A method, electronic device, medium and apparatus for improving signal-to-noise ratio of a seismic profile

Abstract

The application discloses a method, an electronic device, a medium and a device for improving signal-to-noise ratio of a seismic profile, and the method comprises the following steps: inputting an original seismic profile, and extracting a low-frequency skeleton profile of the original seismic profile; obtaining a total model trace of radial prediction filtering according to the low-frequency skeleton profile; and obtaining a final seismic profile based on the total model trace of radial prediction filtering and the original seismic profile. For the seismic profile, since the frequency components are rich, including low-frequency components and high-frequency components, the method of the application filters out the high-frequency components which are unstable and change greatly, the model trace does not appear false frequency, the final seismic profile does not appear false frequency, and the signal-to-noise ratio is greatly improved.

Description

TECHNICAL FIELD

[0001] The present application belongs to the field of seismic signal processing, and more particularly, to a method for improving signal-to-noise ratio of seismic profile, an electronic device, a medium and an apparatus. BACKGROUND

[0002] In field seismic data acquisition, the surface conditions are often complex: rivers, mountains, grasslands, depressions, marshes, gobi, deserts, etc. The complexity of the surface results in that the seismic data collected in the exploration site contains not only effective signals but also various noises. For example, impulse, leakage inductance induction, 50Hz industrial frequency interference, sound wave, linear noise, surface wave and random noise. The noise in the seismic data will affect the analysis and processing of the seismic data, and reduce the accuracy of the obtained seismic profile. Therefore, for the collected seismic data, it is usually necessary to process the seismic data to improve the signal-to-noise ratio of the seismic data.

[0003] The techniques for improving signal-to-noise ratio include two categories of pre-stack and post-stack methods. Radial predictive filtering method is a post-stack method for improving signal-to-noise ratio of seismic profile, but there is a certain instability in obtaining model trace by this method, and false frequency often appears in the model trace, which leads to abnormality on the seismic profile processed by this method, seriously affecting the popularization and application of this method.

[0004] Therefore, it is expected to invent a method for improving signal-to-noise ratio of seismic profile, which can effectively solve the problem of false frequency in model trace when the radial predictive filtering method is used in the prior art. SUMMARY

[0005] The purpose of the present application is to provide a method for improving signal-to-noise ratio of seismic profile, which can solve the problem of false frequency in model trace when the radial predictive filtering method is used in the prior art.

[0006] In order to achieve the above purpose, the present application provides a radial predictive filtering method for seismic profile, comprising:

[0007] inputting an original seismic profile, and extracting a low-frequency skeleton profile of the original seismic profile;

[0008] obtaining a total model trace of radial predictive filtering according to the low-frequency skeleton profile;

[0009] obtaining a final seismic profile based on the total model trace of radial predictive filtering and the original seismic profile.

[0010] Optionally, the extraction of the low-frequency skeleton profile of the original seismic profile comprises:

[0011] performing spectrum analysis on the original seismic profile to determine a low-pass filter cutoff frequency;

[0012] filtering the original seismic profile with the low-pass filter cutoff frequency to obtain a low-frequency skeleton profile.

[0013] Optionally, the low-pass filter cutoff frequency ranges from 20 to 30 Hz.

[0014] Optionally, the total model trace of the radial predictive filtering according to the low-frequency skeleton profile comprises:

[0015] Step (21): dividing the original seismic profile into a plurality of seismic trace data volumes;

[0016] Step (22): performing an inclination scan on the event of the low-frequency skeleton profile in a time window of one of the seismic trace data volumes to obtain corresponding inclination information;

[0017] Step (23): flattening the seismic trace layer of the original seismic profile based on the inclination information to obtain a flattened seismic trace;

[0018] Step (24): performing a weighted summation on the flattened seismic trace to obtain a model trace of the radial predictive filtering;

[0019] Step (25): repeating the steps (22) to (24) for each time window in each seismic trace data volume of the original seismic profile to obtain a total model trace of the radial predictive filtering.

[0020] Optionally, each of the seismic trace data volumes comprises 2N+1 adjacent seismic trace data, N being a natural number.

[0021] In the step (25), each time, a half time window is moved in a time direction, or one seismic trace is moved in a seismic trace direction.

[0022] An electronic device, comprising:

[0023] a memory storing executable instructions;

[0024] a processor running the executable instructions in the memory to implement the seismic profile radial predictive filtering method.

[0025] A computer readable storage medium storing a computer program, the computer program being executed by a processor to implement the seismic profile radial predictive filtering method.

[0026] A seismic profile radial predictive filtering device, comprising:

[0027] a low-frequency skeleton profile extraction module inputting an original seismic profile and extracting a low-frequency skeleton profile of the original seismic profile;

[0028] a total model trace of radial prediction filtering module, obtaining a total model trace of radial prediction filtering according to the low-frequency skeleton profile;

[0029] a final seismic profile, obtaining a final seismic profile based on the total model trace of radial prediction filtering and the original seismic profile.

[0030] Optionally, the total model trace of radial prediction filtering module comprises:

[0031] a seismic trace data volume obtaining module, dividing the original seismic profile into a plurality of seismic trace data volumes;

[0032] an inclination information obtaining module, performing inclination scanning on the event of the low-frequency skeleton profile in a time window of one of the seismic trace data volumes to obtain corresponding inclination information;

[0033] a seismic trace flattening module, performing weighted summation on the target seismic trace after layer flattening to obtain a model trace of the radial prediction filtering;

[0034] a weighted summation module, performing weighted summation on the target seismic trace after layer flattening to obtain a model trace of the radial prediction filtering;

[0035] an iterative calculation module, repeatedly performing the steps (22) to (24) for each time window in each seismic trace data volume of the original seismic profile to obtain the total model trace of radial prediction filtering.

[0036] The present application has the following beneficial effects:

[0037] For the seismic profile, since its frequency components are relatively rich, including low-frequency components and high-frequency components, in the seismic profile radial prediction filtering method of the present application, first, the original seismic profile is input, and the low-frequency skeleton profile of the original seismic profile is extracted, the purpose of this step is to extract relatively stable low-frequency components, and filter out high-frequency components which are not very stable and change relatively sharply; second, the total model trace of radial prediction filtering is obtained according to the low-frequency skeleton profile, since the high-frequency components have been filtered out, when the inclination scanning is performed on the radial prediction filtering, the result of the inclination scanning is very stable, and the total model trace of radial prediction filtering will not appear false frequency, finally, the final seismic profile is obtained based on the total model trace of radial prediction filtering and the original seismic profile, the final seismic profile will not appear false frequency, and the signal-to-noise ratio is greatly improved.

[0038] Other features and advantages of the present application will be described in detail in the following specific embodiments. BRIEF DESCRIPTION OF DRAWINGS

[0039] The above and other objects, features and advantages of the present application will become more apparent from the following detailed description when taken in conjunction with the accompanying drawings in which like reference characters refer to like parts throughout the figures, and wherein:

[0040] Figure 1 A flow chart of a seismic profile radial predictive filtering method according to one embodiment of the present application is shown.

[0041] Figure 2 A profile plot of a raw seismic profile according to one embodiment of the present application is shown.

[0042] Figure 3 A profile plot of a model profile according to radial predictive filtering in the prior art is shown.

[0043] Figure 4 A profile plot of a total model trace of radial predictive filtering according to one embodiment of the present application is shown.

[0044] Figure 5 A profile plot of a final seismic profile according to the prior art is shown.

[0045] Figure 6 A profile plot of a final seismic profile according to one embodiment of the present application is shown.

[0046] Figure 7 A block diagram of a seismic profile radial predictive filtering device according to one embodiment of the present application is shown. DETAILED DESCRIPTION

[0047] Preferred embodiments of the present application will be described herein below in more detail. Although the following describes preferred embodiments of the present application, it is to be understood that the present application can be embodied in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this application will be thorough and complete, and fully convey the scope of the application to those skilled in the art.

[0048] A seismic profile radial predictive filtering method according to the present application comprises:

[0049] inputting a raw seismic profile, and extracting a low frequency skeleton profile of the raw seismic profile;

[0050] obtaining a total model trace of radial predictive filtering according to the low frequency skeleton profile;

[0051] obtaining a final seismic profile based on the total model trace of radial predictive filtering and the raw seismic profile.

[0052] Specifically, for the seismic profile, since its frequency components are rich, including low frequency components and high frequency components, in the radial prediction filtering method of the seismic profile, first, the original seismic profile is input, and the low frequency skeleton profile of the original seismic profile is extracted, the purpose of this step is to extract the relatively stable low frequency components, and the high frequency components which are not stable and change greatly are filtered out; secondly, the total model trace of radial prediction filtering is obtained according to the low frequency skeleton profile, since the high frequency components have been filtered out, when the radial prediction filtering is performed on the dip angle scanning, the result of the dip angle scanning is very stable, and the total model trace of the radial prediction filtering will not appear false frequency; finally, based on the total model trace of the radial prediction filtering and the original seismic profile, the final seismic profile is obtained, and the final seismic profile will not appear false frequency, and the signal-to-noise ratio is greatly improved.

[0053] In one example, extracting the low frequency skeleton profile of the original seismic profile comprises:

[0054] Performing spectrum analysis on the original seismic profile to determine a low-pass filter cutoff frequency;

[0055] Applying the low-pass filter cutoff frequency to filter the original seismic profile to extract the low frequency skeleton profile.

[0056] In one example, the low-pass filter cutoff frequency ranges from 20 to 30 Hz.

[0057] In one example, obtaining the total model trace of radial prediction filtering according to the low frequency skeleton profile comprises:

[0058] Step (21): dividing the original seismic profile into a plurality of seismic trace data bodies;

[0059] Step (22): performing dip angle scanning on the event of the low frequency skeleton profile in a time window of a seismic trace data body to obtain corresponding dip angle information;

[0060] Step (23): based on the dip angle information, flattening the seismic trace layer of the original seismic profile to obtain a layer-flattened seismic trace;

[0061] Step (24): performing weighted summation on the layer-flattened seismic trace to obtain a model trace of radial prediction filtering;

[0062] Step (25): for each time window in each seismic trace data body of the original seismic profile, steps (22) to (24) are repeatedly executed to obtain the total model trace of radial prediction filtering.

[0063] Specifically, in the radial prediction filtering, when processing one seismic trace, N seismic traces are selected on the left and right sides of the target seismic trace along the seismic trace direction (lateral direction) to form a 2N+1 seismic trace data volume, and the processing is performed in time windows in the time direction (vertical direction), wherein the time window length is generally 200-500 ms, and the time windows generally overlap by 50%.

[0064] Further, the dip angle information of the low-frequency skeleton profile is obtained by performing dip angle scanning on the events of the low-frequency skeleton profile, that is, the dip angles corresponding to the N seismic traces on the left and right sides are determined by performing dip angle scanning on the 2N+1 seismic trace data volume in the lateral direction; based on the dip angle information, the seismic trace layer of the original seismic profile is flattened to obtain a flattened seismic trace, that is, the seismic trace layer is flattened according to the dip angle of each seismic trace to obtain a flattened seismic trace; the flattened seismic trace is weighted and summed to obtain a model trace of the radial prediction filtering, wherein the larger the weight coefficient, the closer to the target seismic trace, and the smaller the weight coefficient, the farther from the target seismic trace; after processing one time window, the time window is slid down by half, and the above steps are repeated until the processing in the time direction is completed; after processing the target seismic trace, the seismic trace is slid by one trace in the lateral direction, and the above steps are repeated until all seismic traces are processed, and the total model trace of the radial prediction filtering is output.

[0065] In one example, each seismic trace data volume includes 2N+1 adjacent seismic trace data, and N is a natural number.

[0066] In step (25), the time window is moved by half each time in the time direction, or the seismic trace is moved by one trace in the seismic trace direction.

[0067] In one example, the radial prediction filtering adopts a single-trace processing method.

[0068] Specifically, the radial prediction filtering adopts a multi-trace scanning and single-trace processing method.

[0069] An electronic device, the electronic device comprising:

[0070] a memory storing executable instructions;

[0071] a processor running the executable instructions in the memory to implement the seismic profile radial prediction filtering method.

[0072] A computer readable storage medium storing a computer program, the computer program being executed by a processor to implement the seismic profile radial prediction filtering method.

[0073] A seismic profile radial prediction filtering device, comprising:

[0074] a low-frequency skeleton profile extraction module configured to input an original seismic profile and extract a low-frequency skeleton profile of the original seismic profile;

[0075] a total model trace acquisition module configured to obtain a total model trace of radial prediction filtering based on the low-frequency skeleton profile;

[0076] a final seismic profile acquisition module configured to obtain a final seismic profile based on the total model trace of radial prediction filtering and the original seismic profile.

[0077] In one example, the total model trace acquisition module includes:

[0078] a seismic trace data volume acquisition module configured to divide the original seismic profile into a plurality of seismic trace data volumes;

[0079] an inclination information acquisition module configured to perform inclination scanning on a reflection event of the low-frequency skeleton profile in a time window of a seismic trace data volume to obtain corresponding inclination information;

[0080] a seismic trace flattening module configured to perform weighted summation on the target seismic trace after layer flattening to obtain a model trace of radial prediction filtering;

[0081] a weighted summation module configured to perform weighted summation on the target seismic trace after layer flattening to obtain a model trace of radial prediction filtering;

[0082] an iterative calculation module configured to repeatedly execute steps (22) to (24) for each time window in each seismic trace data volume of the original seismic profile to obtain the total model trace of radial prediction filtering.

[0083] Embodiment One

[0084] Figure 1 A flowchart of a seismic profile radial prediction filtering method according to one embodiment of the present application is shown.

[0085] As shown in Figure 1 the seismic profile radial prediction filtering method includes:

[0086] Step 1: input an original seismic profile and extract a low-frequency skeleton profile of the original seismic profile.

[0087] The extraction of the low-frequency skeleton profile of the original seismic profile includes:

[0088] performing spectral analysis on the original seismic profile to determine a low-pass filter cutoff frequency;

[0089] applying the low-pass filter cutoff frequency to filter the original seismic profile to extract the low-frequency skeleton profile.

[0090] The low-pass filter cutoff frequency ranges from 20 to 30 Hz.

[0091] Step 2: Obtain the total model trace of radial prediction filtering based on the low-frequency skeleton profile.

[0092] The total model channel for radial prediction filtering, obtained from the low-frequency skeleton profile, includes:

[0093] Step (21): Divide the original seismic profile into multiple seismic trace data volumes;

[0094] Step (22): Within a time window of a seismic trace data volume, perform a dip angle scan on the in-phase axis of the low-frequency skeleton profile to obtain the corresponding dip angle information;

[0095] Step (23): Based on the dip angle information, flatten the seismic trace layers of the original seismic profile to obtain the flattened seismic trace layers;

[0096] Step (24): Weight the seismic traces after the layers are flattened to obtain a model trace for radial prediction filtering;

[0097] Step (25): For each time window in each seismic trace data volume of the original seismic profile, repeat steps (22) to (24) to obtain the total model trace of the radial prediction filter.

[0098] Each seismic trace data volume includes 2N+1 adjacent seismic trace data, where N is a natural number;

[0099] In step (25), each time the time window is moved by half a time window along the time direction, or the seismic trace is moved by one seismic trace along the seismic trace direction.

[0100] Step 3: Based on the total model trace and the original seismic profile using radial prediction filtering, obtain the final seismic profile.

[0101] The final seismic profile is obtained by weighted summation of the original seismic profile and the total model trace of the radial prediction filter.

[0102] Specifically, Figure 2 The original seismic profile, such as Figure 2 As shown, the signal-to-noise ratio of the original seismic profile is low, and the continuity of the phase axis is slightly poor. Figure 3 This is a model profile of radial predictive filtering in the prior art, such as... Figure 3 As shown, the signal-to-noise ratio of the model profile of radial prediction filtering in the prior art is very high, and the wave group characteristics of most areas are similar to the original profile. However, false frequencies appear in the areas marked by the boxes, and the phase axis suddenly breaks, which does not match the original seismic profile. Figure 4 This is the total model trace of radial prediction filtering in this invention, compared. Figure 3 and Figure 4It can be seen that the model profiles of the two methods are consistent as a whole, and the model profile of the application has no false frequency at the position marked by the box, and the wave group characteristics are consistent with the original seismic profile as a whole. Figure 5 The final seismic profile in the prior art is compared with Figure 2 and Figure 5 It can be seen that the signal-to-noise ratio of the final seismic profile is greatly improved, but due to the false frequency of the model profile, the final seismic profile also has false frequency at the position marked by the box, and the event is obviously broken; Figure 6 The final seismic profile in the application is compared with Figure 5 Compared with the final seismic profile in the prior art, they are completely consistent except for the position marked by the box, and the final seismic profile in the application has no event break phenomenon at the position marked by the box, and the false frequency problem is well solved.

[0103] Example 2

[0104] Figure 7 The structure block diagram of a seismic profile radial prediction filtering device according to an embodiment of the application is shown.

[0105] As shown in Figure 7 , the seismic profile radial prediction filtering device comprises:

[0106] A low-frequency skeleton profile extraction module inputs the original seismic profile and extracts the low-frequency skeleton profile of the original seismic profile.

[0107] The low-frequency skeleton profile of the original seismic profile is extracted by:

[0108] Performing frequency spectrum analysis on the original seismic profile to determine the low-pass filter cutoff frequency.

[0109] Applying the low-pass filter cutoff frequency to filter the original seismic profile to extract the low-frequency skeleton profile.

[0110] The range of the low-pass filter cutoff frequency is 20-30 Hz.

[0111] A total model trace acquisition module of radial prediction filtering obtains the total model trace of radial prediction filtering according to the low-frequency skeleton profile.

[0112] The total model trace acquisition module of radial prediction filtering comprises:

[0113] A seismic trace data body acquisition module divides the original seismic profile into a plurality of seismic trace data bodies.

[0114] An inclination information acquisition module performs inclination scanning on the event of the low-frequency skeleton profile in a time window of a seismic trace data body to obtain corresponding inclination information.

[0115] The seismic trace flattening module performs weighting summation on the target seismic trace after layer flattening to obtain a model trace of radial predictive filtering.

[0116] The weighting summation module performs weighting summation on the target seismic trace after layer flattening to obtain a model trace of radial predictive filtering.

[0117] The iteration calculation module repeatedly performs steps (22) to (24) for each time window in each seismic trace data volume of the original seismic profile to obtain a total model trace of radial predictive filtering.

[0118] The final seismic profile is obtained by performing weighting summation on the original seismic profile and the total model trace of radial predictive filtering.

[0119] Embodiment three

[0120] The electronic device provided by the present disclosure includes a memory storing executable instructions and a processor running the executable instructions in the memory to implement the seismic profile radial predictive filtering method.

[0121] The electronic device according to the embodiment of the present disclosure includes a memory and a processor.

[0122] The memory is configured to store non-transitory computer-readable instructions. Specifically, the memory can include one or more computer program products, which can include various forms of computer-readable storage media, such as volatile memory and / or non-volatile memory. The volatile memory may, for example, include random access memory (RAM), cache memory, and / or the like. The non-volatile memory may, for example, include read-only memory (ROM), hard disk, flash memory, and / or the like.

[0123] The processor can be a central processing unit (CPU) or other forms of processing units having data processing and / or instruction execution capabilities, and can control other components in the electronic device to perform desired functions. In an embodiment of the present disclosure, the processor is configured to run the computer-readable instructions stored in the memory.

[0124] Those skilled in the art should understand that, in order to solve the technical problem of how to obtain a good user experience effect, the present embodiment can also include well-known structures such as a communication bus, an interface, and the like, which should also be included in the protection scope of the present disclosure.

[0125] Detailed descriptions of the present embodiment can refer to the corresponding descriptions in the foregoing embodiments, which will not be repeated here.

[0126] Embodiment four

[0127] The present disclosure provides a computer readable storage medium, which stores a computer program, and the computer program is executed by a processor to implement the seismic profile radial prediction filtering method.

[0128] The computer readable storage medium according to the embodiments of the present disclosure stores non-transitory computer readable instructions. When the non-transitory computer readable instructions are run by a processor, all or part of the steps of the method of the embodiments of the present disclosure are performed.

[0129] The computer readable storage medium includes, but is not limited to, optical storage media (for example, CD-ROM and DVD), magneto-optical storage media (for example, MO), magnetic storage media (for example, magnetic tape or mobile hard disk), media with built-in rewritable non-volatile memory (for example, memory card), and media with built-in ROM (for example, ROM cartridge).

[0130] The above has described the embodiments of the present disclosure, and the above description is exemplary, not exhaustive, and is not limited to the disclosed embodiments. Many modifications and changes are obvious to those skilled in the art without departing from the scope and spirit of the described embodiments.

Claims

1. A radial prediction filtering method for seismic profiles, characterized in that, include: Input the original seismic profile and extract the low-frequency skeleton profile of the original seismic profile; The total model trace of radial predictive filtering is obtained based on the low-frequency skeleton profile. Based on the total model trace of the radial prediction filter and the original seismic profile, the final seismic profile is obtained; The step of obtaining the total model channel for radial prediction filtering based on the low-frequency skeleton profile includes: Step 21: Divide the original seismic profile into multiple seismic trace data volumes; Step 22: Within a time window of one of the seismic trace data volumes, perform a dip angle scan on the in-phase axis of the low-frequency skeleton profile to obtain the corresponding dip angle information; Step 23: Based on the dip angle information, flatten the seismic trace layers of the original seismic profile to obtain the flattened seismic traces; Step 24: Perform a weighted summation of the flattened seismic traces to obtain a model trace for the radial prediction filter; Step 25: For each time window in each seismic trace data volume of the original seismic profile, repeat steps 22 to 24 to obtain the total model trace of the radial prediction filter.

2. The seismic profile radial prediction filtering method according to claim 1, characterized in that, The extraction of the low-frequency skeleton profile from the original seismic profile includes: Spectral analysis was performed on the original seismic profile to determine the low-pass filter cutoff frequency; The original seismic profile is filtered using the low-pass filter cutoff frequency to extract the low-frequency skeleton profile.

3. The seismic profile radial prediction filtering method according to claim 2, characterized in that, The low-pass filter cutoff frequency range is 20~30Hz.

4. The seismic profile radial prediction filtering method according to claim 1, characterized in that, Each of the aforementioned seismic trace data volumes includes 2N+1 adjacent seismic trace data, where N is a natural number; In step 25, each time the time is moved by half a time window along the time direction, or by one seismic trace along the seismic trace direction.

5. The seismic profile radial prediction filtering method according to claim 1, characterized in that, The final seismic profile is obtained by weighted summation of the original seismic profile and the total model trace of the radial prediction filter.

6. An electronic device, characterized in that, The electronic device includes: Memory, which stores executable instructions; A processor that executes the executable instructions in the memory to implement the seismic profile radial prediction filtering method according to any one of claims 1-5.

7. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores a computer program that, when executed by a processor, implements the seismic profile radial prediction filtering method according to any one of claims 1-5.

8. A radial prediction filtering device for seismic profiles, characterized in that, include: The low-frequency skeleton profile extraction module takes the original seismic profile as input and extracts the low-frequency skeleton profile of the original seismic profile. The total model trace acquisition module of radial prediction filtering obtains the total model trace of radial prediction filtering based on the low-frequency skeleton profile. The final seismic profile is obtained based on the total model trace of the radial prediction filter and the original seismic profile. The total model trace acquisition module for radial prediction filtering includes: The seismic trace data volume acquisition module divides the original seismic profile into multiple seismic trace data volumes; The dip information acquisition module performs dip angle scanning on the phase axis of the low-frequency skeleton profile within a time window of a seismic trace data volume to obtain the corresponding dip angle information. The seismic trace flattening module, based on the dip angle information, flattens the seismic trace layers of the original seismic profile to obtain the flattened seismic traces. The weighted summation module performs a weighted summation on the target seismic traces after the layers are flattened, to obtain a model trace for the radial prediction filter; The iterative calculation module repeatedly executes the steps from the dip information acquisition module to the weighted summation module for each time window in each seismic trace data volume of the original seismic profile to obtain the total model trace of the radial prediction filter.

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