Precise pickup method and system for VSP first arrival of high and steep complex geological structure

Abstract

The invention provides an accurate pickup method and system for a VSP first arrival of a high and steep complex geological structure, and the method comprises the specific steps: obtaining VSP seismic signal data of the high and steep complex geological structure, and carrying out the preprocessing of the VSP seismic signal data; performing high-resolution processing on the preprocessed VSP seismic signal data to obtain high-signal-to-noise-ratio and high-resolution VSP seismic signal data; s2, determining the first arrival of each VSP seismic signal in the high-signal-to-noise-ratio and high-resolution VSP seismic signal data obtained in the step S2 by adopting an energy ratio method, and selecting the first arrival with a clear wave crest and a clear take-off as a standard trace; according to the method, the standard trace is taken as the reference, the DTW algorithm is adopted to carry out fine correction on the first arrival of the VSP seismic signal data near the standard trace, the accurate first arrival of the VSP seismic signal data is obtained, fine picking of the first arrival is achieved, and the problems that the first arrival picking precision of the VSP of the high and steep complex geological structure is not high, and speed calculation is not accurate are solved.

Description

Technical Field

[0001] The invention belongs to the technical field of oil and gas exploration, and in particular to a method and system for accurately picking up the first arrival of a VSP in a high-steep and complex geological structure. Background Art

[0002] As oil and gas exploration and development go deeper and deeper, and geological structures become more and more complex, accurate velocity calculation is crucial for seismic data processing and interpretation. The primary function of VSP is to obtain a reliable time-depth relationship and calculate accurate formation velocity, and the accuracy of VSP first arrival picking will directly determine the reliability of formation velocity calculation. In response to the problem of accurate first arrival picking, many scholars at home and abroad have conducted a large number of related studies and proposed many effective algorithms. However, in ultra-deep well VSP with high-steep and complex geological structures, special phenomena such as forking and complex waves appear in the first arrival, resulting in a large initial picking error, which makes the calculated formation velocity inconsistent with the actual situation. So far, the first arrival picking of high-steep and complex geological structures is still a hot issue in the VSP field.

[0003] Many scholars have proposed different picking methods for ground earthquake or VSP first arrival. Coppens proposed first arrival picking based on energy ratio method in 1985; Xu Yinpo proposed to evaluate the first arrival and select the first arrival with high credibility as a reference to pick the abnormal first arrival for the second time to improve the reliability of first arrival picking; Yue Long and Liu Huaishan proposed to use the instantaneous phase spectrum of the time-frequency analysis signal under the constraint of noise discrimination coefficient, and pick the first arrival when the instantaneous phase passes through zero. Ye Xiaolong, Wang Zhonggang and others proposed an automatic picking method for first arrival travel time based on energy ratio method and correlation. Xu Kaichi, Lu Jingfeng and others carried out wave equation forward modeling, controllable source preprocessing and first arrival tomographic inversion of different ranges on single shot records to guide first arrival picking and improve the reliability of first arrival picking. In recent years, neural network and other related research have been increasingly applied in first arrival picking. These methods usually pick up the first arrival based on the change of instantaneous characteristics such as amplitude, energy, phase or frequency, usually only consider a single feature, and have poor stability. Therefore, the above picking methods are not effective in picking up the first arrival of VSP seismic signal data caused by high-steep and complex geological structures, complex waves, and low signal-to-noise ratio, which will lead to large errors in the subsequent time-depth relationship and calculated velocity, inaccurate layer calibration, and difficulty in meeting production needs. Summary of the invention

[0004] In order to solve the problems existing in the prior art, the present invention provides a method and system for accurately picking up the first arrival of a VSP with a high-steep and complex geological structure. Time-frequency analysis is performed on the VSP seismic signal to obtain relevant parameters such as the main frequency and dominant frequency band of each VSP seismic signal, and the frequency band width is increased by spectral equalization, and the time-frequency coefficients related to noise are filtered out. Then, the energy ratio method is used to automatically pick up the first arrival, and the first arrival with a clear peak and a crisp take-off is selected as the standard track. Finally, DTW is used to finely correct the picked up first arrival to achieve fine picking of the first arrival, so as to solve the problems of low first arrival picking accuracy and inaccurate velocity calculation of the VSP with high-steep and complex geological structures in mountainous areas.

[0005] To achieve the above object, the present invention provides the following technical solution: a method for accurately picking the first arrival of a VSP in a high-steep and complex geological structure, the specific steps of which are as follows:

[0006] S1 obtains VSP seismic signal data of high-steep and complex geological structures and pre-processes the VSP seismic signal data;

[0007] S2 performs high-resolution processing on the pre-processed VSP seismic signal data to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data;

[0008] S3 uses the energy ratio method to determine the first arrival of each VSP seismic signal in the high signal-to-noise ratio and high-resolution VSP seismic signal data obtained in S2, and selects the first arrival with clear wave crest and crisp jump as the standard trace;

[0009] S4 uses the standard track as a reference and adopts the DTW algorithm to make a fine correction to the first arrival of the VSP seismic signal data near the standard track to obtain the accurate first arrival of the VSP seismic signal data.

[0010] Furthermore, in S2, the high-resolution processing is specifically:

[0011] 1) Use discrete wavelet transform to perform multi-scale analysis on each signal of VSP seismic signal data to obtain signals of different scales;

[0012] 2) Perform spectral equalization on signals of different scales;

[0013] 3) Reconstruct the equalized scale signal to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data;

[0014] Furthermore, in S2, the discrete wavelet transform uses a wavelet function to analyze high-frequency signals and a scaling function to analyze low-frequency signals.

[0015] Furthermore, in S2, the discrete wavelet transform is specifically:

[0016]

[0017] Where DWTx(m,n) means that the signal obtained after DWT of signal x(t) is x(m,n), m means the scale parameter is discretized to the power of m, n is the translation parameter, ψ m,n (t) represents the wavelet function;

[0018] Furthermore, in S2, when performing spectrum equalization processing, the wavelet coefficients related to noise are set to zero, and the VSP seismic signal data are reconstructed using the signals of each scale after spectrum equalization and wavelet coefficient setting, so as to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data.

[0019] Furthermore, in S4, the DTW algorithm is used to modify the first arrival of the adjacent channels from the VSP seismic signal standard channel in sequence, and then the first arrival of the adjacent channel is used as the reference channel to modify the next VSP seismic signal until the first arrival of all channels in the VSP seismic signal data is modified.

[0020] Furthermore, in S1, the preprocessing includes performing static correction and consistency processing on the original VSP seismic signal data.

[0021] The present invention also provides a VSP first arrival precision picking system for high-steep and complex geological structures, comprising:

[0022] A data acquisition and processing module is used to acquire VSP seismic signal data of high, steep and complex geological structures in the ground and to pre-process the VSP seismic signal data;

[0023] A high-resolution processing module is used to perform high-resolution processing on the pre-processed VSP seismic signal data to obtain high-signal-to-noise ratio and high-resolution VSP seismic signal data;

[0024] The standard trace determination module is used to determine the first arrival of each VSP seismic signal data in the high signal-to-noise ratio and high-resolution VSP seismic signal data, and select the first arrival with clear wave crest and crisp jump as the standard trace;

[0025] The first arrival correction module is used to use the standard track as a reference and adopt the DTW algorithm to perform fine correction on the first arrival of the VSP seismic signal data near the standard track to obtain the accurate first arrival of the VSP seismic signal data.

[0026] The present invention also provides a terminal device, comprising: a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps in the above method when executing the computer program, or implements the functions of each module in the above system when executing the computer program.

[0027] The present invention also provides a computer-readable medium, comprising a computer program stored in the computer-readable storage medium, wherein the computer program implements the steps in the above method when executed by a processor.

[0028] Compared with the prior art, the present invention has at least the following beneficial effects:

[0029] The invention provides a method for accurately picking up the VSP first arrival of a high-steep and complex geological structure. Starting from the actual characteristics of the VSP first arrival of the high-steep and complex geological structure, based on the instantaneous characteristics of VSP seismic signal data and a signal analysis algorithm, high-resolution processing is performed on the first arrival with complex waves and bifurcation phenomena, and the first arrival is accurately separated. The energy ratio method is used to automatically pick up the first arrival, and the obtained first arrival is true and reliable; the first arrival with clear wave crest and crisp jump is selected as the standard track, and based on this, the DTW algorithm is used to accurately adjust the bifurcation, complex waves and first arrival with large noise, and finally the accurate first arrival of the entire VSP seismic signal data is obtained. The accurate first arrival picking can obtain an accurate time-depth relationship, and provide support for seismic geological layer calibration; the accurate velocity can be obtained through the first arrival, which lays a foundation for well drive processing and well drive interpretation, supports the detailed research of oil and gas reservoirs, and improves the success rate of oil and gas exploration and development. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] Figure 1 flow chart;

[0031] Figure 2 VSP first arrives at the fine picking device interface;

[0032] Figure 3 Characteristics of VSP first arrival in steep and complex geological structures: (a) first arrival of complex wave interference (left); (b) first arrival bifurcation (right);

[0033] Figure 4 The local amplification of the first arrival of VSP complex wave interference in high-steep and complex geological structures;

[0034] Figure 5 Comparison before and after frequency increase, (a) original time-frequency spectrum; (b) time-frequency spectrum after frequency increase;

[0035] Figure 6 VSP first arrival picking after high-resolution processing;

[0036] Figure 7 Energy ratio method first arrival automatic picking;

[0037] Figure 8 Comparison of accurate first arrival picking, (a) accurate first arrival picking; (b) conventional first arrival picking;

[0038] Fig. 9Comparison of formation velocity calculations using accurate first-arrival picking, (a) calculation of formation velocity using accurate first-arrival picking; (b) calculation of formation velocity using conventional first-arrival picking;

[0039] Fig.10 Discrete sequence DTW matching results. DETAILED DESCRIPTION

[0040] The present invention will be further described below in conjunction with the accompanying drawings and specific embodiments.

[0041] like Figure 1 As shown, the present invention comprehensively utilizes the changes in the instantaneous characteristics of VSP seismic signal data, considers multiple characteristics such as frequency and waveform, and combines the signal analysis method to analyze and accurately pick up the first arrival, and specifically proposes a VSP first arrival accurate picking method for high-steep and complex geological structures. The specific steps are as follows:

[0042] (1) Data preprocessing.

[0043] To obtain VSP seismic signal data of high-steep and complex geological structures, the data needs to be loaded into the observation system. According to the observation system, the data is pre-processed by static correction, consistency processing and denoising.

[0044] (2) High-resolution processing based on time-frequency analysis.

[0045] For the preprocessed VSP seismic signal data, the bandwidth of each data is analyzed, and wavelet transform is used to obtain signals and scale coefficients of different scales for each VSP seismic signal data. An appropriate threshold is selected, and spectral equalization is performed on the signals of different scales. Then, the signals of each scale are reconstructed to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data, and the complex waves and fork first arrivals are separated.

[0046] (3) Automatically pick the first arrival based on the energy ratio method.

[0047] For each high-resolution VSP seismic signal data, the energy ratio method is used to determine the first arrival of each trace, and the first arrival with clear wave crest and crisp first arrival is selected as the standard trace.

[0048] (4) VSP first arrival fine correction.

[0049] Taking the standard track as the benchmark, the DTW algorithm is used to match the tracks near the standard track to find the optimal initial arrival point.

[0050] According to the above ideas and solutions, the present invention proposes a VSP first arrival accurate picking method system for high-steep and complex geological structures based on time-frequency analysis and DTW algorithm, including:

[0051] A data acquisition and processing module is used to acquire VSP seismic signal data of high-steep and complex geological structures and pre-process the VSP seismic signal data;

[0052] A high-resolution processing module is used to perform high-resolution processing on the pre-processed VSP seismic signal data to obtain high-signal-to-noise ratio and high-resolution VSP seismic signal data;

[0053] The standard trace determination module is used to determine the first arrival of each VSP seismic signal data in the high signal-to-noise ratio and high-resolution VSP seismic signal data, and select the first arrival with clear wave crest and crisp jump as the standard trace;

[0054] The first arrival correction module is used to use the standard track as a reference and adopt the DTW algorithm to perform fine correction on the first arrival of the VSP seismic signal data near the standard track to obtain the accurate first arrival of the VSP seismic signal data.

[0055] According to the above ideas and solutions, the present invention also provides a terminal device that can be industrially applied to the accurate picking of the first arrival of VSP. The terminal device includes: a processor, a memory, and a computer program stored in the memory and executable on the processor. When the processor executes the computer program, the steps in the above method are implemented, or when the processor executes the computer program, the functions of each module / unit in the above system are implemented. Figure 2 It is the interface of VSP initial fine picking device.

[0056] The above-mentioned computer program may be divided into one or more modules / units, and one or more modules / units are stored in the above-mentioned memory and executed by a processor to complete the present invention.

[0057] The terminal device can be a computing device such as a desktop computer, a notebook, a PDA, or a cloud server.

[0058] The terminal device may include, but is not limited to, a processor and a memory.

[0059] The processor can be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.

[0060] The memory can be used to store the above-mentioned computer programs and / or modules, and the processor implements various functions of the above-mentioned terminal device by running or executing the computer programs and / or modules stored in the memory, and calling the data stored in the memory.

[0061] If the module / unit integrated in the terminal device is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium.

[0062] Based on such understanding, the present invention implements all or part of the processes in the above method, and can also be completed by instructing related hardware through a computer program, and the computer program can be stored in a computer-readable storage medium, and the computer program can implement the above method steps when executed by a processor. Among them, the above computer program includes computer program code, and the above computer program code can be in source code form, object code form, executable file or some intermediate form, etc.

[0063] The above-mentioned computer-readable medium may include: any entity or device capable of carrying the above-mentioned computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory (ROM), random access memory (RAM), electric carrier signal, telecommunication signal and software distribution medium, etc. It should be noted that the content contained in the above-mentioned computer-readable medium may be appropriately increased or decreased according to the requirements of legislation and patent practice in the jurisdiction. For example, in some jurisdictions, according to legislation and patent practice, computer-readable media do not include electric carrier signals and telecommunication signals.

[0064] Example

[0065] 1. VSP first arrival analysis of high-steep and complex geological structures

[0066] For the zero-well source distance VSP first arrival in the high-steep and complex geological structure in western China, when the surface loess is well developed and the shallow gravel layer is obvious, complex wave interference is easy to occur. Figure 3 (a) Figure 4 As shown in Figure 2, when the formation dip is large and there is an obvious height layer, the direct wave is no longer the first arrival, and a fork appears in the high and steep area, such as Figure 3 (b) as shown.

[0067] The complex waves and bifurcation of VSP first arrivals in steep and complex geological structures seriously interfere with the effective first arrivals, resulting in low first arrival picking accuracy. Therefore, accurately separating the effective first arrivals is the primary task of first arrival precise picking.

[0068] 2. VSP seismic signal data preprocessing

[0069] The acquired original VSP seismic signal data contains multiple components as well as monitoring wavelets and auxiliary traces, and cannot be directly picked for first arrival. It is necessary to load the observation system and perform preprocessing such as static correction and consistency processing.

[0070] (1) Loading the observation system: According to the class report, the depth and coordinates of each detector are loaded into the corresponding position of the track head, the source offset and source coordinates are loaded, and the azimuth is calculated.

[0071] (2) Static correction: When using VSP with shot point excitation, it is necessary to perform static correction on the shot point. The correction amount is:

[0072]

[0073] Where: h is the surface elevation of the wellhead; h0 is the elevation of the source excitation point; v is the surface filling velocity.

[0074] (3) Consistency processing: Perform wave field separation on the VSP seismic signal data, select the standard trace as the standard wavelet in the downlink wave, and use the wavelet shaping algorithm to obtain the shaping factor, which is obtained as follows:

[0075]

[0076] Where: a(t) is the anti-wavelet; b(t) is the earthquake wavelet; γ bb (τ) is the autocorrelation of the seismic wavelet; γ db (τ) is the cross-correlation between the desired output and the wavelet.

[0077] By solving the above Topplitz equations, the wavelet shaping factor a(t) is obtained, which is applied to the full wavefield to shape the VSP seismic signal.

[0078] 3. High-resolution processing of VSP seismic signal data

[0079] For the preprocessed VSP seismic signal data, Discrete Wavelet Transform (DWT) is used to perform multi-scale time-frequency analysis on the VSP seismic signal data, that is, filters of different frequencies are used to analyze signals of different frequencies, wavelet functions are used to analyze high-frequency signals, and scaling functions are used to analyze low-frequency signals:

[0080]

[0081] Where DWTx(m,n) means that the signal obtained after DWT of signal x(t) is x(m,n), m means the scale parameter is discretized to the power of m, n is the translation parameter, ψ m,n (t) represents the wavelet function;

[0082] The scaling function is:

[0083]

[0084] The wavelet function is:

[0085]

[0086] Among them, j, k represent scales, j = 0, ±1, ±2, ...; k = 0, ±1, ±2, ...

[0087] Discrete wavelet transform is used to decompose each VSP seismic signal in the VSP seismic signal data to obtain signals of different scales. Spectral equalization is performed on the signals of each scale, and the wavelet coefficients related to noise are set to zero. The VSP seismic signal data are reconstructed using the signals of each scale after spectral equalization and wavelet coefficient setting to obtain VSP seismic signal data with high signal-to-noise ratio and high resolution. Figure 5 is the time-frequency spectrum before and after high resolution. Figure 6 This is the result of separating the complex wave and the first arrival after high resolution.

[0088] 4. Automatically pick up the first arrival of VSP seismic signal data

[0089] Automatically pick the first arrival of high signal-to-noise ratio and high-resolution VSP seismic data. In VSP seismic signals, the energy difference before and after the first arrival at the detector is huge. The energy ratio method is used to determine the first arrival of each trace, realize automatic first arrival picking, and determine the first arrival of each VSP seismic signal in high signal-to-noise ratio and high-resolution VSP seismic signal data;

[0090] The energy ratio method is as follows:

[0091] According to the high signal-to-noise ratio and high-resolution VSP seismic signal data, the VSP first arrival period is estimated to determine the time window. The sliding time window starts from time 0. The energy ratio method is more sensitive to the first arrival. When T0-T2 enters the effective signal, the energy ratio reaches the maximum, which is used to determine the first arrival time of VSP, such as Figure 7 , the first arrival time is T0.

[0092] After determining the time of the first arrival starting point, the first arrival is automatically picked at the maximum amplitude in the T0-T2 time window to obtain the first arrival of each VSP seismic signal.

[0093] 5. VSP seismic signal data first arrival fine correction

[0094] On the automatically picked first arrival data, the first arrival with clear wave crest and crisp first arrival jump is manually selected as the standard track. The DTW algorithm is used to make fine corrections to the first arrivals from the standard track to the adjacent track in sequence. The first arrival of the adjacent track is then used as the reference track to modify the next track until all the first arrivals are modified.

[0095] The DTW algorithm is as follows:

[0096] Assume that the selected standard channel is X, the adjacent channel data is Y, and the lengths are |X| and |Y| respectively.

[0097] The regularized path W is in the form of:

[0098] W=w1,w2,…,w k , where Max(|X|,|Y|)≤K≤|X|+|Y|, K represents the term.

[0099] Where: w k The form is (i,j), where i represents the i coordinate in X and j represents the j coordinate in Y. The regular path must start from w1=(1,1) and end at w k =(|X|,|Y|) to ensure that every coordinate in X and Y appears in W. Among them, i and j in w(i,j) in W must be monotonically increasing, that is:

[0100] w k =(i,j),w k+1 =(i',j')i <i'<i+1,j<j'<j+1

[0101] Finally, the shortest regular path is:

[0102] D(i,j)=Dist(i,j)+min[D(i-1,j),D(i,j-1),D(i-1,j-1)]

[0103] According to this principle, the first arrival peak point of Y that matches the first arrival peak point of the standard track X can be found, thereby achieving fine correction of the adjacent tracks. The above operation is repeated until the first arrival modification of each VSP seismic signal in the high signal-to-noise ratio and high-resolution VSP seismic signal data is completed, that is, the accurate picking of the VSP first arrival of steep and complex geological structures is achieved.

[0104] Carefully pick up the first Figure 8 As shown in (a), the calculated speed is Fig. 9 (a), Compared with conventional picking, the velocity is more accurate to the true formation velocity and reflects the true wellbore velocity.

[0105] Glossary:

[0106] 1. Wavelet transform: Under different scales α, the basic wavelet function after displacement τ is taken as the inner product with the signal to be analyzed X(t). This process is called wavelet transform, that is:

[0107]

[0108] Among them: α>0 is called the scale factor, which is used to adjust the basic wavelet The function is stretched; τ reflects the displacement, and its value can be positive or negative. Both α and τ are continuous variables, so it is also called continuous wavelet transform (CWT for short). At different scales, the duration of the wavelet increases with the increase of the value, and the amplitude increases with the The wave shape remains the same, but decreases inversely.

[0109] The frequency domain equivalent of the above equation is:

[0110]

[0111] 2. Spectral equalization: Spectral equalization is similar to zero-phase deconvolution, that is, keeping the phase spectrum unchanged and whitening the amplitude spectrum. The principle is to decompose the seismic trace to be equalized into multiple narrow-band seismic traces, multiply the seismic traces of different narrow-band decomposed by a coefficient, and sum the equalized filter traces according to the relative amplitude to obtain the final spectrally equalized seismic trace. In addition, the target seismic trace can also be decomposed into several time windows, and the seismic trace can be decomposed, equalized, and summed in each time window.

[0112] The proportional factor k used for equalization depends on the relative amplitude before equalization in the corresponding filter bin. k is determined by the following formula:

[0113]

[0114] Where: A0 is a fixed constant; is the average amplitude value in each time window after narrow-band filtering of the seismic trace; se is the proportional factor index, and its value is The number between.

[0115] The decomposed seismic traces are summed up, and the width of the output seismic trace is determined by the lowest low-cutoff frequency and the highest high-cutoff frequency in all filter frequency bands.

[0116] 3. Energy ratio method for first arrival picking: F.Coppers first proposed the energy ratio method in 1985, which is the energy ratio, that is, the ratio of the energy of the signal in one cycle to the energy of the total time window of the signal, that is,

[0117]

[0118] Where R(τ) is the energy ratio function within the time window [ττ-L]; x(t) is the amplitude value of the actual signal; and L is the length of the apparent period.

[0119] In actual recording, the collected signal has a fixed sampling frequency, and the above formula must be discretized. After discretization, the sliding energy ratio function is:

[0120]

[0121] In the formula: F(a) represents the energy ratio function of the next time window to the previous time window at the signal sample point a; a represents the sampling point in the signal; L1 represents the time window length of the signal in the time window before the sample point a; L2 represents the time window length of the signal in the time window after the sample point a; x(i) represents the amplitude value of the signal at time point i. The energy ratio function is very sensitive to the first arrival of the elastic wave. When the first arrival of the next time window enters the effective signal, the energy ratio will reach the maximum value. Therefore, the energy ratio method can be used to well determine the time when the first arrival of the elastic wave occurs.

[0122] 4. DTW algorithm: DTW stands for Dynamic Time Warping, which was proposed by the famous Japanese scholar Itakura. It was first used to identify isolated words in speech recognition. Later scholars improved it and often applied it to time series matching. The most basic idea of ​​DTW is: for two discrete sequences, use Euclidean distance to calculate their similarity, then use the dynamic time planning algorithm to find the minimum cumulative Euclidean distance, use the path backtracking algorithm to match the two sequences to get the most similar corresponding points of the sequences, and stretch and compress the two sequences to achieve the best match.

[0123] The traditional DTW algorithm for time series matching mainly has the following three steps:

[0124] (1) Establish the sequence Euclidean distance matrix: Suppose two time series with lengths i and j are M = [M1, M2, …, M i ] and N=[N0,N1,…,N j ]. Use Euclidean distance to measure the similarity of each point in sequence M and sequence N, and establish the sequence Euclidean distance matrix, recorded as E:

[0125] E a,b =(M a -N b ) 2

[0126] Among them: a,b=0,1,…,i.

[0127] (2) Establishing the cumulative Euclidean distance matrix of the sequence: The Euclidean distance matrix E reflects the similarity between the points in the two sequences M and N, but lacks a global similarity measurement standard. The cumulative Euclidean distance D is defined to measure the global similarity between the sequences M and N:

[0128] D a,b =E a,b +min(D a-1,b ,D a,b-1 ,Da-1,b-1 )

[0129] When i=0 or j=0, D 0,j =E 0,j , D i,0 =E i,0 .

[0130] (3) Path backtracking matching similar points: In the cumulative Euclidean distance matrix D, we can find similar points from D i,j Back to D 0,0 , the best matching path u can be obtained in the backtracking process, in which the corresponding relationship between each point in sequence M and sequence N is saved. And u must meet the following conditions: ① Boundary conditions, Fig.10 The first and last points must be kept fixed, that is, P0 = (0.0), P K =(i,j). ② Monotonicity: It is necessary to ensure that the points on the path move monotonically over time. Fig.10 The dotted lines in the schematic diagram will not cross. ③ Continuity, ensuring that the points on the path are adjacent to each other and there will be no jumping phenomenon.

Claims

1. A method for accurately picking the first arrival of VSP in high-steep and complex geological structures, characterized in that: The specific steps are as follows: S1 obtains VSP seismic signal data of high-steep and complex geological structures and pre-processes the VSP seismic signal data; S2 performs high-resolution processing on the pre-processed VSP seismic signal data to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data; S3 uses the energy ratio method to determine the first arrival of each VSP seismic signal in the high signal-to-noise ratio and high-resolution VSP seismic signal data obtained in S2, and selects the first arrival with clear wave crest and crisp jump as the standard trace; S4 uses the standard track as a reference and adopts the DTW algorithm to make a fine correction to the first arrival of the VSP seismic signal data near the standard track to obtain the accurate first arrival of the VSP seismic signal data.

2. The method for accurately picking the first arrival of a VSP in a high-steep and complex geological structure according to claim 1, characterized in that: In S2, the high-resolution processing is specifically: 1) Use discrete wavelet transform to perform multi-scale analysis on each signal of VSP seismic signal data to obtain signals of different scales; 2) Perform spectral equalization on signals of different scales; 3) Reconstruct the equalized scale signal to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data.

3. The method for accurately picking the first arrival of VSP in a high-steep and complex geological structure according to claim 2, characterized in that: In S2, the discrete wavelet transform uses a wavelet function to analyze high-frequency signals and a scaling function to analyze low-frequency signals.

4. A method for accurately picking the first arrival of a VSP in a high-steep and complex geological structure according to claim 2 or 3, characterized in that: In S2, the discrete wavelet transform is specifically: Where DWTx(m,n) means that the signal obtained after DWT of signal x(t) is x(m,n), m means the scale parameter is discretized to the power of m, n is the translation parameter, ψ m,n (t) represents the wavelet function.

5. The method for accurately picking the first arrival of VSP in a high-steep and complex geological structure according to claim 2, characterized in that: In S2, when performing spectrum equalization processing, the wavelet coefficients related to noise are set to zero, and the VSP seismic signal data are reconstructed using the signals of each scale after spectrum equalization and wavelet coefficient setting to obtain high signal-to-noise ratio and high-resolution VSP seismic signal data.

6. The method for accurately picking the first arrival of a VSP in a high-steep and complex geological structure according to claim 1, characterized in that: In S4, the DTW algorithm is used to modify the first arrival of the adjacent channels from the VSP seismic signal standard channel in sequence, and then the first arrival of the adjacent channel is used as the reference channel to modify the next VSP seismic signal until the first arrival of all channels in the VSP seismic signal data is modified.

7. The method for accurately picking the first arrival of a VSP in a high-steep and complex geological structure according to claim 1, characterized in that: In S1, the preprocessing includes performing static correction and consistency processing on the original VSP seismic signal data.

8. A VSP first arrival precision picking system for steep and complex geological structures, characterized in that: include: A data acquisition and processing module is used to acquire VSP seismic signal data of high, steep and complex geological structures in the ground and to pre-process the VSP seismic signal data; A high-resolution processing module is used to perform high-resolution processing on the pre-processed VSP seismic signal data to obtain high-signal-to-noise ratio and high-resolution VSP seismic signal data; The standard trace determination module is used to determine the first arrival of each VSP seismic signal data in the high signal-to-noise ratio and high-resolution VSP seismic signal data, and select the first arrival with clear wave crest and crisp jump as the standard trace; The first arrival correction module is used to use the standard track as a reference and adopt the DTW algorithm to perform fine correction on the first arrival of the VSP seismic signal data near the standard track to obtain the accurate first arrival of the VSP seismic signal data.

9. A terminal device, characterized in that: include: A processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the processor implements the steps of any one of the methods of claims 1 to 7 when executing the computer program, or implements the functions of each module in the system of claim 8 when executing the computer program.

10. A computer-readable medium, characterized in that The method comprises a computer program stored in a computer-readable storage medium, wherein when the computer program is executed by a processor, the steps in the method of any one of claims 1 to 7 are implemented.

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