A method and device for denoising DAS seismic data in a well

Abstract

The present application provides a method and device for denoising wellbore DAS seismic data, belonging to the technical field of geophysical exploration. In the embodiments of the present application, the improved median filter is used to separate the first effective data and noise data from the original seismic data; for the noise data, time-frequency domain analysis is carried out through the S transform, and the S transform result function is filtered through the time-frequency domain filter constructed according to the first effective data and noise data, and the second effective data is further extracted from the noise data; finally, the sum of the first effective data and the second effective data is output, so as to obtain the seismic data after suppressing noise. On the basis of the improved median filter, the embodiments of the present application further extract effective data from the noise data through the S transform, effectively suppressing the noise of the wellbore DAS seismic data while maximizing the retention of effective signals, providing effective technical support for improving the imaging accuracy and interpretation reliability of the wellbore DAS seismic data.

Description

Technical Field

[0001] The present application relates to the field of geophysical exploration technologies, and particularly to a method and device for denoising borehole DAS seismic data. Background Art

[0002] Distributed Acoustic Sensing (DAS) is an emerging technology that uses the optical fiber itself as a sensor for signal acquisition. In recent years, it has been gradually applied to multiple data acquisition and transmission industries. Its working principle is based on the scattering effect, integrating sensing and transmission, and enabling long-distance measurement and monitoring. Distributed optical fibers have the advantages of high sensitivity, anti-electromagnetic interference, good insulation, corrosion resistance, and being convenient for networking and long-distance transmission, and are very suitable for applications in some fields where traditional sensors are restricted.

[0003] However, since there is no pushing device during downhole acquisition of the current distributed optical fiber, some optical fibers cannot be attached to the wellbore wall, so there is fiber coupling noise in the recorded data. This noise is extremely severe in the optical fiber acquisition data, and it is difficult to suppress the noise, posing a huge challenge to the subsequent data processing and interpretation, and directly affecting the accuracy and precision of the final results.

[0004] Currently, traditional methods mainly analyze the regular characteristics of different frequency bands of the noise, then separately statistically analyze and invert the fiber coupling noise in each depth segment, and specifically adopt frequency-variable adaptive noise attenuation and inversion techniques to remove it, but the existing methods do not completely suppress the noise. Summary of the Invention

[0005] The present application provides a method and device for denoising borehole DAS seismic data to solve the problem of incomplete suppression of fiber coupling noise in borehole DAS seismic data.

[0006] To solve the above problems, the present application adopts the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a method for denoising borehole DAS seismic data, the method comprising:

[0008] extracting first effective data from the original seismic data through improved median filtering; wherein, the original seismic data includes noise data;

[0009] obtaining noise data according to the difference between the original seismic data and the first effective data;

[0010] performing an S transform on the noise data to obtain an S transform result function;

[0011] obtaining a time-frequency domain filter according to the first effective data and the noise data;

[0012] Filter the S-transform result function through the time-frequency domain filter to obtain second effective data;

[0013] Obtain the seismic data after suppressing noise according to the sum of the first effective data and the second effective data.

[0014] In an embodiment of the present application, extracting first effective data from the original seismic data through improved median filtering includes:

[0015] According to the original seismic data, obtain a data sequence Xi (i = 1, 2, 3,..., m) including m noisy seismic traces, and output the filtered output value of each point in the data sequence Xi through the following steps to obtain the first effective data:

[0016] In the data sequence Xi, take n sample values centered on the j-th point as input; where n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noisy seismic traces containing noise in n.

[0017] Arrange the n sample values in ascending order;

[0018] Take the sample value at the (n - m)-th data position after ascending order arrangement as the filtered output value of the j-th point.

[0019] In an embodiment of the present application, taking n sample values centered on the j-th point as input includes:

[0020] In the case where the n sample values centered on the j-th point reach the left and right boundaries of the original seismic data and n sample values cannot be fully obtained, take n sample values towards the middle of the original seismic data.

[0021] In an embodiment of the present application, performing an S-transform on the noise data to obtain an S-transform result function includes:

[0022] Perform an S-transform on the noise data through the following S-transform formula to obtain an S-transform result function S1(τ, f):

[0023]

[0024] In the formula: S1(τ, f) is the S-transform result function of the noisy seismic trace; h1(t) is the time-domain seismic signal function corresponding to the noisy seismic trace; t represents the seismic wave propagation time before the S-transform; τ represents the seismic wave propagation time after the S-transform; f represents the frequency; j is the imaginary unit.

[0025] In an embodiment of the present application, obtaining a time-frequency domain filter according to the first effective data and the noise data includes:

[0026] Perform an S - transform on the seismic trace data adjacent to the noise data in the first effective data through the S - transform formula, obtaining an S - transform result function S2(τ, f).

[0027] Construct an initial time - frequency domain filtering function according to the time - frequency distribution characteristics of the time - frequency amplitude diagrams of S1(τ, f) and S2(τ, f), and set the value of the initial time - frequency domain filtering function to 0 in places with strong noise and to 1 in places with weak noise.

[0028] Smooth the initial time - frequency domain filtering function through two - dimensional sliding window averaging to obtain a final time - frequency domain filtering function F(τ, f).

[0029] In an embodiment of the present application, filtering the S - transform result function through the time - frequency domain filter to obtain second effective data includes:

[0030] Obtain a filtered S - transform result function S3(τ, f) according to the product of S1(τ, f) and F(τ, f);

[0031] Perform an inverse S - transform on S3(τ, f) to obtain second effective data.

[0032] In an embodiment of the present application, performing an inverse S - transform on S3(τ, f) to obtain second effective data includes:

[0033] Perform an inverse S - transform on S3(τ, f) through the following inverse S - transform formula to obtain second effective data:

[0034]

[0035] Where: S3(τ, f) is the product of S1(τ, f) and F(τ, f); h2(t) is the time - domain seismic signal function obtained by the inverse S - transform; τ represents the seismic wave propagation time before the inverse S - transform; t represents the seismic wave propagation time after the inverse S - transform; f represents the frequency; j is the imaginary unit.

[0036] In a second aspect, based on the same inventive concept, an embodiment of the present application provides a downhole DAS seismic data denoising device, and the device includes:

[0037] An extraction module, configured to extract first effective data from the original seismic data through improved median filtering; wherein, the original seismic data includes noise data;

[0038] A first acquisition module, configured to obtain noise data according to the difference between the original seismic data and the first effective data;

[0039] A second acquisition module, configured to perform an S transform on the noise data to obtain an S transform result function;

[0040] A third acquisition module, configured to obtain a time-frequency domain filter according to the first effective data and the noise data;

[0041] A fourth acquisition module, configured to filter the S transform result function through the time-frequency domain filter to obtain second effective data;

[0042] A fifth acquisition module, configured to obtain seismic data after suppressing noise according to the sum of the first effective data and the second effective data.

[0043] In an embodiment of the present application, the extraction module includes:

[0044] A filtering sub-module, configured to obtain a data sequence Xi (i = 1, 2, 3,..., m) including m noise seismic traces according to the original seismic data, and output a filtered output value of each point in the data sequence Xi through the following sub-modules to obtain the first effective data:

[0045] An input sub-module, configured to take n sample values centered on the j-th point in the data sequence Xi as inputs; where n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noise seismic traces containing noise in n;

[0046] An arrangement sub-module, configured to perform an ascending order arrangement on the n sample values;

[0047] An output sub-module, configured to take the sample value at the (n - m)-th data position after the ascending order arrangement as the filtered output value of the j-th point.

[0048] In an embodiment of the present application, the output sub-module includes:

[0049] A sample complementing sub-module, configured to, when the n sample values centered on the j-th point reach the left and right boundaries of the original seismic data and n sample values cannot be fully obtained, take enough n sample values from the middle of the original seismic data.

[0050] In an embodiment of the present application, the second acquisition module includes:

[0051] A first S transform sub-module, configured to perform an S transform on the noise data through the following S transform formula to obtain an S transform result function S1(τ, f):

[0052]

[0053] Where: S1(τ,f) is the S-transform result function of the noise seismic trace; h1(t) is the time-domain seismic signal function corresponding to the noise seismic trace; t represents the seismic wave propagation time before the S-transform; τ represents the seismic wave propagation time after the S-transform; f represents the frequency; j is the imaginary unit.

[0054] In one embodiment of the present application, the third acquisition module includes:

[0055] A second S-transform sub-module, configured to perform an S-transform on the seismic trace data adjacent to the noise data in the first effective data through the S-transform formula to obtain an S-transform result function S2(τ,f);

[0056] A first filtering sub-module, configured to construct an initial time-frequency domain filtering function according to the time-frequency distribution characteristics of the time-frequency amplitude diagrams of the S1(τ,f) and the S2(τ,f), and set the value of the initial time-frequency domain filtering function to 0 where the noise is strong, and set the value of the initial time-frequency domain filtering function to 1 where the noise is weak;

[0057] A second filtering sub-module, configured to smooth the initial time-frequency domain filtering function through two-dimensional sliding window averaging to obtain a final time-frequency domain filtering function F(τ,f).

[0058] In one embodiment of the present application, the fourth acquisition module includes:

[0059] A first acquisition sub-module, configured to obtain a filtered S-transform result function S3(τ,f) according to the product of the S1(τ,f) and the F(τ,f);

[0060] A second acquisition sub-module, configured to perform an inverse S-transform on the S3(τ,f) to obtain second effective data.

[0061] In one embodiment of the present application, the second acquisition sub-module includes:

[0062] An inverse S-transform sub-module, configured to perform an inverse S-transform on the S3(τ,f) through the following inverse S-transform formula to obtain second effective data:

[0063]

[0064] Where: S3(τ,f) is the product of S1(τ,f) and F(τ,f); h2(t) is the time-domain seismic signal function obtained by the inverse S-transform; τ represents the seismic wave propagation time before the inverse S-transform; t represents the seismic wave propagation time after the inverse S-transform; f represents the frequency; j is the imaginary unit.

[0065] In a third aspect, based on the same inventive concept, an embodiment of the present application provides an electronic device, and the electronic device includes:

[0066] A processor;

[0067] A memory for storing instructions executable by the processor;

[0068] Wherein, the processor is configured to execute the in-well DAS seismic data denoising method proposed in the first aspect of the present application.

[0069] In a fourth aspect, based on the same inventive concept, an embodiment of the present application provides a computer-readable storage medium. When the instructions in the storage medium are executed by a processor of an electronic device, the electronic device can execute the in-well DAS seismic data denoising method proposed in the first aspect of the present application.

[0070] Compared with the prior art, the present application has the following advantages:

[0071] An in-well DAS seismic data denoising method provided by an embodiment of the present application first preliminarily extracts first effective data from the original seismic data through improved median filtering, and obtains the remaining noise data; then performs time-frequency domain analysis on the noise data through S transform, and combines the time-frequency domain characteristics of the first effective data and the noise data to construct a suitable time-frequency domain filter; further filters the S transform result function through the time-frequency domain filter to further extract second effective data from the noise data; finally outputs the sum of the first effective data and the second effective data, thereby obtaining the seismic data after suppressing the noise. Based on the improved median filtering, the embodiment of the present application further extracts effective data from the noise data through S transform, realizes effective suppression of the noise of the in-well DAS seismic data, can significantly improve the signal-to-noise ratio of the in-well DAS seismic data, and retains the effective signal to the greatest extent, providing effective technical support for improving the accuracy of in-well DAS seismic data imaging and the reliability of interpretation. Description of the Drawings

[0072] In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for use in the description of the embodiments or the prior art. Obviously, the following drawings are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0073] Figure 1 It is a flowchart of the steps of the in-well DAS seismic data denoising method in an embodiment of the present application;

[0074] Figure 2 It is a schematic diagram of the functional modules of the in-well DAS seismic data denoising device in an embodiment of the present application.

[0075] Reference numerals: 200 - Downhole DAS seismic data denoising device; 201 - Extraction module; 202 - First acquisition module; 203 - Second acquisition module; 204 - Third acquisition module; 205 - Fourth acquisition module; 206 - Fifth acquisition module. Detailed implementation mode

[0076] Next, the technical solutions in the embodiments of the present invention will be clearly and completely described in conjunction with the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative work shall fall within the protection scope of the present invention.

[0077] It should be noted in this embodiment that in the seismic exploration industry, based on the DAS (Distributed Acoustic Sensing) technology, the efficiency of downhole seismic data acquisition is very high. However, in the obtained DAS data, in addition to the conventional downhole seismic data noise, there is also a kind of noise in the form of periodic oscillation - fiber coupling noise. Since the frequency distribution range of the fiber coupling noise is wide, it has multi - frequency attributes, overlaps with the effective signal frequency band more, and has characteristics such as strong interference energy and strong regularity, making the suppression of this type of noise by the existing technology often incomplete, and may also damage the effective signal when suppressing the noise.

[0078] Aiming at the defects existing in the prior art, the embodiment of the present application provides a downhole DAS seismic data denoising method based on improved median filtering and S - transform. First, the effective data is extracted from the original seismic data to the greatest extent through improved median filtering; for the remaining noise data, time - frequency domain analysis is performed through S - transform, and a time - frequency domain filter is designed to further suppress the noise data, so as to extract more effective data from the noise data, and finally output all the effective data. The embodiment of the present application can effectively suppress the noise while extracting as many effective signals as possible, thereby improving the quality of DAS seismic data for subsequent processing and interpretation of DAS downhole seismic data, and promoting the wide application of DAS - VSP technology.

[0079] Referring to Figure 1 , a downhole DAS seismic data denoising method of the present application is shown, and the method may include the following steps:

[0080] Step S101: Extract the first effective data from the original seismic data through improved median filtering; wherein, the original seismic data includes noise data.

[0081] It should be noted that in this embodiment, the downhole seismic data collected by the Distributed Acoustic Sensing (DAS) technology usually contains various noise data, among which the fiber optic coupling noise is particularly serious. Therefore, in this embodiment, the first effective data can be extracted from the original seismic data to the greatest extent through improved median filtering.

[0082] It should be further noted that in practical applications, in order to improve production efficiency and facilitate the identification of seismic waves, seismic waves are received simultaneously at many observation points each time an artificial seismic wave is excited. Therefore, the original seismic data usually consists of multiple seismic traces. Among them, a seismic trace is a one-dimensional seismic signal trace that records the process of seismic waves starting from the excitation point, passing through the formation filter, and returning to the receiving point in space. Therefore, it carries a large amount of information about the crustal geological structure and records the process of seismic wave changes from the moment of excitation to the end of vibration in time.

[0083] In this embodiment, when the distributed optical fiber is collected downhole, due to the lack of a pushing device, some optical fibers cannot be attached to the wellbore wall. Usually, one or more seismic traces corresponding to the optical fibers that cannot be attached to the wellbore wall contain fiber optic coupling noise. The seismic traces containing fiber optic coupling noise are denoted as noise seismic traces. In this embodiment, according to the noise seismic traces in the original seismic data, a data sequence Xi (i = 1, 2, 3,..., m) containing m noise seismic traces can be obtained, and the filtered output value of each point in the data sequence Xi can be output through the following sub-steps to obtain the first effective data:

[0084] Sub-step S101-1: In the data sequence Xi, take n sample values centered on the j-th point as the input; where n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noise seismic traces containing noise in n.

[0085] It should be noted that in this embodiment, n is the number of seismic traces used for calculation, which is also called the span of median filtering. To further improve the reliability of median filtering, when selecting the span of median filtering, a sufficiently large span n should be selected so that n > m holds, to avoid the situation where the filtered output value of the sample point is still noise data because all the seismic traces used for calculation are noise seismic traces.

[0086] In this embodiment, considering that some sample points in the data sequence Xi may reach the left and right boundaries of the original seismic data with n sample points centered on this point and it is impossible to obtain enough n sample points. Therefore, to ensure that a reliable filtered output value can be output for each sample point, in this case, n sample points are taken towards the middle of the original seismic data to achieve the purpose of eliminating isolated noise points.

[0087] Sub-step S101-2: Sort the n sample values in ascending order.

[0088] Sub-step S101-3: Take the sample value at the (n - m)-th data position after the ascending order as the filtered output value of the j-th point.

[0089] It should be noted that the basic principle of median filtering is to replace the value of a point in a digital image or digital sequence with the median of the values of the points in a neighborhood of that point, making the surrounding pixel values closer to the true values, thereby eliminating isolated noise points.

[0090] In this embodiment, considering that the sample values corresponding to noise data are usually greater than the sample values corresponding to noise-free data (i.e., valid data), therefore, after sorting the n sample values in ascending order, the m sample points with larger sample values will be concentrated at the back end of this ascending order. By taking the sample value at the (n - m)-th data position after the ascending order as the filtered output value of this point, the influence of noise data can be effectively shielded, and valid data can be output as much as possible. Therefore, compared with the conventional median filtering that directly outputs the median of this ascending order, the improved median filtering provided in this embodiment can obtain a more accurate and reliable filtered output value.

[0091] Step S102: Obtain noise data according to the difference between the original seismic data and the first valid data.

[0092] In this embodiment, the original seismic data can be denoted as D0, and the first valid data obtained based on the improved median filtering can be denoted as D1. By subtracting the first valid data D1 from the original seismic data D0, data with obvious noise can be obtained, and this noise data is denoted as Dn, that is, Dn = D0 - D1.

[0093] It should be noted that although the improved median filtering can extract the first valid data D1 to the greatest extent, there may still be a part of valid data retained in the noise data Dn. Therefore, this part of valid data still needs to be further extracted.

[0094] Step S103: Perform an S transform on the noise data to obtain an S transform result function.

[0095] In this embodiment, time-frequency analysis is performed on the noise data Dn, that is, through the S transform, the noise data Dn in the time domain is transformed into the time-frequency domain to obtain the S transform result function S1(τ, f).

[0096] Specifically, in step S103, the following S transform formula is used to perform an S transform on the noise data to obtain the S transform result function S1(τ, f):

[0097]

[0098] Where: S1(τ,f) is the S-transform result function of the noise seismic trace; h1(t) is the time-domain seismic signal function corresponding to the noise seismic trace; t represents the seismic wave propagation time before the S-transform; τ represents the seismic wave propagation time after the S-transform; f represents the frequency; j is the imaginary unit.

[0099] Step S104: Obtain a time-frequency domain filter according to the first effective data and the noise data.

[0100] In this embodiment, by comparing and analyzing the time-frequency distribution characteristics of the first effective data D1 and the noise data Dn in the time-frequency domain, the distribution of the noise data Dn in the original seismic data can be obtained. That is to say, it can be known where the noise is strong and where the noise is weak. Furthermore, according to the noise distribution in the noise data Dn, a time-frequency domain filter F(τ,f) can be designed, and the filter is used to filter at the places where the noise is strong to achieve the purpose of eliminating the noise at that point.

[0101] Step S105: Filter the S-transform result function through the time-frequency domain filter to obtain second effective data.

[0102] In this embodiment, step S105 may specifically include the following sub-steps:

[0103] Sub-step S105-1: Obtain a filtered S-transform result function S3(τ,f) according to the product of the S1(τ,f) and the F(τ,f).

[0104] In this embodiment, multiplying the S-transform result function S1(τ,f) obtained by performing the S-transform on the noise data Dn and the time-frequency domain filter F(τ,f) can effectively suppress the amplitude at the places with noise in the noise data Dn, and then obtain the filtered S-transform result function S3(τ,f).

[0105] Sub-step S105-2: Perform an inverse S-transform on the S3(τ,f) to obtain second effective data.

[0106] It should be noted that since the S-transform result function S3(τ,f) is a function in the time-frequency domain at this time, an inverse S-transform needs to be performed on the S3(τ,f) to obtain the second effective data Dres, and this second effective data Dres is the effective signal further extracted from the noise data Dn.

[0107] Specifically, in sub-step S105-2, the following inverse S-transform formula is used to perform an inverse S-transform on the S3(τ,f) to obtain second effective data:

[0108]

[0109] Wherein: S3(τ, f) is the product of S1(τ, f) and F(τ, f); h2(t) is the time-domain seismic signal function obtained by the inverse S transform; τ represents the seismic wave propagation time before the inverse S transform; t represents the seismic wave propagation time after the inverse S transform; f represents the frequency; j is the imaginary unit.

[0110] Step S106: Obtain the seismic data with suppressed noise according to the sum of the first effective data and the second effective data.

[0111] In this embodiment, denote the seismic data with suppressed noise as Ds. Then Ds is the sum of the first effective data D1 and the second effective data Dres, that is, Ds = D1 + Dres.

[0112] In this embodiment, on the basis of obtaining the first effective data D1 through the improved median filtering, the second effective data Dres is further extracted from the noise data through the S transform, realizing the effective suppression of the noise in the downhole DAS seismic data, significantly improving the signal-to-noise ratio of the downhole DAS seismic data, retaining the effective signal to the greatest extent, improving the quality of the DAS seismic data, and providing effective technical support for improving the imaging accuracy and interpretation reliability of the downhole DAS seismic data.

[0113] In a feasible embodiment, step S104 may specifically include the following sub-steps:

[0114] Sub-step S104-1: Perform the S transform on the seismic trace data adjacent to the noise data in the first effective data through the S transform formula to obtain the S transform result function S2(τ, f).

[0115] In this embodiment, considering that adjacent seismic traces usually contain the same time-frequency characteristics, therefore, by selecting the seismic trace data adjacent to the noise data Dn in the first effective data D1 and comparing this seismic trace data with the noise data, the distribution of the noise data Dn in the original seismic data can be known. Furthermore, the time-frequency domain filter F(τ, f) can be designed according to the noise distribution in the noise data Dn.

[0116] Sub-step S104-1: Construct an initial time-frequency domain filtering function according to the time-frequency distribution characteristics of the time-frequency amplitude diagrams of S1(τ, f) and S2(τ, f), and set the value of the initial time-frequency domain filtering function to 0 in the place with strong noise and to 1 in the place with weak noise.

[0117] In this embodiment, when the S-transform result function S1(τ, f) is filtered by the time-frequency domain filter F(τ, f), since F(τ, f) and S1(τ, f) are multiplied, through the subsequent multiplication process, the amplitude at the noisy places can be set to zero, while other places remain unchanged, thereby achieving the purpose of suppressing noise.

[0118] Sub-step S104-1: Smooth the initial time-frequency domain filter function through two-dimensional sliding window averaging to obtain the final time-frequency domain filter function F(τ, f).

[0119] It should be noted that in this embodiment, the specific process of two-dimensional sliding window averaging includes: first specifying a two-dimensional window of a preset size, calculating the arithmetic mean of all F(τ, f) values within the window as the output value at the center position of the window, and then sliding the two-dimensional window until the output values at all positions are calculated to complete the smoothing process of the initial time-frequency domain filter function, and finally obtaining the time-frequency domain filter function F(τ, f).

[0120] Second, based on the same inventive concept, an embodiment of the present application provides a downhole DAS seismic data denoising device 200, and the device includes:

[0121] An extraction module 201, configured to extract first effective data from the original seismic data through improved median filtering; wherein, the original seismic data includes noise data;

[0122] A first obtaining module 202, configured to obtain noise data according to the difference between the original seismic data and the first effective data;

[0123] A second obtaining module 203, configured to perform an S-transform on the noise data to obtain an S-transform result function;

[0124] A third obtaining module 204, configured to obtain a time-frequency domain filter according to the first effective data and the noise data;

[0125] A fourth obtaining module 205, configured to filter the S-transform result function through the time-frequency domain filter to obtain second effective data;

[0126] A fifth obtaining module 206, configured to obtain the seismic data after suppressing noise according to the sum of the first effective data and the second effective data.

[0127] In an embodiment of the present application, the extraction module 201 includes:

[0128] A filtering sub-module, configured to obtain a data sequence Xi (i = 1, 2, 3,..., m) including m noisy seismic traces based on the original seismic data, and output the filtered output value of each point in the data sequence Xi through the following sub-modules to obtain the first effective data:

[0129] An input sub-module, configured to take n sample values centered on the j-th point as inputs in the data sequence Xi; where n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noisy seismic traces containing noise in n;

[0130] An arrangement sub-module, configured to perform ascending order arrangement on the n sample values;

[0131] An output sub-module, configured to take the sample value at the (n - m)-th data position after ascending order arrangement as the filtered output value of the j-th point.

[0132] In an embodiment of the present application, the output sub-module includes:

[0133] A sample complementing sub-module, configured to, when the n samples centered on the j-th point reach the left and right boundaries of the original seismic data and n samples cannot be fully taken, take n samples from the middle of the original seismic data.

[0134] In an embodiment of the present application, the second obtaining module 203 includes:

[0135] A first S-transform sub-module, configured to perform S-transform on the noise data through the following S-transform formula to obtain an S-transform result function S1(τ, f):

[0136]

[0137] In the formula: S1(τ, f) is the S-transform result function of the noisy seismic trace; h1(t) is the time-domain seismic signal function corresponding to the noisy seismic trace; t represents the seismic wave propagation time before S-transform; τ represents the seismic wave propagation time after S-transform; f represents the frequency; j is the imaginary unit.

[0138] In an embodiment of the present application, the third obtaining module 204 includes:

[0139] A second S-transform sub-module, configured to perform S-transform on the seismic trace data adjacent to the noise data in the first effective data through the S-transform formula to obtain an S-transform result function S2(τ, f);

[0140] The first filtering sub-module is configured to construct an initial time-frequency domain filtering function according to the time-frequency distribution characteristics of the time-frequency amplitude diagrams of the S1(τ,f) and the S2(τ,f), and set the value of the initial time-frequency domain filtering function to 0 where the noise is strong and set the value of the initial time-frequency domain filtering function to 1 where the noise is weak;

[0141] The second filtering sub-module is configured to smooth the initial time-frequency domain filtering function through two-dimensional sliding window averaging to obtain a final time-frequency domain filtering function F(τ,f).

[0142] In an embodiment of the present application, the fourth obtaining module 205 includes:

[0143] The first obtaining sub-module is configured to obtain a filtered S-transform result function S3(τ,f) according to the product of the S1(τ,f) and the F(τ,f);

[0144] The second obtaining sub-module performs an inverse S-transform on the S3(τ,f) to obtain second effective data.

[0145] In an embodiment of the present application, the second obtaining sub-module includes:

[0146] The inverse S-transform sub-module is configured to perform an inverse S-transform on the S3(τ,f) through the following inverse S-transform formula to obtain second effective data:

[0147]

[0148] where: S3(τ,f) is the product of S1(τ,f) and F(τ,f); h2(t) is the time-domain seismic signal function obtained by the inverse S-transform; τ represents the seismic wave propagation time before the inverse S-transform; t represents the seismic wave propagation time after the inverse S-transform; f represents the frequency; and j is the imaginary unit.

[0149] It should be noted that the specific implementation manner of the downhole DAS seismic data denoising device in the embodiments of the present application refers to the specific implementation manner of the downhole DAS seismic data denoising method proposed in the first aspect of the present application described above, and will not be elaborated here.

[0150] In a third aspect, based on the same inventive concept, an embodiment of the present application provides an electronic device, where the electronic device includes:

[0151] A processor;

[0152] A memory for storing instructions executable by the processor;

[0153] wherein, the processor is configured to execute the downhole DAS seismic data denoising method proposed in the first aspect of the present application.

[0154] It should be noted that the specific implementation of the electronic device in the embodiments of the present application refers to the specific implementation of the in-well DAS seismic data denoising method proposed in the first aspect of the embodiments of the present application, which will not be elaborated here.

[0155] Fourthly, based on the same inventive concept, the embodiments of the present application provide a computer-readable storage medium. When the instructions in the storage medium are executed by the processor of an electronic device, the electronic device can execute the in-well DAS seismic data denoising method proposed in the first aspect of the present application.

[0156] It should be noted that the specific implementation of the computer-readable storage medium in the embodiments of the present application refers to the specific implementation of the in-well DAS seismic data denoising method proposed in the first aspect of the embodiments of the present application, which will not be elaborated here.

[0157] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a device, or a computer program product. Therefore, the embodiments of the present invention can take the form of an all-hardware embodiment, an all-software embodiment, or an embodiment combining software and hardware aspects. Moreover, the embodiments of the present invention can take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0158] The embodiments of the present invention are described with reference to the flowcharts and / or block diagrams of methods, terminal devices (systems), and computer program products according to the embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, and the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing terminal devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing terminal devices generate a device for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0159] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing terminal device to work in a specific manner, so that the instructions stored in the computer-readable memory generate a manufactured product including an instruction device, and the instruction device implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 one block or multiple blocks.

[0160] These computer program instructions can also be loaded onto a computer or other programmable data processing terminal device, so that a series of operation steps are executed on the computer or other programmable terminal device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable terminal device provide steps for implementing the functions specified in one process or multiple processes and / or blocks. Figure 1 one process or multiple processes and / or blocks Figure 1 steps for implementing the functions specified in one block or multiple blocks.

[0161] Although the preferred embodiments of the embodiments of the present invention have been described, those skilled in the art can make additional changes and modifications once they learn the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications falling within the scope of the embodiments of the present invention.

[0162] Finally, it should also be noted that in this text, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or terminal device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or also includes elements inherent to such process, method, article or terminal device. Without further limitation, an element defined by the statement "comprising one..." does not exclude the existence of additional identical elements in the process, method, article or terminal device comprising the said element.

[0163] The above has introduced in detail a method and device for denoising borehole DAS seismic data provided by the present invention. Specific examples are used in this text to elaborate on the principle and implementation manner of the present invention. The description of the above embodiments is only used to help understand the method and its core idea of the present invention; at the same time, for those of ordinary skill in the art, according to the idea of the present invention, there will be changes in the specific implementation manner and application scope. In summary, the content of this specification should not be construed as a limitation of the present invention.

Claims

1. A method for denoising DAS seismic data in a well, characterized in that, The method includes: extracting first effective data from the original seismic data through improved median filtering; wherein, the original seismic data includes noise data; obtaining noise data according to the difference between the original seismic data and the first effective data; performing an S transform on the noise data to obtain an S transform result function; obtaining a time-frequency domain filter according to the first effective data and the noise data; performing filtering processing on the S transform result function through the time-frequency domain filter to obtain second effective data; obtaining seismic data after noise suppression according to the sum of the first effective data and the second effective data; wherein, extracting first effective data from the original seismic data through improved median filtering includes: obtaining a data sequence Xi including m noise seismic traces according to the original seismic data, i = 1, 2, 3,..., m, and outputting a filtered output value for each point in the data sequence Xi through the following steps to obtain the first effective data: in the data sequence Xi, taking n sample values centered on the j-th point as input; wherein, n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noise seismic traces containing noise in n; sorting the n sample values in ascending order; taking the sample value at the (n - m)-th data position after ascending order sorting as the filtered output value of the j-th point.

2. The method according to claim 1, wherein Taking n sample values centered on the j-th point as input includes: in the case that n sample values centered on the j-th point reach the left and right boundaries of the original seismic data and n sample values cannot be fully obtained, taking n sample values towards the middle of the original seismic data.

3. The method according to claim 1, wherein Performing an S transform on the noise data to obtain an S transform result function includes: performing an S transform on the noise data through the following S transform formula to obtain an S transform result function S1(τ, f): In the formula: S1(τ, f) is the S transform result function of the noise seismic trace; h1(t) is the time-domain seismic signal function corresponding to the noise seismic trace; t represents the seismic wave propagation time before the S transform; τ represents the seismic wave propagation time after the S transform; f represents the frequency; j is the imaginary unit.

4. The method according to claim 3, wherein Obtaining a time-frequency domain filter according to the first effective data and the noise data includes: performing an S transform on the seismic trace data adjacent to the noise data in the first effective data through the S transform formula to obtain an S transform result function S2(τ, f); constructing an initial time-frequency domain filtering function according to the time-frequency distribution characteristics of the time-frequency amplitude diagrams of S1(τ, f) and S2(τ, f), and setting the value of the initial time-frequency domain filtering function to 0 in places with strong noise and setting the value of the initial time-frequency domain filtering function to 1 in places with weak noise; performing smoothing processing on the initial time-frequency domain filtering function through two-dimensional sliding window averaging to obtain a final time-frequency domain filtering function F(τ, f).

5. The method according to claim 4, wherein Performing filtering on the S transform result function through the time-frequency domain filter to obtain second effective data includes: obtaining a filtered S transform result function S3(τ, f) according to the product of S1(τ, f) and F(τ, f); Perform an inverse S transform on the S3(τ,f) to obtain the second effective data.

6. The method according to claim 5, characterized in that, Performing an inverse S transform on the S3(τ,f) to obtain the second effective data includes: Perform an inverse S transform on the S3(τ,f) through the following inverse S transform formula to obtain the second effective data: In the formula: S3(τ,f) is the product of S1(τ,f) and F(τ,f); h2(t) is the time-domain seismic signal function obtained by the inverse S transform; τ represents the seismic wave propagation time before the inverse S transform; t represents the seismic wave propagation time after the inverse S transform; f represents the frequency; j is the imaginary unit.

7. A DAS seismic data denoising device in a well, characterized in that, The device includes: An extraction module for extracting the first effective data from the original seismic data through improved median filtering; wherein the original seismic data includes noise data; A first acquisition module for obtaining noise data based on the difference between the original seismic data and the first effective data; A second acquisition module for performing an S transform on the noise data to obtain an S transform result function; A third acquisition module for obtaining a time-frequency domain filter based on the first effective data and the noise data; A fourth acquisition module for filtering the S transform result function through the time-frequency domain filter to obtain the second effective data; A fifth acquisition module for obtaining the seismic data with suppressed noise based on the sum of the first effective data and the second effective data; Among them, the extraction module includes: A filtering sub-module for obtaining a data sequence Xi containing m noisy seismic traces from the original seismic data, i = 1, 2, 3,..., m, and outputting the filtered output value of each point in the data sequence Xi through the following sub-modules to obtain the first effective data: An input sub-module for taking n sample values centered on the j-th point in the data sequence Xi as input; where n is greater than m, n is the number of seismic traces used for calculation, and m is the number of noisy seismic traces containing noise in n; An arrangement sub-module for arranging the n sample values in ascending order; An output sub-module for taking the sample value at the (n - m)-th data position after ascending order arrangement as the filtered output value of the j-th point.

8. An electronic device, characterized in that, The electronic device includes: A processor; A memory for storing instructions executable by the processor; Among them, the processor is configured to execute the in-well DAS seismic data denoising method according to any one of claims 1-6.

9. A computer-readable storage medium, when the instructions in the storage medium are executed by the processor of the electronic device, enabling the electronic device to execute the in-well DAS seismic data denoising method according to any one of claims 1-6.

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