A noise suppression method, system, storage medium and electronic device

Abstract

This application relates to the field of seismic data processing, and specifically relates to a noise suppression method, system, device and electronic device, which solves the problem that it is difficult to suppress Schulte waves and water layer waves in seismic data in the prior art. The method includes: preprocessing the seismic data; determining the weighting coefficient of the Schulte waves in the seismic data based on the preprocessed seismic data; determining the first polarization characteristic information of the seismic data based on the weighting coefficient of the Schulte waves; suppressing the Schulte waves in the seismic data based on the first polarization characteristic information of the seismic data; determining the weighting coefficient of the water layer waves in the seismic data based on the seismic data after suppressing the Schulte waves; determining the second polarization characteristic information of the seismic data based on the weighting coefficient of the water layer waves; suppressing the water layer waves in the seismic data based on the second polarization characteristic information of the seismic data to obtain a seismic signal after suppressing noise.

Description

Technical Field

[0001] The present application relates to the technical field of seismic data processing, and particularly to a noise suppression method, system, storage medium and electronic device. Background Art

[0002] In shallow sea seismic exploration, Schulte waves and water layer waves are two common types of noise. Among them, Schulte waves have characteristics such as low frequency, low velocity, dispersion, and strong energy, while water layer waves have characteristics such as wide frequency band and strong energy. In marine exploration, when far from the water-solid interface, the energy of Schulte waves attenuates faster in the water layer than in the solid medium. Therefore, the amplitude of Schulte waves in hydrophones mainly sensing the water layer pressure will be much smaller than that in geophones sensing both the water layer and the solid medium. On the contrary, most of the energy of water layer waves propagates in the water layer, and only a small part is decomposed in the solid medium under the water layer. The energy of water layer waves in hydrophones is much greater than that in geophones. Conventional polarization analysis methods cannot extract the polarization attributes used to separate Schulte waves and water layer waves. Due to the characteristic differences between the two noise signals, it is often difficult to identify and suppress these two noise signals when filtering noise from seismic data. Moreover, among common denoising methods, there are high requirements for the sampling density of seismic signals, and the effect depends on the sampling density of seismic data, as well as the frequency and apparent velocity of the signals. Insufficient sampling density will bring serious aliasing problems. Summary of the Invention

[0003] In view of the above problems, the present application provides a noise suppression method, which can effectively suppress noise in OBC / OBN dual-sensor seismic data through weighted polarization filtering and protect the effective signals in the seismic data.

[0004] In a first aspect, the present application provides a noise suppression method, which includes:

[0005] Performing preprocessing on the seismic data;

[0006] Based on the preprocessed seismic data, determining the weighted coefficient of Schulte waves in the seismic data;

[0007] Based on the weighted coefficient of the Schulte waves, determining the first polarization characteristic information of the seismic data;

[0008] Based on the first polarization characteristic information of the seismic data, suppressing the Schulte waves in the seismic data;

[0009] Based on the seismic data after suppressing the Schulte waves, determining the weighted coefficient of water layer waves in the seismic data;

[0010] Based on the weighted coefficient of the water layer waves, determining the second polarization characteristic information of the seismic data;

[0011] Suppress the water layer wave in the seismic data based on the second polarization feature information of the seismic data to obtain the seismic data after noise suppression.

[0012] In some embodiments, the seismic data includes hydrophone data and geophone data. The obtaining of the weighted coefficient of the Schulte wave based on the preprocessed seismic data includes:

[0013] Obtain the amplitudes of the Schulte waves in the hydrophone data and the geophone respectively;

[0014] Based on the amplitude of the Schulte wave in the geophone and the amplitude of the Schulte wave in the hydrophone data, determine the weighted coefficient of the Schulte wave through the weighted coefficient calculation formula;

[0015] The weighted coefficient calculation formula is:

[0016] w s = scholte / H scholte ;

[0017] Wherein, G scholte is the amplitude of the Schulte wave in the geophone, H scholte is the amplitude of the Schulte wave in the hydrophone, and w s is the weighted coefficient of the Schulte wave.

[0018] In some embodiments, the first polarization feature information includes: the first ellipticity. The determining of the first ellipticity of the seismic data based on the weighted coefficient of the Schulte wave includes:

[0019] Based on the weighted coefficient of the Schulte wave, respectively determine the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within a preset time window;

[0020] Based on the weighted average value of the hydrophone data and the average value of the geophone data, determine the characteristic value of the seismic data;

[0021] Based on the characteristic value, determine the first ellipticity of the seismic data through the ellipticity calculation formula;

[0022] The ellipticity calculation formula is:

[0023]

[0024] Wherein, ε s is the ellipticity of the seismic data, and λ1 and λ2 are the characteristic values of the seismic data respectively.

[0025] In some embodiments, determining the weighted average of the hydrophone data within a preset time window and the average of the geophone data within the preset time window based on the weighted coefficients of the Schulte wave includes:

[0026] Determine the weighted average of the seismic data in the hydrophone data within the preset time window according to the weighted average calculation formula

[0027] The weighted average calculation formula is:

[0028]

[0029] Determine the average of the seismic data in the geophone data within the preset time window according to the average calculation formula

[0030] The average calculation formula is:

[0031]

[0032] Where H i represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, and G i represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 are the preset time windows.

[0033] In some embodiments, determining the eigenvalue of the seismic data based on the weighted average of the hydrophone data and the average of the geophone data includes:

[0034] Construct a covariance function of the hydrophone data and the geophone data in the seismic data based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average of the geophone data;

[0035] The covariance function is:

[0036]

[0037] Determine the covariance matrix based on the covariance function as:

[0038] Determine the eigenvalue conditional relation based on the covariance matrix: Cu = λu, where λ is the eigenvalue and u is the eigenvector;

[0039] When λ satisfies the eigenvalue conditional relation, determine the eigenvalues λ1 and λ2 of the seismic data.

[0040] In some embodiments, suppressing the Schulte wave in the seismic data based on the first polarization feature information of the seismic data includes:

[0041] Based on spectral analysis, determining the frequency range of the Schulte wave in the seismic data;

[0042] Based on the first polarization feature information of the seismic data, determining the ellipticity threshold for suppressing noise;

[0043] Based on the first polarization feature information, the ellipticity threshold, and the frequency range, suppressing the Schulte wave in the seismic data according to a filtering function;

[0044] The filtering function is:

[0045]

[0046] where F(ε) is a filter set based on the polarization feature information of the Schulte wave, f(t) is the input signal of the seismic data, is the seismic data after suppressing the Schulte wave.

[0047] In some embodiments, the seismic data includes hydrophone data and geophone data. Determining the weighting coefficient of the water layer wave based on the seismic data after suppressing the Schulte wave includes:

[0048] Respectively obtaining the amplitudes of the water layer waves in the hydrophone data and the geophones;

[0049] Based on the amplitude of the water layer wave in the geophones and the amplitude of the water layer wave in the hydrophone data, determining the weighting coefficient of the water layer through a weighting coefficient calculation formula;

[0050] The weighting coefficient calculation formula is:

[0051] w w = G water / H water ;

[0052] where G water is the amplitude of the water layer wave in the geophones, H water is the amplitude of the water layer wave in the hydrophone, and w w is the weighting coefficient of the water layer wave.

[0053] In some embodiments, the second polarization feature information includes: polarization direction and second ellipticity. Determining the second polarization feature information of the seismic data based on the weighting coefficient of the water layer wave includes:

[0054] Based on the weighting coefficients of the water layer waves, obtain the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window respectively;

[0055] Based on the weighted average value of the hydrophone data and the average value of the geophone data, determine the eigenvalue and eigenvector of the seismic data;

[0056] Based on the eigenvalue, determine the second ellipticity of the seismic data through the ellipticity calculation formula;

[0057] The ellipticity calculation formula is:

[0058]

[0059] where ε w is the second ellipticity of the seismic data, and λ1 and λ2 are the eigenvalues of the seismic data respectively;

[0060] Based on the eigenvector, determine the polarization direction of the seismic data through the polarization direction calculation formula;

[0061] The polarization direction calculation formula is:

[0062] α = tan -1 (m1 / n1);

[0063] where α is the polarization direction of the seismic data, and m1 and n1 are the coordinate values of the eigenvector.

[0064] In some embodiments, the determining the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window based on the weighting coefficients of the water layer waves includes:

[0065] According to the weighted average value calculation formula, determine the weighted average value of the seismic data in the hydrophone data within the preset time window

[0066] The weighted average value calculation formula is:

[0067]

[0068] According to the average value calculation formula, determine the average value of the seismic data in the geophone data within the preset time window

[0069] The average value calculation formula is:

[0070]

[0071] where H idenotes the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, G i denotes the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 are preset time windows.

[0072] In some embodiments, determining the eigenvalue and eigenvector of the seismic data based on the weighted average of the hydrophone data and the average of the geophone data includes:

[0073] Based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average of the geophone data, construct the covariance function of the hydrophone data and the geophone data in the seismic data;

[0074] The covariance function is:

[0075]

[0076] Based on the covariance function, determine that the covariance matrix is:

[0077] Based on the covariance matrix, determine the eigenvalue conditional relation: Cu = λu, where λ is the eigenvalue and u is the eigenvector;

[0078] When λ satisfies the eigenvalue conditional relation, determine the eigenvalues λ1 and λ2 of the seismic data.

[0079] In some embodiments, suppressing the water layer wave in the seismic data based on the second polarization characteristic information of the seismic data includes

[0080] Based on the velocity of the water layer wave, determine the velocity range for filtering application;

[0081] Based on the second polarization characteristic information of the seismic data, determine the second ellipticity threshold and polarization direction threshold for suppressing noise;

[0082] Based on the velocity range, the second polarization characteristic information, the second ellipticity threshold, and the polarization direction threshold, suppress the water layer wave in the seismic data according to the filtering function;

[0083] The filtering function is:

[0084]

[0085] where F1(ε) is a filter set based on the second ellipticity in the second polarization characteristic information of the seismic data, F2() is a filter set based on the polarization direction in the second polarization characteristic information of the seismic data, and f(t) is the input signal of the seismic data after suppressing the Schulte wave, Seismic data after suppressing surface waves

[0086] In a second aspect, the present application provides a noise suppression system, the system comprising:

[0087] A preprocessing module for preprocessing seismic data;

[0088] A first calculation module for determining a weighting coefficient of the Schulte wave in the seismic data based on the preprocessed seismic data;

[0089] A first analysis module for analyzing and determining first polarization characteristic information of the seismic data based on the weighting coefficient of the Schulte wave;

[0090] A first filtering module for suppressing the Schulte wave in the seismic data based on the first polarization characteristic information of the seismic data;

[0091] A second calculation module for determining a weighting coefficient of the surface wave in the seismic data based on the seismic data after suppressing the Schulte wave;

[0092] A second analysis module for analyzing and determining second polarization characteristic information of the seismic data based on the weighting coefficient of the surface wave;

[0093] A second filtering module for suppressing the surface wave in the seismic data based on the second polarization characteristic information of the seismic data to obtain seismic data after suppressing noise.

[0094] In a third aspect, the present application provides a storage medium, characterized in that a computer program stored in the storage medium, when executed by one or more processors, is used to implement the noise suppression method as described above.

[0095] In a fourth aspect, the present application provides an electronic device, comprising a memory and a processor, wherein a computer program is stored on the memory, and when the computer program is executed by the processor, the noise suppression method as described above is executed.

[0096] A noise suppression method, system, storage medium and electronic device provided by the present application can effectively separate and suppress the Schulte wave and the surface wave in the seismic data by analyzing the polarization characteristics of the noise data in the geophones and hydrophones, and at the same time ensure that the effective signals in the seismic data are well protected. BRIEF DESCRIPTION OF THE DRAWINGS

[0097] The present application will be described in more detail below based on embodiments with reference to the drawings.

[0098] Figure 1Flow schematic diagram of a noise method provided by an embodiment of the present application;

[0099] Figure 2 Schematic diagram of data recording of a hydrophone and a geophone provided by an embodiment of the present application;

[0100] Figure 3 Schematic diagram of the relationship between ellipticity and polarization characteristics provided by an embodiment of the present application;

[0101] Figure 4 Schematic diagram of seismic data and ellipticity provided by an embodiment of the present application;

[0102] Figure 5 Schematic diagram of the effect of suppressing Schult waves in seismic data provided by an embodiment of the present application;

[0103] Figure 6 Schematic diagram of seismic data, polarization direction, and ellipticity provided by an embodiment of the present application;

[0104] Figure 7 Schematic diagram of the effect of suppressing water layer waves in seismic data provided by an embodiment of the present application;

[0105] Figure 8a Schematic diagram of the comparison effect before and after suppressing noise obtained by related technologies provided by an embodiment of the present application;

[0106] Figure 8b Schematic diagram of the comparison effect before and after suppressing noise obtained by the method described in the present application provided by an embodiment of the present application;

[0107] In the drawings, the same components are denoted by the same reference numerals, and the drawings are not drawn to actual scale. Detailed implementation manners

[0108] The following will describe in detail the implementation manners of the present application in conjunction with the drawings and embodiments, so as to fully understand how the present application uses technical means to solve technical problems and the implementation process of achieving corresponding technical effects and implement accordingly. Each feature in the embodiments of the present application can be combined with each other on the premise of not conflicting, and the formed technical solutions are all within the protection scope of the present application.

[0109] Example 1

[0110] The present application provides a noise suppression method, Figure 1 which is a flow schematic diagram of a noise method provided by an embodiment of the present application. As Figure 1 shown, the method can execute steps S1 - S7 through an electronic device. The specific steps include:

[0111] Step S1, preprocess the seismic data.

[0112] In the embodiments described in the present application, the seismic data can be obtained by OBC / OBN seismic exploration. In some embodiments, the seismic data includes two types of noise, the Schulte wave and the water layer wave, and both types of noise can be obtained by the hydrophones and geophones in the OBC / OBN seismic acquisition system. In some embodiments, based on the polarization characteristics of the Schulte wave and the water layer wave that are different from other signals, the Schulte wave and the water layer wave in the seismic data can be suppressed. For specific content, refer to steps S2 - S7.

[0113] In some embodiments, preprocessing refers to removing surge noise, bubble noise, etc. from the seismic data through filtering methods.

[0114] Step S2, based on the preprocessed seismic data, determine the weighting coefficient of the Schulte wave in the seismic data.

[0115] In the embodiments described in the present application, the seismic data includes hydrophone data and geophone data. Among them, the hydrophone data refers to the vertical - component seismic data obtained by the hydrophone, and the geophone data refers to the vertical - component seismic data obtained by the geophone. When the Schulte wave is far from the water - solid interface, its energy attenuates faster in the water layer than in the solid medium. Therefore, the amplitude of the Schulte wave in the hydrophone, which mainly senses the water layer pressure, will be much smaller than that in the geophone, which senses both the water layer and the solid medium. On the contrary, most of the energy of the water layer wave propagates in the water layer, and only a small part is decomposed in the solid medium under the water layer. The energy of the water layer wave in the hydrophone is much greater than that in the geophone. As Figure 2 shown, it is a schematic diagram of the recorded data of the hydrophone and the geophone provided by the embodiments of the present application.

[0116] In the embodiments described in the present application, respectively obtain the amplitudes of the Schulte wave in the hydrophone data and the geophone; based on the amplitude of the Schulte wave in the geophone and the amplitude of the Schulte wave in the hydrophone data, determine the Schulte wave weighting coefficient through the weighting coefficient calculation formula.

[0117] In some embodiments, the weighting coefficient calculation formula of the Schulte wave is shown in formula (1):

[0118] w s =G scholte / H scholte (1);

[0119] Wherein, G scholte is the amplitude of the Schulte wave in the geophone, H scholte is the amplitude of the Schulte wave in the hydrophone, and w s is the Schulte wave weighting coefficient.

[0120] Step S3, based on the weighting coefficients of the Schulte wave, determine the first polarization characteristic information of the seismic data.

[0121] In some embodiments, the first polarization characteristic information may include a first ellipticity. The first ellipticity may be determined based on the weighting coefficients of the Schulte wave. The relationship between the seismic data and the ellipticity is as Figure 4 shown.

[0122] In some embodiments, based on the weighting coefficients of the Schulte wave, respectively determine the weighted average of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window; based on the weighted average of the hydrophone data and the average value of the geophone data, determine the characteristic value of the seismic data; based on the characteristic value, determine the first ellipticity of the seismic data through the ellipticity calculation formula.

[0123] In some embodiments, the ellipticity calculation formula is as shown in formula (2):

[0124]

[0125] where ε s is the first ellipticity of the seismic data, and λ1 and λ2 are respectively the characteristic values of the seismic data. The geometric relationship between the ellipticity and the characteristic value is as Figure 3 shown.

[0126] Regarding the specific calculation methods of the weighted average of the hydrophone data within the preset time window, the average value of the geophone data within the preset time window, and the characteristic value of the seismic data determined based on the weighting coefficients of the Schulte wave, reference may be made to Embodiment 2 and its detailed content.

[0127] Step S4, based on the first polarization characteristic information of the seismic data, suppress the Schulte wave in the seismic data.

[0128] In the embodiments described in the present application, the frequency range of the Schulte wave in the seismic data may be determined based on spectral analysis. By spectral analysis, the general frequency range of the Schulte wave is between 0 and 13 Hz.

[0129] In some embodiments, a first ellipticity threshold may be determined based on the first polarization characteristic information of the seismic data. The ellipticity ranges from 0 to 1, and the ellipticity threshold may be set to any value within the range of 0 to 1. For example, within the range of the first ellipticity from 0 to 1, the first ellipticity threshold is determined to be 0.35 for suppressing signals with an ellipticity greater than this threshold.

[0130] In some embodiments, based on the frequency range, the first polarization characteristic information, and the first ellipticity threshold, the Schulte wave in the seismic data can be suppressed according to a filtering function. The filtering function is shown in Equation (3):

[0131]

[0132] where F(ε) is a filter set based on the polarization characteristic information of the Schulte wave, f(t) is the input signal of the seismic data, is the seismic data after suppressing the Schulte wave. The effect of suppressing the Schulte wave in the seismic data is as shown in Figure 5 shown.

[0133] Step S5: Based on the seismic data after suppressing the Schulte wave, determine the weighting coefficient of the water layer wave in the seismic data.

[0134] In the embodiments of the present application, the energy of the water layer wave in the hydrophone is very strong, while it is relatively weak in the geophone component. The polarization direction and the second ellipticity are attributes that can be used to attenuate the water layer wave. The second polarization characteristic information of the seismic data is obtained by weighted polarization analysis of the seismic data after suppressing the Schulte wave.

[0135] In some embodiments, the amplitudes of the water layer wave in the hydrophone data and the geophone can be obtained separately; based on the amplitude of the water layer wave in the geophone and the amplitude of the water layer wave in the hydrophone data, the weighting coefficient of the water layer wave is determined through a weighting coefficient calculation formula.

[0136] In some embodiments, the weighting coefficient calculation formula of the water layer wave is shown in Equation (4):

[0137] w w = G water / H water [[ID=3l]] (4);

[0138] where G water is the amplitude of the water layer wave in the geophone, H water is the amplitude of the water layer wave in the hydrophone, and w w is the weighting coefficient of the water layer wave.

[0139] Step S6: Based on the weighting coefficient of the water layer wave, determine the second polarization characteristic information of the seismic data.

[0140] In some embodiments, the second polarization characteristic information may include a second ellipticity and a polarization direction, where the polarization direction may also be referred to as the rising angle. The seismic data, the polarization direction, and the ellipticity are as shown in Figure 6 shown.

[0141] In some embodiments, based on the weighting coefficients of the water layer waves, the weighted average of the hydrophone data within a preset time window and the average of the geophone data within the preset time window are respectively obtained; based on the weighted average of the hydrophone data and the average of the geophone data, the eigenvalue and eigenvector of the seismic data are determined; based on the eigenvalue, the second ellipticity of the seismic data is determined through the ellipticity calculation formula.

[0142] In some embodiments, the ellipticity calculation formula is as shown in formula (5):

[0143]

[0144] where ε w is the second ellipticity of the seismic data, and λ1 and λ2 are respectively the eigenvalues of the seismic data;

[0145] In some embodiments, the polarization direction of the seismic data can be determined based on the eigenvector through the polarization direction calculation formula. In some embodiments, the polarization direction calculation formula is as shown in formula (6):

[0146] α = tan -1 (m1 / n1) (6);

[0147] where α is the polarization direction of the seismic data, and m1 and n1 are the coordinate values of the eigenvector. The geometric relationship between the polarization direction and the polarization characteristics is as Figure 3 shown.

[0148] Regarding the specific calculation methods of the weighted average of the hydrophone data within the preset time window, the average of the geophone data within the preset time window, and the eigenvalue of the seismic data determined based on the weighting coefficients of the water layer waves, reference can be made to Embodiment 3 and its detailed content.

[0149] Step S7, based on the second polarization characteristic information of the seismic data, suppress the water layer waves in the seismic data to obtain the seismic data after suppressing the water layer waves.

[0150] In the embodiments described in the present application, the velocity range for filtering application can be determined based on the velocity range of the water layer waves.

[0151] In some embodiments, based on the velocity range and the polarization characteristic information of the seismic data, the water layer waves in the seismic data can be suppressed according to the filtering function. The filtering function is as shown in formula (7):

[0152]

[0153] Among them, F1(ε) is a filter set based on the second ellipticity in the polarization characteristic information of the water layer wave, F2() is a filter set based on the polarization direction rate in the polarization characteristic information of the water layer wave, and f(t) is the input signal of the seismic data after suppressing the Schulte wave. is the seismic data after suppressing the water layer wave. The effect of suppressing the seismic data of the water layer wave is as Figure 7 shown.

[0154] Example 2

[0155] This embodiment provides a calculation method for the weighted average of the hydrophone data and the average value of the geophone data of the seismic data determined based on the weighted coefficient of the Schulte wave within a preset time window.

[0156] In some embodiments, the weighted average of the seismic data in the hydrophone data within a preset time window can be determined according to the weighted average calculation formula.

[0157] In some embodiments, the weighted average calculation formula is as shown in formula (8):

[0158]

[0159] In some embodiments, the average value of the seismic data in the geophone data within a preset time window can be determined according to the average value calculation formula.

[0160] In some embodiments, the average value calculation formula is as shown in formula (9):

[0161]

[0162] Among them, H i represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, and G i represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 is the preset time window.

[0163] This embodiment also provides a method for determining the characteristic value of the seismic data determined based on the weighted coefficient of the Schulte wave.

[0164] In some embodiments, the covariance function of the hydrophone data and the geophone data in the seismic data can be constructed based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average value of the geophone data.

[0165] In some embodiments, the covariance function is as shown in formula (10):

[0166]

[0167] Based on the covariance function, the covariance matrix is determined as:

[0168] Based on the covariance matrix, an eigenvalue conditional relation is determined: Cu = λu, where λ is an eigenvalue and u is an eigenvector; when λ satisfies the eigenvalue conditional relation, the eigenvalues λ1 and λ2 of the seismic data are determined.

[0169] Example 3

[0170] This embodiment provides a calculation method for the weighted average of hydrophone data within a preset time window and the average value of geophone data within a preset time window based on the determination of the weighted coefficient of the water layer wave.

[0171] In some embodiments, the weighted average of the seismic data in the hydrophone data within a preset time window can be determined according to the weighted average calculation formula.

[0172] In some embodiments, the weighted average calculation formula is as shown in formula (11):

[0173]

[0174] In some embodiments, the average value of the seismic data in the geophone data within a preset time window can be determined according to the average value calculation formula.

[0175] In some embodiments, the average value calculation formula is as shown in formula (12):

[0176]

[0177] where H i represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, G i represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 is the preset time window.

[0178] This embodiment also provides a method for determining the eigenvalues and eigenvectors of the seismic data based on the determination of the weighted coefficient of the water layer wave.

[0179] In some embodiments, the covariance function of the hydrophone data and the geophone data in the seismic data can be constructed based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average value of the geophone data.

[0180] In some embodiments, the covariance function is as shown in formula (13):

[0181]

[0182] Based on the covariance function, the covariance matrix is determined as:

[0183] Based on the covariance matrix, an eigenvalue conditional relation is determined: Cu = λu, where λ is the eigenvalue and u is the eigenvector; when λ satisfies the eigenvalue conditional relation, the eigenvalues λ1 and λ2 of the seismic data are determined.

[0184] Figure 8a and Figure 8b respectively show the schematic diagrams of the comparison before and after suppressing noise obtained by the related technology and the schematic diagrams of the comparison before and after suppressing noise obtained by the method described in this application. The embodiments described in this application at least include the following advantages:

[0185] 1. By using the hydrophone and the vertical component data of the geophone in shallow water OBC / OBN seismic acquisition, weighted polarization analysis is performed on the signal and noise, solving the problem of difficult noise identification caused by the energy difference of noise in two components in OBC / OBN data, and effectively extracting and separating noise and effective signals.

[0186] 2. By using the different polarization attributes of the water layer wave and the Scholte wave, filters with different polarization parameters are designed, and filtering processing is performed within the frequency range of the noise, effectively suppressing the Scholte wave and the water layer wave while ensuring that the effective signal is not filtered.

[0187] 3. In this application, by calculating the seismic traces of the same physical point and independently processing the multi-component data of each receiving point, the influence of spatial aliasing is avoided.

[0188] Example 4

[0189] This embodiment also provides a noise suppression system. The system includes:

[0190] A preprocessing module, configured to perform preprocessing based on seismic data;

[0191] A first calculation module, configured to determine the weighting coefficient of the Scholte wave in the preprocessed seismic data;

[0192] A first analysis module, configured to analyze and determine the first polarization feature information of the seismic data based on the weighting coefficient of the Scholte wave;

[0193] A first filtering module, configured to suppress the Scholte wave in the seismic data based on the first polarization feature information of the seismic data;

[0194] A second calculation module, configured to determine a weighting coefficient of the water layer wave in the seismic data based on the seismic data after suppressing the Schulte wave;

[0195] A second analysis module, configured to determine second polarization characteristic information of the seismic data based on the weighting coefficient of the water layer wave;

[0196] A second filtering module, configured to suppress the water layer wave in the seismic data based on the second polarization characteristic information of the seismic data to obtain seismic data after suppressing relevant noise.

[0197] In some embodiments, the first calculation module may further be configured to include:

[0198] Obtain the amplitudes of the Schulte waves in the hydrophone data and the geophone respectively;

[0199] Based on the amplitude of the Schulte wave in the geophone and the amplitude of the Schulte wave in the hydrophone data, determine the weighting coefficient of the Schulte wave through a weighting coefficient calculation formula;

[0200] The weighting coefficient calculation formula is:

[0201] w s = G scholte / H scholte ;

[0202] Wherein, G scholte is the amplitude of the Schulte wave in the geophone, H scholte is the amplitude of the Schulte wave in the hydrophone, and w s is the weighting coefficient of the Schulte wave.

[0203] In some embodiments, the first analysis module may further be configured to include:

[0204] Based on the weighting coefficient of the Schulte wave, determine the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window respectively;

[0205] Based on the weighted average value of the hydrophone data and the average value of the geophone data, determine the characteristic value of the seismic data;

[0206] Based on the characteristic value, determine the first ellipticity of the seismic data through an ellipticity calculation formula;

[0207] The ellipticity calculation formula is:

[0208]

[0209] Wherein, ε sis the first ellipticity of the seismic data, and λ1 and λ2 are the eigenvalues of the seismic data respectively.

[0210] In some embodiments, the first analysis module further includes a first calculation module for:

[0211] Determine the weighted average value of the seismic data in the hydrophone data within a preset time window according to the weighted average calculation formula

[0212] The weighted average calculation formula is:

[0213]

[0214] Determine the average value of the seismic data in the geophone data within a preset time window according to the average value calculation formula

[0215] The average value calculation formula is:

[0216]

[0217] where H i represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, and G i represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 is the preset time window.

[0218] In some embodiments, the first analysis module further includes a second calculation module for:

[0219] Based on the hydrophone data, the geophone data, the weighted average value of the hydrophone data, and the average value of the geophone data, construct the covariance function of the hydrophone data and the geophone data in the seismic data;

[0220] The covariance function is:

[0221]

[0222] Based on the covariance function, determine that the covariance matrix is:

[0223] Based on the covariance matrix, determine the eigenvalue conditional relation: Cu = λu, where λ is the eigenvalue and u is the eigenvector;

[0224] When λ satisfies the eigenvalue conditional relation, determine the eigenvalues λ1 and λ2 of the seismic data.

[0225] In some embodiments, the first filtering module can also be used to include:

[0226] Based on spectral analysis, determine the frequency range of the Schulte wave in the seismic data;

[0227] Based on the frequency range of the Schulte wave, determine the frequency range of filtering;

[0228] Based on the first polarization characteristic information of the seismic data, determine the first ellipticity threshold.

[0229] Based on the first polarization characteristic information, the first ellipticity threshold, and the frequency range, suppress the Schulte wave in the seismic data according to the filtering function;

[0230] The filtering function is:

[0231]

[0232] where F(ε) is a filter set based on the first polarization characteristic information of the Schulte wave, f(t) is the input signal of the seismic data, is the seismic data after suppressing the Schulte wave.

[0233] In some embodiments, the second calculation module can also be used to include:

[0234] Obtain the water layer wave amplitudes in the hydrophone data and the geophone respectively;

[0235] Based on the water layer wave amplitude in the geophone and the water layer wave amplitude in the hydrophone data, determine the weighting coefficient of the water layer wave through the weighting coefficient calculation formula;

[0236] The weighting coefficient calculation formula is:

[0237] w w =G water / H water ;

[0238] where G water is the water layer wave amplitude in the geophone, H water is the water layer wave amplitude in the hydrophone, and w w is the weighting coefficient of the water layer wave.

[0239] In some embodiments, the second analysis module can also be used to include:

[0240] Based on the weighting coefficient of the water layer wave, obtain the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window respectively;

[0241] Based on the weighted average value of the hydrophone data and the average value of the geophone data, determine the eigenvalue and eigenvector of the seismic data;

[0242] Based on the eigenvalue, determine the second ellipticity of the seismic data through the ellipticity calculation formula;

[0243] The ellipticity calculation formula is:

[0244]

[0245] where ε w is the second ellipticity of the seismic data, and λ1 and λ2 are the eigenvalues of the seismic data respectively;

[0246] Based on the eigenvector, determine the polarization direction of the seismic data through the polarization direction calculation formula;

[0247] The polarization direction calculation formula is:

[0248] α = tan -1 (m1 / n1);

[0249] where α is the polarization direction of the seismic data, and m1 and n1 are the coordinate values of the eigenvector.

[0250] In some embodiments, the second analysis module further includes a first calculation module for:

[0251] Determine the weighted average value of the seismic data in the hydrophone data within a preset time window according to the weighted average value calculation formula

[0252] The weighted average value calculation formula is:

[0253]

[0254] Determine the average value of the seismic data in the geophone data within a preset time window according to the average value calculation formula

[0255] The average value calculation formula is:

[0256]

[0257] where H i represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, G i represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, and t1 to t2 is the preset time window.

[0258] In some embodiments, the second analysis module further includes a second calculation module for:

[0259] Construct a covariance function of the hydrophone data and the geophone data in the seismic data based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average of the geophone data;

[0260] The covariance function is:

[0261]

[0262] Based on the covariance function, determine that the covariance matrix is:

[0263] Based on the covariance matrix, determine the eigenvalue conditional relation: Cu = λu, where λ is the eigenvalue and u is the eigenvector;

[0264] When λ satisfies the eigenvalue conditional relation, determine the eigenvalues λ1 and λ2 of the seismic data.

[0265] In some embodiments, the second filtering module can also be used to include:

[0266] Based on the velocity range of the water layer wave, determine the velocity range for filtering application;

[0267] Based on the rising angle and ellipticity, determine the rising angle threshold and ellipticity threshold for suppressing the water layer wave;

[0268] Based on the velocity range, the polarization characteristic information and threshold of the water layer wave, suppress the water layer wave in the seismic data according to the filtering function;

[0269] The filtering function is:

[0270]

[0271] where F1(ε) is a filter set based on the ellipticity in the polarization characteristic information of the water layer wave, F2(α) is a filter set based on the polarization direction rate in the polarization characteristic information of the water layer wave, f(t) is the input signal of the seismic data after suppressing the Schulte wave, is the seismic data after suppressing the water layer wave.

[0272] Example 5

[0273] A computer-readable storage medium, such as a flash memory, a hard disk, a multimedia card, a card-type memory (e.g., SD or DX memory, etc.), a random access memory (RAM), a static random access memory (SRAM), a read-only memory (ROM), an electrically erasable programmable read-only memory (EEPROM), a programmable read-only memory (PROM), a magnetic memory, a magnetic disk, an optical disk, a server, an App application store, etc., stores a computer program thereon, and when the computer program is executed by a processor, the noise suppression method as described above can be implemented.

[0274] For the specific implementation process of the above method steps, refer to Embodiments 1 to 3. This embodiment will not be repeated here.

[0275] Example 6

[0276] An embodiment of the present application provides an electronic device, which can be a mobile phone, a computer, a tablet computer, etc., including a memory and a processor. A calculator program is stored on the memory, and when the computer program is executed by the processor, the application management method described in Embodiment 1 is implemented. It can be understood that the electronic device may further include a multimedia component, an input / output (I / O) interface, and a communication component.

[0277] Among them, the processor is used to execute all or part of the steps in the application management method in Embodiment 1. The memory is used to store various types of data, which may include, for example, instructions of any application program or method in the electronic device, and data related to the application program.

[0278] The processor can be implemented by an application specific integrated circuit (ASIC), a digital signal processor (DSP), a digital signal processing device (DSPD), a programmable logic device (PLD), a field programmable gate array (FPGA), a controller, a microcontroller, a microprocessor, or other electronic components, and is used to execute the application management method in Embodiment 1 above.

[0279] The memory can be implemented by any type of volatile or non-volatile storage device, or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disc.

[0280] The multimedia component may include a screen and an audio component. The screen may be a touch screen. The audio component is used to output and / or input audio signals. For example, the audio component may include a microphone for receiving external audio signals. The received audio signal may be further stored in the memory or sent through the communication component. The audio component also includes at least one speaker for outputting audio signals.

[0281] The I / O interface provides an interface between the processor and other interface modules, and the other interface modules may be a keyboard, a mouse, buttons, etc. These buttons may be virtual buttons or physical buttons.

[0282] The communication component is used for wired or wireless communication between the electronic device and other devices. Wireless communication, such as Wi-Fi, Bluetooth, near field communication (NFC), 2G, 3G or 4G, or a combination of one or more of them. Accordingly, the communication component 405 may include: a Wi-Fi module, a Bluetooth module, an NFC module.

[0283] In summary, a noise suppression method, system, storage medium and electronic device provided by the present application.

[0284] In several embodiments provided by the embodiments of the present application, it should be understood that the disclosed systems and methods may also be implemented in other ways. The system and method embodiments described above are merely illustrative.

[0285] It should be noted that in this text, the term "including", "comprising" or any other variant thereof is intended to cover non-exclusive inclusion, such that a process, method, article or device comprising a series of elements not only includes those elements but also other elements not expressly listed, or further includes elements inherent to such process, method, article or device. Without further limitation, an element defined by the phrase "comprising an..." does not exclude the presence of additional identical elements in the process, method, article or device comprising said element.

[0286] Although the embodiments disclosed in this application are as described above, the content described is only an embodiment adopted for the convenience of understanding this application and is not intended to limit this application. Any person skilled in the art within the technical field to which this application pertains may make any modifications and changes in the form of implementation and details without departing from the spirit and scope disclosed in this application. However, the scope of patent protection of this application shall still be subject to the scope defined by the appended claims.

Claims

1. A noise suppression method, characterized in that, The method includes: Preprocessing the seismic data; Based on the preprocessed seismic data, determining the weighting coefficient of the Schulte wave in the seismic data; Based on the weighting coefficient of the Schulte wave, determining the first polarization characteristic information of the seismic data; Based on the first polarization characteristic information of the seismic data, suppressing the Schulte wave in the seismic data; Based on the seismic data after suppressing the Schulte wave, determining the weighting coefficient of the water layer wave in the seismic data; Based on the weighting coefficient of the water layer wave, determining the second polarization characteristic information of the seismic data; Based on the second polarization characteristic information of the seismic data, suppressing the water layer wave in the seismic data to obtain a seismic signal after suppressing noise.

2. The method according to claim 1, characterized in that, The seismic data includes hydrophone data and geophone data. The determining of the Schulte wave weighting coefficient based on the preprocessed seismic data includes: Respectively obtaining the amplitudes of the Schulte wave in the hydrophone data and the geophone; Based on the amplitude of the Schulte wave in the geophone and the amplitude of the Schulte wave in the hydrophone data, determining the weighting coefficient of the Schulte wave through a weighting coefficient calculation formula; The weighting coefficient calculation formula is: ； Among them, is the amplitude of the Schulte wave in the geophone, is the amplitude of the Schulte wave in the hydrophone, is the weighting coefficient of the Schulte wave.

3. The method according to claim 2, wherein The polarization characteristic information includes: ellipticity. The determining of the first polarization characteristic information of the seismic data based on the weighting coefficient of the Schulte wave includes: Based on the weighting coefficient of the Schulte wave, respectively determining the weighted average of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window; Based on the weighted average of the hydrophone data and the average value of the geophone data, determining the characteristic value of the seismic data; Based on the characteristic value, determining the first ellipticity of the seismic data through an ellipticity calculation formula; The ellipticity calculation formula is: ； wherein, is the ellipticity of the seismic data, and are the eigenvalues of the seismic data respectively.

4. The method according to claim 3, wherein The respectively determining the weighted average of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window based on the weighting coefficient of the Schulte wave includes: Determine the weighted average of the seismic data in the hydrophone data within a preset time window according to the weighted average calculation formula ; The weighted average calculation formula is: ； Determine the average value of the seismic data in the seismic detector data within a preset time window according to the average value calculation formula ; The average value calculation formula is: ； Wherein, represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, is a preset time window.

5. The method according to claim 4, characterized in that, The determining of the characteristic value of the seismic data based on the weighted average of the hydrophone data and the average value of the geophone data includes: Based on the hydrophone data, the geophone data, the weighted average of the hydrophone data, and the average value of the geophone data, constructing a covariance function of the hydrophone data and the geophone data in the seismic data; The covariance function is: ； Based on the covariance function, the covariance matrix is determined as follows: ; Based on the covariance matrix, determine the eigenvalue conditional relation: , where is the eigenvalue and u is the eigenvector; In When the eigenvalue condition relation is satisfied, determine the eigenvalue of the seismic data and .

6. The method according to any one of claims 3 to 4, characterized in that, The suppressing of the Schulte wave in the seismic data based on the first polarization characteristic information of the seismic data includes: Based on spectral analysis, determining the frequency range of the Schulte wave in the seismic data; Based on the first polarization characteristic information of the seismic data, determining the first ellipticity threshold for suppressing noise; Based on the first polarization characteristic information, the first ellipticity threshold, and the frequency range, suppressing the Schulte wave in the seismic data according to a filtering function; The filtering function is: ； Among them, is a filter set based on the polarization characteristic information of the Schulte wave, is the input signal of the seismic data, is the seismic data after suppressing the Schulte wave.

7. The method according to claim 1, wherein The seismic data includes hydrophone data and geophone data. Determining the weighting coefficient of the water layer wave based on the seismic data after suppressing the Schulte wave includes: Respectively obtaining the water layer wave amplitudes in the hydrophone data and the geophone; Based on the water layer wave amplitude in the geophone and the water layer wave amplitude in the hydrophone data, determining the weighting coefficient of the water layer wave through a weighting coefficient calculation formula; The weighting coefficient calculation formula is: ； Among them, is the amplitude of the water layer wave in the geophone, is the amplitude of the water layer wave in the hydrophone, is the weighting coefficient of the water layer wave.

8. The method according to claim 7, wherein The second polarization characteristic information includes: polarization direction and ellipticity. Determining the polarization characteristic information of the seismic data based on the weighting coefficient of the water layer wave includes: Based on the weighting coefficient of the water layer wave, respectively obtaining the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window; Based on the weighted average value of the hydrophone data and the average value of the geophone data, determining the eigenvalue and eigenvector of the seismic data; Based on the eigenvalue, determining the second ellipticity of the seismic data through an ellipticity calculation formula; The ellipticity calculation formula is: ； wherein, is the second ellipticity of the seismic data, and are the eigenvalues of the seismic data respectively; Based on the eigenvector, determining the polarization direction of the seismic data through a polarization direction calculation formula; The polarization direction calculation formula is: ； Among them, is the polarization direction of seismic data, and are the coordinate values of the eigenvector.

9. The method according to claim 8, characterized in that Determining the weighted average value of the hydrophone data within a preset time window and the average value of the geophone data within the preset time window based on the weighting coefficient of the water layer wave respectively includes: Determine the weighted average value of the seismic data in the hydrophone data within a preset time window according to the weighted average calculation formula ; The weighted average value calculation formula is: ； Determine the average value of the seismic data in the seismic geophone data within a preset time window according to the average value calculation formula ; The average value calculation formula is: ； Among them, represents the amplitude value of the seismic data obtained by the hydrophone at the i-th moment, represents the amplitude value of the seismic data obtained by the geophone at the i-th moment, is a preset time window.

10. The method according to claim 9, wherein Determining the eigenvalue and eigenvector of the seismic data based on the weighted average value of the hydrophone data and the average value of the geophone data includes: Based on the hydrophone data, the geophone data, the weighted average value of the hydrophone data and the average value of the geophone data, constructing a covariance function of the hydrophone data and the geophone data in the seismic data; The covariance function is: ； Based on the covariance function, determine the covariance matrix as follows: ; Based on the covariance matrix, determine the eigenvalue conditional relation: , where is the eigenvalue and u is the eigenvector; When the eigenvalue of the seismic data is determined under the condition that the eigenvalue condition relational expression is satisfied and .

11. The method according to any one of claims 8 to 10, characterized in that, Suppressing the water layer wave in the seismic data based on the second polarization characteristic information of the seismic data includes: Based on the velocity of the water layer wave, determining the velocity range for filtering application; Based on the second polarization characteristic information of the seismic data, determining the second ellipticity threshold and polarization direction threshold for suppressing noise; Based on the velocity range, the second polarization characteristic information, the second ellipticity threshold and the polarization direction threshold, suppressing the water layer wave in the seismic data according to a filtering function; The filtering function is: ； Among them, is a filter set for the second ellipticity in the second polarization characteristic information based on the seismic data, is a filter set for the polarization direction in the second polarization characteristic information based on the seismic data, is the input signal of the seismic data after suppressing the Schulte wave, is the seismic data after suppressing the water layer wave.

12. A noise suppression system, characterized in that, The system includes: A preprocessing module for preprocessing seismic data; A first calculation module for determining the weighting coefficient of the Schulte wave in the seismic data based on the preprocessed seismic data; A first analysis module for analyzing and determining the first polarization characteristic information of the seismic data based on the weighting coefficient of the Schulte wave; A first filtering module for suppressing the Schulte wave in the seismic data based on the first polarization characteristic information of the seismic data; A second calculation module for determining the weighting coefficient of the water layer wave in the seismic data based on the seismic data after suppressing the Schulte wave; A second analysis module, configured to determine second polarization feature information of the seismic data based on the weighting coefficients of the water layer waves; A second filtering module, configured to suppress the water layer waves in the seismic data based on the second polarization feature information of the seismic data, so as to obtain the seismic data after noise suppression.

13. A storage medium, characterized in that, When the computer program stored in the storage medium is executed by one or more processors, it is used to implement the noise suppression method according to any one of claims 1-11.

14. An electronic device, characterized in that, It includes a memory and a processor, and a computer program is stored on the memory. When the computer program is executed by the processor, it executes the noise suppression method according to any one of claims 1-11.

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