CN117741764A

CN117741764A - Denoising method and device for seismic data

Info

Publication number: CN117741764A
Application number: CN202211125153.XA
Authority: CN
Inventors: 吴玉; 李博
Original assignee: Sinopec Petroleum Geophysical Exploration Technology Research Institute Co ltd; China Petroleum and Chemical Corp
Current assignee: Sinopec Petroleum Geophysical Exploration Technology Research Institute Co ltd; China Petroleum and Chemical Corp
Priority date: 2022-09-14
Filing date: 2022-09-14
Publication date: 2024-03-22

Abstract

The disclosure relates to the technical field of seismic data denoising, and provides a denoising method and device for seismic data. The method comprises the following steps: acquiring noise-containing seismic data and noise model data, wherein the frequency and amplitude between coherent noise data in the noise-containing seismic data and the noise model data are consistent; converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data of the complex number domain; calculating a target phase difference between the coherent noise data of the complex domain and the noise model data; denoising the noisy seismic data based on the target phase difference. The embodiment of the disclosure can effectively eliminate the signal difference problem caused by the phase difference, improve the attenuation effect of coherent noise, improve the signal-to-noise ratio of data, provide high-quality input data for subsequent imaging, and reduce the false image in an imaging result.

Description

Denoising method and device for seismic data

Technical Field

The disclosure relates to the technical field of seismic data denoising, in particular to a denoising method and device for seismic data.

Background

In oil and gas exploration and development, the collected prestack seismic data often need to be denoised. In the prior art, the technology for denoising the seismic data can relatively accurately evaluate a noise data model in the seismic data, but the phase difference between noise in the real seismic data and the noise data model cannot be well processed for accurately evaluating, so that the denoising effect is unstable, and the quality of the pre-stack seismic data is difficult to guarantee.

Disclosure of Invention

In view of this, embodiments of the present disclosure provide a method and an apparatus for denoising seismic data, so as to solve the problems in the prior art.

In a first aspect of an embodiment of the present disclosure, a method for denoising seismic data is provided, including:

acquiring noise-containing seismic data and noise model data, wherein the frequency and amplitude between coherent noise data in the noise-containing seismic data and the noise model data are consistent;

converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data of the complex number domain;

calculating a target phase difference between the coherent noise data of the complex domain and the noise model data;

denoising the noisy seismic data based on the target phase difference.

In some embodiments, where the phase difference between the coherent noise data and the noise model data of the complex domain is a constant that does not change over time, the target phase difference is calculated using a first calculation formula that is:

where e represents a natural constant, i represents an imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < > >Noise model data representing the complex domain,' representing the conjugate transpose.

In some embodiments, where the phase difference between the coherent noise data and the noise model data of the complex domain is time-varying, the target phase difference is calculated using a second calculation formula that is:

where e represents a natural constant, i represents an imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain, ' conjugate transpose,'t time, ' g gaussian smoothing,<> _t,g means that Gaussian smoothing is performed in the time direction, | _t Representing the change over time.

In some embodiments, the above method converts the coherent noise data and the noise model data from a real-number domain to a complex-number domain by a hilbert transform.

In a second aspect of an embodiment of the present disclosure, there is provided a denoising apparatus for seismic data, including:

the acquisition module is used for acquiring noise-containing seismic data and noise model data, wherein the frequency and the amplitude of coherent noise data in the noise-containing seismic data are consistent with those of the noise model data;

the conversion module is used for converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data in the complex number domain;

A calculation module for calculating a target phase difference between the coherent noise data of the complex domain and the noise model data;

and the denoising module is used for denoising the noisy seismic data based on the target phase difference.

where e represents a natural constant, i represents an imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain,' representing the conjugate transpose.

wherein e representsThe natural constant, i represents the imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain, ' conjugate transpose,'t time, ' g gaussian smoothing, <> _t,g Means that Gaussian smoothing is performed in the time direction, | _t Representing the change over time.

In some embodiments, the apparatus converts the coherent noise data and the noise model data from a real-number domain to a complex-number domain by a hilbert transform.

In a third aspect of the disclosed embodiments, there is provided an electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, the steps implemented by the processor when executing the computer program comprising:

denoising the noisy seismic data based on the target phase difference.

In a fourth aspect of the disclosed embodiments, there is provided a computer-readable storage medium storing a computer program which, when executed by a processor, performs steps comprising:

denoising the noisy seismic data based on the target phase difference.

where e represents a natural constant, i represents an imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing complex domain,' representing conjugateAnd (5) transposition.

Advantageous effects

Compared with the prior art, the beneficial effects of the embodiment of the disclosure at least comprise: through converting coherent noise data and noise model data in noise-containing seismic data from real number domain to complex number domain to obtain corresponding data of complex number domain, and performing correlation calculation, accurate phase difference between the coherent noise data and the noise model data can be obtained, so that the problem of signal difference caused by the phase difference can be effectively eliminated, the attenuation effect of the coherent noise is improved, the signal-to-noise ratio of data is improved, high-quality input data is provided for subsequent imaging, and artifacts in imaging results are reduced.

Drawings

In order to more clearly illustrate the technical solutions of the embodiments of the present disclosure, the drawings that are required for the embodiments or the description of the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are only the embodiments, and other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.

FIG. 1 is a schematic diagram of one scenario of a method of denoising seismic data provided in accordance with an embodiment of the present disclosure;

FIG. 2 is a flow chart of a second embodiment of a method for denoising seismic data provided in accordance with an embodiment of the present disclosure;

fig. 3a to 3d are schematic diagrams of denoising effects for different situations according to a denoising method for seismic data provided in an embodiment of the present disclosure;

FIG. 4 is a flow chart of embodiment three of another method of denoising seismic data provided in accordance with an embodiment of the present disclosure;

FIG. 5 is a simplified schematic diagram of a denoising apparatus for seismic data according to an embodiment of the present disclosure;

fig. 6 is a schematic diagram of an electronic device provided according to an embodiment of the present disclosure.

Detailed Description

Embodiments of the present disclosure will be described in more detail below with reference to the accompanying drawings. While certain embodiments of the present disclosure are shown in the drawings, it should be understood that the present disclosure may be embodied in various forms and should not be construed as limited to the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete. It should be understood that the drawings and embodiments of the present disclosure are for illustration purposes only and are not intended to limit the scope of the present disclosure.

It should be further noted that, for convenience of description, only a portion relevant to the present disclosure is shown in the drawings. Embodiments of the present disclosure and features of embodiments may be combined with each other without conflict.

It should be noted that the terms "first," "second," and the like in this disclosure are merely used to distinguish between different systems, devices, modules, or units and are not intended to limit the order or interdependence of functions performed by such systems, devices, modules, or units.

It should be noted that references to "one", "a plurality" and "a plurality" in this disclosure are intended to be illustrative rather than limiting, and those of ordinary skill in the art will appreciate that "one or more" is intended to be understood as "one or more" unless the context clearly indicates otherwise.

The names of messages or information interacted between the various devices in the embodiments of the present disclosure are for illustrative purposes only and are not intended to limit the scope of such messages or information.

The present disclosure will be described in detail below with reference to the accompanying drawings in conjunction with embodiments.

Embodiment one:

fig. 1 is a schematic diagram of an application scenario of a denoising method of seismic data according to a first embodiment of the present disclosure.

In the application scenario of fig. 1, first, a computing device 101 may acquire noisy seismic data 102 and noise model data 103, where frequencies and amplitudes between coherent noise data 104 in the noisy seismic data 102 and the noise model data are consistent.

Second, the computing device 101 may convert the coherent noise data 104 and the noise model data 103 from the real-number domain to the complex-number domain, resulting in coherent noise data 106 and noise model data 105 in the complex-number domain.

Again, the computing device 101 may calculate a target phase difference 107 between the complex-domain coherent noise data 106 and the noise model data 105.

Finally, the computing device 101 may denoise the noisy seismic data 102 based on the target phase difference 107.

The computing device 101 may be hardware or software. When the computing device is hardware, the computing device may be implemented as a distributed cluster formed by a plurality of servers or terminal devices, or may be implemented as a single server or a single terminal device. When the computing device is embodied as software, it may be installed in the hardware devices listed above. It may be implemented as a plurality of software or software modules, for example, for providing distributed services, or as a single software or software module. The present invention is not particularly limited herein.

It should be understood that the number of computing devices in fig. 1 is merely illustrative. There may be any number of computing devices, as desired for an implementation.

Embodiment two:

with continued reference to FIG. 2, a flow 200 of a second embodiment of a denoising method of seismic data according to the present disclosure is shown. The method may be performed by the computing device 101 in fig. 1. The denoising method of the seismic data comprises the following steps:

step 201, obtaining noisy seismic data and noise model data, wherein the frequency and amplitude between coherent noise data in the noisy seismic data and the noise model data are consistent.

In some alternative implementations, the executing body of the denoising method of the seismic data (such as the computing device 101 shown in fig. 1) may connect to the target device through a wired connection manner or a wireless connection manner, and then acquire noisy seismic data and noise model data, where frequencies and amplitudes between coherent noise data in the noisy seismic data and the noise model data are consistent.

Noisy seismic data may refer to seismic data mixed with coherent noise. Noise can be divided into coherent noise and random noise relative to seismic data. Coherent noise may refer to correlation with seismic data, with spatial continuity, i.e., continuity across the seismic profile. Random noise may refer to noise other than coherent noise. The present disclosure is primarily directed to coherent noise removal. The noise model may refer to model noise data that is produced to be consistent with the frequency and amplitude of coherent noise in the seismic data, where consistent may refer to the exact identity of the frequency and amplitude, or may refer to the approximate identity of the frequency and amplitude within a certain numerical range. It should be noted that the noise model is out of phase with the coherent noise, which is also the subject of the core processing of the present disclosure.

It should be noted that the wireless connection may include, but is not limited to, 3G/4G/5G connection, wiFi connection, bluetooth connection, wiMAX connection, zigbee connection, UWB (ultra wideband) connection, and other now known or later developed wireless connection.

And step 202, converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data in the complex number domain.

In some embodiments, the executing body may convert the coherent noise data and the noise model data from a real-number domain to a complex-number domain by using various existing conversion methods (such as euler formulas, etc.), so as to obtain coherent noise data and noise model data in the complex-number domain.

In some optional implementations of some embodiments, the executing entity may convert the coherent noise data and the noise model data from a real-number domain to a complex-number domain via a hilbert transform.

Step 203 calculates a target phase difference between the coherent noise data of the complex domain and the noise model data.

In some embodiments, the above-described execution body may calculate the target phase difference between the coherent noise data of the complex domain and the noise model data by:

In step 2031, when the phase difference between the coherent noise data and the noise model data in the complex domain is a constant that does not change with time, the execution body may calculate the target phase difference using a first calculation formula:

Step 2032, when the phase difference between the coherent noise data and the noise model data in the complex domain is time-varying, calculating the target phase difference using a second calculation formula, the second calculation formula being:

When the noise model is complex, the phase difference between the noise model and the real noise is not a constant, but is time-varying, and the phase difference at different times can be better calculated based on the second step processing.

And step 204, denoising the noisy seismic data based on the target phase difference.

In some embodiments, the executing entity may denoise the noisy seismic data based on the target phase difference.

First, the effect of step 2031 (i.e., the phase difference between the coherent noise data and the noise model data in the complex domain does not change with time) is shown below by way of one detailed embodiment:

referring to fig. 3a and 3b, the horizontal axis of each partial schematic diagram represents the seismic trace number, and the vertical axis represents time.

Part (1) in fig. 3a may refer to seismic data containing noisy seismic data with a phase difference that is a constant that does not change over time, and part (2) may refer to noise model data corresponding to the coherent noise in (1). Part (1) includes a first signal at the uppermost side (i.e., a signal corresponding to 100) and other signals, wherein the signal at the uppermost side is an effective signal in the seismic data, and the other signals are coherent noise data. The signal in part (2) corresponds to the other signals in part (1), but the color shades are different (i.e., indicate a phase difference).

With continued reference to fig. 3b corresponding to fig. 3a, the (1) in fig. 3b may refer to the seismic data that is denoised without coherent noise matching, and the (1) in fig. 3b may refer to the seismic data that is denoised after coherent noise matching. Obviously, after denoising without coherent noise matching, although part of the coherent noise is removed, there is still coherent noise which is not removed cleanly. On the contrary, after the coherent noise is matched, the coherent noise is completely removed.

Next, the effect of step 2032 (i.e., the phase difference between the coherent noise data and the noise model data in the complex domain varies with time) is shown by a detailed embodiment below:

referring to fig. 3c and 3d, the horizontal axis of each partial schematic diagram represents the seismic trace number, and the vertical axis represents the time.

Part (1) in fig. 3c may refer to seismic data containing noisy seismic data with a phase difference that is constant over time, and part (2) may refer to noise model data corresponding to the coherent noise in (1). Part (1) includes a first signal at the uppermost side (i.e., a signal corresponding to 100) and other signals, wherein the signal at the uppermost side is an effective signal in the seismic data, and the other signals are coherent noise data. The signal in part (2) corresponds to the other signals in part (1), but the color shades are different (i.e., indicate a phase difference).

With continued reference to fig. 3d corresponding to fig. 3c, the (1) in fig. 3d may refer to the seismic data that is denoised without coherent noise matching, and the (1) in fig. 3d may refer to the seismic data that is denoised after coherent noise matching. Obviously, after denoising without coherent noise matching, although part of the coherent noise is removed, there is still coherent noise which is not removed cleanly. On the contrary, after the coherent noise is matched, the coherent noise is completely removed.

It can be seen that the effect on coherent noise removal is very pronounced from the illustrations of fig. 3a, 3b, 3c and 3 d.

The beneficial effects of one of the implementation manners of the above embodiments of the disclosure include at least: through converting coherent noise data and noise model data in noise-containing seismic data from real number domain to complex number domain to obtain corresponding data of complex number domain, and performing correlation calculation, accurate phase difference between the coherent noise data and the noise model data can be obtained, so that the problem of signal difference caused by the phase difference can be effectively eliminated, the attenuation effect of the coherent noise is improved, the signal-to-noise ratio of data is improved, high-quality input data is provided for subsequent imaging, and artifacts in imaging results are reduced.

Embodiment III:

with continued reference to fig. 4, a flow 400 of a third embodiment of a method of denoising seismic data according to the present disclosure is shown, which may be performed by the computing device 101 of fig. 1. The denoising method of the seismic data comprises the following steps:

step 401, obtaining noisy seismic data and noise model data, wherein the frequency and amplitude between coherent noise data in the noisy seismic data and the noise model data are consistent.

In some embodiments, the executing body may acquire noisy seismic data and noise model data, where frequency and amplitude between coherent noise data in the noisy seismic data and the noise model data are consistent.

Step 402, converting the coherent noise data and the noise model data from real number domain to complex number domain by hilbert transformation, so as to obtain coherent noise data and noise model data in complex number domain.

In some embodiments, the executing entity may convert the coherent noise data and the noise model data from a real domain to a complex domain through a hilbert transform, to obtain coherent noise data and noise model data in the complex domain.

Step 403, calculating the target phase difference by using a first calculation formula when the phase difference between the coherent noise data and the noise model data in the complex domain is a constant which does not change with time.

Wherein, the first calculation formula is:

Step 404, calculating the target phase difference by using a second calculation formula when the phase difference between the coherent noise data and the noise model data in the complex domain is time-varying.

Wherein, the second calculation formula is:

where e represents a natural constant, i represents an imaginary unit,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain, ' conjugate transpose,'t time, ' g gaussian smoothing, <> _t,g Means that Gaussian smoothing is performed in the time direction, | _t Representing the change over time.

And step 405, denoising the noisy seismic data based on the target phase difference.

First, the denoising effect when the phase difference between the coherent noise data and the noise model data in the complex domain does not change with time is shown by one detailed embodiment as follows:

Next, the denoising effect when the phase difference between the coherent noise data and the noise model data in the complex domain is changed with time is shown by the following detailed embodiment:

The beneficial effects of one of the above embodiments of the present disclosure include at least: through converting coherent noise data and noise model data in noise-containing seismic data from real number domain to complex number domain to obtain corresponding data of complex number domain, and performing correlation calculation, accurate phase difference between the coherent noise data and the noise model data can be obtained, so that the problem of signal difference caused by the phase difference can be effectively eliminated, the attenuation effect of the coherent noise is improved, the signal-to-noise ratio of data is improved, high-quality input data is provided for subsequent imaging, and artifacts in imaging results are reduced.

All the above optional solutions may be combined arbitrarily to form an optional embodiment of the present application, which is not described here in detail.

Embodiment four:

the following are device embodiments of the present disclosure that may be used to perform method embodiments of the present disclosure. For details not disclosed in the embodiments of the apparatus of the present disclosure, please refer to the embodiments of the method of the present disclosure.

With further reference to fig. 5, as an implementation of the method described above for each of the above figures, the present disclosure provides an embodiment of a denoising apparatus for seismic data, which corresponds to the embodiment described above for fig. 2.

As shown in fig. 5, the denoising apparatus 500 of the seismic data of the present embodiment includes:

the obtaining module 501 is configured to obtain noisy seismic data and noise model data, where frequency and amplitude between coherent noise data in the noisy seismic data and the noise model data are consistent.

The conversion module 502 is configured to convert the coherent noise data and the noise model data from a real number domain to a complex number domain, so as to obtain coherent noise data and noise model data in the complex number domain.

A calculation module 503, configured to calculate a target phase difference between the coherent noise data in the complex domain and the noise model data.

And a denoising module 504, configured to denoise the noisy seismic data based on the target phase difference.

In some optional implementations of some embodiments, where the phase difference between the coherent noise data and the noise model data of the complex domain is a constant that does not change over time, the target phase difference is calculated using a first calculation formula that is:

In some optional implementations of some embodiments, in the case where the phase difference between the coherent noise data and the noise model data of the complex domain is time-varying, the target phase difference is calculated using a second calculation formula:

In some optional implementations of some embodiments, the apparatus converts the coherent noise data and the noise model data from a real-number domain to a complex-number domain by a hilbert transform.

It will be appreciated that the modules described in the apparatus 500 correspond to the various steps in the method described with reference to fig. 2. Thus, the operations, features and resulting benefits described above with respect to the method are equally applicable to the apparatus 500 and the modules contained therein, and are not described in detail herein.

Fifth embodiment:

as shown in fig. 6, the electronic device 600 may include a processing means (e.g., a central processing unit, a graphics processor, etc.) 601, which may perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM) 602 or a program loaded from a storage means 608 into a Random Access Memory (RAM) 603. In the RAM 603, various programs and data required for the operation of the electronic apparatus 600 are also stored. The processing device 601, the ROM 602, and the RAM 603 are connected to each other through a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

In general, the following devices may be connected to the I/O interface 605: input devices 606 including, for example, a touch screen, touchpad, keyboard, mouse, camera, microphone, accelerometer, gyroscope, and the like; an output device 607 including, for example, a Liquid Crystal Display (LCD), a speaker, a vibrator, and the like; storage 608 including, for example, magnetic tape, hard disk, etc.; and a communication device 609. The communication means 609 may allow the electronic device 600 to communicate with other devices wirelessly or by wire to exchange data. While fig. 6 shows an electronic device 600 having various means, it is to be understood that not all of the illustrated means are required to be implemented or provided. More or fewer devices may be implemented or provided instead. Each block shown in fig. 6 may represent one device or a plurality of devices as needed.

In particular, according to the present embodiment, the process described above with reference to the flowcharts may be implemented as a computer software program. For example, the present embodiment includes a computer program product comprising a computer program embodied on a computer readable medium, the computer program containing program code for performing the method shown in the flowchart. In the present embodiment, the computer program can be downloaded and installed from a network through the communication means 609, or installed from the storage means 608, or installed from the ROM 602. When the computer program is executed by the processing means 601, the following steps may be performed:

and acquiring noise-containing seismic data and noise model data, wherein the frequency and amplitude between coherent noise data in the noise-containing seismic data and the noise model data are consistent.

In some optional implementations, the executing entity may acquire noisy seismic data and noise model data, where frequency and amplitude between coherent noise data in the noisy seismic data and the noise model data are consistent.

And converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data in the complex number domain.

A target phase difference between the complex-domain coherent noise data and the noise model data is calculated.

in the case where the phase difference between the coherent noise data and the noise model data in the complex domain is a constant that does not change with time, the execution body may calculate the target phase difference using a first calculation formula that is:

When the phase difference between the coherent noise data and the noise model data in the complex domain is time-varying, calculating the target phase difference using a second calculation formula:

wherein e represents a natural constant, iRepresenting the units of an imaginary number,indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain, ' conjugate transpose,'t time, ' g gaussian smoothing,<>t, g represents Gaussian smoothing in the time direction _t Representing the change over time.

Denoising the noisy seismic data based on the target phase difference.

It should be noted that, in this embodiment, the computer readable medium may be a computer readable signal medium or a computer readable storage medium, or any combination of the two. The computer readable storage medium can be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In this embodiment, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In the present embodiment, however, the computer-readable signal medium may include a data signal propagated in baseband or as part of a carrier wave, with the computer-readable program code embodied therein. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination of the foregoing. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: electrical wires, fiber optic cables, RF (radio frequency), and the like, or any suitable combination of the foregoing.

In some implementations, the clients, servers may communicate using any currently known or future developed network protocol, such as HTTP (HyperText Transfer Protocol ), and may be interconnected with any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include a local area network ("LAN"), a wide area network ("WAN"), the internet (e.g., the internet), and peer-to-peer networks (e.g., ad hoc peer-to-peer networks), as well as any currently known or future developed networks.

The computer readable medium may be embodied in the apparatus; or may exist alone without being incorporated into the electronic device. The computer readable medium carries one or more programs which, when executed by the electronic device, cause the electronic device to perform the steps of:

Denoising the noisy seismic data based on the target phase difference.

The computer program code for carrying out operations of the present embodiments may be written in one or more programming languages, including an object oriented programming language such as Java, smalltalk, C ++ and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computer (for example, through the Internet using an Internet service provider).

The flowcharts and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.

The modules described in the present embodiment may be implemented by software or hardware. The described modules may also be provided in a processor, for example, as:

The acquisition module is used for acquiring the noisy seismic data and the noise model data, wherein the frequency and the amplitude of the coherent noise data in the noisy seismic data are consistent with those of the noise model data.

And the conversion module is used for converting the coherent noise data and the noise model data from a real number domain to a complex number domain to obtain coherent noise data and noise model data in the complex number domain.

And the calculation module is used for calculating a target phase difference between the coherent noise data of the complex domain and the noise model data.

The functions described above herein may be performed, at least in part, by one or more hardware logic components. For example, without limitation, exemplary types of hardware logic components that may be used include: a Field Programmable Gate Array (FPGA), an Application Specific Integrated Circuit (ASIC), an Application Specific Standard Product (ASSP), a system on a chip (SOC), a Complex Programmable Logic Device (CPLD), and the like.

The foregoing description is only of the preferred embodiments of the present disclosure and description of the principles of the technology being employed. It will be appreciated by those skilled in the art that the scope of the invention in the embodiments of the present disclosure is not limited to the specific combination of the above technical features, but encompasses other technical features formed by any combination of the above technical features or their equivalents without departing from the spirit of the invention. Such as the above-described features, are mutually substituted with (but not limited to) the features having similar functions disclosed in the embodiments of the present disclosure.

Claims

1. A method of denoising seismic data, comprising:

denoising the noisy seismic data based on the target phase difference.

2. The method according to claim 1, wherein in the case where a phase difference between coherent noise data and noise model data of the complex domain is a constant that does not change with time, the target phase difference is calculated using a first calculation formula that is:

3. The method according to claim 1, wherein in the case where a phase difference between the coherent noise data and the noise model data of the complex domain is time-varying, the target phase difference is calculated using a second calculation formula:

where e represents a natural constant, i represents an imaginary unit, Indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain, ' conjugate transpose,'t time, ' g gaussian smoothing,<> _t,g means that Gaussian smoothing is performed in the time direction, | _t Representing the change over time.

4. The method of claim 1, wherein the coherent noise data and the noise model data are converted from a real domain to a complex domain by a hilbert transform.

5. A denoising apparatus for seismic data, comprising:

6. The apparatus of claim 5, wherein in the case where a phase difference between coherent noise data and noise model data of the complex domain is a constant that does not change with time, the target phase difference is calculated using a first calculation formula that:

wherein e represents a natural constant, i represents an imaginary unit，Indicating the target phase difference>Coherent noise data representing the complex domain, < >>Noise model data representing the complex domain,' representing the conjugate transpose.

7. The apparatus of claim 5, wherein in the case where a phase difference between the coherent noise data and the noise model data in the complex domain is time-varying, the target phase difference is calculated using a second calculation formula:

8. The apparatus of claim 5, wherein the coherent noise data and the noise model data are converted from a real domain to a complex domain by a hilbert transform.

9. An electronic device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor implements the steps of the method according to any of claims 1 to 4 when the computer program is executed.

10. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the method according to any one of claims 1 to 4.