Time-to-depth conversion curve estimation method, device, storage medium and program product

Abstract

The present application provides a method, device, storage medium and program product for estimating a time-depth conversion curve. The method obtains an initial time-depth conversion curve, a well-side channel seismic signal and a depth-domain logging wave impedance, and obtains an initial time-domain logging reflection coefficient based on the initial time-depth conversion curve and the depth-domain logging wave impedance. Then, according to the initial time-domain logging reflection coefficient, the well-side channel seismic signal and a preset notch point operator, a first notch point map corresponding to the initial time-domain logging reflection coefficient and a second notch point map of the well-side channel seismic signal are obtained. Then, the first notch point map and the second notch point map are matched in the time direction to obtain a notch point matching result. According to the notch point matching result, a time-depth conversion curve is obtained, and there is no need to estimate the seismic wavelet, which effectively improves the accuracy of the time-depth conversion curve estimation.

Description

Technical Field

[0001] The present application relates to the technical field of seismic data processing, and in particular to a time-to-depth conversion curve estimation method, device, storage medium and program product. Background Art

[0002] Seismic data processing is the use of digital computers to process and transform the original data obtained from field seismic exploration, which can provide high-quality, intuitive and reliable geological information for geological interpretation. Since seismic data has a wide horizontal coverage, low vertical resolution and limited effective frequency band, while well logging data has high vertical resolution and wide frequency band, but is single-point data in space, combining the two is of great significance for high-precision seismic data processing. Time-to-depth conversion is a method of matching seismic data with well logging data, that is, converting the well logging data in the depth domain to the time domain, and then matching the seismic data with the well logging data.

[0003] In the prior art, the time-to-depth conversion curve is usually estimated using the well-side channel seismic signal. First, the seismic wavelet is estimated using the logging reflection coefficient and the well-side channel seismic signal to obtain the corresponding artificially synthesized seismic signal. Then, the well-side channel and the artificially synthesized seismic signal are matched. Finally, the time-to-depth conversion curve is estimated using the matching result.

[0004] However, the estimation of seismic wavelets and time-to-depth conversion curves influence each other, so the estimation results of the time-to-depth conversion curves generally have large errors. Summary of the invention

[0005] The present application provides a time-to-depth conversion curve estimation method, device, storage medium and program product to solve the problem of inaccurate estimation results of the time-to-depth conversion curve in the prior art.

[0006] In a first aspect, the present application provides a time-to-depth conversion curve estimation method, comprising:

[0007] Obtain initial time-to-depth conversion curve, well bypass seismic signal and depth domain logging wave impedance;

[0008] Obtaining an initial time-domain logging reflection coefficient according to the initial time-depth conversion curve and the depth-domain logging wave impedance;

[0009] According to the initial time-domain logging reflection coefficient, the well-side channel seismic signal and a preset notch point operator, a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-side channel seismic signal are obtained;

[0010] Matching the first notch point map and the second notch point map in a time direction to obtain a notch point matching result;

[0011] A time-to-depth conversion curve is obtained according to the notch point matching result.

[0012] Optionally, obtaining a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-bypass seismic signal according to the initial time-domain logging reflection coefficient, the well-bypass seismic signal and a preset notch point operator includes:

[0013] Performing short-time Fourier transform on the initial time-domain logging reflection coefficient and the well-side track seismic signal respectively to obtain a first time-frequency amplitude spectrum corresponding to the initial time-domain logging reflection coefficient and a second time-frequency amplitude spectrum corresponding to the well-side track seismic signal;

[0014] Using the time-frequency amplitude spectrum corresponding to the well bypass seismic signal to estimate the effective frequency band, and obtaining a first time-frequency amplitude spectrum and a second time-frequency amplitude spectrum within the effective frequency band;

[0015] Substituting each element in the first time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the first notch point spectrum;

[0016] Substitute each element in the second time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the second notch point spectrum.

[0017] Optionally, the preset notch point operator is defined as follows:

[0018]

[0019] The window size of the notch point operator is (2w1+1)(2w2+1), a i，j is an element in the first time-frequency amplitude spectrum or the second time-frequency amplitude spectrum, w1 and w2 are parameters representing the window size, Represents the element a in the time-frequency amplitude spectrum i，j The value obtained after mapping.

[0020] Optionally, matching the first notch point map and the second notch point map in a time direction to obtain a notch point matching result includes:

[0021] The cost matrix is ​​calculated according to the following formula:

[0022]

[0023] Where C is a cost matrix of size n×n, c i，j is an element in the cost matrix, Among them, w is the parameter that controls the window size. is a two-dimensional image block composed of column vectors corresponding to multiple moments in the first notch point map, is a two-dimensional image block composed of column vectors corresponding to multiple moments in the second notch point spectrum, Indicates the structural similarity of the corresponding two-dimensional image patches in the two notch point maps;

[0024] According to the cost matrix, a distance matrix is ​​calculated, and the shortest path is obtained according to the distance matrix;

[0025] The notch point matching result is obtained according to the shortest path, and the notch point matching result is a new notch point map.

[0026] Optionally, obtaining a time-to-depth conversion curve according to the notch point matching result includes:

[0027] The time series in the initial time-to-depth conversion curve is updated to a new time series in the new notch point map, and the time-to-depth conversion curve is obtained according to the new time series and the depth corresponding to the new time series.

[0028] Optionally, obtaining an initial time-domain logging reflection coefficient according to the initial time-depth conversion curve and the depth-domain logging wave impedance includes:

[0029] Obtaining time domain logging wave impedance according to the initial time-to-depth conversion curve and the depth domain logging wave impedance;

[0030] The initial time-domain logging reflection coefficient is obtained according to the time-domain logging wave impedance.

[0031] In a second aspect, the present application provides a time-to-depth conversion curve estimation device, comprising:

[0032] An acquisition module is used to acquire the initial time-depth conversion curve, the well side track seismic signal and the depth domain logging wave impedance;

[0033] A first processing module, configured to obtain an initial time domain logging reflection coefficient according to the initial time-depth conversion curve and the depth domain logging wave impedance;

[0034] A second processing module is used to obtain a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-bypass seismic signal according to the initial time-domain logging reflection coefficient, the well-bypass seismic signal and a preset notch point operator;

[0035] A matching module, used for matching the first notch point spectrum with the second notch point spectrum in a time direction to obtain a notch point matching result;

[0036] The third processing module is used to obtain a time-to-depth conversion curve according to the notch point matching result.

[0037] In a third aspect, the present application provides an electronic device, comprising: a processor, and a memory communicatively connected to the processor;

[0038] The memory stores computer-executable instructions;

[0039] The processor executes the computer-executable instructions stored in the memory to implement the method described in the first aspect.

[0040] In a fourth aspect, the present application provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer execution instructions, and when the computer execution instructions are executed by a processor, they are used to implement a time-to-depth conversion curve estimation method described in the first aspect.

[0041] In a fifth aspect, the present application provides a computer program product, comprising a computer program, wherein the method described in the first aspect is performed when the computer program is executed by a processor.

[0042] The present application provides a method, device, storage medium and program product for estimating a time-depth conversion curve. The method obtains an initial time-depth conversion curve, a well-side channel seismic signal and a depth-domain logging wave impedance, and obtains an initial time-domain logging reflection coefficient based on the initial time-depth conversion curve and the depth-domain logging wave impedance. Then, according to the initial time-domain logging reflection coefficient, the well-side channel seismic signal and a preset notch point operator, a first notch point map corresponding to the initial time-domain logging reflection coefficient and a second notch point map of the well-side channel seismic signal are obtained. Then, the first notch point map and the second notch point map are matched in the time direction to obtain a notch point matching result. According to the notch point matching result, a time-depth conversion curve is obtained, and there is no need to estimate the seismic wavelet, which effectively improves the accuracy of the time-depth conversion curve estimation. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present application and, together with the description, serve to explain the principles of the present application.

[0044] Figure 1 A schematic diagram of a flow chart of a time-to-depth conversion curve estimation method provided in Example 1 of the present application;

[0045] Figure 2 It is a schematic diagram of a second time-frequency amplitude spectrum corresponding to the well-side channel seismic signal in the first embodiment of the present application;

[0046] Figure 3 A schematic diagram of an effective frequency band in Embodiment 1 of the present application;

[0047] Figure 4 Schematic diagram of the second notch point spectrum in Example 1 of the present application;

[0048] Figure 5 This is a schematic diagram of the data during the experiment of this application;

[0049] Figure 6 This is a schematic diagram of the notch point matching results;

[0050] Figure 7 A comparison diagram of the matching effect of the time-to-depth conversion curve obtained by the time-to-depth conversion curve estimation method of the first embodiment of the present application and the time-to-depth conversion curve estimation result of the traditional DTW algorithm in the prior art on the well logging data and the seismic data;

[0051] Figure 8 A schematic diagram of the structure of a time-to-depth conversion curve estimation device provided in Embodiment 2 of the present application;

[0052] Fig. 9 A schematic diagram of the structure of a time-to-depth conversion curve estimation device provided in Embodiment 3 of the present invention.

[0053] The above drawings have shown clear embodiments of the present application, which will be described in more detail later. These drawings and text descriptions are not intended to limit the scope of the present application in any way, but to illustrate the concept of the present application to those skilled in the art by referring to specific embodiments. DETAILED DESCRIPTION

[0054] Exemplary embodiments will be described in detail herein, examples of which are shown in the accompanying drawings. When the following description refers to the drawings, the same numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the following exemplary embodiments do not represent all implementations consistent with the present application. Instead, they are merely examples of devices and methods consistent with some aspects of the present application as detailed in the appended claims.

[0055] Since seismic data is time domain data, its horizontal coverage is wide, its vertical resolution is low and its effective frequency band is limited, while well logging data is depth domain data, its vertical resolution is high, its frequency band is wide, but it is single-point data in space, so combining the two is of great significance for high-precision seismic data processing. However, due to the different acquisition methods of seismic data and well logging data, the absorption attenuation of seismic data, the inaccurate well-seismic time-depth conversion curve and various noise interference factors, there is a mismatch between well logging data and seismic data at the same location. The premise of combining well-seismic data is to convert well logging data to the time domain, and converting well logging data to the time domain depends on accurate time-depth conversion curves. Therefore, the estimation of time-depth conversion curves is one of the important research contents of matching seismic data with well logging data.

[0056] In the prior art, the time-to-depth conversion curve is usually estimated using the well-side channel seismic signal. The initial time-to-depth conversion curve and the depth domain logging reflection coefficient are first used to obtain the initial time domain logging reflection coefficient, and then the initial time domain logging reflection coefficient and the well-side channel seismic signal are used to estimate the seismic wavelet to obtain the corresponding artificially synthesized seismic signal. Then, the dynamic time warping (Dynamic Time Warpping, referred to as DTW) algorithm is used to match the well-side channel and the artificially synthesized seismic signal to obtain a matching result, and finally the time-to-depth conversion curve is estimated using the matching result. The above process can be iterated for several steps until the set termination condition is met, such as the maximum number of iteration steps or the time-to-depth conversion curve no longer changes.

[0057] At present, the DTW algorithm has been widely used in the matching of well logging data and seismic data. The estimation methods of time-to-depth conversion curves based on the DTW algorithm all need to use the well logging reflection coefficient and the well bypass seismic signal to estimate the seismic wavelet and the time-to-depth conversion curve in turn. However, the estimation of the seismic wavelet and the time-to-depth conversion curve affects each other, that is, when the well logging reflection coefficient and the well bypass seismic signal do not match, the seismic wavelet estimation result cannot be accurately obtained, and the inaccurate seismic wavelet estimation result will affect the accuracy of the time-to-depth conversion curve estimation.

[0058] The above-mentioned estimation method of the time-to-depth conversion curve generally results in a large error in the estimation result. When estimating the time-to-depth conversion curve, the characteristic that the notch points in the time-frequency amplitude spectrum of the seismic signal are only related to the reflection coefficient can be used to match the two, and it is no longer necessary to estimate the seismic wavelet, thereby solving the problems faced by the above-mentioned estimation method of the time-to-depth conversion curve based on the DTW algorithm.

[0059] Therefore, the present application provides a method for estimating a time-to-depth conversion curve, which matches the notch point spectrum corresponding to the time logging reflection coefficient with the notch point spectrum corresponding to the well side channel seismic signal to obtain the notch point matching result, and then updates the initial time-to-depth conversion curve according to the notch point matching result to obtain the estimated result of the time-to-depth conversion curve. There is no need to estimate the seismic wavelet, which effectively improves the accuracy of the time-to-depth conversion curve estimation.

[0060] The method of the present application can be applied to the analysis of seismic data. Combined with the logging data in the depth domain obtained during the exploration of various types of resources, such as oil exploration and coalbed methane exploration, a time-to-depth conversion curve with high accuracy can be obtained. It can be understood that the application scenarios of the present application include but are not limited to the above, and the listed logging data acquisition scenarios are not intended to limit the present application.

[0061] The technical solution of the present application and how the technical solution of the present application solves the above-mentioned technical problems are described in detail below with specific embodiments. The following specific embodiments may exist independently or in combination with each other, and the same or similar concepts or processes may not be described in detail in some embodiments. The embodiments of the present application will be described below in conjunction with the accompanying drawings.

[0062] refer to Figure 1 , Figure 1 A flow chart of a time-to-depth conversion curve estimation method provided in Embodiment 1 of the present application is provided. The method can be executed by a time-to-depth conversion curve estimation device, which can be a server. The method includes the following steps.

[0063] S101, obtaining an initial time-to-depth conversion curve, a well side track seismic signal, and a depth domain logging wave impedance.

[0064] The server can obtain the initial time-to-depth conversion curve and depth domain logging wave impedance in the logging data measured by the logging tool, and can obtain the well side channel seismic signal measured by the seismic exploration tool. The time-to-depth conversion curve can be understood as the corresponding relationship between depth and time. For example, it can be expressed as t=f(d), where d represents depth and t represents time.

[0065] S102, obtaining an initial time-domain logging reflection coefficient according to the initial time-depth conversion curve and the depth-domain logging wave impedance.

[0066] The server can obtain the initial time domain logging reflection coefficient based on the initial time-to-depth conversion curve and the depth domain logging wave impedance, as follows:

[0067] The depth domain logging wave impedance is mapped to the time domain according to the initial time-depth conversion curve to obtain the time domain logging wave impedance. For example, it can be expressed as the time domain logging wave impedance I t (f(d))=I d (d), that is, converting a function about d into a function about t using the time-to-depth conversion curve.

[0068] Then, the time domain logging reflection coefficient at each continuous moment is calculated according to formula (1):

[0069]

[0070] Among them, r(t) is the time domain logging reflection coefficient at time t, I(t) is the time domain logging wave impedance at time t, and I(t+1) is the time domain logging wave impedance at time t+1.

[0071] After obtaining the time domain logging reflection coefficients at each continuous moment, the server can obtain the initial time domain logging reflection coefficient. That is, it can be understood that the initial time domain logging reflection coefficient is a one-dimensional signal composed of the time domain logging reflection coefficients at each continuous moment.

[0072] S103, obtaining a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-side track seismic signal according to the initial time-domain logging reflection coefficient, the well-side track seismic signal and a preset notch point operator.

[0073] After the server obtains the initial time-domain logging reflection coefficient, it can obtain the first notch point map corresponding to the initial time-domain logging reflection coefficient and the second notch point map of the well-side channel seismic signal according to the initial time-domain logging reflection coefficient, the acquired well-side channel seismic signal and the preset notch point operator, as follows:

[0074] (1) Perform short-time Fourier transform on the initial time-domain logging reflection coefficient and the well-side track seismic signal, respectively, to obtain a first time-frequency amplitude spectrum corresponding to the initial time-domain logging reflection coefficient and a second time-frequency amplitude spectrum corresponding to the well-side track seismic signal. For example, the second time-frequency amplitude spectrum corresponding to the well-side track seismic signal can refer to Figure 2 .

[0075] (2) The effective frequency band can be estimated by using the time-frequency amplitude spectrum corresponding to the well side track seismic signal to obtain the cutoff frequency. Specifically, the frequency range corresponding to the value of the second time-frequency amplitude spectrum greater than the preset threshold value is taken as the effective frequency band. For example, Figure 3 As shown, the cut-off frequencies f at both ends of the effective frequency band are L With f H The value of the amplitude spectrum in the corresponding ordinate is greater than the preset threshold.

[0076] (3) Then, according to the cutoff frequency, the first time-frequency amplitude spectrum and the second time-frequency amplitude spectrum within the effective frequency band are intercepted, that is, the time-frequency amplitude spectrum within the effective frequency band is used to form the notch point spectrum, which can increase the accuracy of the notch point spectrum.

[0077] (4) Substitute each element in the first time-frequency amplitude spectrum within the effective frequency band into the definition formula of the preset notch point operator, and substitute each element in the second time-frequency amplitude spectrum within the effective frequency band into the definition formula of the preset notch point operator, and obtain the first notch point spectrum and the second notch point spectrum respectively. The definition formula of the preset notch point operator is as shown in formula (2):

[0078]

[0079] Among them, the window size of the notch point operator is (2w1+1)(2w2+1), a i，jis an element in the first time-frequency amplitude spectrum or the second time-frequency amplitude spectrum, w1 and w2 are parameters representing the window size, Represents the element a in the time-frequency amplitude spectrum i，j Substitute into formula (2) and get the value after mapping.

[0080] For example, the second notch point map can refer to Figure 4 , Figure 4 for Figure 2 The corresponding notch point map.

[0081] S104, matching the first notch point spectrum and the second notch point spectrum in the time direction to obtain a notch point matching result.

[0082] After obtaining the first notch point map and the second notch point map, the server matches the first notch point map and the second notch point map in the time direction, as follows:

[0083] (1) The cost matrix is ​​calculated according to formula (3):

[0084]

[0085] Where C is a cost matrix of size n×n, c i，j is the element in the cost matrix, Among them, w is the parameter that controls the window size. It is a two-dimensional graphic block composed of column vectors corresponding to multiple moments in the first notch point spectrum. is a two-dimensional image block composed of column vectors corresponding to multiple moments in the second notch point map, Represents the structural similarity (SSIM) of the corresponding two-dimensional image blocks in the two notch point maps. SSIM is used to calculate the distance between two blocks, which is independent of the brightness and contrast of the image. Compared with the mean square error, it can better reflect the similarity of the notch points in the two image blocks.

[0086] The definition of SSIM is as follows:

[0087]

[0088] in, yes The mean of yes The mean of yes The variance of yes The variance of yes and The covariance of , the two constants C1 and C2 are chosen as follows:

[0089] C1=(K1L) 2 , C2=(K2L) 2 (4)

[0090] Among them, K1, K2<<1, L is and dynamic range.

[0091] (2) According to the cost matrix, the distance matrix is ​​calculated as follows:

[0092] The first row of the distance matrix is ​​calculated as The first column is calculated as The remaining elements are calculated as d i，j =min(d i-1，j , d i-1，j-1 , d i，j-1 )+c i，j , where i, j = 2, ..., n, c i，j are the elements of the cost matrix.

[0093] After obtaining the distance matrix, the shortest path is found, which can be described as p = (p1, p2, ..., p k ), where p I =(i,j),I=1,…,k,p I =(i, j) means and , and i, j = 1,…, n.

[0094] Fix the shortest path start and end p1 = (1, 1) and p k =(n, n), and the path should satisfy the properties of progressiveness and continuity, that is, p I+1 -p I ∈{(0, 1), (1, 1), (1, 0)}, from p k Start backtracking, and it is known that p I =(i, j) is as follows:

[0095] p I-1 =(i′, j′) (5)

[0096] d i′，j′ =min(d i-1，j , d i-1，j-1 , d i，j-1 ) (6)

[0097] When i=1,j>1,p I-1 =(1, j-1); when i>1, j=1, pI-1 =(i-1, j), when i=1, j=1, backtracking ends and the complete shortest path is obtained.

[0098] (3) According to the obtained shortest path, the corresponding relationship between the column vectors of the first notch point map and the second notch point map can be obtained, and the shortest path can be recorded as p I =(i I , j I ), then the new time series corresponding to the first notch point map and the second notch point map are and Then the time series corresponding to the well bypass seismic signal is restored to (t1, ..., t n ), and according to the corresponding relationship during restoration, the notch point matching result is obtained, that is, the new notch point map. The new time series corresponding to the initial time domain logging reflection coefficient in the map is (t′1, …, t′ n ), after matching, the notch point spectrum corresponding to the time domain logging reflection coefficient can be expressed as

[0099] S105: Obtain a time-to-depth conversion curve according to the notch point matching result.

[0100] After the server obtains the notch point matching result, it can update the time series in the initial time-depth conversion curve to the new time series (t′1, …, t′ n ), and obtain the time-to-depth conversion curve according to the new time series and the depth corresponding to each time in the new time series.

[0101] After obtaining the estimated result of the time-depth conversion curve, the estimated result of the time-depth conversion curve can be applied to the synthesis of well logging data and seismic data. Specifically, the server can recalculate the time-domain well logging reflection coefficient based on the estimated result of the time-depth conversion curve and the depth-domain well logging wave impedance, specifically referring to formula (1), and use the recalculated time-domain well logging reflection coefficient and the well-side channel seismic signal to estimate the seismic wavelet and synthesize the well logging seismic signal. The server can evaluate the matching result of the well logging data and the seismic data by observing the similarity of the seismic wavelet estimation result, the synthesized well logging seismic signal and the well-side channel seismic signal.

[0102] In the above application, the present application verifies the validity of the estimation result of the time-to-depth conversion curve of the present invention through experiments. Figure 5This is a schematic diagram of the data during the experiment of this application, from left to right, a schematic diagram of the acquired depth domain logging wave impedance, a comparison diagram of the real time-to-depth conversion curve and the time-to-depth conversion curve after adding disturbance, a comparison diagram of the time domain logging wave impedance and the time domain logging wave impedance after adding disturbance, and a comparison diagram of the real time domain logging reflection coefficient and the time domain logging reflection coefficient after adding disturbance. Among them, the real time-to-depth conversion curve is an ideal time-to-depth conversion curve artificially simulated by the server, and the time-to-depth conversion curve after adding disturbance can be understood as some errors added to the real time-to-depth conversion curve.

[0103] In the experiment, the time-domain logging reflection coefficient before adding disturbance is convolved with the seismic wavelet estimation result, and the obtained seismic signal is used as the well bypass seismic signal. The time-to-depth conversion curve after adding disturbance is used as the initial time-to-depth conversion curve, and its corresponding time-domain logging reflection coefficient is used as the initial time-domain logging reflection coefficient.

[0104] Figure 6 is the notch point matching result graph, Figure 6 From top to bottom in the figure, they are the notch point spectrum corresponding to the synthesized logging seismic signal, the notch point spectrum corresponding to the initial time domain logging reflection coefficient, and the notch point spectrum corresponding to the matched time domain logging reflection coefficient. It can be seen from the figure that after matching, the stretching transformation of the notch point spectrum caused by the inaccurate time-to-depth conversion curve has been restored, and the notch point spectrum corresponding to the matched time domain logging reflection coefficient is obviously better corresponding to the notch point spectrum corresponding to the synthesized logging seismic signal.

[0105] from Figure 7 It can be seen that the time-depth conversion curve estimation result obtained by the time-depth conversion curve estimation method of the present application is compared with the time-depth conversion curve estimation result of the traditional DTW algorithm in the prior art in the matching effect of logging data and seismic data. From left to right, there are the comparison diagrams of the time-depth conversion curve estimation result of the present application, the time-depth conversion curve estimation result of the DTW algorithm, and the real time-depth conversion curve, the time-domain logging reflection coefficient recalculated according to the estimation result of the time-depth conversion curve of the present application and the depth-domain logging wave impedance, and the time-domain logging reflection coefficient recalculated according to the estimation result of the time-depth conversion curve of the DTW algorithm and the depth-domain logging wave impedance. The logging wave impedance recalculates the time domain logging reflection coefficient, and the comparison diagram of the real time domain logging reflection coefficient, the comparison diagram of the logging seismic signal synthesized according to the estimation result of the time-depth conversion curve of the present application and the logging seismic signal synthesized according to the estimation result of the time-depth conversion curve of the DTW algorithm and the real well side channel seismic signal, the comparison diagram of the seismic wavelet estimated according to the estimation result of the time-depth conversion curve of the present application and the seismic wavelet before estimation according to the estimation result of the time-depth conversion curve of the present application and the seismic wavelet estimated according to the estimation result of the time-depth conversion curve of the DTW algorithm and the real seismic wavelet.

[0106] from Figure 7 It can be seen from the seismic wavelet estimation result in the rightmost figure that when the reflection coefficient does not match the seismic signal, an accurate seismic wavelet estimation result cannot be obtained, and an inaccurate seismic wavelet estimation result will affect the accuracy of the time-to-depth conversion curve estimation. The present invention avoids the seismic wavelet estimation process by matching the notch points in the time domain and the frequency domain, and can obtain a more accurate time-to-depth conversion curve estimation result.

[0107] In this embodiment, the server obtains the initial time-to-depth conversion curve, the well-side channel seismic signal and the depth-domain logging wave impedance, and obtains the initial time-domain logging reflection coefficient based on the initial time-to-depth conversion curve and the depth-domain logging wave impedance, and then obtains the first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and the second notch point spectrum of the well-side channel seismic signal based on the initial time-domain logging reflection coefficient, the well-side channel seismic signal and the preset notch point operator, and then matches the first notch point spectrum and the second notch point spectrum in the time direction to obtain the notch point matching result, and obtains the time-to-depth conversion curve based on the notch point matching result, without estimating the seismic wavelet, effectively improving the accuracy of the time-to-depth conversion curve estimation.

[0108] refer to Figure 8 , Figure 8 The schematic diagram of the structure of a time-to-depth conversion curve estimation device provided in the second embodiment of the present application is as follows: the device 80 comprises: an acquisition module 801 , a first processing module 802 , a second processing module 803 , a matching module 804 and a third processing module 805 .

[0109] The acquisition module 801 is used to acquire the initial time-depth conversion curve, the well side track seismic signal and the depth domain logging wave impedance.

[0110] The first processing module 802 is used to obtain an initial time domain logging reflection coefficient according to the initial time-depth conversion curve and the depth domain logging wave impedance.

[0111] The second processing module 803 is used to obtain a first notch point spectrum corresponding to the initial time domain logging reflection coefficient and a second notch point spectrum corresponding to the well side track seismic signal according to the initial time domain logging reflection coefficient, the well side track seismic signal and a preset notch point operator.

[0112] The matching module 804 is used to match the first notch point spectrum with the second notch point spectrum in the time direction to obtain a notch point matching result.

[0113] The third processing module 805 is used to obtain a time-to-depth conversion curve according to the notch point matching result.

[0114] Optionally, the second processing module 803 is specifically configured to:

[0115] The initial time-domain logging reflection coefficient and the well-side track seismic signal are respectively subjected to short-time Fourier transform to obtain a first time-frequency amplitude spectrum corresponding to the initial time-domain logging reflection coefficient and a second time-frequency amplitude spectrum corresponding to the well-side track seismic signal.

[0116] The effective frequency band is estimated using the time-frequency amplitude spectrum corresponding to the well bypass seismic signal, and the first time-frequency amplitude spectrum and the second time-frequency amplitude spectrum in the effective frequency band are obtained.

[0117] Substitute each element in the first time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the first notch point spectrum.

[0118] Substitute each element in the second time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the second notch point spectrum.

[0119] Optionally, the default notch point operator is defined as follows:

[0120]

[0121] Among them, the window size of the notch point operator is (2w1+1)(2w2+1), a i，j is an element in the first time-frequency amplitude spectrum or the second time-frequency amplitude spectrum, w1 and w2 are parameters representing the window size, Represents the element a in the time-frequency amplitude spectrum i，j The value obtained after mapping.

[0122] Optionally, the matching module 804 is specifically used for:

[0123] The cost matrix is ​​calculated according to the following formula:

[0124]

[0125] Where C is a cost matrix of size n×n, c i，j is the element in the cost matrix, Among them, w is the parameter that controls the window size. is a two-dimensional image block composed of column vectors corresponding to multiple moments in the first notch point map. is a two-dimensional image block composed of column vectors corresponding to multiple moments in the second notch point map, Indicates the structural similarity of the corresponding 2D image patches in two notch point maps.

[0126] According to the cost matrix, the distance matrix is ​​calculated, and the shortest path is obtained according to the distance matrix.

[0127] According to the shortest path, the notch point matching result is obtained, and the notch point matching result is a new notch point map.

[0128] Optionally, the third processing module 805 is specifically used for:

[0129] The time series in the initial time-to-depth conversion curve is updated to a new time series in the new notch point map, and the time-to-depth conversion curve is obtained according to the new time series and the depth corresponding to the new time series.

[0130] Optionally, the first processing module 802 is specifically configured to:

[0131] The time domain logging impedance is obtained based on the initial time-to-depth conversion curve and the depth domain logging impedance.

[0132] According to the time domain logging wave impedance, the initial time domain logging reflection coefficient is obtained.

[0133] The device of this embodiment can be used to execute the steps of a time-to-depth conversion curve estimation method in the first embodiment. The specific implementation method and technical effect are similar and will not be repeated here.

[0134] Fig. 9 A schematic diagram of the structure of a time-to-depth conversion curve estimation device provided in Embodiment 3 of the present invention is shown in FIG. Fig. 9 As shown, the device 90 includes: a processor 901, a memory 902, and a transceiver 903, the memory 902 is used to store instructions, the transceiver 903 is used to communicate with other devices, and the processor 901 is used to execute the instructions stored in the memory, so that the device 90 performs a time-depth conversion curve estimation method step as in the first embodiment. The specific implementation method and technical effect are similar, and will not be repeated here.

[0135] Embodiment 4 of the present invention provides a computer-readable storage medium, in which a computer program is stored. When the computer program is executed by a processor, it is used to implement the steps of a time-to-depth conversion curve estimation method as in the above-mentioned embodiment 1. The specific implementation method and technical effect are similar and will not be repeated here.

[0136] Embodiment 5 of the present invention provides a computer program product, including a computer program. When the computer program is executed by a processor, the steps of a time-to-depth conversion curve estimation method as in the above embodiment 1 are implemented. The specific implementation method and technical effect are similar and will not be repeated here.

[0137] Those skilled in the art will readily appreciate other embodiments of the present application after considering the specification and practicing the invention disclosed herein. The present application is intended to cover any modification, use or adaptation of the present application, which follows the general principles of the present application and includes common knowledge or customary techniques in the art that are not disclosed in the present application. The specification and examples are intended to be exemplary only, and the true scope and spirit of the present application are indicated by the following claims.

[0138] It should be understood that the present application is not limited to the precise structures that have been described above and shown in the drawings, and that various modifications and changes may be made without departing from the scope thereof. The scope of the present application is limited only by the appended claims.

Claims

1. A time-to-depth conversion curve estimation method, characterized in that: include: Obtain initial time-to-depth conversion curve, well side channel seismic signal and depth domain logging wave impedance; Obtaining an initial time-domain logging reflection coefficient according to the initial time-depth conversion curve and the depth-domain logging wave impedance; According to the initial time-domain logging reflection coefficient, the well-side channel seismic signal and a preset notch point operator, a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-side channel seismic signal are obtained; Matching the first notch point map and the second notch point map in a time direction to obtain a notch point matching result; A time-to-depth conversion curve is obtained according to the notch point matching result.

2. The method according to claim 1, characterized in that: The method of obtaining a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-bypass seismic signal according to the initial time-domain logging reflection coefficient, the well-bypass seismic signal and a preset notch point operator comprises: Performing short-time Fourier transform on the initial time-domain logging reflection coefficient and the well-side track seismic signal respectively to obtain a first time-frequency amplitude spectrum corresponding to the initial time-domain logging reflection coefficient and a second time-frequency amplitude spectrum corresponding to the well-side track seismic signal; Using the time-frequency amplitude spectrum corresponding to the well bypass seismic signal to estimate the effective frequency band, and obtaining a first time-frequency amplitude spectrum and a second time-frequency amplitude spectrum within the effective frequency band; Substituting each element in the first time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the first notch point spectrum; Substitute each element in the second time-frequency amplitude spectrum into the definition formula of the preset notch point operator to obtain the second notch point spectrum.

3. The method according to claim 2, characterized in that The definition of the preset notch point operator is as follows: The window size of the notch point operator is (2w1+1)(2w2+1), a i，j is an element in the first time-frequency amplitude spectrum or the second time-frequency amplitude spectrum, w1 and w2 are parameters representing the window size, Represents the element a in the time-frequency amplitude spectrum i，j The value obtained after mapping.

4. The method according to claim 3, characterized in that The matching of the first notch point map and the second notch point map in a time direction to obtain a notch point matching result includes: The cost matrix is ​​calculated according to the following formula: Where C is a cost matrix of size n×n, c i，j is the element in the cost matrix, Among them, w is the parameter that controls the window size. is a two-dimensional image block composed of column vectors corresponding to multiple moments in the first notch point map, is a two-dimensional image block composed of column vectors corresponding to multiple moments in the second notch point spectrum, Indicates the structural similarity of the corresponding two-dimensional image patches in the two notch point maps; According to the cost matrix, a distance matrix is ​​calculated, and the shortest path is obtained according to the distance matrix; The notch point matching result is obtained according to the shortest path, and the notch point matching result is a new notch point map.

5. The method according to claim 4, characterized in that The step of obtaining a time-to-depth conversion curve according to the notch point matching result includes: The time series in the initial time-to-depth conversion curve is updated to a new time series in the new notch point map, and the time-to-depth conversion curve is obtained according to the new time series and the depth corresponding to the new time series.

6. The method according to any one of claims 1 to 5, characterized in that: The step of obtaining the initial time-domain logging reflection coefficient according to the initial time-depth conversion curve and the depth-domain logging wave impedance includes: Obtaining time domain logging wave impedance according to the initial time-to-depth conversion curve and the depth domain logging wave impedance; The initial time-domain logging reflection coefficient is obtained according to the time-domain logging wave impedance.

7. A time-to-depth conversion curve estimation device, characterized in that: include: An acquisition module is used to acquire the initial time-depth conversion curve, the well side track seismic signal and the depth domain logging wave impedance; A first processing module, configured to obtain an initial time domain logging reflection coefficient according to the initial time-depth conversion curve and the depth domain logging wave impedance; A second processing module is used to obtain a first notch point spectrum corresponding to the initial time-domain logging reflection coefficient and a second notch point spectrum corresponding to the well-bypass seismic signal according to the initial time-domain logging reflection coefficient, the well-bypass seismic signal and a preset notch point operator; A matching module, used for matching the first notch point spectrum with the second notch point spectrum in a time direction to obtain a notch point matching result; The third processing module is used to obtain a time-to-depth conversion curve according to the notch point matching result.

8. A time-to-depth conversion curve estimation device, characterized in that: include: A processor, and a memory communicatively connected to the processor; The memory stores computer-executable instructions; The processor executes the computer-executable instructions stored in the memory to implement the method according to any one of claims 1 to 6.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and when the computer-executable instructions are executed by a processor, they are used to implement a time-to-depth conversion curve estimation method according to any one of claims 1 to 6.

10. A computer program product, characterized in that The invention comprises a computer program, which implements the method according to any one of claims 1 to 6 when being executed by a processor.

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