Deghosting method, electronic device, storage medium, and program product

Abstract

A deghosting method, comprising: obtaining a frequency-slowness domain seismic dataset on the basis of a pre-stack seismic gather, the pre-stack seismic gather being a seismic dataset in a time-space domain (S101); performing deghosting on the frequency-slowness domain seismic dataset to obtain an initial deghosted seismic dataset, the data domain of the initial deghosted seismic dataset being a frequency-slowness domain (S102); performing inversion processing on the initial deghosted seismic dataset to obtain a target deghosted seismic dataset (S103); and obtaining a target seismic dataset on the basis of the target deghosted seismic dataset, the target seismic dataset being a deghosted seismic dataset in the time-space domain (S104). Deghosting of the seismic dataset in the time-space domain is completed, solving the problem of inaccurate deghosting. Also provided are an electronic device for deghosting, a storage medium, and a program product.

Description

Ghost wave suppression method, electronic device, storage medium and program product

[0001] The present application claims priority to the Chinese patent application No. 202411318710.9, filed on September 20, 2024, and entitled "Ghost wave suppression method, electronic device, storage medium and program product", the whole content of which is incorporated herein by reference. TECHNICAL FIELD

[0002] The present application relates to the field of marine seismic exploration, and in particular to a ghost wave suppression method, an electronic device, a storage medium and a program product. BACKGROUND

[0003] In marine seismic exploration, due to the uniqueness of the field acquisition observation system, both the shot point and the receiver point are located below the sea surface, even reaching several tens of meters. After the shot point source is excited, part of the energy will directly propagate upwards to the sea surface, reflect at the sea surface and propagate to the deep underground. When reaching the underground interface, it is reflected back again and received by the receiver of the receiver point, forming a ghost wave at the shot point end following the first reflection wave. Similarly, there is also a ghost wave at the receiver point end. The existence of the ghost wave will cause a frequency gap and a low frequency loss in the seismic data, making the spectral width of the seismic data narrow, and thus reducing the signal-to-noise ratio and resolution of the seismic record.

[0004] In the prior art, for the suppression of the ghost wave, a deconvolution method is often used for processing, that is, the seismic data is transformed and mapped to other data domains, a ghost wave delay operator is constructed, and then in the mapped data domain, the ghost wave suppression is realized by using the ghost wave delay operator based on the deconvolution algorithm.

[0005] However, the prior art scheme has the problem of inaccurate ghost wave suppression. SUMMARY

[0006] The embodiments of the present application provide a ghost wave suppression method, an electronic device, a storage medium and a program product to solve the problem of inaccurate ghost wave suppression.

[0007] In a first aspect, the embodiments of the present application provide a ghost wave suppression method, comprising:

[0008] According to a pre-stack seismic trace gather, a frequency-slowness domain seismic data set is obtained, the pre-stack seismic trace gather being a time-space domain seismic data set; the frequency-slowness domain seismic data set is subjected to inverse ghost processing to obtain an initial inverse ghost seismic data set, a data domain of the initial inverse ghost seismic data set being a frequency-slowness domain; the initial inverse ghost seismic data set is subjected to inversion processing to obtain a target inverse ghost seismic data set; according to the target inverse ghost seismic data set, a target seismic data set is obtained, the target seismic data set being a time-space domain inverse ghost seismic data set.

[0009] In a possible implementation, the inversion processing of the initial inverse ghost seismic data set to obtain the target inverse ghost seismic data set comprises: performing three-dimensional tilt stack inverse transformation on the initial inverse ghost seismic data set to obtain a first seismic data set, the first seismic data set being a frequency-space domain inverse ghost seismic data set; obtaining an inversion constraint equation according to the initial inverse ghost seismic data set and the first seismic data set; performing at least one iteration inversion on the inversion constraint equation to obtain the target inverse ghost seismic data set.

[0010] In a possible implementation, the at least one iteration inversion of the inversion constraint equation to obtain the target inverse ghost seismic data set comprises: determining a first inversion constraint parameter according to a constraint relationship corresponding to the inversion constraint equation, the first inversion constraint parameter being used to update the initial inverse ghost seismic data set; obtaining a second inversion constraint parameter according to the first inversion constraint parameter and the updated initial inverse ghost seismic data set; if a difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is less than a preset threshold, obtaining the target inverse ghost seismic data set; if the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is greater than or equal to the preset threshold, continuing the iteration inversion.

[0011] Optionally, by introducing sparse inversion constraints to solve a linear equation set under an L1 norm condition, using a fast augmented Lagrange multiplier algorithm, and through at least one iteration inversion, a convergent optimal solution, i.e., the target inverse ghost seismic data set, can be obtained, and the suppression precision of the ghost is improved.

[0012] In a possible implementation, the obtaining the frequency-slowness domain seismic data set according to the pre-stack seismic trace set comprises: performing Fourier forward transform on the pre-stack seismic trace set to obtain a second seismic data set, the second seismic data set being a frequency-space domain seismic data set; obtaining a vector offset between a shot point and a receiver point according to the pre-stack seismic trace set; obtaining a conjugate transform operator of three-dimensional dip stack forward transform according to the vector offset, the conjugate transform operator comprising a transverse conjugate transform operator and a longitudinal conjugate transform operator; and obtaining the frequency-slowness domain seismic data set according to the second seismic data set and the conjugate transform operator.

[0013] In a possible implementation, the performing de-ghost processing on the frequency-slowness domain seismic data set to obtain an initial de-ghost seismic data set comprises: obtaining sink depth data according to the pre-stack seismic trace set, the sink depth data comprising shot point sink depth data and receiver point sink depth data; determining a ghost delay time according to the sink depth data, the ghost delay time comprising a shot point end ghost delay time and a receiver point end ghost delay time; obtaining a de-ghost operator according to the ghost delay time, the de-ghost operator comprising a shot point end de-ghost operator and a receiver point end de-ghost operator; and obtaining the initial de-ghost seismic data set according to the de-ghost operator and the frequency-slowness domain seismic data set.

[0014] In a possible implementation, the determining the ghost delay time according to the sink depth data comprises: obtaining a ray parameter, the ray parameter comprising a transverse ray parameter in a dip stack domain and a longitudinal ray parameter in the dip stack domain; and determining the ghost delay time according to the sink depth data and the ray parameter.

[0015] In a possible implementation, the obtaining the target seismic data set according to the target de-ghost seismic data set comprises: performing three-dimensional dip stack reverse transform on the target de-ghost seismic data set to obtain a third seismic data set, the third seismic data set being a de-ghost seismic data set in a frequency-space domain after inversion processing; and performing Fourier inverse transform on the third seismic data set to obtain the target seismic data set.

[0016] In a second aspect, an embodiment of the present application provides a ghost wave suppressing device, comprising:

[0017] a first processing module configured to obtain a frequency-slowness domain seismic data set according to a pre-stack seismic trace set, the pre-stack seismic trace set being a time-space domain seismic data set;

[0018] a second processing module, configured to perform inverse ghost processing on the frequency-slowness domain seismic data set to obtain an initial inverse ghost seismic data set, a data domain of the initial inverse ghost seismic data set being a frequency-slowness domain;

[0019] a third processing module, configured to perform inversion processing on the initial inverse ghost seismic data set to obtain a target inverse ghost seismic data set;

[0020] a determination module, configured to obtain a target seismic data set from the target inverse ghost seismic data set, the target seismic data set being a set of inverse ghost seismic data in a time-space domain.

[0021] In a possible implementation, when the third processing module performs inversion processing on the initial inverse ghost seismic data set to obtain the target inverse ghost seismic data set, the third processing module is specifically configured to perform three-dimensional dip stack inverse transformation on the initial inverse ghost seismic data set to obtain a first seismic data set, the first seismic data set being a set of inverse ghost seismic data in a frequency-space domain; obtain an inversion constraint equation from the initial inverse ghost seismic data set and the first seismic data set; and perform at least one iteration inversion on the inversion constraint equation to obtain the target inverse ghost seismic data set.

[0022] In a possible implementation, when the third processing module performs at least one iteration inversion on the inversion constraint equation to obtain the target inverse ghost seismic data set, the third processing module is specifically configured to determine a first inversion constraint parameter according to a constraint relationship corresponding to the inversion constraint equation, the first inversion constraint parameter being used to update the initial inverse ghost seismic data set; obtain a second inversion constraint parameter according to the first inversion constraint parameter and the updated initial inverse ghost seismic data set; if a difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is less than a preset threshold, obtain the target inverse ghost seismic data set; and if the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is greater than or equal to the preset threshold, continue the iteration inversion.

[0023] In a possible implementation, when the first processing module obtains the frequency-slowness domain seismic data set from the prestack seismic trace set, the first processing module is specifically configured to perform Fourier forward transformation on the prestack seismic trace set to obtain a second seismic data set, the second seismic data set being a set of seismic data in a frequency-space domain; obtain a vector offset from the prestack seismic trace set, the vector offset being used to indicate a distance between a shot point and a receiver point; obtain a conjugate transformation operator of three-dimensional dip stack forward transformation according to the vector offset, the conjugate transformation operator including a transverse conjugate transformation operator and a longitudinal conjugate transformation operator; and obtain the frequency-slowness domain seismic data set from the second seismic data set and the conjugate transformation operator.

[0024] In a possible implementation, when the second processing module performs deghosting on the frequency-slowness domain seismic data set to obtain an initial deghosted seismic data set, the second processing module is specifically configured to: obtain sink depth data according to the prestack seismic trace set, the sink depth data including shot sink depth data and receiver sink depth data; determine a deghosting delay time according to the sink depth data, the deghosting delay time including shot-end deghosting delay time and receiver-end deghosting delay time; obtain a deghosting operator according to the deghosting delay time, the deghosting operator including a shot-end deghosting operator and a receiver-end deghosting operator; and obtain the initial deghosted seismic data set according to the deghosting operator and the frequency-slowness domain seismic data set.

[0025] In a possible implementation, when the second processing module determines the deghosting delay time according to the sink depth data, the second processing module is specifically configured to: obtain ray parameters, the ray parameters including transverse ray parameters in the dip stack domain and longitudinal ray parameters in the dip stack domain; and determine the deghosting delay time according to the sink depth data and the ray parameters.

[0026] In a possible implementation, when the determining module obtains the target seismic data set according to the target deghosted seismic data set, the determining module is specifically configured to: perform three-dimensional dip stack inverse transformation on the target deghosted seismic data set to obtain a third seismic data set, the third seismic data set being a deghosted seismic data set in a frequency space domain after inversion processing; and perform inverse Fourier transformation on the third seismic data set to obtain the target seismic data set.

[0027] In a third aspect, an embodiment of the present application provides an electronic device, including: a memory, a processor;

[0028] The memory stores computer-executed instructions;

[0029] The processor executes the computer-executed instructions stored in the memory, so that the processor executes the first aspect and / or various possible implementations of the first aspect.

[0030] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, the computer-readable storage medium storing computer-executed instructions, the computer-executed instructions being executed by a processor to implement the first aspect and / or various possible implementations of the first aspect.

[0031] In a fifth aspect, an embodiment of the present application provides a computer program product, including a computer program, the computer program being executed by a processor to implement the first aspect and / or various possible implementations of the first aspect.

[0032] The ghost wave suppression method, the electronic device, the storage medium and the program product provided by the embodiments of the present application, by obtaining a frequency-slowness domain seismic data set according to a pre-stack seismic gather, the pre-stack seismic gather is a time-space domain seismic data set; performing anti-ghost wave processing on the frequency-slowness domain seismic data set to obtain an initial anti-ghost wave seismic data set, the data domain of the initial anti-ghost wave seismic data set is a frequency-slowness domain; performing inversion processing on the initial anti-ghost wave seismic data set to obtain a target anti-ghost wave seismic data set; obtaining a target seismic data set according to the target anti-ghost wave seismic data set, the target seismic data set is a time-space domain anti-ghost wave seismic data set. On the basis of processing the pre-stack seismic gather into the frequency-slowness domain seismic data set, the ghost wave of the frequency-slowness domain seismic data set is suppressed by the anti-ghost wave operator constructed, and further by iterative inversion processing, the optimal solution under the constraint condition is obtained, that is, the target anti-ghost wave seismic data set, and then by performing three-dimensional tilt stack inverse transformation and Fourier inverse transformation on the target anti-ghost wave seismic data set, the anti-ghost wave seismic data set in the time-space domain can be obtained, that is, the target seismic data set, the ghost wave of the seismic data set in the time-space domain is suppressed, and the problem of inaccurate ghost wave suppression is solved. BRIEF DESCRIPTION OF DRAWINGS

[0033] FIG. 1 is a schematic diagram of an application scenario of the ghost wave suppression method provided by the present application;

[0034] FIG. 2 is a flowchart of the ghost wave suppression method provided by one embodiment of the present application;

[0035] FIG. 3 is a process diagram of the specific implementation steps of step S101 in the embodiment shown in FIG. 2;

[0036] FIG. 4 is a process diagram of the specific implementation steps of step S102 in the embodiment shown in FIG. 2;

[0037] FIG. 5 is a process diagram of the specific implementation steps of step S1022 in the embodiment shown in FIG. 4;

[0038] FIG. 6 is a process diagram of the specific implementation steps of step S104 in the embodiment shown in FIG. 2;

[0039] FIG. 7 is a flowchart of the ghost wave suppression method provided by another embodiment of the present application, as shown in FIG. 7;

[0040] FIG. 8 is a schematic diagram of the energy spectrum change before and after the sparse inversion constraint of the tilt stack domain seismic data provided by the present application;

[0041] FIG. 9 is a comparative schematic diagram of the ghost wave suppression of the marine seismic data provided by the present application;

[0042] Fig. 10 is a schematic diagram of a frequency spectrum analysis of marine seismic data after suppressing ghost wavefronts according to the present application;

[0043] Fig. 11 is a schematic diagram of a comparison of marine seismic data stack profiles before and after suppressing ghost wavefronts according to the present application;

[0044] Fig. 12 is a schematic diagram of a structure of a ghost wave suppressing device according to an embodiment of the present application;

[0045] Fig. 13 is a schematic diagram of a structure of an electronic device according to the present application. DETAILED DESCRIPTION

[0046] The exemplary embodiments will be described in detail herein with reference to the attached drawings. The following description is made with reference to the accompanying drawings in which like reference numerals refer to like elements, unless the context of use indicates otherwise. The following description of exemplary embodiments is not representative of all embodiments consistent with the present application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of the present application as detailed in the appended claims.

[0047] First, the terms involved in the present application are explained:

[0048] Pre-stack seismic gather: is a collection of seismic records organized according to certain rules. These records usually contain information about seismic waves reflected or transmitted from different locations and depths in the subsurface;

[0049] Three-dimensional dip moveout transformation: is an important technique in seismic data processing, mainly used to improve the signal-to-noise ratio and resolution of seismic data, especially in the processing of complex geological structures.

[0050] The application scenarios of the embodiments of the present application are explained as follows:

[0051] FIG. 1 is a schematic diagram of an application scenario of the ghost wave suppression method provided by the present application. As shown in FIG. 1, the specific application scenario of the present application is to obtain seismic data after suppressing ghost waves in the process of marine seismic exploration. The execution subject of the method provided by the embodiments of the present application can be an electronic control unit, a server or a terminal device. The terminal device is taken as the execution subject for illustration. In the process of marine seismic exploration, the shooting point and the receiving point are both located below the sea surface. After the shooting point source is excited, part of the energy will directly propagate upward to the sea surface, reflect at the sea surface and propagate to the deep underground. When reaching the underground interface, it is reflected back again and received by the geophone of the receiving point, forming the shot point end ghost wave trailing behind the primary reflection wave. Similarly, part of the energy will propagate downward, reflect back to the sea surface when encountering the underground interface, and then be received by the geophone after being reflected again at the sea surface, forming the geophone end ghost wave trailing behind the primary reflection wave. Then, the electronic device processes the original seismic data containing ghost waves according to the method provided by the present application, so as to obtain the target seismic data after suppressing the ghost waves, thereby solving the problem of frequency gap and low frequency loss in the seismic data caused by the existence of ghost waves. The arrow mark position in the figure is the ghost wave.

[0052] In combination with the above scenario, it can be known that in the prior art, the ghost wave is often suppressed by using the deconvolution method, that is, the seismic data is transformed and mapped to other data domains, a ghost wave delay operator is constructed, and then the ghost wave is suppressed by using the ghost wave delay operator in the mapped data domain based on the deconvolution algorithm. However, since the estimation of the delay time difference between the primary wave and the ghost wave in the deconvolution algorithm is not accurate, the ghost wave suppression is not accurate.

[0053] The technical solutions of the present application and how the technical solutions of the present application solve the above technical problems will be described in detail in the following specific embodiments. The following specific embodiments can be combined with each other, and the same or similar concepts or processes can not be described again in some embodiments. The embodiments of the present application will be described in combination with the drawings.

[0054] FIG. 2 is a flowchart of the ghost wave suppression method provided by an embodiment of the present application. As shown in FIG. 2, the execution subject of the ghost wave suppression method provided by the embodiment of the present application can be an electronic control unit, a server or a terminal device. For example, the terminal device is taken as the execution subject of the method of the embodiment for illustration. The ghost wave suppression method provided by the embodiment includes the following steps:

[0055] In step S101, a frequency-slowness domain seismic data set is obtained according to a prestack seismic gather. The prestack seismic gather is a time-space domain seismic data set.

[0056] Exemplarily, the pre-stack seismic trace set corresponds to original marine seismic data containing ghost waves in the scenario shown in FIG. 1, and the data domain is a time space domain. The frequency-slowness domain seismic data set can be obtained by mapping the pre-stack seismic trace set to a frequency-slowness domain through data transformation. Specifically, for example, the pre-stack seismic trace set is first transformed from a time space domain to a frequency space domain to obtain a seismic data set with a data domain of a frequency space domain; and then, the three-dimensional dip stack transformation is performed on the seismic data set with the data domain of the frequency space domain, so as to obtain the frequency-slowness domain seismic data set.

[0057] In a possible implementation, FIG. 3 is a process schematic diagram of a specific step of step S101 in the embodiment shown in FIG. 2. As shown in FIG. 3, the specific step of step S101 includes:

[0058] Step S1011, performing Fourier forward transformation on the pre-stack seismic trace set to obtain a second seismic data set, and the second seismic data set is a seismic data set in a frequency space domain.

[0059] Exemplarily, the pre-stack seismic trace set is denoted as d(x, y, t). The data of each receiver in the pre-stack seismic trace set d(x, y, t) is Fourier forward transformed along a time direction, so as to convert the pre-stack seismic trace set with a data domain of a time space domain into a seismic data set in a frequency space domain, that is, a second seismic data set D(x, y, ω), wherein ω is a circular frequency of the data in the pre-stack seismic trace set, and ω is calculated according to formula (1); ω = 2πf (1)

[0060] wherein,

[0061] It can be understood that the pre-stack seismic trace set can also be processed by using fast Fourier forward transformation, which is not described herein again.

[0062] Step S1012, obtaining a vector offset according to the pre-stack seismic trace set, and the vector offset is used to indicate the distance between a shot point and a receiver.

[0063] Step S1013, obtaining a conjugate transformation operator of three-dimensional dip stack forward transformation according to the vector offset, and the conjugate transformation operator includes a transverse conjugate transformation operator and a longitudinal conjugate transformation operator.

[0064] Exemplarily, according to the shot point coordinates (s x ,s y ) and the receiver coordinates (r x ,r y), the distance from each receiver point to the shot point, i.e. the vector offset, is calculated, and is represented by vector offsetx and offsety, wherein the shot point corresponds to the excitation point in the scenario shown in FIG. 1, and the receiver point corresponds to the receiving point in the scenario shown in FIG. 1.

[0065] Exemplarily, first, a transform operator of three-dimensional dip moveout transformation is constructed according to the vector offset, and the transform operator includes a lateral transform operator and a longitudinal transform operator, and is constructed as shown in formula (2),

[0066] wherein L x is the lateral transform operator, L y is the longitudinal transform operator, m is the number of lateral seismic traces, is the lateral ray parameter of the dip moveout domain, k is the lateral trace number of the dip moveout domain, n is the number of lateral seismic traces, is the lateral ray parameter of the dip moveout domain, j is the lateral trace number of the dip moveout domain, and i represents an imaginary unit.

[0067] Further, a corresponding conjugate transform operator is obtained based on the transform operator calculated according to the above formula (2), and is shown in formula (3),

[0068] wherein, is the lateral conjugate transform operator, is the longitudinal conjugate transform operator.

[0069] Step S1014, a frequency-slowness domain seismic data set is obtained according to the second seismic data set and the conjugate transform operator.

[0070] Exemplarily, the second seismic data D(x, y, ω) is subjected to three-dimensional dip moveout forward transformation according to the conjugate transform operator, i.e. a frequency-slowness domain seismic data set M(p x , p y , ω) is obtained, i.e. the conversion of seismic data from the frequency space domain to the frequency-slowness domain is completed, and is shown in formula (4),

[0071] wherein p k is the lateral ray parameter of the dip moveout domain, and p j is the lateral ray parameter of the dip moveout domain.

[0072] Step S102, the frequency-slowness domain seismic data set is subjected to inverse ghost processing to obtain an initial inverse ghost seismic data set, and the data domain of the initial inverse ghost seismic data set is the frequency-slowness domain.

[0073] Exemplarily, the frequency-slowness domain seismic data set is subjected to inverse ghost processing by constructing an inverse ghost operator, and an initial inverse ghost seismic data set is obtained.

[0074] Specifically, FIG. 4 is a process diagram of the implementation steps of step S102 in the embodiment shown in FIG. 2, as shown in FIG. 4,

[0075] Step S1021, obtaining the depth data from the pre-stack seismic gather, the depth data including the shot depth data and the receiver depth data.

[0076] Exemplarily, as known from the application scenario shown in FIG. 1, both the shot and the receiver are located below the sea surface, and the depth in the seawater is the depth, so the shot depth data S and the receiver depth data R can be obtained from the pre-stack seismic gather. d d .

[0077] Step S1022, determining the ghost delay time from the depth data, the ghost delay time including the shot-end ghost delay time and the receiver-end ghost delay time.

[0078] Exemplarily, since the ghost includes the shot-end ghost and the receiver-end ghost, the ghost delay time includes the shot-end ghost delay time and the receiver-end ghost delay time, which are calculated by formula (5),

[0079] wherein Δt s is the shot-end ghost delay time; Δt r is the receiver-end ghost delay time; S d is the shot depth data; R d is the receiver depth data; and v is the speed of seawater, which is known data; and θ is the exit angle of the ghost.

[0080] Further, FIG. 5 is a process diagram of the implementation steps of step S1022 in the embodiment shown in FIG. 4, as shown in FIG. 5,

[0081] Step S10221, obtaining the ray parameter, the ray parameter including the transverse ray parameter of the tilt stack domain and the longitudinal ray parameter of the tilt stack domain.

[0082] Step S10222, determining the ghost delay time from the depth data and the ray parameter.

[0083] Exemplarily, the ray parameter of the three-dimensional tilt stack transformation includes the transverse ray parameter of the tilt stack domain and the longitudinal ray parameter of the tilt stack domain, and the relationship is shown in formula (6),

[0084] wherein p is the ray parameter of the three-dimensional tilt stack transformation, p x ​p is a lateral ray parameter of the tilted stack domain y p is a longitudinal ray parameter of the tilted stack domain.

[0085] Further, the relationship between the ray parameter p and the emergence angle θ of the ghost wave is shown in equation (7),

[0086] where v is the velocity of seawater, and is known data.

[0087] Further, substituting equation (6) and equation (7) into equation (5), the ghost wave delay time based on the depth data and the ray parameter can be obtained, as shown in equation (8),

[0088] In step S1023, the anti-ghost operator is obtained according to the ghost wave delay time, and the anti-ghost operator includes a shot-end anti-ghost operator and a receiver-end anti-ghost operator.

[0089] Exemplarily, since the ghost wave includes a shot-end ghost wave and a receiver-end ghost wave, the anti-ghost operator includes a shot-end anti-ghost operator and a receiver-end anti-ghost operator, and the anti-ghost operator is calculated by equation (9),

[0090] where G s (p x ,p y ,ω) is the shot-end anti-ghost operator, G r (p x ,p y ,ω) is the receiver-end anti-ghost operator; R is the reflection coefficient of the water surface, which is known data; Δt s is the shot-end ghost wave delay time; Δt r is the receiver-end ghost wave delay time; ω is the circular frequency of the pre-stack seismic trace data set, and i represents the imaginary unit.

[0091] In step S1024, the initial anti-ghost seismic data set is obtained according to the anti-ghost operator and the frequency-slowness domain seismic data set.

[0092] Exemplarily, the initial anti-ghost seismic data set determined based on the anti-ghost operator and the frequency-slowness domain seismic data set is calculated by equation (10), and the data domain of the initial anti-ghost seismic data set is the frequency-slowness domain,

[0093] where, is the initial anti-ghost seismic data set; G s (p x ,p y ,ω) is the shot-end anti-ghost operator, G r (p x ,p y, ω) is the detector end inverse ghost operator; M (p x ,p y , ω) is the frequency slowness domain seismic data set.

[0094] Step S103, the initial inverse ghost seismic data set is processed by inversion to obtain a target inverse ghost seismic data set.

[0095] Exemplarily, the initial inverse ghost seismic data set is processed by inversion to transform into a multivariate function optimization solving problem under multiple equation constraints, that is, under the premise that the constraint condition is established, an optimal solution after iterative inversion is obtained, that is, the target inverse ghost seismic data set

[0096] Step S104, according to the target inverse ghost seismic data set, a target seismic data set is obtained, and the target seismic data set is a set of inverse ghost seismic data in the time-space domain.

[0097] Exemplarily, since the data domain of the target inverse ghost seismic data set is the frequency slowness domain, the target inverse ghost seismic data set is processed by three-dimensional dip stack inverse transformation and inverse Fourier transformation to obtain a set of inverse ghost seismic data in the time-space domain, that is, the target seismic data set , that is, the suppression of ghosts of the seismic data set in the time-space domain is completed.

[0098] Specifically, for example, FIG. 6 is a process schematic diagram of the specific implementation steps of step S104 in the embodiment shown in FIG. 2, as shown in FIG. 6, the specific implementation steps of step S104 include:

[0099] Step S1041, the target inverse ghost seismic data set is processed by three-dimensional dip stack inverse transformation to obtain a third seismic data set, and the third seismic data set is a set of inverse ghost seismic data in the frequency-space domain after inversion processing.

[0100] Step S1042, the third seismic data set is processed by inverse Fourier transformation to obtain the target seismic data set.

[0101] Exemplarily, the data domain of the target inverse ghost seismic data set is the frequency slowness domain, and the target inverse ghost seismic data set is processed by three-dimensional dip stack inverse transformation based on the transformation operators L x and L y shown in equation (2) to obtain a set of inverse ghost seismic data in the frequency-space domain after inversion processing, that is, the third seismic data set , as shown in equation (11),

[0102] Further, inverse Fourier transform is performed on the third seismic data set to convert the deghosted seismic data set in the frequency space domain into a deghosted seismic data set in the time space domain, i.e., to obtain the target seismic data set

[0103] It can be understood that the pre-stack seismic trace set can also be processed by using fast inverse Fourier transform, which is not described herein.

[0104] In the embodiment, the frequency-slowness domain seismic data set is obtained according to the pre-stack seismic trace set, the pre-stack seismic trace set is a seismic data set in the time space domain; the initial deghosted seismic data set is obtained by performing deghosting processing on the frequency-slowness domain seismic data set, the data domain of the initial deghosted seismic data set is the frequency-slowness domain; the target deghosted seismic data set is obtained by performing inversion processing on the initial deghosted seismic data set; the target seismic data set is obtained according to the target deghosted seismic data set, the target seismic data set is a deghosted seismic data set in the time space domain. On the basis of processing the pre-stack seismic trace set into the frequency-slowness domain seismic data set, the deghosting is performed on the frequency-slowness domain seismic data set by using the deghosting operator constructed, and further the optimal solution under the constraint condition, i.e., the target deghosted seismic data set, is obtained by performing iterative inversion processing, and then the deghosted seismic data set in the time space domain, i.e., the target seismic data set, is obtained by performing three-dimensional dip stack inverse transform and inverse Fourier transform on the target deghosted seismic data set, and the deghosting of the seismic data set in the time space domain is completed, and the problem of inaccurate deghosting is solved.

[0105] FIG. 7 is a flowchart of a deghosting method provided by another embodiment of the application, as shown in FIG. 7, the deghosting method provided by the embodiment is further refined on the basis of the deghosting method provided by the embodiment shown in FIG. 2, and then the deghosting method provided by the embodiment includes the following steps:

[0106] In step S201, a frequency-slowness domain seismic data set is obtained according to a pre-stack seismic trace set, the pre-stack seismic trace set is a seismic data set in the time space domain.

[0107] In step S202, an initial deghosted seismic data set is obtained by performing deghosting processing on the frequency-slowness domain seismic data set, the data domain of the initial deghosted seismic data set is the frequency-slowness domain.

[0108] In step S203, a first seismic data set is obtained by performing three-dimensional dip stack inverse transform on the initial deghosted seismic data set, the first seismic data set is a deghosted seismic data set in the frequency space domain.

[0109] Exemplarily, the data domain of the initial cwave seismic data set is a frequency-slowness domain, and a transform operator L x and L y is performed on the initial cwave seismic data set to obtain a cwave seismic data set in a frequency-space domain, i.e., a first seismic data set as shown in equation (12),

[0110] In step S204, an inversion constraint equation is obtained according to the initial cwave seismic data set and the first seismic data set.

[0111] In step S205, at least one iteration inversion is performed on the inversion constraint equation to obtain a target cwave seismic data set.

[0112] Exemplarily, the L1 norm is used for sparse constraint, and equation (12) is simplified into a linear equation group as shown in equation (13),

[0113] wherein A = L x L y .

[0114] Further, based on the fast inversion method of the augmented Lagrange multiplier, the linear equation group corresponding to equation (13) is converted into a multivariate function under multiple equality constraints, and then the solution of the linear equation group of equation (13) can be converted into the optimization solution of the multivariate function, and the multivariate function is shown in equation (14),

[0115] wherein y i and μ i are sparse inversion constraint parameters, i (i≥1) is the number of iteration inversions, and the minimum value

[0116] Specifically, according to the constraint relationship corresponding to the inversion constraint equation, a first inversion constraint parameter is determined, and the first inversion constraint parameter is used to update the initial cwave seismic data set; as shown in equation (15), the first inversion constraint parameter μ i is:

[0117] wherein λ is a coordination parameter, and generally takes a value of 0.9; a soft threshold function soft is set, and

[0118] The updated initial cwave seismic data set is shown in equation (16),

[0119] wherein τ is generally equal to 10000;

[0120] According to the first inversion constraint parameter μ i and the updated initial deghosted seismic data set to obtain the second inversion constraint parameter y i ; the second inversion constraint parameter y i As shown in equation (17),

[0121] Further, based on the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion, it is determined whether to terminate iteration; specifically, if the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is less than a preset threshold, the target deghosted seismic data set is obtained; if the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is greater than or equal to the preset threshold, the iteration inversion is continued. For example, when y m -y m-1 <0.0001, the target deghosted seismic data set is obtained It can be understood that is a simplified writing of

[0122] FIG. 8 is a schematic diagram of energy spectrum changes before and after sparse inversion constraint on seismic data in a tilt stack domain provided by the present application, as shown in FIG. 8, FIG. 8(a) is the energy spectrum before sparse inversion constraint, and FIG. 8(b) is the energy spectrum after sparse inversion constraint.

[0123] In the step of the present embodiment, by introducing sparse inversion constraint to solve the linear equation set under the L1 norm condition, using the fast augmented Lagrange multiplier algorithm, and through at least one iteration inversion, the convergent optimal solution, i.e., the target deghosted seismic data set, can be obtained, and the suppression precision of the ghost is improved.

[0124] In step S206, the target seismic data set is obtained according to the target deghosted seismic data set, and the target seismic data set is a set of deghosted seismic data in the time-space domain.

[0125] In the present embodiment, the implementation manners of steps S201-S202 and step S206 are the same as those of steps S101-S102 and step S104 in the embodiment shown in FIG. 2 of the present application, and will not be repeated here.

[0126] ​FIG. 9 is a comparison diagram of the ghost wave suppression of marine seismic data provided by the present application. As shown in FIG. 9, FIG. 9(a) is a schematic diagram of the original marine seismic data containing ghost waves corresponding to the pre-stack seismic gather, and the arrow indicates the ghost wave; FIG. 9(b) is a schematic diagram of the marine seismic data (target seismic data set) after the ghost wave suppression, and the ghost wave indicated by the arrow has been suppressed.

[0127] FIG. 10 is a spectral analysis diagram of the marine seismic data before and after the ghost wave suppression provided by the present application. As shown in FIG. 10, the black line is the data curve before the ghost wave suppression, and the gray line is the data curve after the ghost wave suppression, and the low frequency and the notch point are effectively compensated, wherein the horizontal axis is frequency (Hz), and the vertical axis is amplitude (dB).

[0128] FIG. 11 is a comparison diagram of the marine seismic data stack sections before and after the ghost wave suppression provided by the present application. As shown in FIG. 11, FIG. 11(a) is the marine seismic data stack section before the ghost wave suppression, and FIG. 11(b) is the marine seismic data stack section after the ghost wave suppression.

[0129] FIG. 12 is a structural diagram of the ghost wave suppression device provided by an embodiment of the present application. As shown in FIG. 12, the ghost wave suppression device 3 provided by the embodiment includes:

[0130] The first processing module 31 is configured to obtain a frequency-slowness domain seismic data set according to the pre-stack seismic gather, and the pre-stack seismic gather is a time-space domain seismic data set;

[0131] The second processing module 32 is configured to perform anti-ghost wave processing on the frequency-slowness domain seismic data set to obtain an initial anti-ghost wave seismic data set, and the data domain of the initial anti-ghost wave seismic data set is a frequency-slowness domain;

[0132] The third processing module 33 is configured to perform inversion processing on the initial anti-ghost wave seismic data set to obtain a target anti-ghost wave seismic data set;

[0133] The determining module 34 is configured to obtain a target seismic data set according to the target anti-ghost wave seismic data set, and the target seismic data set is a time-space domain anti-ghost wave seismic data set.

[0134] In a possible implementation, when the third processing module 33 performs inversion processing on the initial anti-ghost wave seismic data set to obtain a target anti-ghost wave seismic data set, the third processing module 33 is specifically configured to: perform three-dimensional tilt stack inverse transformation on the initial anti-ghost wave seismic data set to obtain a first seismic data set, and the first seismic data set is a frequency-space domain anti-ghost wave seismic data set; obtain an inversion constraint equation according to the initial anti-ghost wave seismic data set and the first seismic data set; and perform at least one iteration inversion on the inversion constraint equation to obtain the target anti-ghost wave seismic data set.

[0135] In a possible implementation, the third processing module 33, when performing the at least one iteration inversion on the inversion constraint equation to obtain the target deghosted seismic data set, is specifically configured to: determine a first inversion constraint parameter according to a constraint relationship corresponding to the inversion constraint equation, the first inversion constraint parameter being used to update the initial deghosted seismic data set; obtain a second inversion constraint parameter according to the first inversion constraint parameter and the updated initial deghosted seismic data set; if a difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is less than a preset threshold, obtain the target deghosted seismic data set; and if the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is greater than or equal to the preset threshold, continue the iteration inversion.

[0136] In a possible implementation, the first processing module 31, when obtaining the frequency-slowness domain seismic data set according to the prestack seismic trace set, is specifically configured to: perform Fourier forward transformation on the prestack seismic trace set to obtain a second seismic data set, the second seismic data set being a seismic data set in a frequency-space domain; obtain a vector offset according to the prestack seismic trace set, the vector offset being used to indicate a distance between a shot point and a receiver point; obtain a conjugate transformation operator of three-dimensional dip stack forward transformation according to the vector offset, the conjugate transformation operator including a transverse conjugate transformation operator and a longitudinal conjugate transformation operator; and obtain the frequency-slowness domain seismic data set according to the second seismic data set and the conjugate transformation operator.

[0137] In a possible implementation, the second processing module 32, when performing deghosting processing on the frequency-slowness domain seismic data set to obtain the initial deghosted seismic data set, is specifically configured to: obtain sink depth data according to the prestack seismic trace set, the sink depth data including shot point sink depth data and receiver point sink depth data; determine a ghost delay time according to the sink depth data, the ghost delay time including a shot point end ghost delay time and a receiver point end ghost delay time; obtain a deghosting operator according to the ghost delay time, the deghosting operator including a shot point end deghosting operator and a receiver point end deghosting operator; and obtain the initial deghosted seismic data set according to the deghosting operator and the frequency-slowness domain seismic data set.

[0138] In a possible implementation, the second processing module 32, when determining the ghost delay time according to the sink depth data, is specifically configured to: obtain ray parameters, the ray parameters including a transverse ray parameter in a dip stack domain and a longitudinal ray parameter in the dip stack domain; and determine the ghost delay time according to the sink depth data and the ray parameters.

[0139] In a possible implementation, the determining module 34 is specifically configured to: perform three-dimensional tilt stack inverse transformation on the target deghosted seismic data set to obtain a third seismic data set, the third seismic data set being a deghosted seismic data set in a frequency space domain after inversion processing; and perform inverse Fourier transform on the third seismic data set to obtain the target seismic data set when obtaining the target seismic data set according to the target deghosted seismic data set.

[0140] The first processing module 31, the second processing module 32, the third processing module 33, and the determining module 34 are sequentially connected. The deghosting device 3 provided in this embodiment can implement the technical solutions of any one of the method embodiments shown in FIGS. 2-11, and has similar implementation principles and technical effects, which will not be described here again.

[0141] FIG. 13 is a structural schematic diagram of an electronic device provided in the application. As shown in FIG. 13, the electronic device 50 provided in this embodiment includes at least one processor 501 and a memory 502. Optionally, the device 50 further includes a communication component 503. The processor 501, the memory 502, and the communication component 503 are connected through a bus 504.

[0142] In the implementation process, the at least one processor 501 executes computer-executed instructions stored in the memory 502, so that the at least one processor 501 executes the method described above.

[0143] The specific implementation process of the processor 501 can refer to the method embodiments described above, which have similar implementation principles and technical effects, and will not be described here again in this embodiment.

[0144] In the above embodiments, it should be understood that the processor can be a central processing unit (CPU), and can also be other general-purpose processors, digital signal processors (DSP), application specific integrated circuits (ASIC), etc. The general-purpose processor can be a microprocessor or the processor can also be any conventional processor, etc. The steps of the method disclosed in the application can be directly embodied as execution completed by a hardware processor, or executed by a combination of hardware and software modules in the processor.

[0145] The memory can include a random access memory (RAM), and can also include a non-volatile memory (NVM), for example, at least one disk memory.

[0146] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. The bus can be divided into an address bus, a data bus, a control bus, etc. For the convenience of representation, the bus in the drawings of the present application does not limit to only one bus or one type of bus.

[0147] The present application also provides a computer program product, comprising a computer program, which, when executed by a processor, implements the method described above.

[0148] The present application also provides a computer readable storage medium, which stores computer execution instructions, and when a processor executes the computer execution instructions, the method described above is implemented.

[0149] The readable storage medium described above can be realized by any type of volatile or non-volatile storage device or their combination, 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 storage, flash memory, magnetic disk or optical disk. The readable storage medium can be any available medium that can be accessed by a general or special purpose computer.

[0150] An exemplary readable storage medium is coupled to the processor, so that the processor can read information from the readable storage medium, and can write information to the readable storage medium. Of course, the readable storage medium can also be an integral part of the processor. The processor and the readable storage medium can be located in an application specific integrated circuit (ASIC). Of course, the processor and the readable storage medium can also exist as discrete components in the device.

[0151] The division of units is only a logical functional division, and in actual implementation, there can be another division manner, for example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the coupling or direct coupling or communication connection between the units shown or discussed can be indirect coupling or communication connection through some interfaces, devices or units, which can be electrical, mechanical or other forms.

[0152] The units described as separate components may or may not be physically separate, and the components displayed as units may or may not be physical units, i.e. may be located in one place, or may be distributed to multiple network units. Part or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.

[0153] In addition, each functional unit in each embodiment of the present application can be integrated into one processing unit, or each unit can exist physically, or two or more units can be integrated into one unit.

[0154] If the functions are realized in the form of software function units and sold or used as independent products, they can be stored in a computer readable storage medium. Based on this understanding, the technical solutions of the present application essentially or the parts that contribute to the prior art or parts of the technical solutions can be embodied in the form of a software product. The computer software product is stored in a storage medium and includes several instructions for causing a computer device (which can be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods of the various embodiments of the present application. The aforementioned storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM, Read-Only Memory), a random access memory (RAM, Random Access Memory), a magnetic disk or an optical disk, and various media that can store program codes.

[0155] Those of ordinary skill in the art can understand that all or part of the steps of the above-mentioned method embodiments can be completed by program instruction-related hardware. The aforementioned program can be stored in a computer readable storage medium. The program, when executed, executes steps including the above-mentioned method embodiments; and the aforementioned storage medium includes: ROM, RAM, magnetic disk or optical disk, and various media that can store program codes.

[0156] Finally, it should be noted that those skilled in the art, after considering the specification and practicing the invention disclosed herein, will easily think of other embodiments of the present application. The present application is intended to cover any variations, uses or adaptations of the present application that follow the general principles of the present application and include common knowledge or conventional techniques in the art that are not disclosed in the present application, and is not limited to the precise structure described above and shown in the drawings, and various modifications and changes can be made without departing from the scope thereof. The scope of the present application is only limited by the appended claims.

Claims

1. A ghost wave suppression method, characterized by, The method comprises: According to the pre-stack seismic trace set, a frequency-slowness domain seismic data set is obtained, the pre-stack seismic trace set being a time-space domain seismic data set; The frequency-slowness domain seismic data set is subjected to inverse ghost processing to obtain an initial inverse ghost seismic data set, a data domain of the initial inverse ghost seismic data set being a frequency-slowness domain; The initial inverse ghost seismic data set is subjected to inversion processing to obtain a target inverse ghost seismic data set; According to the target inverse ghost seismic data set, a target seismic data set is obtained, the target seismic data set being a time-space domain inverse ghost seismic data set.

2. The method of claim 1, wherein, The initial inverse ghost seismic data set is subjected to inversion processing to obtain a target inverse ghost seismic data set, comprising: The initial inverse ghost seismic data set is subjected to three-dimensional tilt stack inverse transformation to obtain a first seismic data set, the first seismic data set being a frequency-space domain inverse ghost seismic data set; According to the initial inverse ghost seismic data set and the first seismic data set, an inversion constraint equation is obtained; The inversion constraint equation is subjected to at least one iteration inversion to obtain the target inverse ghost seismic data set.

3. The method of claim 2, wherein, The initial inverse ghost seismic data set is subjected to inversion processing to obtain a target inverse ghost seismic data set, comprising: According to a constraint relationship corresponding to the inversion constraint equation, a first inversion constraint parameter is determined, the first inversion constraint parameter being used for updating the initial inverse ghost seismic data set; According to the first inversion constraint parameter and the updated initial inverse ghost seismic data set, a second inversion constraint parameter is obtained; If a difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is less than a preset threshold, the target inverse ghost seismic data set is obtained; If the difference between the second inversion constraint parameter corresponding to the current iteration inversion and the second inversion constraint parameter corresponding to the last iteration inversion is greater than or equal to the preset threshold, iteration inversion is continued.

4. The method according to any one of claims 1 to 3, characterized in that, The initial inverse ghost seismic data set is subjected to inversion processing to obtain a target inverse ghost seismic data set, comprising: The pre-stack seismic trace set is subjected to Fourier forward transformation to obtain a second seismic data set, the second seismic data set being a frequency-space domain seismic data set; According to the pre-stack seismic trace set, a vector shot-receiver distance is obtained, the vector shot-receiver distance being used for indicating a distance between a shot point and a receiver point; According to the vector shot-receiver distance, a conjugate transformation operator of three-dimensional tilt stack forward transformation is obtained, the conjugate transformation operator comprising a transverse conjugate transformation operator and a longitudinal conjugate transformation operator; The second seismic data set and the conjugate transformation operator are used to obtain the frequency-slowness domain seismic data set.

5. The method according to any one of claims 1 to 4, characterized in that, The initial inverse ghost seismic data set is obtained by subjecting the frequency-slowness domain seismic data set to inverse ghost processing, comprising: According to the pre-stack seismic trace set, sink depth data is obtained, the sink depth data comprising shot point sink depth data and receiver point sink depth data; According to the sink depth data, ghost delay time is determined, the ghost delay time comprising shot point end ghost delay time and receiver point end ghost delay time; According to the ghost delay time, an anti-ghost operator is obtained, the anti-ghost operator including a shot-end anti-ghost operator and a receiver-end anti-ghost operator; According to the anti-ghost operator and the frequency slowness domain seismic data set, the initial anti-ghost seismic data set is obtained.

6. The method of claim 5, wherein, The determination of the ghost delay time according to the setting depth data includes: Obtaining ray parameters, the ray parameters including transverse ray parameters in a dip stack domain and longitudinal ray parameters in the dip stack domain; Determining the ghost delay time according to the setting depth data and the ray parameters.

7. The method according to any one of claims 1 to 6, characterized in that, The obtaining of the target seismic data set according to the target anti-ghost seismic data set includes: Performing three-dimensional dip stack inverse transformation on the target anti-ghost seismic data set to obtain a third seismic data set, the third seismic data set being an anti-ghost seismic data set based on an inversion-processed frequency space domain; Performing inverse Fourier transformation on the third seismic data set to obtain the target seismic data set.

8. An electronic device, comprising: It includes: A processor and a memory connected in communication with the processor; The memory stores computer execution instructions; The processor executes the computer execution instructions stored in the memory to implement the method in any one of claims 1 to 7.

9. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer execution instructions, and the computer execution instructions are executed by the processor to implement the ghost suppression method in any one of claims 1 to 7.

10. A computer program product, characterised in that, It includes a computer program, and the computer program is executed by the processor to implement the ghost suppression method in any one of claims 1 to 7.

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