Interlayer multiple prediction method and device, electronic equipment and medium

Abstract

The invention discloses an interlayer multiple prediction method and device, electronic equipment and a medium. The method comprises the following steps: converting seismic data into a cylindrical coordinate system, and performing Fourier transform on data of the cylindrical coordinate system from a spatial domain to a frequency domain; bessel transformation is carried out on the frequency domain data in the radial direction, constant background speed offset is carried out on the wavenumber frequency domain data, and input data are obtained; calculating a vertical wave number according to the horizontal wave number of the polar radius so as to predict interlayer multiples; and performing progressive Bessel inverse transformation and Fourier inverse transformation on the interlayer multiples to return to a time-space domain, and obtaining data after the interlayer multiples are suppressed through an adaptive subtraction method. According to the method, the accurate phase and the approximate amplitude of the interlayer multiples can be predicted, and the interlayer multiples are effectively suppressed.

Description

Technical Field

[0001] The present invention relates to the field of geophysical exploration, and more specifically, to an interlayer multiple wave prediction method, device, electronic equipment and medium. Background Art

[0002] In marine and land seismic exploration, due to the existence of strong reflection interfaces on the seabed and underground, seismic waves are reflected multiple times on the seabed and between strong reflection interfaces to form interlayer multiple waves. The interlayer multiple waves and the primary reflection waves overlap and interfere with each other, which seriously reduces the resolution of seismic data, increases the difficulty of identifying effective waves, and affects the quality of seismic imaging and the authenticity and reliability of seismic interpretation. Therefore, attenuating or eliminating interlayer multiple waves is an important link in seismic data processing.

[0003] In order to eliminate the interference of multiple waves between layers and improve data resolution, the geophysical exploration community has proposed two types of multiple wave suppression methods: one is a filtering method based on the characteristic difference between the primary wave and the multiple waves; the other is a predictive subtraction method based on wave theory. The filtering method includes predictive deconvolution method, fk filtering method, Radon transform method, beam filtering method, etc. When the assumption conditions are well met, the filtering method can effectively attenuate or eliminate multiple waves, and the calculation amount is small, easy to implement, and efficient. However, the filtering method requires more underground assumption information. When the characteristic difference between the primary wave and the multiple waves is small or non-existent, it is difficult to obtain the ideal effect, and even the primary wave will be seriously damaged. The predictive subtraction method avoids the limitations of the filtering method and does not require prior information. It is the main development trend of the multiple wave suppression method. It mainly includes the feedback iteration method and the inverse scattering series method. For the suppression of interlayer multiple waves, the feedback iteration method requires certain manual intervention, and predicts the interlayer multiple waves by specifying the multiple wave generation layer layer by layer, while the inverse scattering series method is completely data-driven, without manual intervention, and predicts through the algorithm itself. It can predict all interlayer multiple waves at once, and is currently the most advanced interlayer multiple wave suppression method. However, this method has high data requirements and large calculation amount, and faces many problems in practical applications.

[0004] At present, there is still a need to develop an inter-layer multiple wave prediction method based on progressive Bessel transform.

[0005] The information disclosed in the background technology section of the present invention is only intended to deepen the understanding of the general background technology of the present invention, and should not be regarded as acknowledging or suggesting in any form that the information constitutes the prior art already known to those skilled in the art. Summary of the invention

[0006] The present invention proposes a method, device, electronic device and medium for predicting multiple waves between layers. Under the condition of one-dimensional approximation of underground medium, the algorithm is optimized and progressive Bessel transformation is performed through medium symmetry, so as to improve the calculation efficiency of the algorithm while ensuring the accuracy of multiple wave prediction. The improved algorithm maintains the superiority of the original method, is completely data-driven, and does not require a known underground velocity model.

[0007] In a first aspect, an embodiment of the present disclosure provides an inter-layer multiple wave prediction method, comprising:

[0008] Convert the seismic data into a cylindrical coordinate system, and perform Fourier transform on the cylindrical coordinate system data from the spatial domain to the frequency domain;

[0009] Performing Bessel transform on the frequency domain data in the radial direction and performing constant background velocity shift on the wavenumber frequency domain data to obtain input data;

[0010] The vertical wave number is calculated based on the horizontal wave number of the polar diameter, and then the interlayer multiple waves are predicted;

[0011] The interlayer multiple waves are subjected to progressive inverse Bessel transform and inverse Fourier transform to return to the time-space domain, and the data after the interlayer multiple waves are suppressed are obtained by adaptive subtraction method.

[0012] As a specific implementation of the embodiment of the present disclosure, the seismic data is converted to a cylindrical coordinate system by the following formula:

[0013]

[0014] in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

[0015] As a specific implementation of the embodiment of the present disclosure, Bessel transform is performed on the frequency domain data in the radial direction by the following formula:

[0016]

[0017] Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

[0018] As a specific implementation of the embodiment of the present disclosure, the vertical wave number is:

[0019]

[0020] Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e., the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

[0021] As a specific implementation of the embodiment of the present disclosure, the interlayer multiple waves are predicted by the following formula:

[0022]

[0023] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j (j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

[0024] As a specific implementation method of the embodiment of the present disclosure, the progressive inverse Bessel transform is:

[0025]

[0026] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0027] In a second aspect, the embodiments of the present disclosure further provide an inter-layer multiple wave prediction device, comprising:

[0028] A conversion module converts the seismic data into a cylindrical coordinate system and performs Fourier transformation on the cylindrical coordinate system data from the spatial domain to the frequency domain;

[0029] Bessel transform module, which performs Bessel transform on frequency domain data in radial direction and performs constant background velocity offset on wave number frequency domain data to obtain input data;

[0030] The prediction module calculates the vertical wave number based on the horizontal wave number of the polar diameter, and then predicts the interlayer multiple waves;

[0031] The inverse transformation module performs progressive Bessel inverse transformation and Fourier inverse transformation on the interlayer multiple waves to return to the time-space domain, and obtains the data after the interlayer multiple waves are suppressed by an adaptive subtraction method.

[0032] As a specific implementation of the embodiment of the present disclosure, the seismic data is converted to a cylindrical coordinate system by the following formula:

[0033]

[0034] in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

[0035] As a specific implementation of the embodiment of the present disclosure, Bessel transform is performed on the frequency domain data in the radial direction by the following formula:

[0036]

[0037] Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

[0038] As a specific implementation of the embodiment of the present disclosure, the vertical wave number is:

[0039]

[0040] Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

[0041] As a specific implementation of the embodiment of the present disclosure, the interlayer multiple waves are predicted by the following formula:

[0042]

[0043] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j(j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

[0044] As a specific implementation method of the embodiment of the present disclosure, the progressive inverse Bessel transform is:

[0045]

[0046] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0047] In a third aspect, an embodiment of the present disclosure further provides an electronic device, the electronic device comprising:

[0048] A memory storing executable instructions;

[0049] A processor runs the executable instructions in the memory to implement the inter-layer multiple wave prediction method.

[0050] In a fourth aspect, an embodiment of the present disclosure further provides a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the inter-layer multiple wave prediction method is implemented.

[0051] The methods and apparatus of the present invention have other features and advantages that will be apparent from, or will be described in detail in, the accompanying drawings and subsequent detailed descriptions incorporated herein, which together serve to explain the specific principles of the present invention. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] The above and other objects, features and advantages of the present invention will become more apparent through a more detailed description of exemplary embodiments of the present invention in conjunction with the accompanying drawings, wherein like reference numerals generally represent like components throughout the exemplary embodiments of the present invention.

[0053] Figure 1 A flow chart showing the steps of an inter-layer multiple wave prediction method according to an embodiment of the present invention.

[0054] Figure 2a , Figure 2b , Figure 2cSchematic diagrams of simulation data according to an embodiment of the present invention, interlayer multiple waves predicted based on conventional Bessel transform data, and interlayer multiple waves predicted based on progressive Bessel transform data are respectively shown.

[0055] Figure 3a , Figure 3b Schematic diagrams comparing the simulation data according to an embodiment of the present invention and the interlayer multiple waves predicted based on conventional and progressive Bessel transform data in the near path and far path are shown respectively.

[0056] Figure 4 A block diagram of an inter-layer multiple wave prediction device according to an embodiment of the present invention is shown.

[0057] Description of reference numerals:

[0058] 201, conversion module; 202, Bessel transform module; 203, prediction module; 204, inverse transform module. DETAILED DESCRIPTION

[0059] 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 to the embodiments set forth herein.

[0060] To facilitate understanding of the solutions and effects of the embodiments of the present invention, six specific application examples are given below. Those skilled in the art should understand that the examples are only for facilitating understanding of the present invention, and any specific details thereof are not intended to limit the present invention in any way.

[0061] Example 1

[0062] Figure 1 A flow chart showing the steps of an inter-layer multiple wave prediction method according to an embodiment of the present invention.

[0063] like Figure 1 As shown, the interlayer multiple wave prediction method includes: step 101, converting seismic data into a cylindrical coordinate system, performing Fourier transform on the cylindrical coordinate system data to transform from the space domain to the frequency domain; step 102, performing Bessel transform on the frequency domain data in the radial direction, performing constant background velocity offset on the wavenumber frequency domain data, and obtaining input data; step 103, calculating the vertical wave number according to the horizontal wave number of the polar radius, and then predicting the interlayer multiple waves; step 104, performing progressive Bessel inverse transform and Fourier inverse transform on the interlayer multiple waves to return to the time-space domain, and obtaining the data after the interlayer multiple waves are suppressed by the adaptive subtraction method.

[0064] In one example, seismic data is converted to a cylindrical coordinate system by:

[0065]

[0066] in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

[0067] In one example, the frequency domain data is Bessel transformed in the radial direction by the following formula:

[0068]

[0069] Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

[0070] In one example, the vertical wave number is:

[0071]

[0072] Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e., the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

[0073] In one example, the interlayer multiples are predicted by:

[0074]

[0075] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j (j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

[0076] In one example, the inverse progressive Bezier transform is:

[0077]

[0078] Among them, r hk is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0079] Specifically, the experiment assumed by the three-dimensional algorithm is a point source (three-dimensional source) and a three-dimensional underground medium, that is, the point source excites seismic waves on the ground, the wave field propagates to the three-dimensional medium underground and reflects back to the ground, and the seismic data of the wave field is received and recorded by a three-dimensional multi-line detector. In actual seismic exploration, sometimes the underground medium is approximately a horizontal layered structure, so it can be assumed that the underground medium is a one-dimensional medium. According to the symmetry of the data under the one-dimensional medium, the three-dimensional seismic data is only related to the offset and time, that is, At the same time, according to the spatial symmetry in the cylindrical coordinate system, the data can be transformed from the Cartesian rectangular coordinate system to the cylindrical coordinate system, that is, in and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source. In the cylindrical coordinate system, the three-dimensional inverse scattering series interlayer multiple wave prediction algorithm can be degenerated into the inverse scattering series interlayer multiple wave prediction algorithm for the one-dimensional medium of the three-dimensional point source:

[0080]

[0081] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium; ε s and ε g is the depth of the source and the receiver; z j (j=1,2,3) is the pseudo depth of constant background velocity imaging. b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain. In order to obtain the input data, the seismic data is first Fourier transformed and then Bessel transformed:

[0082]

[0083] where k rh For r h The Fourier conjugate variable of J0 is the Jacobian determinant. Finally, a constant background velocity offset is performed to obtain b1(k rh ,z). In order to transform to the data domain, the conventional method is to first perform an inverse Bessel transform to obtain the spatial frequency domain seismic data:

[0084]

[0085] The frequency is further inversely transformed by Fourier to obtain the seismic data after multiple wave suppression in the time and space domain. However, the inverse Bessel transform is computationally intensive, so the progressive inverse Bessel transform is used instead to improve computational efficiency:

[0086]

[0087] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0088] When approximating the one-dimensional underground medium, the three-dimensional inverse scattering series interlayer multiple wave prediction algorithm can be simplified, and multiple wave prediction is performed for each common center point gather, which reduces the number of integrals and improves the calculation efficiency. At the same time, when transforming the data forward and backward, the progressive Bessel transform is used to replace the original transformation, which improves the calculation efficiency while ensuring accuracy. The simplified algorithm maintains the advantages of the original algorithm, only needs to input seismic data, is completely data-driven, and does not require a known underground velocity model.

[0089] First, convert the seismic data into a common center point gather, then Fourier transform it into the frequency wavenumber domain and substitute it into Finally, the model data was processed to verify that this method is completely data-driven, does not require known underground structure and velocity models, can effectively predict the accurate phase and approximate amplitude of interlayer multiple waves, and provides a reliable multiple wave model for suppressing interlayer multiple waves.

[0090] Convert seismic data to cylindrical coordinates, perform Fourier transform on the cylindrical coordinates data from spatial domain to frequency domain; use Bessel transform is performed on the frequency domain data in the radial direction; constant background velocity offset is performed on the wavenumber frequency domain data; vertical wavenumber is calculated based on the horizontal wavenumber of the polar radius; and the wavenumber of the vertical direction is calculated using the wavenumber of the polar radius. Predict interlayer multiple waves; perform progressive inverse Bessel transform and inverse Fourier transform on the predicted interlayer multiple waves to return to the time-space domain; obtain the data after the interlayer multiple waves are suppressed by adaptive subtraction method.

[0091] Example 2

[0092] The present invention also provides an interlayer multiple wave prediction device, comprising:

[0093] A conversion module converts the seismic data into a cylindrical coordinate system and performs Fourier transformation on the cylindrical coordinate system data from the spatial domain to the frequency domain;

[0094] Bessel transform module, which performs Bessel transform on frequency domain data in radial direction and performs constant background velocity offset on wave number frequency domain data to obtain input data;

[0095] The prediction module calculates the vertical wave number based on the horizontal wave number of the polar diameter, and then predicts the interlayer multiple waves;

[0096] The inverse transformation module performs progressive Bessel inverse transformation and Fourier inverse transformation on the interlayer multiple waves back to the time and space domain, and obtains the data after the interlayer multiple waves are suppressed by the adaptive subtraction method.

[0097] In one example, seismic data is converted to a cylindrical coordinate system by:

[0098]

[0099] in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

[0100] In one example, the frequency domain data is Bessel transformed in the radial direction by the following formula:

[0101]

[0102] Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

[0103] In one example, the vertical wave number is:

[0104]

[0105] Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e., the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

[0106] In one example, the interlayer multiples are predicted by:

[0107]

[0108] Among them, krh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j (j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

[0109] In one example, the inverse progressive Bezier transform is:

[0110]

[0111] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0112] Specifically, the experiment assumed by the three-dimensional algorithm is a point source (three-dimensional source) and a three-dimensional underground medium, that is, the point source excites seismic waves on the ground, the wave field propagates to the three-dimensional medium underground and reflects back to the ground, and the seismic data of the wave field is received and recorded by a three-dimensional multi-line detector. In actual seismic exploration, sometimes the underground medium is approximately a horizontal layered structure, so it can be assumed that the underground medium is a one-dimensional medium. According to the symmetry of the data under the one-dimensional medium, the three-dimensional seismic data is only related to the offset and time, that is, At the same time, according to the spatial symmetry in the cylindrical coordinate system, the data can be transformed from the Cartesian rectangular coordinate system to the cylindrical coordinate system, that is, in and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source. In the cylindrical coordinate system, the three-dimensional inverse scattering series interlayer multiple wave prediction algorithm can be degenerated into the inverse scattering series interlayer multiple wave prediction algorithm for the one-dimensional medium of the three-dimensional point source:

[0113]

[0114] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium; εs and ε g is the depth of the source and the receiver; z j (j=1,2,3) is the pseudo depth of constant background velocity imaging. b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain. In order to obtain the input data, the seismic data is first Fourier transformed and then Bessel transformed:

[0115]

[0116] where k rh For r h The Fourier conjugate variable of J0 is the Jacobian determinant. Finally, a constant background velocity offset is performed to obtain b1(k rh ,z). In order to transform to the data domain, the conventional method is to first perform an inverse Bessel transform to obtain the spatial frequency domain seismic data:

[0117]

[0118] The frequency is further inversely transformed by Fourier to obtain the seismic data after multiple wave suppression in the time and space domain. However, the inverse Bessel transform is computationally intensive, so the progressive inverse Bessel transform is used instead to improve computational efficiency:

[0119]

[0120] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0121] When approximating the one-dimensional underground medium, the three-dimensional inverse scattering series interlayer multiple wave prediction algorithm can be simplified, and multiple wave prediction is performed for each common center point gather, which reduces the number of integrals and improves the calculation efficiency. At the same time, when transforming the data forward and backward, the progressive Bessel transform is used to replace the original transformation, which improves the calculation efficiency while ensuring accuracy. The simplified algorithm maintains the advantages of the original algorithm, only needs to input seismic data, is completely data-driven, and does not require a known underground velocity model.

[0122] First, convert the seismic data into a common center point gather, then Fourier transform it into the frequency wavenumber domain and substitute it into Finally, the model data was processed to verify that this method is completely data-driven, does not require known underground structure and velocity models, can effectively predict the accurate phase and approximate amplitude of interlayer multiple waves, and provides a reliable multiple wave model for suppressing interlayer multiple waves.

[0123] Convert seismic data to cylindrical coordinates, perform Fourier transform on the cylindrical coordinates data from spatial domain to frequency domain; use Bessel transform is performed on the frequency domain data in the radial direction; constant background velocity offset is performed on the wavenumber frequency domain data; vertical wavenumber is calculated based on the horizontal wavenumber of the polar radius; and the wavenumber of the vertical direction is calculated using the wavenumber of the polar radius. Predict interlayer multiple waves; perform progressive inverse Bessel transform and inverse Fourier transform on the predicted interlayer multiple waves to return to the time-space domain; obtain the data after the interlayer multiple waves are suppressed by adaptive subtraction method.

[0124] Example 3

[0125] Figure 2a , Figure 2b , Figure 2c Schematic diagrams of simulation data according to an embodiment of the present invention, interlayer multiple waves predicted based on conventional Bessel transform data, and interlayer multiple waves predicted based on progressive Bessel transform data are respectively shown.

[0126] Figure 3a , Figure 3b Schematic diagrams comparing the simulation data according to an embodiment of the present invention and the interlayer multiple waves predicted based on conventional and progressive Bessel transform data in the near path and far path are shown respectively.

[0127] According to the one-dimensional underground medium assumption of this method, the simulation data is generated by a layered model. The model has two reflection interfaces at 100m and 150m respectively, the source and the detector are at 0m on the surface, and the source uses a Ricker wavelet with a main frequency of 25Hz, with a total of 301 channels, a channel spacing of 5m, a sampling interval of 0.001s, and a recording time of 0.5s. Figure 2a For simulation data, there are three events, namely the first primary wave, the second primary wave, and the first-order inter-order multiple waves. Figure 2b is the interlayer multiple wave predicted based on conventional Bessel transform data, Figure 2c The interlayer multiple waves predicted based on the progressive Bessel transform data. It can be seen that both can predict the accurate phase and very close amplitude of the multiple waves, providing a prepared multiple wave model for eliminating the interlayer multiple waves. The amount of data calculation based on the progressive Bessel transform is reduced, which improves the calculation efficiency. In order to further compare the waveform and amplitude, from Figure 2a-2c The multiple wave parts of the near and far paths in the data are selected for comparison. Figure 3a and Figure 3bThe comparison of interlayer multiple waves predicted by simulation data, conventional and progressive Bessel transform data in the near and far paths, respectively. The red line represents the simulation data, the green line represents the interlayer multiple waves predicted based on conventional Bessel transform data, and the blue dotted line represents the interlayer multiple waves predicted based on progressive Bessel transform data. It can be seen that the travel time of the interlayer multiple waves predicted by both in the near and far paths is completely accurate, and the predicted amplitude of the interlayer multiple waves is close to the original data. During the test, only simulation data needs to be input without the need for a known velocity model. The test data results verify the accuracy of the prediction of interlayer multiple waves based on progressive Bessel transform data in a one-dimensional underground medium with a three-dimensional point source. The processing results of the model data verify that this method can predict the accurate phase and approximate amplitude of interlayer multiple waves, and effectively suppress interlayer multiple waves.

[0128] Example 4

[0129] Figure 4 A block diagram of an inter-layer multiple wave prediction device according to an embodiment of the present invention is shown.

[0130] like Figure 4 As shown, the interlayer multiple wave prediction device comprises:

[0131] The conversion module 201 converts the seismic data into a cylindrical coordinate system and performs a Fourier transform on the cylindrical coordinate system data from the spatial domain to the frequency domain;

[0132] Bessel transformation module 202, performs Bessel transformation on the frequency domain data in the radial direction, performs constant background velocity shift on the wave number frequency domain data, and obtains input data;

[0133] Prediction module 203, calculates the vertical wave number according to the horizontal wave number of the polar diameter, and then predicts the interlayer multiple waves;

[0134] The inverse transformation module 204 performs progressive inverse Bessel transformation and inverse Fourier transformation on the interlayer multiple waves to return to the time-space domain, and obtains the data after the interlayer multiple waves are suppressed by an adaptive subtraction method.

[0135] As a specific implementation of the embodiment of the present disclosure, the seismic data is converted to a cylindrical coordinate system by the following formula:

[0136]

[0137] in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

[0138] As a specific implementation of the embodiment of the present disclosure, Bessel transform is performed on the frequency domain data in the radial direction by the following formula:

[0139]

[0140] Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

[0141] As a specific implementation of the embodiment of the present disclosure, the vertical wave number is:

[0142]

[0143] Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

[0144] As a specific implementation of the embodiment of the present disclosure, the interlayer multiple waves are predicted by the following formula:

[0145]

[0146] Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j (j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

[0147] As a specific implementation method of the embodiment of the present disclosure, the progressive inverse Bessel transform is:

[0148]

[0149] Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

[0150] Example 5

[0151] The present disclosure provides an electronic device, which includes: a memory storing executable instructions; and a processor, which runs the executable instructions in the memory to implement the above-mentioned inter-layer multiple wave prediction method.

[0152] An electronic device according to an embodiment of the present disclosure includes a memory and a processor.

[0153] The memory is used to store non-temporary 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 (cache), etc. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, etc.

[0154] The processor may be a central processing unit (CPU) or other forms of processing units having 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 present disclosure, the processor is used to run the computer-readable instructions stored in the memory.

[0155] Those skilled in the art should be able to understand that in order to solve the technical problem of how to obtain a good user experience, the present embodiment may also include well-known structures such as a communication bus and an interface, and these well-known structures should also be included in the protection scope of the present disclosure.

[0156] For detailed description of this embodiment, reference may be made to the corresponding descriptions in the aforementioned embodiments, which will not be repeated here.

[0157] Example 6

[0158] The embodiment of the present disclosure provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the inter-layer multiple wave prediction method is implemented.

[0159] According to the computer-readable storage medium of the embodiment of the present disclosure, non-transitory computer-readable instructions are stored thereon. When the non-transitory computer-readable instructions are executed by a processor, all or part of the steps of the method of each embodiment of the present disclosure are executed.

[0160] The above-mentioned 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 mobile hard disk), media with built-in rewritable non-volatile memory (e.g., memory card) and media with built-in ROM (e.g., ROM box).

[0161] Those skilled in the art should understand that the purpose of the above description of the embodiments of the present invention is only to exemplarily illustrate the beneficial effects of the embodiments of the present invention, and is not intended to limit the embodiments of the present invention to any given examples.

[0162] The embodiments of the present invention have been described above, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes will be apparent to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A method for predicting interlayer multiple waves, characterized in that: include: Convert the seismic data into a cylindrical coordinate system, and perform Fourier transform on the cylindrical coordinate system data from the spatial domain to the frequency domain; Performing Bessel transform on the frequency domain data in the radial direction and performing constant background velocity shift on the wavenumber frequency domain data to obtain input data; The vertical wave number is calculated based on the horizontal wave number of the polar diameter, and then the interlayer multiple waves are predicted; The interlayer multiple waves are subjected to progressive inverse Bessel transform and inverse Fourier transform to return to the time-space domain, and the data after the interlayer multiple waves are suppressed are obtained by adaptive subtraction method.

2. The method for predicting interlayer multiple waves according to claim 1, wherein: The seismic data is converted to the cylindrical coordinate system by the following formula: in, and are the horizontal positions of the source and the detector, respectively, h is the horizontal distance between the detector and the source.

3. The method for predicting interlayer multiple waves according to claim 1, wherein: The frequency domain data is transformed in the radial direction by the following formula: Among them, b1(k rh ,ω) is the wave number frequency domain data, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e. the horizontal wave number, ω is the circular frequency, and J0 is the Jacobian determinant.

4. The interlayer multiple wave prediction method according to claim 1, wherein: The vertical wave number is: Among them, k rh is the horizontal distance r between the detector and the source h is the Fourier conjugate variable of , i.e., the horizontal wave number, ω is the circular frequency, and c0 is the water velocity in the background medium.

5. The interlayer multiple wave prediction method according to claim 1, wherein: The interlayer multiples are predicted by the following equation: Among them, k rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable is the horizontal wave number, q is the vertical wave number, ω is the circular frequency, i is the imaginary unit, c0 is the water velocity in the background medium, ε s and ε g is the depth of the source and receiver, z j (j=1,2,3) is the pseudo depth of constant background velocity imaging, b1 is the plane wave field of the common center point seismic data D in the pseudo depth domain, and b3 is the first-order inter-layer multiple wave data predicted in the common center point domain.

6. The inter-layer multiple wave prediction method according to claim 1, wherein: The progressive inverse Bessel transform is: Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

7. An interlayer multiple wave prediction device, characterized in that: include: A conversion module converts the seismic data into a cylindrical coordinate system and performs Fourier transformation on the cylindrical coordinate system data from the spatial domain to the frequency domain; Bessel transform module, which performs Bessel transform on frequency domain data in radial direction and performs constant background velocity offset on wave number frequency domain data to obtain input data; The prediction module calculates the vertical wave number based on the horizontal wave number of the polar diameter, and then predicts the interlayer multiple waves; The inverse transformation module performs progressive Bessel inverse transformation and Fourier inverse transformation on the interlayer multiple waves to return to the time-space domain, and obtains the data after the interlayer multiple waves are suppressed by an adaptive subtraction method.

8. The inter-layer multiple wave prediction device according to claim 7, wherein: The progressive inverse Bessel transform is: Among them, r h k is the horizontal distance between the detector and the source, rh is the horizontal distance r between the detector and the source h The Fourier conjugate variable of , i.e. the horizontal wave number, is the vertical wave number.

9. An electronic device, characterized in that: The electronic device comprises: A memory storing executable instructions; A processor, wherein the processor runs the executable instructions in the memory to implement the inter-layer multiple wave prediction method according to any one of claims 1 to 6.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the inter-layer multiple wave prediction method according to any one of claims 1 to 6 is implemented.

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