavefield separation of a target segment signal provided by an optional embodiment of the present invention;

[0038] Figure 3 This is a schematic diagram of the interference process principle provided by an optional embodiment of the present invention;

[0039] Figure 4 This is a schematic diagram of a noise signal provided by an optional embodiment of the present invention;

[0040] Figure 5 This is a comparison diagram of interference results provided by an optional embodiment of the present invention;

[0041] Figure 6 This is a block diagram of a passive source surface wave data processing device based on wavefield separation, provided in an optional embodiment of the present invention. Detailed Implementation

[0042] To enable those skilled in the art to better understand the technical solutions of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0043] Figure 1 This is a flowchart of a passive source surface wave data processing method based on wavefield separation provided by one embodiment of the present invention, as shown below. Figure 1 As shown, a passive source surface wave data processing method based on wavefield separation is described, the method comprising:

[0044] Step S101: Preprocess the acquired raw noise data;

[0045] In this embodiment, the preprocessing includes at least one of filtering, resampling, and bad sector removal.

[0046] Step S102: Remove near-wave interference, i.e., select the target segment signal from the preprocessed original noise data;

[0047] In this embodiment, due to the location of the near-wave field, the noise signal has strong energy, and the surface wave signal is not yet fully developed, which seriously affects the signal-to-noise ratio of the surface wave signal extracted by the interferometric processing. Therefore, when selecting data of the target segment signal with an appropriate time length, the data segment with strong near-wave field energy should be avoided to reduce its impact on the interferometric results.

[0048] Step S103: Perform wave field separation on the target segment signal to obtain a noise signal with a single propagation direction.

[0049] As a further optimization of this embodiment, in step S103, such as Figure 2 As shown, wavefield separation is performed on the target segment signal to obtain a noise signal with a single propagation direction, including:

[0050] Step a01: Transform the target segment signal from the time-space domain to the frequency-wavenumber domain to obtain the frequency-wavenumber domain data of the target segment signal.

[0051] Specifically, performing a two-dimensional Fourier transform on the target segment signal can transform the data of the target segment signal from the time-space domain (tx domain) to the frequency-wavenumber domain (fk). The formula for transforming the target segment signal from the time-space domain to the frequency-wavenumber domain is as follows:

[0052] ;

[0053] In the formula, f For frequency, k For wave number, t For time, x For the number of earthquake traces, i The imaginary unit, m For the time-space domain data of the target segment signal, M This is the frequency-wavenumber domain data of the target segment signal.

[0054] Step a02: Remove unfavorable signals from the frequency-wavenumber domain data of the target segment signal and retain favorable signals.

[0055] In this embodiment, since the propagation direction of the wave field is different, the slope range of its signal energy in the frequency wavenumber domain is also different. Complex wave fields often exhibit energy information with different slope ranges in the frequency wavenumber domain. Therefore, based on the slope range characteristics, unfavorable signals are removed and favorable signals are left, so as to achieve the purpose of converting complex wave field signals into simpler wave field signals.

[0056] Step a03: Transform the favorable signal from the frequency-wavenumber domain to the time-space domain to obtain a noise signal with a single propagation direction.

[0057] In this embodiment, after removing the unfavorable signal in step a02, it is transformed back to the time-space domain (tx domain) to obtain a noise signal of a simple wave field, thus transforming the complex signal into a noise signal that propagates in a single direction.

[0058] Specifically, the formula for transforming the favorable signal from the frequency-wavenumber domain to the time-space domain is as follows:

[0059] ;

[0060] In the formula, m ′ represents the time-space domain data of the noise signal. M ′ represents the frequency-wavenumber domain data of the favorable signal. f For frequency, k For wave number, t For time, x For the number of earthquake traces, i It is the imaginary unit.

[0061] Step S104: Perform interference processing on the noise signal in a single propagation direction to obtain a surface wave signal with a high signal-to-noise ratio.

[0062] In this embodiment, after obtaining a noise signal with a single propagation direction, the effective signal can be extracted from the noise signal through interference processing. Interference processing typically has the following three methods: cross-correlation interference, deconvolution interference, and mutual interference. The present invention preferably adopts the deconvolution interference method, that is, the propagation effect of the surface wave between the two detectors is calculated by deconvolution between the two noise signal data.

[0063] Specifically, deconvolution interferometry is performed on noise signals propagating in a single direction to obtain surface wave signals, including:

[0064] Step b01: Calculate the noise signal in a single propagation direction between the two detectors;

[0065] In this embodiment, as Figure 3 As shown, assuming there are two detectors (A and B), the wave field expression at point A is:

[0066] ;

[0067] In the formula: for A Point wave field, x n ′ For the first n The location of the earthquake source. x A for A Point of signal reception location, n The number of earthquake focal points. For frequency, A For amplitude, R Indicates a right-traveling wave field. j The imaginary unit, K For wave number.

[0068] The wave field expression at point B is:

[0069] ;

[0070] In the formula: for B Point wave field, x n ′ The location of the nth earthquake source. x B for B Point of signal reception location, n The number of earthquake focal points. For frequency, A For amplitude, R Indicates a right-traveling wave field. j The imaginary unit, K For wave number.

[0071] Step b02: Process the noise signal in a single propagation direction between the two detectors based on deconvolution interferometry to obtain the surface wave signal.

[0072] Specifically, the calculation formula for processing noise signals in a single propagation direction between two detectors based on deconvolution interferometry is as follows:

[0073] ;

[0074] This invention eliminates the influence of the source wavelet by dividing the amplitude in the frequency domain through deconvolution interferometry and normalizes the amplitude information of each frequency, thereby broadening the effective frequency band of the interference result.

[0075] This invention separates a complex noise wavefield to obtain a signal propagating in a single direction. Then, it performs deconvolution interferometry on the separated unidirectional propagating signal. This improved interferometry method effectively extracts a surface wave signal with a higher signal-to-noise ratio from a shorter noise record.

[0076] like Figure 4 , 5 As shown, where Figure 4 (a) is a complex noise wave field containing signals propagating in two directions. Figure 4 (b) is the noise signal obtained after wave field separation, which has a single propagation direction. Figure 5 (c) shows the results of complex wavefield interferometry. Figure 5(d) shows the interference result after wavefield separation, based on... Figure 4 and Figure 5 As can be seen from the comparison, the present invention can efficiently extract high-precision, high signal-to-noise ratio surface wave signals from noise records, and also reduces the time and cost of data acquisition and processing to a certain extent.

[0077] Figure 6 This is a block diagram of a passive source surface wave data processing device based on wavefield separation, provided in an optional embodiment of the present invention, as shown below. Figure 6 As shown, a passive source surface wave data processing device based on wavefield separation is disclosed. The device is used to implement the aforementioned passive source surface wave data processing method based on wavefield separation. The device includes:

[0078] The processing module is used to preprocess the acquired raw noise data;

[0079] The selection module is used to select the target segment signal from the preprocessed raw noise data.

[0080] The separation module is used to separate the wave field of the target segment signal to obtain a noise signal with a single propagation direction;

[0081] The interference module is used to perform interference processing on noise signals propagating in a single direction to obtain surface wave signals with high signal-to-noise ratio.

[0082] The present invention also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the above-described passive source surface wave data processing method based on wavefield separation.

[0083] This invention can extract effective surface wave response features from short-duration passive source noise records. Tests demonstrate that effective surface wave signals can be extracted from noise data shorter than 4 seconds, reducing data processing workload and data acquisition costs to a certain extent.

[0084] Furthermore, this invention improves the process of extracting surface wave signals from passive source noise signals through wavefield separation processing. This reduces the influence of complex wavefields on the interference process, thereby improving the signal-to-noise ratio of the interference results.

[0085] The optional embodiments of the present invention have been described in detail above with reference to the accompanying drawings. However, the embodiments of the present invention are not limited to the specific details in the above embodiments. Within the scope of the technical concept of the embodiments of the present invention, various simple modifications can be made to the technical solutions of the embodiments of the present invention, and these simple modifications all fall within the protection scope of the embodiments of the present invention.

[0086] It should also be noted that the various specific technical features described in the above embodiments can be combined in any suitable manner without contradiction. To avoid unnecessary repetition, the embodiments of the present invention will not describe the various possible combinations separately.

[0087] Those skilled in the art will understand that all or part of the steps in the methods of the above embodiments can be implemented by a program instructing related hardware. This program is stored in a storage medium and includes several instructions to cause a microcontroller, chip, or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as a USB flash drive, a portable hard drive, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk.

[0088] Furthermore, various different implementations of the present invention can be combined arbitrarily, as long as they do not violate the spirit of the present invention, they should also be regarded as the content disclosed in the present invention.

Claims

1. A passive source surface wave data processing method based on wavefield separation, characterized in that: The method includes: The acquired raw noise data is preprocessed; Select the target segment signal from the preprocessed original noise data; Wavefield separation is performed on the target segment signal to obtain a noise signal with a single propagation direction; To obtain a surface wave signal with high signal-to-noise ratio by interferometric processing of a noise signal propagating in a single direction, the method includes: calculating the noise signal in a single propagation direction between two detectors; and processing the noise signal in a single propagation direction between the two detectors based on interferometry to obtain a surface wave signal with high signal-to-noise ratio. The calculation formula for processing noise signals in a single propagation direction between two detectors based on interferometry is as follows: ； In the formula, for B Point wave field, for A Point wave field; B The expression for a point wave field is: ； A The expression for a point wave field is: ； in, x n ′ For the first n The location of the earthquake source. x A for A Point of signal reception location, x B for B Point of signal reception location, n The number of earthquake focal points. For frequency, A For amplitude, R Indicates a right-traveling wave field. j The imaginary unit, K Wave number; Wavefield separation is performed on the target segment signal to obtain a noise signal with a single propagation direction, including: The target segment signal is transformed from the time-space domain to the frequency-wavenumber domain to obtain the frequency-wavenumber domain data of the target segment signal; the calculation formula for transforming the target segment signal from the time-space domain to the frequency-wavenumber domain is as follows: ； In the formula, f For frequency, k For wave number, t For time, x For the number of earthquake traces, i The imaginary unit, m For the time-space domain data of the target segment signal, M For the frequency-wavenumber domain data of the target segment signal; Remove unfavorable signals from the frequency-wavenumber domain data of the target segment signal and retain favorable signals; The favorable signal is transformed from the frequency-wavenumber domain to the time-space domain, resulting in a noise signal with a single propagation direction. The calculation formula for transforming the favorable signal from the frequency-wavenumber domain to the time-space domain is as follows: ； In the formula, m ′ represents the time-space domain data of the noise signal. M ′ represents the frequency-wavenumber domain data of the favorable signal. f For frequency, k For wave number, t For time, x For the number of earthquake traces, i It is the imaginary unit.

2. The passive source surface wave data processing method based on wavefield separation according to claim 1, characterized in that: The preprocessing includes at least one of filtering, resampling, and bad sector removal.

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