A method, device, equipment and medium for dynamic correction based on deconvolution third-order cumulant

Abstract

This invention discloses a dynamic correction method, apparatus, device, and medium based on third-order cumulant deconvolution. The method includes: acquiring zero-offset and non-zero-offset reflected waves from a common center point gather; reconstructing the zero-offset and non-zero-offset reflected waves based on the third-order cumulant to obtain a virtual reflection corresponding to the common center point gather; the virtual reflection includes the normal time difference between the zero-offset and non-zero-offset reflected waves; performing dynamic correction processing on the virtual reflection based on the third-order cumulant to obtain a dynamically corrected first reflected wave corresponding to the common center point gather; processing the first reflected wave using deconvolution to obtain a second reflected wave corresponding to the common center point gather; and superimposing the second reflected waves corresponding to different common center point gathers in phase to obtain a target reflected wave. This invention solves the problem of stretching during long-offset dynamic correction, improves the resolution and amplitude fidelity of seismic data, and enhances the signal-to-noise ratio of seismic data.

Description

Technical Field

[0001] This invention relates to the field of oil and gas geophysical exploration technology, and in particular to a dynamic correction method, apparatus, equipment and medium based on the third-order cumulative quantity of deconvolution. Background Technology

[0002] Dynamic correction is an essential step in seismic data processing, aiming to eliminate the influence of shot-receiver offset on propagation time. However, traditional methods are highly dependent on the speed of dynamic correction and often employ a "point-by-point relocation and interpolation" approach, which frequently leads to waveform stretching and spectral distortion of reflected waves. This phenomenon is particularly pronounced in shallow and long-offset records. These distortions severely reduce the signal-to-noise ratio and fidelity of common-center gathers, hindering subsequent horizontal stacking and AVO analysis. Summary of the Invention

[0003] This invention provides a dynamic correction method, apparatus, device, and medium based on the third-order cumulant of deconvolution to solve the problem of dynamic correction stretching at long offsets, improve the resolution and amplitude fidelity of seismic data, and improve the signal-to-noise ratio of seismic data.

[0004] According to one aspect of the present invention, a dynamic correction method based on the third-order cumulant of deconvolution is provided, the method comprising:

[0005] Obtain the zero-offset and non-zero-offset reflected waves of the common center point gather, and reconstruct the zero-offset and non-zero-offset reflected waves based on the third-order cumulant to obtain the virtual reflections corresponding to the common center point gather; the virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves.

[0006] Based on the third-order cumulant, the virtual reflection is dynamically corrected to obtain the first reflected wave after dynamic correction corresponding to the common center point gather.

[0007] The first reflected wave is processed by deconvolution to obtain the second reflected wave corresponding to the common center point gather;

[0008] The target reflected wave is obtained by superimposing the second reflected waves corresponding to different common center point gathers in phase.

[0009] According to another aspect of the present invention, a dynamic correction device based on the third-order cumulant of deconvolution is provided, the device comprising:

[0010] The virtual reflection determination module is used to acquire the zero-offset reflected wave and the non-zero-offset reflected wave of the common center point gather, and reconstruct the zero-offset reflected wave and the non-zero-offset reflected wave based on the third-order cumulant to obtain the virtual reflection corresponding to the common center point gather; the virtual reflection includes the normal time difference between the zero-offset reflected wave and the non-zero-offset reflected wave.

[0011] The first reflection wave determination module is used to perform dynamic correction processing on the virtual reflection based on the third-order cumulant to obtain the dynamically corrected first reflection wave corresponding to the common center point gather.

[0012] The second reflected wave determination module is used to process the first reflected wave by deconvolution to obtain the second reflected wave corresponding to the common center point gather.

[0013] The target reflected wave determination module is used to superimpose the second reflected waves corresponding to different common center point gathers in phase to obtain the target reflected wave.

[0014] According to another aspect of the present invention, an electronic device is provided, the electronic device comprising:

[0015] At least one processor; and

[0016] A memory communicatively connected to the at least one processor; wherein,

[0017] The memory stores a computer program that can be executed by the at least one processor, which enables the at least one processor to perform the dynamic correction method based on the third-order cumulant of deconvolution as described in any embodiment of the present invention.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided, the computer-readable storage medium storing computer instructions for causing a processor to execute and implement the dynamic correction method based on the third-order cumulant of deconvolution as described in any embodiment of the present invention.

[0019] The technical solution of this invention involves acquiring zero-offset and non-zero-offset reflected waves from a common center point gather, reconstructing the zero-offset and non-zero-offset reflected waves based on a third-order cumulant to obtain virtual reflections corresponding to the common center point gather; the virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves; and performing dynamic correction processing on the virtual reflections based on the third-order cumulant to obtain the dynamically corrected first reflected wave corresponding to the common center point gather. This application achieves dynamic correction of the common center point gather without requiring velocity parameters, solving the long-channel stretching problem. Furthermore, the third-order cumulant utilizes three reflected waves as data input, which has a certain protective effect on weak signals and is more conducive to suppressing random noise, improving the signal-to-noise ratio of seismic data. The first reflected wave is further processed using deconvolution to obtain the second reflected wave corresponding to the common center point gather; and the second reflected waves corresponding to different common center point gathers are superimposed in phase to obtain the target reflected wave. The introduction of deconvolution effectively improves the resolution of the dynamically corrected reflected wave. Therefore, this invention improves the resolution and amplitude fidelity of seismic data.

[0020] It should be understood that the description in this section is not intended to identify key or essential features of the embodiments of the present invention, nor is it intended to limit the scope of the invention. Other features of the invention will become readily apparent from the following description. Attached Figure Description

[0021] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0022] Figure 1 This is a flowchart of a dynamic correction method based on the third-order cumulant of deconvolution according to an embodiment of the present invention;

[0023] Figure 2 This is a schematic diagram illustrating the implementation process of the dynamic correction method based on the third-order cumulant of deconvolution, applicable according to an embodiment of the present invention.

[0024] Figure 3 This is a schematic diagram of a normalized spectrum comparison applicable to embodiments of the present invention;

[0025] Figure 4 This is a schematic diagram illustrating the comparison of three different methods for achieving dynamic correction according to embodiments of the present invention;

[0026] Figure 5 This is a schematic diagram illustrating a single-channel comparison of three different methods for achieving dynamic correction according to embodiments of the present invention;

[0027] Figure 6 This is a schematic diagram comparing the spectra of three different methods for achieving dynamic correction according to embodiments of the present invention;

[0028] Figure 7 This is a schematic diagram comparing three different methods applied according to embodiments of the present invention to achieve dynamic correction of noisy data;

[0029] Figure 8 This is a schematic diagram illustrating a single-channel comparison of three different methods for implementing dynamic correction of noisy data according to embodiments of the present invention;

[0030] Figure 9 This is a schematic diagram comparing the spectrum of three different methods applied according to embodiments of the present invention to achieve dynamic correction of noisy data;

[0031] Figure 10 This is a schematic diagram of a dynamic correction device based on the third-order cumulant of deconvolution according to an embodiment of the present invention;

[0032] Figure 11 This is a schematic diagram of the structure of an electronic device that implements the dynamic correction method based on the third-order cumulant of deconvolution according to an embodiment of the present invention. Detailed Implementation

[0033] To enable those skilled in the art to better understand the present invention, the technical solutions of the present invention will be clearly and completely described below with reference to the accompanying drawings of the embodiments of the present invention. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present invention.

[0034] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of the invention described herein can be implemented in orders other than those illustrated or described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover a non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0035] Example 1

[0036] Figure 1 This is a flowchart illustrating a dynamic correction method based on third-order deconvolution cumulants, provided as an embodiment of the present invention. This embodiment is applicable to the dynamic correction of reflected waves in seismic data. The method can be executed by a dynamic correction device based on third-order deconvolution cumulants, which can be implemented in hardware and / or software and can be configured in any electronic device with network communication capabilities. Figure 1 As shown, the dynamic correction method based on the third-order cumulant of deconvolution of the present invention includes:

[0037] S110. Obtain the zero-offset and non-zero-offset reflected waves of the common center point gather. Reconstruct the zero-offset and non-zero-offset reflected waves based on the third-order cumulant to obtain the virtual reflections corresponding to the common center point gather. The virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves.

[0038] The common center point gather is a gather formed by combining seismic records from different receivers that share a common reflection point. Non-zero offset reflections are received when there is a predetermined horizontal distance (non-zero offset) between the receiver and the source; zero offset reflections are received when the source and receiver are at the same location. The third-order cumulant contains the phase information characteristics of the signal, is completely blind to zero-mean Gaussian noise, and is sensitive to anomalous signals, thus providing a high degree of freedom.

[0039] Specifically, virtual reflections corresponding to common center point gathers are obtained by reconstructing zero-offset and non-zero-offset reflections based on the third-order cumulant. The zero-offset reflection is a single reflection, and the non-zero-offset reflection is a double reflection. The third-order cumulant uses three reflections as data input, which has a certain protective effect on weak signals, is more conducive to suppressing random noise, and improves the signal-to-noise ratio of seismic data.

[0040] Furthermore, the virtual reflection virG is represented by the following formula. j (Δt):

[0041] virG j (Δt)=cum3x[U0(t0),U j (t j ),U j+1 (t j+1 )];

[0042] Among them, virG j (Δt) represents the non-zero offset reflected wave U. j (t j The virtual reflection between the zero-offset reflected wave U0(t0) and the zero-offset reflected wave U0(t0), where cum3x represents the third-order cumulant operator, U j (t j ) and U j+1 (t j+1 All are non-zero offset reflected waves, U0(t0) is a zero offset reflected wave, and virG j (Δt) includes the non-zero offset reflected wave U j (t j The normal time difference between the reflected wave U0(t0) and the zero-offset reflected wave U0(t0).

[0043] S120. Based on the third-order cumulant, perform dynamic correction processing on the virtual reflection to obtain the first reflected wave after dynamic correction corresponding to the common center point gather.

[0044] Specifically, the first reflected wave after dynamic correction is represented by the following formula.

[0045]

[0046] Among them, virG j+1 (Δt j+1 ) represents the non-zero offset reflected wave U j+1 (t j+1 The virtual reflection between the zero-offset reflected wave U0(t0) and the zero-offset reflected wave U0(t0).

[0047] S130. The first reflected wave is processed by deconvolution to obtain the second reflected wave corresponding to the common center point gather.

[0048] Specifically, the introduction of the third-order cumulant operator will make the reflected wave thicker and reduce the resolution. Therefore, deconvolution is introduced to reshape it, and the second reflected wave is represented by the following formula.

[0049]

[0050] Where |A| represents the power spectrum of the source wavelet, and δ represents the stability factor.

[0051] S140. The second reflected waves corresponding to different common center point gathers are superimposed in phase to obtain the target reflected wave.

[0052] Specifically, according to seismic interferometry theory, superimposing all dynamically corrected second reflected waves in phase yields an enhanced reflected wave, i.e., the target reflected wave. Stable-phase superposition is beneficial for reducing residual noise after the compressive braking correction process, further improving the signal-to-noise ratio of the reflected wave. Specifically, the target reflected wave SuperU is expressed by the following formula:

[0053]

[0054] The technical solution of this invention involves acquiring zero-offset and non-zero-offset reflected waves from a common center point gather, reconstructing the zero-offset and non-zero-offset reflected waves based on a third-order cumulant to obtain virtual reflections corresponding to the common center point gather; the virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves; and performing dynamic correction processing on the virtual reflections based on the third-order cumulant to obtain the dynamically corrected first reflected wave corresponding to the common center point gather. This application achieves dynamic correction of the common center point gather without requiring velocity parameters, solving the long-channel stretching problem. Furthermore, the third-order cumulant utilizes three reflected waves as data input, which has a certain protective effect on weak signals and is more conducive to suppressing random noise, improving the signal-to-noise ratio of seismic data. The first reflected wave is further processed using deconvolution to obtain the second reflected wave corresponding to the common center point gather; and the second reflected waves corresponding to different common center point gathers are superimposed in phase to obtain the target reflected wave. The introduction of deconvolution effectively improves the resolution of the dynamically corrected reflected wave. Therefore, this invention improves the resolution and amplitude fidelity of seismic data.

[0055] Example 2

[0056] Since seismic waves are time-varying signals, their frequency and amplitude change with propagation distance and time. Therefore, to demonstrate the implementation process of the dynamic correction method based on the third-order cumulant of deconvolution, attenuated seismic waves are obtained through forward modeling, such as... Figure 2 (a)-2(c).

[0057] Figure 2 (a) is a zero-offset reflected wave. Figure 2 (b) and Figure 2 (c) represents a non-zero offset reflected wave; as the offset distance increases, the seismic wave amplitude and dominant frequency continuously decrease. Using the above signal as input, we obtain... Figure 2 The virtual reflection shown in (d) includes the normal time difference between the zero-offset reflected wave and the non-zero-offset reflected wave, and its travel time is exactly... Figure 2 (a) and Figure 2 (b) time difference. Figure 2 (e) is the first reflected wave after dynamic correction corresponding to the common center point gather, obtained by dynamic correction of the virtual reflection based on the third-order cumulant. Its travel time is... Figure 2 (a) Completely identical, but with subwavelobe sidelobes. Figure 2 (f) is to process the first reflected wave by deconvolution to obtain the second reflected wave corresponding to the common center point gather. It can be found that the wavelet sidelobes are effectively suppressed and the resolution of the reflected wave is improved.

[0058] from Figure 3 As shown in the normalized spectrum, although the generation of wavelet sidelobes narrows the bandwidth, the dominant frequency of the seismic wavelet remains consistent before and after dynamic correction using the third-order cumulant, indicating no distortion. The third-order cumulant utilizes high-frequency information from zero offset, and the dominant frequency of the dynamically corrected seismic wave is higher than that of the wavelet. Figure 2 (b) The dominant frequency demonstrates that the proposed method can not only effectively achieve dynamic correction and solve the spectral distortion problem of traditional methods, but also improve the dominant frequency information after dynamic correction. The spectrum after deconvolution and Figure 2 (a) shows high spectral consistency, indicating the effectiveness of the proposed method.

[0059] Establish such as Figure 4 (a) shows multiple in-phase axis models. Figure 4 (b) indicates that the traditional method is... Figure 4(a) The processed results show that as the offset increases, the seismic wavelet stretching becomes more severe, and the waveform distortion occurs, leading to a decrease in the correlation of the phase axes on the dynamic correction common center point gather, especially the shallow phase axes. Although all five reflected wave phase axes are flattened, the waveforms of the first and second phase axes show significant stretching at far offsets, while the waveforms of the third and fourth phase axes show less stretching at far offsets. Shallow phase axes are generally rare in seismic data; directly removing them would inevitably reduce the resolution and fidelity of shallow seismic data. Figure 4 (c) indicates that... Figure 4 (a) The result of the third-order cumulative dynamic correction is that the five phase axes of the reflected waves are flattened and there is no dynamic correction stretching phenomenon on the cross section, but there are wavelet sidelobes. Figure 4 (d) indicates that in Figure 4 The result of deconvolution based on (c) Figure 4 (c) The sidelobes are effectively suppressed, and the seismic wavelet morphology at different offsets is well preserved. Figure 5 Comparison of near and far offset single track and Figure 6 The comparison of the normalized spectrum further demonstrates the effectiveness of the proposed method.

[0060] With the increasing complexity of seismic exploration environments, seismic waves acquired in the field are often contaminated by irregular random noise (such as microseisms, passing vehicles, and wind rustling), thus affecting the signal-to-noise ratio of seismic data. To verify the noise resistance of a dynamic correction method based on the third-order cumulant of deconvolution, [the following is a separate, unrelated sentence:] ... Figure 4 (a) Add random noise to obtain Figure 7 (a) shows the noisy data. The added random noise masks most of the effective signal, especially the weak energy reflected waves from the far channel, resulting in a signal-to-noise ratio as low as -4.18 dB for the entire common center point gather. Figure 7 (b) indicates that... Figure 7 (a) The results obtained using the traditional method show that even with an accurate dynamic correction speed, the correction effect remains poor. As the offset increases, severe waveform distortion occurs, and spurious in-phase axes are generated. Clearly, the traditional dynamic correction method lacks the ability to suppress random noise; strong random noise still exists and may even interfere with the dynamic correction results of the valid signal. Figure 7 (c) is for Figure 7 (a) The result of dynamic correction using the third-order cumulant is that the signal-to-noise ratio is improved to 3.47 dB, indicating that the third-order cumulant has the ability to suppress random noise. Figure 7 (d) is in Figure 7 Based on (c), the result of deconvolution processing suppresses the wavelet sidelobes and further improves the signal-to-noise ratio to 4.37dB.

[0061] To further showcase the details, Figure 8 A comparison of single-channel records under different offsets is presented. It shows that the single-channel record obtained by the traditional method still retains strong-amplitude random noise. The single-channel record obtained after cross-correlation still retains some random noise, but the amplitude of the residual noise is small, manifesting as small-range sawtooth jitter. This indicates that the cross-correlation method has suppressed most of the random noise. The single-channel record obtained by the third-order cumulant method shows that random noise is basically suppressed, and the entire single-channel record is clean. The single-channel comparison results show that the third-order cumulant method is more effective than cross-correlation in suppressing random noise, and the traditional dynamic correction method has no ability to suppress random noise. Figure 9 The presentation shows a spectral comparison, revealing that noise causes irregular jitter in the original seismic data spectrum. Traditional methods result in severe spectral distortion, completely altering the dominant frequency and bandwidth. Cross-correlation and third-order cumulants effectively preserve the dominant frequency and bandwidth of seismic waves. Combining the above multi-angle comparisons, the proposed dynamic correction method based on deconvolution third-order cumulants effectively solves the dynamic correction stretching problem, exhibits good noise suppression capabilities, and can compress wavelet sidelobes, improving the vertical resolution of seismic data.

[0062] The dynamic correction method based on the third-order cumulant of deconvolution in this invention can effectively solve the stretching distortion problem of traditional dynamic correction methods at long offsets, has good noise suppression capability, and can improve the resolution of reflected waves. The dynamic correction method based on the third-order cumulant of deconvolution is of great significance for improving the resolution and amplitude fidelity of seismic data.

[0063] Example 3

[0064] Figure 10 This is a schematic diagram of a dynamic correction device based on the third-order cumulant of deconvolution, provided by an embodiment of the present invention. This embodiment is applicable to the dynamic correction of reflected waves in seismic data. The dynamic correction device based on the third-order cumulant of deconvolution can be implemented in hardware and / or software, and can be configured in any electronic device with network communication capabilities. Figure 10 As shown, the dynamic correction device based on the third-order cumulant of deconvolution of the present invention includes:

[0065] The virtual reflection determination module 210 is used to acquire the zero-offset reflected wave and the non-zero-offset reflected wave of the common center point gather, and reconstruct the zero-offset reflected wave and the non-zero-offset reflected wave based on the third-order cumulant to obtain the virtual reflection corresponding to the common center point gather; the virtual reflection includes the normal time difference between the zero-offset reflected wave and the non-zero-offset reflected wave.

[0066] The first reflection wave determination module 220 is used to perform dynamic correction processing on the virtual reflection based on the third-order cumulant to obtain the dynamically corrected first reflection wave corresponding to the common center point gather.

[0067] The second reflected wave determination module 230 is used to process the first reflected wave by deconvolution to obtain the second reflected wave corresponding to the common center point gather;

[0068] The target reflected wave determination module 240 is used to superimpose the second reflected waves corresponding to different common center point gathers in phase to obtain the target reflected wave.

[0069] Based on the above embodiments, optionally, the virtual reflection virG can be represented by the following formula. j (Δt):

[0070] virG j (Δt)=cum3x[U0(t0),U j (t j ),U j+1 (t j+1 )];

[0071] Among them, virG j (Δt) represents the non-zero offset reflected wave U. j (t j The virtual reflection between the zero-offset reflected wave U0(t0) and the zero-offset reflected wave U0(t0), where cum3x represents the third-order cumulant operator, U j (t j ) and U j+1 (t j+1 All are non-zero offset reflected waves, U0(t0) is a zero offset reflected wave, and virG j (Δt) includes the non-zero offset reflected wave U j (t j The normal time difference between the reflected wave U0(t0) and the zero-offset reflected wave U0(t0).

[0072] Based on the above embodiments, optionally, the first reflected wave after dynamic correction can be represented by the following formula.

[0073]

[0074] Among them, virG j+1 (Δt j+1 ) represents the non-zero offset reflected wave U j+1 (t j+1 The virtual reflection between the zero-offset reflected wave U0(t0) and the zero-offset reflected wave U0(t0).

[0075] Based on the above embodiments, optionally, the second reflected wave can be represented by the following formula.

[0076]

[0077] Where |A| represents the power spectrum of the source wavelet, and δ represents the stability factor.

[0078] Based on the above embodiments, optionally, the target reflected wave SuperU can be represented by the following formula:

[0079]

[0080] Based on the above embodiments, optionally, the common center point gather is a gather formed by combining seismic records from different receivers that have a common reflection point in the seismic data.

[0081] Based on the above embodiments, optionally, the non-zero offset reflected wave is the reflected wave received when there is a preset horizontal distance between the receiving point and the seismic source; the zero offset reflected wave is the reflected wave received when the seismic source and the receiving point are at the same position.

[0082] The dynamic correction device based on the third-order cumulant of deconvolution provided in the embodiments of the present invention can execute the dynamic correction method based on the third-order cumulant of deconvolution provided in any embodiment of the present invention, and has the corresponding functional modules and beneficial effects of the method.

[0083] Example 4

[0084] According to embodiments of this disclosure, this disclosure also provides an electronic device, a readable storage medium, and a computer program product.

[0085] Figure 11 A schematic diagram of an electronic device is shown, which can be used to implement the dynamic correction method based on the third-order cumulant of deconvolution, as described in embodiments of the present invention. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processors, cellular phones, smartphones, wearable devices (e.g., helmets, glasses, watches, etc.), and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely illustrative and are not intended to limit the implementation of the invention described and / or claimed herein.

[0086] like Figure 11As shown, the electronic device 10 includes at least one processor 11 and a memory, such as a read-only memory (ROM) 12 or a random access memory (RAM) 13, communicatively connected to the at least one processor 11. The memory stores computer programs executable by the at least one processor. The processor 11 can perform various appropriate actions and processes based on the computer program stored in the ROM 12 or loaded from storage unit 18 into the RAM 13. The RAM 13 may also store various programs and data required for the operation of the electronic device 10. The processor 11, ROM 12, and RAM 13 are interconnected via a bus 14. An input / output (I / O) interface 15 is also connected to the bus 14.

[0087] Multiple components in electronic device 10 are connected to I / O interface 15, including: input unit 16, such as keyboard, mouse, etc.; output unit 17, such as various types of displays, speakers, etc.; storage unit 18, such as disk, optical disk, etc.; and communication unit 19, such as network card, modem, wireless transceiver, etc. Communication unit 19 allows electronic device 10 to exchange information / data with other devices through computer networks such as the Internet and / or various telecommunications networks.

[0088] Processor 11 can be a variety of general-purpose and / or special-purpose processing components with processing and computing capabilities. Some examples of processor 11 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various special-purpose artificial intelligence (AI) computing chips, various processors running machine learning model algorithms, a digital signal processor (DSP), and any suitable processor, controller, microcontroller, etc. Processor 11 performs the various methods and processes described above, such as the dynamic correction method based on the third-order cumulant of deconvolution.

[0089] In some embodiments, the dynamic correction method based on the third-order cumulant of deconvolution can be implemented as a computer program tangibly contained in a computer-readable storage medium, such as storage unit 18. In some embodiments, part or all of the computer program can be loaded and / or installed on electronic device 10 via ROM 12 and / or communication unit 19. When the computer program is loaded into RAM 13 and executed by processor 11, one or more steps of the dynamic correction method based on the third-order cumulant of deconvolution described above can be performed. Alternatively, in other embodiments, processor 11 can be configured to perform the dynamic correction method based on the third-order cumulant of deconvolution by any other suitable means (e.g., by means of firmware).

[0090] Various embodiments of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field-programmable gate arrays (FPGAs), application-specific integrated circuits (ASICs), application-specific standard products (ASSPs), systems-on-a-chip (SoCs), complex programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various embodiments may include implementations in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which may be a dedicated or general-purpose programmable processor, capable of receiving data and instructions from a storage system, at least one input device, and at least one output device, and transmitting data and instructions to the storage system, the at least one input device, and the at least one output device.

[0091] Computer programs used to implement the methods of the present invention may be written in any combination of one or more programming languages. These computer programs may be provided to a processor of a general-purpose computer, a special-purpose computer, or other programmable data processing device, such that when executed by the processor, the computer programs cause the functions / operations specified in the flowcharts and / or block diagrams to be performed. The computer programs may be executed entirely on a machine, partially on a machine, or as a standalone software package, partially on a machine and partially on a remote machine, or entirely on a remote machine or server.

[0092] In the context of this invention, a computer-readable storage medium can be a tangible medium that may contain or store a computer program for use by or in conjunction with an instruction execution system, apparatus, or device. A computer-readable storage medium may include, but is not limited to, electronic, magnetic, optical, electromagnetic, infrared, or semiconductor systems, apparatus, or devices, or any suitable combination thereof. Alternatively, a computer-readable storage medium may be a machine-readable signal medium. More specific examples of machine-readable storage media include electrical connections based on one or more wires, portable computer disks, hard disks, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM or flash memory), optical fibers, portable compact disk read-only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination thereof.

[0093] To provide interaction with a user, the systems and techniques described herein can be implemented on an electronic device having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to the user; and a keyboard and pointing device (e.g., a mouse or trackball) through which the user provides input to the electronic device. Other types of devices can also be used to provide interaction with the user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including sound input, voice input, or tactile input).

[0094] The systems and technologies described herein can be implemented in computing systems that include backend components (e.g., as data servers), or computing systems that include middleware components (e.g., application servers), or computing systems that include frontend components (e.g., user computers with graphical user interfaces or web browsers through which users can interact with implementations of the systems and technologies described herein), or any combination of such backend, middleware, or frontend components. The components of the system can be interconnected via digital data communication of any form or medium (e.g., communication networks). Examples of communication networks include local area networks (LANs), wide area networks (WANs), blockchain networks, and the Internet.

[0095] A computing system can include clients and servers. Clients and servers are generally located far apart and typically interact through communication networks. The client-server relationship is created by computer programs running on the respective computers and having a client-server relationship with each other. The server can be a cloud server, also known as a cloud computing server or cloud host, which is a hosting product within the cloud computing service system to address the shortcomings of traditional physical hosts and VPS services, such as high management difficulty and weak business scalability.

[0096] It should be understood that the various forms of processes shown above can be used, with steps reordered, added, or deleted. For example, the steps described in this invention can be executed in parallel, sequentially, or in different orders, as long as the desired result of the technical solution of this invention can be achieved, and this is not limited herein.

[0097] The specific embodiments described above do not constitute a limitation on the scope of protection of this invention. Those skilled in the art should understand that various modifications, combinations, sub-combinations, and substitutions can be made according to design requirements and other factors. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of this invention should be included within the scope of protection of this invention.

Claims

1. A dynamic correction method based on the third-order cumulant of deconvolution, characterized in that, The method includes: Obtain the zero-offset and non-zero-offset reflected waves of the common center point gather, and reconstruct the zero-offset and non-zero-offset reflected waves based on the third-order cumulant to obtain the virtual reflections corresponding to the common center point gather; the virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves. Based on the third-order cumulant, the virtual reflection is dynamically corrected to obtain the first reflected wave corresponding to the common center point gather; The first reflected wave is processed by deconvolution to obtain the second reflected wave corresponding to the common center point gather; The target reflected wave is obtained by superimposing the second reflected waves corresponding to different common center point gathers in phase.

2. The method according to claim 1, characterized in that, Based on the third-order cumulants, the virtual reflections corresponding to the common center point gather are reconstructed from the zero-offset and non-zero-offset reflected waves, including: The virtual reflection virG is expressed by the following equation j (Δt): virG j (Δt) = cum3x [U0(t0), U j (t j ), U j+1 (t j+1 )]; where virG j (Δt) is the non-zero-offset reflected wave U j (t j ) and the zero-offset reflected wave U0(t0), the virtual reflection between j (t j ) and U j+1 (t j+1 ) are both non-zero-offset reflected waves, U0(t0) is the zero-offset reflected wave, virG j (Δt) contains the normal moveout between the non-zero-offset reflected wave U j (t j ) and the zero-offset reflected wave U0(t0).

3. The method according to claim 2, characterized in that, Based on the third-order cumulant, dynamic correction processing is performed on the virtual reflection to obtain the dynamically corrected first reflected wave corresponding to the common center point gather, including: The first reflected wave after dynamic correction is expressed by the following formula. Among them, virG j+1 (Δt j+1 ) represents the non-zero offset reflected wave U j+1 (t j+1 The virtual reflection between the zero-offset reflected wave U0(t0) and the zero-offset reflected wave U0(t0).

4. The method according to claim 3, characterized in that, The second reflected wave corresponding to the common center point gather is obtained by processing the first reflected wave using deconvolution, including: The second reflected wave is represented by the following formula. Where |A| represents the power spectrum of the source wavelet, and δ represents the stability factor.

5. The method according to claim 1, characterized in that, The target reflected wave is obtained by in-phase superposition of the second reflected waves corresponding to different common center point gathers, including: The target reflected wave SuperU is represented by the following formula:

6. The method according to claim 1, characterized in that, The common center point gather is a gather formed by combining seismic records from different receivers that share a common reflection point in seismic data.

7. The method according to claim 1, characterized in that, The non-zero offset reflected wave is the reflected wave received when there is a preset horizontal distance between the receiving point and the seismic source; the zero offset reflected wave is the reflected wave received when the seismic source and the receiving point are at the same position.

8. A dynamic correction device based on the third-order cumulant of deconvolution, characterized in that, The device includes: The virtual reflection determination module is used to acquire the zero-offset and non-zero-offset reflected waves of the common center point gather, and reconstruct the virtual reflections corresponding to the common center point gather based on the third-order cumulant; the virtual reflections include the normal time difference between the zero-offset and non-zero-offset reflected waves. The first reflection wave determination module is used to perform dynamic correction processing on the virtual reflection based on the third-order cumulant to obtain the dynamically corrected first reflection wave corresponding to the common center point gather. The second reflected wave determination module is used to process the first reflected wave by deconvolution to obtain the second reflected wave corresponding to the common center point gather; The target reflected wave determination module is used to superimpose the second reflected waves corresponding to different common center point gathers in phase to obtain the target reflected wave.

9. An electronic device, characterized in that, The electronic device includes: At least one processor; and A memory communicatively connected to the at least one processor; wherein, The memory stores a computer program that can be executed by the at least one processor, the computer program being executed by the at least one processor to enable the at least one processor to perform the dynamic correction method based on the third-order cumulant of deconvolution as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer instructions that cause a processor to execute the dynamic correction method based on the third-order cumulant of deconvolution as described in any one of claims 1-7.

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