A method and apparatus, system, storage medium for extracting scholte wave attenuation coefficients

Abstract

The application discloses a method and device for extracting Scholte wave attenuation coefficients, a system and a storage medium, and comprises the following steps: collecting seabed seismic data of an observation area; obtaining a pretreated common-receiver gather based on the seabed seismic data of the observation area; based on the CRG gather data in the SU format pretreated by the seabed seismograph, using high-resolution forward and inverse transformation, separating and extracting the base-order CRG gather with energy focusing and single order from the CRG gather coupled and stacked by multiple-order Scholte waves; based on the base-order CRG seismic gather, calculating the attenuation coefficients of any two gathers, and after the cyclic calculation of all gather pairs is completed, the average attenuation coefficient model corresponding to the gather pair is obtained. By using the technical scheme of the application, the Scholte wave dispersion order can be accurately separated, and the base-order attenuation coefficient can be specially extracted.

Description

Technical Field

[0001] This invention belongs to the field of marine seismic exploration technology, specifically relating to a method, apparatus, system, and storage medium for extracting Scholte wave attenuation coefficients, used to stably extract reliable Scholte wave (interface wave propagating at the seabed interface) attenuation coefficients from airgun source signals recorded by an Ocean Bottom Seismometer (OBS). Background Technology

[0002] In marine sediment surveys and the construction of seafloor acoustic parameter models, it is essential to obtain reliable attenuation characteristics of shallow sedimentary layers and the shallow spheres of the solid Earth beneath the seafloor interface, i.e., the quality factor of the medium. Traditional acoustic surveys can obtain high-frequency seafloor sediment attenuation parameters, but obtaining ultra-low frequency (e.g., <10Hz) attenuation parameters is difficult, mainly because the decrease in detection frequency leads to an increase in sound wave wavelength, resulting in larger traditional acoustic detection devices and greater challenges in equipment integration and offshore operations. Developing an attenuation imaging method based on seafloor interface waves (Scholte waves) recorded by seafloor seismometers can overcome the aforementioned difficulties and limitations of acoustic detection.

[0003] Scholte waves are elastic waves generated by seismic sources such as air guns and propagating at the seabed-seabed sediment interface in marine seismic exploration. Their propagation characteristics (such as phase velocity, group velocity, and attenuation) are extremely sensitive to the physical properties of seabed sediments (such as shear wave velocity, density, and viscoelasticity). Their main frequency band is focused on low frequencies (for active-source air gun sources, the Scholte wave frequency band recorded in shallow sedimentary layers is generally less than 10 Hz), and the quality factor of the seabed sediment can be obtained through seismic methods. The first and most crucial step in inverting the quality factor is to extract reliable and stable attenuation coefficients from the common receiver points of the seabed seismometers excited by the air gun source. Therefore, using Scholte waves to invert the quality factor (Q value) or attenuation coefficient of the seabed medium is of great significance for marine engineering geological exploration, seabed resource exploration, and geophysical model construction.

[0004] Currently, methods for extracting surface wave attenuation coefficients from active-source seismic data largely borrow from those used in terrestrial seismology, such as the amplitude-distance attenuation method. However, these methods face two main challenges when applied to OBS airgun data. First, there is the issue of multi-mode aliasing. In seabed structures containing low-velocity layers, excited Scholte waves typically contain multiple propagation modes, including the fundamental and higher-order modes. These modes superimpose in the time-frequency domain, and their amplitude spectrum is the result of the combined effect of all modes. If these modes are not separated, directly using the amplitude of the mixed wavefield for attenuation calculations will lead to severe distortion of the extracted attenuation coefficients, failing to accurately reflect the shallow sediment characteristics represented by the fundamental mode. Second, there are the effects of source and geometric diffusion. The energy of an airgun source is not isotropic, and the wavefront undergoes geometric diffusion during propagation. These factors can mask the inherent amplitude attenuation caused by medium absorption.

[0005] Existing research lacks methods for estimating attenuation of Scholte waves based on airgun sources from seafloor seismometers. The core reason is the failure to effectively address issues such as multi-mode separation and attenuation coefficient extraction, leading to low reliability and poor applicability of subsequent inversion results. Therefore, developing a method capable of accurately separating the dispersion orders of Scholte waves and specifically extracting the fundamental attenuation coefficient is a pressing technical problem in this field. Summary of the Invention

[0006] To address the problems existing in the prior art, this invention provides a method, apparatus, system, and storage medium for extracting the Scholte wave attenuation coefficient. This solves the problem of effectively extracting the attenuation coefficient—the first step in the quality factor inversion of shallow sedimentary layers or seabed sediments in marine geological engineering surveys. This attenuation coefficient extraction method can be applied to large-area geological surveys of shallow sedimentary layers in marine geological engineering, providing a technical possibility for rapid and efficient regional marine geological engineering surveys. Furthermore, it can provide an important shallow prior model for medium quality factors in marine multi-wave, multi-component seismic exploration.

[0007] To achieve the above objectives, the present invention provides the following solution: A method for extracting the attenuation coefficient of Scholte waves includes: Collect submarine seismic data in the observation area; Based on the submarine seismic data of the observation area, the preprocessed common receiver point gather was obtained; Based on CRG gather data in SU format preprocessed by the seabed seismograph, high-resolution pull-forward and inverse transformations are used to separate and extract the basic order CRG gather with focused energy and single order from the CRG gather coupled and superimposed with multiple Scholte waves. Based on the basic CRG seismic gathers, the attenuation coefficients of any two gathers are calculated. After iterative calculation of all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

[0008] As a preferred option, the seafloor seismic data for the observation area includes: the location of the seafloor seismometer deployment, the location of the air gun source activation, the time interval between air gun source activations, and the location of the starting point of the survey line.

[0009] As a preferred method, based on the excitation location and time information of the air gun source, the common receiver point seismic gather is extracted from the continuous data sequence of the seabed seismometer, and the original data format is converted into SU data format. Preprocessing such as clock correction, trace equalization and bandpass filtering are then performed to obtain the preprocessed common receiver point gather.

[0010] The present invention also provides a device for extracting the Scholte wave attenuation coefficient, comprising: The first processing module is used to collect submarine seismic data in the observation area; The second processing module is used to obtain the preprocessed common receiver point gather based on the seafloor seismic data of the observation area; The third processing module is used to preprocess SU format CRG gather data based on the seafloor seismograph, and use high resolution to pull forward and inverse transformations to separate and extract the energy-focused, single-order basic CRG gathers from the multi-order Scholte wave coupled and superimposed CRG gathers. The fourth processing module is used to calculate the attenuation coefficient of any two traces based on the basic order CRG seismic gathers. After iteratively calculating all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

[0011] As a preferred option, the seafloor seismic data for the observation area includes: the location of the seafloor seismometer deployment, the location of the air gun source activation, the time interval between air gun source activations, and the location of the starting point of the survey line.

[0012] As a preferred embodiment, the second processing module extracts common receiver point seismic gathers from the continuous data sequence of the seabed seismograph based on the excitation location and time information of the air gun source, converts the original data format to SU data format, and performs preprocessing such as clock correction, trace equalization and bandpass filtering to obtain the preprocessed common receiver point gathers.

[0013] The present invention also provides a system for extracting the Scholte wave attenuation coefficient, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes a method for extracting the Scholte wave attenuation coefficient when executed by the processor.

[0014] The present invention also provides a storage medium storing a computer program, which executes a method for extracting the Scholte wave attenuation coefficient when running.

[0015] Compared with the prior art, the beneficial effects of the present invention are as follows: First, it boasts high precision and high reliability. By first separating the fundamental Scholte wave and then performing attenuation analysis, it fundamentally eliminates the contamination of amplitude information by higher-order mode aliasing, enabling the final extracted attenuation coefficient α(f) to truly and accurately reflect the attenuation characteristics of shallow seabed sediments.

[0016] Second, it has strong anti-interference capabilities. The calculation between any two stages in the method can effectively eliminate the geometric diffusion effect, effectively eliminate the amplitude attenuation caused by non-medium absorption factors, and improve the physical meaning and reliability of the results.

[0017] Third, it has wide applicability. This invention can be directly applied to seafloor seismograph and airgun source data widely collected in conventional marine seismic exploration. No special acquisition process is required, and it is easy to promote in actual production and scientific research, providing higher quality methods and technologies for seafloor engineering geological evaluation and geophysical modeling. Attached Figure Description

[0018] To more clearly illustrate the technical solution of the present invention, the drawings used in the embodiments are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0019] Figure 1 This is a flowchart of the method for extracting the Scholte wave attenuation coefficient according to an embodiment of the present invention; Figure 2 This is a schematic diagram of the observation system and attenuation coefficient extraction points of the present invention; wherein, Locations for deploying submarine seismic observation equipment and instruments. This is the starting point for the air gun's vibration source. The endpoint of the air gun's excitation source. The distance between the air gun firing point and the firing point. The offset distance of the air gun's excitation gather. Observation point (i.e., the location corresponding to the average attenuation coefficient model result). Detailed Implementation

[0020] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0021] To make the above-mentioned objects, features and advantages of the present invention more apparent and understandable, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0022] Example 1 like Figure 1 As shown, this invention provides a method for extracting the Scholte wave attenuation coefficient, comprising: Step 101: Design the seabed seismic data acquisition system for the observation area, including the deployment locations of seabed seismometers, the excitation locations of air gun sources, the excitation time intervals of air gun sources, and the starting point of the survey line. Then, conduct marine seismic operations according to the observation system, specifically including the deployment of seabed seismometers, the firing of air guns, the retrieval of seabed seismometers, and the recovery of seabed seismometer data.

[0023] Step 102: Based on the excitation location and time information of the air gun source, extract the common receiver point seismic gather from the continuous data sequence of the seabed seismometer, convert the original data format to SU (Seismic Unix) data format, and complete preprocessing such as clock correction, channel equalization and bandpass filtering to obtain the preprocessed common receiver point gather (CRG gather).

[0024] Step 103: Based on the preprocessing of SU format CRG gather data by the seabed seismograph, the basic order CRG gather with focused energy and single order is separated and extracted from the multi-order Scholte wave coupled and superimposed CRG gather using high-resolution pull-forward and inverse transformation.

[0025] Step 104: Based on the basic CRG seismic gathers, the attenuation coefficients of any two gathers can be calculated. After iteratively calculating all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

[0026] Step 105: Save the output attenuation coefficient model as the input model for the next step of inverting the quality factor of the seabed sediment or shallow sedimentary layer.

[0027] In step 101 above, with Figure 2 Taking an example, to obtain the points in the diagram The attenuation coefficient of the Scholte wave at the point of origin requires first setting the start and end points of the airgun excitation source. The start point of the airgun excitation source is related to the minimum offset of the seismic gather, generally taken as a minimum of 500m, to eliminate the problem of Scholte wave and body wave superposition and coupling that cannot be extracted due to close offset, and the minimum offset must be greater than the maximum wavelength of the Scholte wave; the end point of the airgun involves the maximum offset of the seismic gather, generally taken as 2500m, a large offset will improve the resolution of dispersive energy imaging and mode separation. Finally, the deployment depth of the airgun and the distance between the excitation points are designed. The airgun deployment depth ranges from 5-10m, depending on the operating vessel, sea state, and airgun equipment, and the distance between the excitation points is... The following formula must be satisfied: in, For the minimum Scholte wave phase velocity, Extract the maximum frequency for the attenuation coefficient.

[0028] In step 103 above, the method for separating the fundamental Scholte wave CRG gather from the preprocessed CRG gather is as follows. Specifically, it includes: (1) constructing a high-resolution dispersion spectrum model in the Radon domain (also known as the τ-p domain); (2) manually truncating the fundamental energy in the high-resolution model; and (3) inversely transforming the high-resolution linear Radon transform result back to the spatiotemporal domain (also known as the τ-p domain). - domain).

[0029] For (1) the construction of the high-resolution dispersion spectrum model in the Radon domain, the problem is first defined and the matrix is ​​constructed. The extraction process of dispersion imaging is expressed as a linear inversion problem: in: This is an observation data vector. It consists of a specific frequency. Below, a one-dimensional vector is formed by arranging the amplitude (or envelope) values ​​of the empirical Green's function between all station pairs. Its dimension is... ,in It refers to the number of stations. This is the model parameter vector. It represents the phase velocities at a preset range. Above, at that frequency The corresponding energy (or weight) value. Its dimension is... The problem of constructing a dispersive energy spectrum is now transformed into this. Solving for matrices. This is the kernel matrix (positive operator). Its elements... Determined by the theoretical dispersion relation. For the first... Each station pair (spacing is) ) and the Phase velocity Its value is: in, It is a zero-order Bessel function of the first kind, which describes the fundamental Scholte wave in a homogeneous medium at a phase distance of [missing information]. The theoretical response between two points. Matrix The dimension is .

[0030] The following step requires introducing high-resolution constraints (a crucial step), as direct solution... It is unstable and has low resolution. High-resolution methods obtain solutions by solving a constrained least-squares problem: This introduces two key covariance matrices. The first is the data covariance matrix. Used to characterize observation data The uncertainty or noise level of each data point. It can usually be assumed that the data errors are uncorrelated and have the same variance, therefore... It can be simplified to an identity matrix. Multiply by a constant (e.g.) This constant is canceled out or normalized during the minimization process, therefore it is often used in practical calculations. The alternative is the model covariance matrix. It is key to building a "high-resolution" dispersion spectrum model, and it is used to describe the model parameters. The correlation between different velocity points. The solution for the final dispersion spectrum is expected to be sparse, that is, the energy is concentrated only at a few "correct" velocity points.

[0031] To improve the energy resolution of the dispersion spectrum, an iterative reweighting strategy is adopted to construct... Instead of using a fixed covariance matrix, let... In the first iteration, let... (Identity matrix). This is equivalent to performing a traditional, unrestricted least-squares inversion to obtain an initial, lower-resolution model. Subsequent iterations In the middle, the model obtained from the previous iteration is used. To construct a new model covariance matrix . It is usually constructed as a diagonal matrix, whose diagonal elements are Functions: in, It is the th in the previous iteration Model values ​​for each velocity point. It is a very small positive number used to prevent the denominator from being zero and to ensure numerical stability. This construction method means that if a certain velocity point had a large energy in the previous iteration ( If the value is large, then in this iteration, it is in The corresponding weights will decrease. According to the properties of the least squares method, this is equivalent to relaxing the constraint on that point, allowing it to absorb more energy in this iteration. Conversely, for points with low energy, the constraint will become tighter, making it more difficult for them to grow. After several iterations, the energy will become increasingly concentrated at the true phase velocity location, resulting in a very "sharp" and high-resolution model.

[0032] To obtain the complete dispersive energy spectrum, it is only necessary to consider the above single frequency points. This can be extended to iterative calculation of all frequency points. Generally, this needs to be done over a wide frequency range (e.g., 1 Hz to 10 Hz) with small frequency intervals (typically 0.1 Hz), repeating the entire process. Finally, combining the inversion results of all frequency points yields a high-resolution frequency-phase velocity spectrum.

[0033] For step (2) of step 103, the fundamental energy in the high-resolution model is manually extracted. From the obtained high-resolution frequency-phase velocity spectrum, the fundamental energy spectrum generally has strong energy and the lowest velocity. Within the constructed frequency range, the peak points of the Scholte wave dispersion energy spectrum are continuous, and the velocity decreases with frequency. The peak points of the dispersion energy spectrum of each order correspond to the dispersion curve of that order. Due to the high resolution, energy clusters of different orders (such as the fundamental and first order) will be well separated, so the energy spectrum of the fundamental order can be "picked" manually or automatically to achieve "order separation" of the dispersion energy spectrum, that is, setting all energy spectrum values ​​other than the fundamental order to 0.

[0034] For step (3) in step 103, the high-resolution linear Radon transform result is inversely transformed back to the spatiotemporal domain. Specifically, for the above high-resolution Radon transform model with non-basic orders removed... It contains each frequency and each phase velocity c (or slowness) The energy value on the frequency-phase velocity domain. Its corresponding spatiotemporal frequency-offset data It can be synthesized using the following formula: in, This is a zero-order Bessel function of the first kind. The core of this equation is that, for a certain offset in the space-time domain... The wave field at that point is a linear superposition of all plane waves with different slowness (i.e., different plane waves), and the shape of each plane wave is determined by the Bessel function. describe.

[0035] In practice, an inverse transform is first performed based on frequency. Since the entire process is conducted in the frequency domain, an inverse transform needs to be performed independently for each frequency, cyclically repeating the process for each frequency. From the results of high-resolution Radon transform In, extract the frequency The next slice. This is a one-dimensional vector containing the energy value m corresponding to all phase velocities at this frequency. First, loop through each offset. (i.e., the spacing between each gun pair), for a given ( , ), calculate kernel function This will result in a one-dimensional vector whose length is related to the phase velocity. The number is the same. Complete this frequency. All offset distances After calculation, a frequency slice is obtained from the inverse-transformed frequency-offset spectrum. Repeat the above steps until all frequencies have been processed. .

[0036] Finally, converting back to the spacetime domain, we now have a two-dimensional array. However, this is still frequency domain data and needs to be converted back to the familiar spatiotemporal domain seismic gathers. For each offset distance Perform inverse Fourier transform: that is, from The offset distance is taken from the middle. This is a frequency sequence. Perform an inverse Fourier transform on this complex sequence. The real part obtained is the offset. Corresponding spatiotemporal domain seismic traces Repeat the above steps for all offsets. The process is then performed. Ultimately, a two-dimensional array is obtained. That is, the basic order spatiotemporal domain CRG seismic gather is obtained by removing the non-basic order (only retaining the basic order) from the Radon transform dispersion spectrum model and then performing an inverse transform.

[0037] In step 104 above, based on the basic-order CRG seismic gather, the attenuation coefficients of any two traces can be calculated. The calculation method is as follows: in, The offset distance is The amplitude, This represents the spacing between two traces. The calculation is repeated iteratively to complete all trace gather pairs. back( (For the Dao Collection sequence number), obtain the corresponding position of that Dao Collection. Average attenuation coefficient model: in, The total number of Dao set indexes.

[0038] Example 2 The present invention also provides a device for extracting the Scholte wave attenuation coefficient, comprising: The first processing module is used to collect submarine seismic data in the observation area; The second processing module is used to obtain the preprocessed common receiver point gather based on the seafloor seismic data of the observation area; The third processing module is used to preprocess SU format CRG gather data based on the seafloor seismograph, and use high resolution to pull forward and inverse transformations to separate and extract the energy-focused, single-order basic CRG gathers from the multi-order Scholte wave coupled and superimposed CRG gathers. The fourth processing module is used to calculate the attenuation coefficient of any two traces based on the basic order CRG seismic gathers. After iteratively calculating all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

[0039] As one embodiment of the present invention, the seafloor seismic data of the observation area includes: the deployment location of the seafloor seismograph, the excitation location of the air gun source, the excitation time interval of the air gun source, and the location of the starting point of the survey line.

[0040] As one embodiment of the present invention, the second processing module extracts the common receiver point seismic gather from the continuous data sequence of the seabed seismograph based on the excitation location and time information of the air gun source, converts the original data format to SU data format, and performs preprocessing such as clock correction, channel equalization processing and bandpass filtering to obtain the preprocessed common receiver point gather.

[0041] Example 3 The present invention also provides a system for extracting the Scholte wave attenuation coefficient, comprising: a memory and a processor, wherein the memory stores a computer program executed by the processor, and the computer program executes a method for extracting the Scholte wave attenuation coefficient when executed by the processor.

[0042] Example 4 The present invention also provides a storage medium storing a computer program, which executes a method for extracting the Scholte wave attenuation coefficient when running.

[0043] The embodiments described above are merely preferred embodiments of the present invention and are not intended to limit the scope of the present invention. Various modifications and improvements made to the technical solutions of the present invention by those skilled in the art without departing from the spirit of the present invention should fall within the protection scope defined by the claims of the present invention.

Claims

1. A method for extracting the attenuation coefficient of a Scholte wave, characterized in that, include: Collect submarine seismic data in the observation area; Based on the submarine seismic data of the observation area, the preprocessed common receiver point gather was obtained; Based on CRG gather data in SU format preprocessed by the seabed seismograph, high-resolution pull-forward and inverse transformations are used to separate and extract the basic order CRG gather with focused energy and single order from the CRG gather coupled and superimposed with multiple Scholte waves. Based on the basic CRG seismic gathers, the attenuation coefficients of any two gathers are calculated. After iterative calculation of all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

2. The method for extracting the Scholte wave attenuation coefficient as described in claim 1, characterized in that, The seafloor seismic data for the observation area includes: the location of the seafloor seismometer deployment, the location of the air gun source activation, the time interval between air gun source activations, and the location of the starting point of the survey line.

3. The method for extracting the Scholte wave attenuation coefficient as described in claim 1, characterized in that, Based on the excitation location and time information of the air gun source, the seismic gather of common receiving points is extracted from the continuous data sequence of the seabed seismometer, and the original data format is converted into SU data format. It also performs preprocessing such as clock correction, channel equalization, and bandpass filtering to obtain the preprocessed common receiver point gather.

4. A device for extracting the attenuation coefficient of a Scholte wave, characterized in that, include: The first processing module is used to collect submarine seismic data in the observation area; The second processing module is used to obtain the preprocessed common receiver point gather based on the seafloor seismic data of the observation area; The third processing module is used to preprocess SU format CRG gather data based on the seafloor seismograph, and use high resolution to pull forward and inverse transformations to separate and extract the energy-focused, single-order basic CRG gathers from the multi-order Scholte wave coupled and superimposed CRG gathers. The fourth processing module is used to calculate the attenuation coefficient of any two traces based on the basic order CRG seismic gathers. After iteratively calculating all gather pairs, the average attenuation coefficient model corresponding to that gather is obtained.

5. The apparatus for extracting the Scholte wave attenuation coefficient as described in claim 4, characterized in that, The seafloor seismic data for the observation area includes: the location of the seafloor seismometer deployment, the location of the air gun source activation, the time interval between air gun source activations, and the location of the starting point of the survey line.

6. The apparatus for extracting the Scholte wave attenuation coefficient as described in claim 5, characterized in that, The second processing module extracts common receiver seismic gathers from the continuous data sequence of the seabed seismograph based on the excitation location and time information of the air gun source, and converts the original data format into SU data format. It also performs preprocessing such as clock correction, channel equalization, and bandpass filtering to obtain the preprocessed common receiver point gather.

7. A system for extracting the attenuation coefficient of a Scholte wave, characterized in that, include: A memory and a processor, wherein the memory stores a computer program executed by the processor, the computer program, when executed by the processor, performs the method for extracting the Scholte wave attenuation coefficient as described in any one of claims 1-3.

8. A storage medium, characterized in that, The storage medium stores a computer program that, when executed, performs the method for extracting the Scholte wave attenuation coefficient as described in any one of claims 1-3.

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