CN111679317A

CN111679317A - Seismic signal medium-frequency component extraction method, high-frequency component reconstruction method and system

Info

Publication number: CN111679317A
Application number: CN201910179694.2A
Authority: CN
Inventors: 夏竹; 梁星如; 张立彬; 杜新江; 李圣明; 张胜
Original assignee: China National Petroleum Corp; BGP Inc
Current assignee: China National Petroleum Corp; BGP Inc
Priority date: 2019-03-11
Filing date: 2019-03-11
Publication date: 2020-09-18
Anticipated expiration: 2039-03-11
Also published as: CN111679317B

Abstract

The invention provides a method for extracting medium-frequency components and a method for reconstructing high-frequency components of seismic signals, and a system for extracting and reconstructing medium-frequency and high-frequency components in the same-domain seismic signals by using an extremum characteristic point screening and waveform reconstruction technology in a time domain waveform self-adaptive window, which can organically establish natural connection between multi-scale information in the time domain seismic signals and geological target sedimentary bodies of different levels, thereby providing a more intuitive and reasonable multi-scale seismic analytic data body for seismic geological interpretation, reservoir fine description and subsequent reservoir inversion.

Description

Seismic signal medium-frequency component extraction method, high-frequency component reconstruction method and system

Technical Field

The invention relates to the technical field of seismic exploration, in particular to a method for extracting medium-frequency components of seismic signals, a method for reconstructing high-frequency components and a system.

Background

In the process of seismic exploration and development, the analysis of the sub-scale time domain or time-frequency domain signal characteristics suitable for geological meaning is carried out on seismic data, different-level geological target body characteristics and depositional evolution information are obtained from different-scale seismic signal components, and the method is one of core tasks for carrying out reservoir sedimentary facies prediction and reservoir fine description by utilizing seismic information.

At present, multi-scale decomposition of signals in seismic data processing is often carried out in a time-frequency domain, and the methods mainly comprise a linear time-frequency transformation method, a quadratic time-frequency transformation method and a greedy algorithm. Typical linear time-frequency analysis methods include short-time window Fourier transform, Gabor transform, continuous wavelet transform, S transform, generalized S transform, and the like. The linear time-frequency analysis method is derived from Fourier transformation, and both satisfy the linear superposition Principle, but are limited by Heisenberg uncertainty Principle (Heisenberg uncertainty Principle), and the time resolution and the frequency resolution cannot reach the best at the same time. Typical quadratic time-frequency transformation methods include Wigner-Ville distribution and Cohen-like methods. The time-frequency transformation method reflects the time-frequency distribution of signal energy, and although the frequency resolution is generally higher, the time-frequency transformation method does not meet the linear superposition principle and has cross terms. The greedy algorithm mainly includes a matching pursuit method and a Hilbert-Huang method. The matching pursuit algorithm is to adaptively decompose a non-stationary signal into a linear combination of a group of time-frequency atoms, and can obtain a time-frequency representation with high energy aggregation in a two-dimensional time-frequency plane. The problem of window function is broken through by time-frequency atom matching, tracking and decomposing, but in actual signal processing, due to the lack or insufficiency of the prior information of a signal to be analyzed, a constructed time-frequency atom set can not accurately depict the local structural features of the signal. The Hilbert-Huang transform is capable of adaptively decomposing a time signal into a plurality of Intrinsic Mode Functions (IMFs) using an Empirical Mode Decomposition (EMD) algorithm of the signal. Both greedy algorithms seek an optimal solution in each cycle, rather than a globally optimal solution, and may leave much of the energy in the signal in the remaining signal. In addition, the high operation cost is also an important factor for restricting the practicability of the two methods.

The multi-scale time-frequency analysis method for the seismic data has the main problems that: information conversion (inverse transformation) between a time domain and a frequency domain is difficult to form a good corresponding and matching relationship, and a tight and corresponding coupling relationship between multi-scale time-frequency information and different-level geological unit information in seismic signals cannot be effectively established, so that a sub-scale time-frequency analysis result is difficult to more intuitively, effectively and accurately reflect multi-level geological unit characteristics and a deposition evolution rule.

Disclosure of Invention

In order to solve at least one of the problems, the invention provides a method for extracting medium-frequency components in seismic signals, a method for reconstructing high-frequency components, a system, an electronic device and a computer readable medium, wherein medium-high frequency components in the same-domain seismic signals are extracted and reconstructed by a time domain waveform adaptive window internal extremum characteristic point screening and waveform reconstruction technology, and natural connection can be established between multi-scale information in the time domain seismic signals and different levels of geological target depositional bodies organically, so that a more visual and reasonable multi-scale seismic analytic data body is provided for seismic geological interpretation, reservoir fine description and subsequent reservoir inversion.

In some embodiments, a method of extracting frequency components in a seismic signal comprises:

screening primary frequency reduction extreme value characteristic points from the seismic records; and extracting medium-frequency components in the seismic record based on the position of each primary frequency reduction extremum characteristic point corresponding to the seismic record.

In some embodiments, a method of seismic signal high frequency component reconstruction includes:

screening primary frequency reduction extreme value characteristic points from the seismic records; and performing waveform reconstruction on high-frequency components in the seismic records based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

In certain embodiments, a seismic signal intermediate frequency component extraction system comprises:

the screening module screens out primary frequency reduction extreme value characteristic points from the seismic records; and the medium-frequency component extraction module is used for extracting medium-frequency components in the seismic record based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

In certain embodiments, a seismic signal high frequency component reconstruction system comprises:

the screening module screens out primary frequency reduction extreme value characteristic points from the seismic records; and the high-frequency component waveform reconstruction module is used for reconstructing the waveform of the high-frequency component in the seismic record based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

In certain embodiments, an electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, the processor when executing the program implementing the steps of the method of extracting frequency components in seismic signals as claimed above; alternatively, the processor implements the seismic signal high frequency component reconstruction method as described above when executing the program.

In certain embodiments, a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements the steps of the seismic signal mid-frequency component extraction method as described above; alternatively, the computer program, when executed by a processor, implements a seismic signal high frequency component reconstruction method as described above.

The invention has the following beneficial effects:

the invention provides a seismic signal medium-frequency component extraction method, a high-frequency component reconstruction method, a system, electronic equipment and a computer readable medium, which are signal scaling processing technologies with waveform self-constraint and strict fidelity of extreme value feature point positions. Therefore, the method can decompose and reconstruct the original seismic signals into multi-scale, complete and continuous frequency division signals according to the distribution rule of the extreme characteristic points of the seismic record and the sequence from low frequency to high frequency (second-stage frequency reduction → first-stage frequency increase → second-stage frequency increase). The multi-scale seismic information and the original seismic record have the same waveform property at the corresponding extreme point, have strict inheritance and fidelity, can eliminate mutual superposition and interference among geologic bodies with different scales, and each single-frequency component reflects the response of a geologic target body matched with the scale. The invention is applied to the two-dimensional seismic section and the three-dimensional seismic data volume, and the frequency division seismic section and the seismic data volume with a plurality of different scales of the time domain can be directly obtained. The frequency division data can be used for carrying out the works of seismic geological fine interpretation, reservoir characteristics, sedimentary facies prediction and the like. And the reasonability, reliability and accuracy of the seismic geological interpretation result can be comprehensively improved through interactive comparison, constraint and verification among the multi-scale seismic data geological interpretation results.

Drawings

In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.

Fig. 1 is a schematic flow chart of a method for extracting frequency components from seismic signals according to an embodiment of the present invention.

Fig. 2 shows a detailed flowchart of step S100 in fig. 1 in the embodiment of the present invention.

Fig. 3 shows a detailed flowchart of step S110 in fig. 2 in the embodiment of the present invention.

Fig. 4 shows a detailed flowchart of step S120 in fig. 2 in the embodiment of the present invention.

Fig. 5 shows a detailed flowchart of step S200 in fig. 1 in the embodiment of the present invention.

FIG. 6 is a flow chart of a seismic signal high frequency component reconstruction method according to an embodiment of the present invention.

Fig. 7 shows a detailed flowchart of step S300 in fig. 6 in the embodiment of the present invention.

Fig. 8 shows a detailed flowchart of step S302 in fig. 6 in the embodiment of the present invention.

Fig. 9 shows one of the specific flow diagrams of step S304 in fig. 6 in the embodiment of the present invention.

Fig. 10 is a second flowchart illustrating the step S304 of fig. 6 according to the embodiment of the present invention.

FIG. 11 is a schematic diagram showing the initial positive and negative pole characteristic points of the seismic recording waveform in the embodiment of the invention.

Fig. 12 is a schematic diagram illustrating a first-order down-conversion extreme characteristic point sequence screened from an initial extreme characteristic point sequence according to an embodiment of the present invention.

FIG. 13 is a schematic diagram illustrating the extraction of frequency components in seismic signals within a waveform adaptive window in an embodiment of the present invention.

FIG. 14 is a schematic diagram illustrating reconstruction of a high frequency component waveform of a seismic recording within a waveform adaptation window according to an embodiment of the invention.

Fig. 15 shows a schematic diagram of an interpolation algorithm of a cosine function between two points in the embodiment of the present invention.

FIG. 16 is a schematic diagram of a single-channel four-frequency-division seismic signal obtained based on an extraction method and a reconstruction method in the embodiment of the present invention.

FIG. 17 shows a conventional (raw) seismic data slice (T8+20ms) schematic in an embodiment of the invention.

FIGS. 18 a-18 d show development of planar sedimentary facies analysis plots (T8+50ms) based on quad-sectioned data volume stratigraphic slices in an embodiment of the present invention.

Fig. 19 a-19 d show development of planar sedimentary facies analysis plots (T8+20ms) based on quad-sectioned data volume stratigraphic slices in an embodiment of the present invention.

FIG. 20 is a schematic diagram of a system for extracting frequency components from a seismic signal according to an embodiment of the present invention.

Fig. 21 shows a specific structural diagram of the screening module 100.

Fig. 22 is a schematic structural diagram of the initial extreme feature point sequence composition module 110 in fig. 21 according to an embodiment of the present invention.

Fig. 23 is a schematic structural diagram of the first-stage down-conversion extreme characteristic point sequence composition module 120 in fig. 4 according to an embodiment of the present invention.

Fig. 24 is a schematic structural diagram of the intermediate frequency component extraction module 200 in fig. 20 according to an embodiment of the present invention.

FIG. 25 is a schematic structural diagram of a seismic signal high frequency component reconstruction system according to an embodiment of the present invention.

Fig. 26 is a schematic structural diagram of the high-frequency component waveform reconstruction module 300 in fig. 25 according to an embodiment of the present invention.

Fig. 27 is a schematic structural diagram illustrating the location interval determination unit 302 in the seismic recording of the high-frequency component in fig. 26 according to the embodiment of the present invention.

Fig. 28 is a schematic structural diagram of the waveform reconstructing unit 304 in fig. 26 according to an embodiment of the present invention.

Fig. 29 is a second schematic structural diagram of the high-frequency component waveform reconstruction module 300 in fig. 25 according to the embodiment of the present invention.

Fig. 30 shows a schematic structural diagram of an electronic device suitable for implementing an embodiment of the present application.

Detailed Description

The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.

The main problems of the existing seismic data multi-scale time-frequency analysis method are as follows: 1) information conversion (inverse transformation) between a time domain and a frequency domain hardly forms a good corresponding and matching relationship; 2) close and corresponding coupling relation between multi-scale time-frequency information and different-level geological unit information in seismic signals cannot be effectively established, so that the multi-level geological unit characteristics and the deposit evolution rule are difficult to be reflected more intuitively, effectively and accurately by a sub-scale time-frequency analysis result.

The present invention will be described in detail with reference to the accompanying drawings.

In a first aspect, the present invention provides a method for extracting frequency components from seismic signals, which is shown in fig. 1, and includes:

and S100, screening primary frequency reduction extreme value characteristic points from the seismic records.

And S200, extracting medium-frequency components in the seismic records based on the position of each primary frequency-reduction extreme characteristic point corresponding to the seismic records.

In some embodiments, as shown in fig. 2, step S100 specifically includes:

s110, screening initial extreme characteristic points from the seismic records and forming an initial extreme characteristic point sequence;

and S120, screening primary frequency reduction extreme characteristic points in the initial extreme characteristic point sequence, and forming a primary frequency reduction extreme characteristic point sequence.

In some embodiments, as shown in fig. 3, step S110 specifically includes:

s111, acquiring sampling points of which the sampling point values are larger than those of adjacent sampling points in the first sampling points; the first sampling point is a sampling point of which the sampling point value in the seismic record is greater than zero;

s112, acquiring sampling points of which the sampling point values are smaller than those of the adjacent sampling points in the second sampling points; the second sampling point is a sampling point of which the sampling point value in the seismic record is less than zero;

and S113, taking the acquired first sampling point and the acquired second sampling point as initial extreme characteristic points, and forming an initial extreme characteristic point sequence by all the initial extreme characteristic points according to the front and back sequence of the positions of the initial extreme characteristic points in the seismic record.

In one embodiment, the seismic record is a uniformly sampled data sequence, denoted x_k(k ═ 1,2,3, … nx), where x is_kThe seismic record sample point value at the sample point k is shown, and nx is the number of the seismic record sample points.

The initial extreme characteristic points of the waveform in step S100 include initial positive extreme characteristic points and initial negative value characteristic points, and the sampling point value x at the kth sampling point in the data sequence of the seismic signal corresponding to the initial positive value characteristic points_kNeed to conform to x_k0 and sample value x at the sample point k-1 adjacent to the sample point_k-1And the sample point value x at the next adjacent sample point k +1_k+1Satisfy x_k-1＜x_k＞x_k+1The relative relationship of (a); sampling point value x at kth sampling point in data sequence of seismic signals corresponding to initial negative value characteristic point_kNeeds to satisfy x_k< 0 and its previous neighboring sample point k-1_k-1And the sample point value x at the next adjacent sample point k +1_k+1Satisfy x_k-1＞x_k＜x_k+1The relative relationship of (a).

Obviously, the first sampling point determined to be yes is the initial positive value feature point, and the second sampling point determined to be yes is the initial negative value feature point. And all the initial extreme characteristic points form an initial extreme characteristic point sequence according to the front and back sequence of the positions of the initial extreme characteristic points in the seismic record. In one embodiment, the initial positive characteristic point is denoted as p_ip(ip ═ 1,2,3, … np), and the initial negative pole value characteristic point is denoted as q_iq(iq — 1,2,3, … nq), np being the number of initial positive-electrode-value feature points satisfying the above condition; nq is the number of initial negative value feature points satisfying the above conditions.

The initial extreme value characteristic point sequence is composed of an initial positive pole value characteristic point sequence p_ip(ip ═ 1,2,3, … np) and the initial negative extremumWithin sequence of characteristic points q_iq(iq-1, 2,3, … nq) and is denoted as pq_ipq(ipq ═ 1,2,3, … npq), where npq ═ np + nq; the sequence is sequentially ordered according to the front and back sequence of the positions of the sampling points in the seismic record where the characteristic points are located.

Further, as shown in fig. 4, step S120 specifically includes:

s121, acquiring points of which the sampling point values are greater than those of adjacent initial extreme value characteristic points in the first initial extreme value characteristic points; the first initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is greater than zero;

s122, acquiring points of which the sampling point values are smaller than those of the adjacent initial extreme value characteristic points in the second initial extreme value characteristic points; the second initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is less than zero;

and S123, taking the obtained first initial extreme value characteristic point and the second initial extreme value characteristic point as primary frequency reduction extreme value characteristic points, and forming a primary frequency reduction extreme value characteristic point sequence by all the primary frequency reduction extreme value characteristic points according to the front and back sequence of the positions of the primary frequency reduction extreme value characteristic points in the seismic record.

The first-order down-conversion extreme value feature points in step S120 include a first-order down-conversion positive value feature point and a first-order down-conversion negative value feature point, and the ip-th initial positive value feature point p in the initial extreme value feature point sequence corresponding to the first-order down-conversion positive value feature point_ipNeed to meet p_ipThe initial feature point p adjacent to the previous (the ip-1 st) one_ip-1And the next (ip +1) th adjacent initial feature point p_ip+1Satisfy p_ip-1＜p_ip＞p_ip+1A relative relationship; the iq-th initial negative pole value characteristic point q in the initial extreme value characteristic point sequence corresponding to the primary frequency-reduction negative pole value characteristic point_iqNeed to meet q_iqInitial feature point q adjacent to its previous (iq-1 st)_iq-1And the next (iq +1) th adjacent initial feature point q_iq+1Satisfy p_ip-1＜p_ip＞p_ip+1Relative relationship.

Obviously, the first initial extreme value feature point determined as yes is the first-level down-conversion positive value feature point, and the second initial extreme value feature point determined as yesThe initial extreme characteristic point is the first-stage frequency-reduction negative characteristic point. And all the first-stage frequency-reduction extreme value characteristic points form a first-stage frequency-reduction extreme value characteristic point sequence according to the front and back sequence of the positions of the first-stage frequency-reduction extreme value characteristic points in the seismic record. In one embodiment, the first order down-conversion positive characteristic point is denoted as pd1_ipd1(ipd1 ═ 1,2,3, … npd1), and the first order down-conversion negative pole value characteristic point is recorded as qd1_iqd1(iqd1 ═ 1,2,3, … nqd1), npd1 is the number of first-order down-conversion positive characteristic points satisfying the above conditions, and nqd1 is the number of first-order down-conversion negative characteristic points satisfying the above conditions.

The first-order down-conversion extreme characteristic point sequence is composed of a first-order down-conversion positive characteristic point sequence pd1_ipd1(ipd1 ═ 1,2,3, … npd1) and first order down-conversion negative eigenvalue sequence qd1_iqd1(iqd1 ═ 1,2,3, … nqd1) and is reported as pqd1_ipqd1(ipqd1 ═ 1,2,3, … npqd1), where npqd1 ═ npd1+ nqd 1; the sequence is sequentially ordered according to the front and back sequence of the positions of the sampling points in the seismic record where the characteristic points are located.

As shown in fig. 5, step S200 specifically includes:

s201, using the position interval of the seismic records corresponding to the two adjacent first-stage frequency reduction extreme value characteristic points as a waveform self-adaptive window, and determining the interval between the positions of the seismic records corresponding to the front end return zero point corresponding to the first initial characteristic point and the rear end return zero point corresponding to the last initial characteristic point in each window as the position interval of the intermediate frequency component;

s202, extracting the waveform in the position interval where the medium frequency component is located, wherein the extracted waveform is the medium frequency component in the seismic record.

Specifically, pqd1 is used as a waveform adaptive window by taking the position interval of the seismic record where the adjacent characteristic points in the first-stage frequency-reduction extreme value characteristic point sequence are located as_ipqd1The (ipqd1 ═ 1,2,3, … npqd1) sequence ipqd1 feature points and the seismic record sample point positions k _ ipqd1 and k _ ipqd1_1 of the next adjacent (ipqd 1+ 1) feature points are used as waveform adaptive windows.

The first initial feature point in the adaptive window is the initial extreme value feature point sequence pq in the waveform adaptive window (k _ ipqd1, k _ ipqd1_1)_jpqd1(jpqd1＝1,2,3, … m), any one of the m primary extremal feature points pq_jpqd1All the positions k _ jpqd1 of the seismic record sampling points meet k _ ipqd1 < k _ jpqd1 < k _ ipqd1_ 1).

Setting the front zero point corresponding to the first initial characteristic point in the adaptive window, namely setting the position of the seismic record sample point where the initial characteristic point is located as k0_ jpqd1, and recording the corresponding seismic record sample point as x_{k0_jpqd1}In seismic recording sequences x_k(k is 1,2,3, … nx) using k0_ jpqd1 as the starting position to search forward for the corresponding waveform zero-returning point x_k0At the front-end waveform return-to-zero point k0, its sample value x_k0With its previous sample value x at k0-1_k0-1Different numbers, i.e. x_k0*x_k0-10 and any sampling point value x in the interval [ k0, k0_ jpqd1) ]_kAnd x_{k0_jpqd1}Same sign, i.e. x_k*x_{k0_jpqd1}＞0。

And (3) setting the position of the seismic recording sample point of the initial characteristic point as k1_ jpqd1 and the corresponding seismic recording sample point as x_{k1_jpqd1}In seismic recording sequences x_k(k1, 2,3, … nx) using k1_ jpqd1 as the starting position to search backward the corresponding waveform zero-returning point x_k1At the back-end waveform zero-return point k1, its sample value x_k1With the sample value x at the next sample point k1+1_k1+1Different numbers, i.e. x_k1*x_k1+10 and interval (k1_ jpqd1, k1)]Value x of any one of the above samples_kAnd x_{k1_jpqd1}Same sign, i.e. x_k*x_{k1_jpqd1}＞0。

Taking the seismic recording waveform between the position of the front end return zero point corresponding to the first initial characteristic point and the position of the rear end return zero point corresponding to the last initial characteristic point in the window as the intermediate frequency component of the seismic signal, namely the interval [ k0, k1 ]]For the window, the seismic waveform x in the window_k(k∈[k0,k1]The intermediate frequency component of the seismic signal within the waveform adaptive window is extracted. And sequentially carrying out the operation on each waveform self-adaptive window of the first-stage frequency reduction extreme value characteristic point sequence to finish the extraction of the intermediate frequency component of the seismic signal.

The description of the embodiment can show that the method for extracting the medium-frequency components of the seismic signals can decompose the original seismic signals according to the distribution rule of extreme characteristic points of the seismic records and the sequence from low frequency to high frequency (second-level frequency reduction → first-level frequency increase → second-level frequency increase), the multi-scale seismic information and the original seismic records have the same waveform property at the corresponding extreme points, the method has strict inheritance and fidelity, the mutual superposition and interference among geological bodies with different scales can be eliminated, and each single-frequency component reflects the response of a geological target body matched with the scale. The medium-frequency components extracted by the method can be used as one of the bases for subsequently developing the work of seismic geological fine interpretation, reservoir characteristics, sedimentary facies prediction and the like, and further, the rationality, reliability and accuracy of seismic geological interpretation results can be comprehensively improved through interactive comparison, constraint and verification among multi-scale seismic data geological interpretation results.

Further, a second aspect of the present invention provides a seismic signal high-frequency component reconstruction method, which is shown in fig. 6, and specifically includes:

And S300, based on the position of the seismic record corresponding to each primary frequency reduction extremum characteristic point, performing waveform reconstruction on high-frequency components in the seismic record.

Wherein, step S100 is completely the same as step S100 in the method for extracting frequency components from seismic signals provided in the first aspect, and this aspect is not repeated.

The following mainly describes S300 in detail. As shown in fig. 7, step S300 specifically includes:

s301, taking the position interval of the corresponding sampling point in the seismic record of the two adjacent frequency reduction extremum characteristic points in the primary frequency reduction extremum characteristic point sequence as a waveform self-adaptive window;

s302, screening the initial extreme characteristic points in each waveform self-adaptive window based on the absolute value of the sampling point value of the initial extreme characteristic point in the waveform self-adaptive window, and determining the position interval of the high-frequency component in the seismic record according to the screened initial extreme characteristic points;

s303, determining and supplementing a plurality of set extreme value feature points based on the first initial extreme value feature point and the last initial extreme value feature point in the position interval of each high-frequency component in the seismic record;

s304, determining a waveform reconstruction interval based on the first initial extreme value characteristic point, the last initial extreme value characteristic point and a plurality of set extreme value characteristic points in the position interval of each high-frequency component in the seismic record, and performing waveform reconstruction on the seismic signal in each waveform reconstruction interval.

Specifically, as shown in fig. 8, step S302 specifically includes:

s302, 302a, sequencing each initial extreme characteristic point in the waveform self-adaptive window at least comprising three initial extreme characteristic points according to the sequence of the absolute value of the sample point value from small to large;

s302b, screening a plurality of initial extreme characteristic points arranged in front of the set position, and sequencing the screened initial extreme characteristic points according to the front and back sequence of the position of the corresponding seismic record;

s302, 302c, determining the interval between the positions of the seismic records corresponding to the first initial extremum characteristic point and the last initial extremum characteristic point in the sequence of the positions of the corresponding seismic records as the position interval of the high-frequency component in the seismic records.

In one embodiment, the initial feature points are filtered within the waveform adaptation window, i.e., the initial extremum feature point sequence pq within the waveform adaptation window (k _ ipqd1, k _ ipqd1_1) is determined_jpqd1(jpqd1 ═ 1,2,3, … m), m is the number of initial characteristic points in the window, when m is larger than 2, the m initial extreme characteristic points are sorted from small to large according to the absolute values of the sample point values, the (m +1)/2 characteristic points with smaller absolute values at the front end of the sorted sequence are screened, and the interval determined by the forefront and the last positions of the seismic records where the (m +1)/2 characteristic points are located is used as the interval where the high-frequency component of the signal is located.

Further, step S303 specifically includes:

uniformly arranging a plurality of set extreme value characteristic points with preset sample point values in a position interval of each high-frequency component in the seismic record according to the interval length; and the preset sample point value and the position of the corresponding set extreme characteristic point in the seismic record have a set corresponding relationship.

In a particular embodiment, the sequence pqu2 of initial extremum feature points in the high frequency component interval is applied_ipqu2(ipqu2 ═ 1,2,3, … npqu2) by supplementing the initial feature points with the ipqu2 feature points pqu2 in the sequence_ipqu2And its next (the ipqu2+ 1) feature point pqu2_{ipqu2_1}Two extreme characteristic points are added in between, and the characteristic point pqu2 is recorded_ipqu2The sampling position of the seismic record is k _ ipqu2, and the characteristic point pqu2 is recorded_{ipqu2_1}The sampling position of the seismic record is k _ ipqu2_1, and two sampling points (namely one third of the total interval and two thirds of the total interval) are uniformly arranged between k _ ipqu2 and k _ ipqu2_1 and respectively correspond to a supplementary sampling point value of 2 x pqu2_{ipqu2_1}/3 and 2 × pqu2_ipqu2Two extreme feature points of/3. In this embodiment, the preset sample value between k _ ipqu2 and k _ ipqu2_1 is 2 × pqu2_{ipqu2_1}/3 and 2 × pqu2_ipqu2/3. The correspondence relationship stated in this embodiment is that a preset sample point value corresponding to a third position between k _ ipqu2 and k _ ipqu2_1, namely k _ ipqu2+ (k _ ipqu2_1-k _ ipqu2)/3, is 2 × pqu2_{ipqu2_1}3, the corresponding preset sample value at two thirds of the position between k _ ipqu2 and k _ ipqu2_1, namely k _ ipqu2_1- (k _ ipqu2_1-k _ ipqu2)/3 is 2 x pqu2_ipqu2And/3, of course, in other embodiments, the present invention is not limited thereto, for example, three, four, etc. supplementary extremum feature points which are limited in number and conform to the common rationale may be supplemented, and the corresponding relationship may also be set or calculated according to the actual situation.

Further, as shown in fig. 9, step S304 specifically includes:

s304a, sequencing the first initial extreme characteristic point, the last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record according to the position sequence of the corresponding seismic record, and determining the interval between the positions of the seismic record corresponding to each two adjacent characteristic points as a waveform reconstruction interval;

s304b, judging whether the sampling point values of the two characteristic points corresponding to each waveform reconstruction interval are different in sign;

s304c, if yes, determining that the corresponding waveform is a single wave, and determining the sampling point position and the sampling point value of the reconstructed sampling point in the waveform reconstruction interval according to a cosine function difference algorithm;

s304d, if the judgment is negative, the corresponding waveform is determined to be a complex wave, the waveform reconstruction interval is equally divided into two subintervals of supplementary sample points according to the length, and the sample point position and the sample point value of the reconstruction sample point are respectively determined in the two subintervals according to a cosine function interpolation algorithm.

Taking the example of supplementing two supplementary extreme characteristic points in the above embodiment as an example, four extreme characteristic points are counted, and the sampling positions of the four extreme characteristic points in the seismic record are as follows:

1)k_ipqu2；2)k_ipqu2+(k_ipqu2_1-k_ipqu2)/3；

3)k_ipqu2_1-(k_ipqu2_1-k_ipqu2)/3；4)k_ipqu2_1。

namely, the waveform reconstruction interval is:

1) k _ ipqu2 to k _ ipqu2+ (k _ ipqu2_1-k _ ipqu 2)/3;

2) k _ ipqu2+ (k _ ipqu2_1-k _ ipqu2)/3 to k _ ipqu2_1- (k _ ipqu2_1-k _ ipqu 2)/3;

3) k _ ipqu2_1- (k _ ipqu2_1-k _ ipqu2)/3 to k _ ipqu2_ 1.

The two-point cosine function interpolation algorithm is that the sample values at two sample points of k0 and k1 are known to be x respectively_k0And x_k1If x_k0And x_k1Opposite sign, i.e. x_k0*x_k1< 0, then for the sample value x at k samples located between k0 and k1_kThe following formula is adopted for interpolation to obtain: x is the number of_k＝x_k0+coe*(x_k1-x_k0) Wherein coe is 0.5+0.5 cos (pi (k1-k)/(k1-k0)), the resulting waveform is a single wave. If x_k0And x_k1Same sign, i.e. x_k0*x_k10, the sample value x is then supplemented at the intermediate position k01 ═ k1, (k0+ k1)/2 between k0 and k1_k01＝0.5*min(x_k0,x_k1) Then, for the sample point value x at the kk sample point between the k0 and k01_kkThe following formula is adopted for interpolation to obtain: x is the number of_kk＝x_k0+coe*(x_k01-x_k0) Wherein coe ═ 0.5+0.5 ═ cos (pi (k01-kk)/(k01-k 0)). For sample point value x at kk sample point between k01 and k1_kkThe following formula is adopted for interpolation to obtain: x is the number of_kk＝x_k01+coe*(x_k1-x_k01) Wherein coe ═ 0.5+0.5 ═ cos (pi (k1-kk)/(k1-k01)), the resulting waveform between points k0 and k1 is a complex wave. Wherein, Coe is the interpolation weight coefficient at various points in the cosine function interpolation formula.

Namely, in the three waveform reconstruction intervals described above, k0 and k1 represent:

1) k0 denotes: the k _ ipqu2 is,

k1 denotes: k _ ipqu2+ (k _ ipqu2_1-k _ ipqu 2)/3.

2) k0 denotes: k _ ipqu2+ (k _ ipqu2_1-k _ ipqu2)/3,

k1 denotes: k _ ipqu2_1- (k _ ipqu2_1-k _ ipqu 2)/3.

3) k0 denotes: k _ ipqu2_1- (k _ ipqu2_1-k _ ipqu2)/3,

k1 denotes: k _ ipqu2_ 1.

Therefore, the calculation is carried out by utilizing a cosine function interpolation algorithm between two points, and the reconstructed high-frequency waveform is further obtained.

Further, in some embodiments, there may be some problem of discontinuity of the reconstructed waveform "fault", and at this time, a relevant compensation is required, please refer to fig. 10, in which step S304 further includes:

s304a-01, performing waveform return-to-zero supplementation on the seismic signals between the first initial characteristic point of each waveform reconstruction interval and the corresponding front end return-to-zero point; and/or

And S304a-02, performing waveform zero-returning compensation on the seismic signals between the last initial characteristic point of each waveform reconstruction interval and the corresponding rear-end zero-returning point.

In a specific implementation, at least one of the step S304a-1 and the step S304a-2 may be implemented as appropriate, for example, when the waveform reconstruction interval is discontinuous after reconstruction, the front end back zero point compensation needs to be performed first to form a continuous waveform, and when the waveform reconstruction interval is discontinuous after reconstruction, the rear end back zero point compensation needs to be performed first to form a continuous waveform.

Referring to fig. 11 to 19d, first, identifying initial positive and negative characteristic points of a seismic recording waveform and forming an initial extreme characteristic point sequence;

FIG. 11 is a schematic diagram showing the initial positive and negative values of the seismic waveform. The curve in the figure is a seismic record waveform; the dots are characteristic points of each initial positive value; the asterisks are characteristic points of each initial negative value. Then, primary frequency-reduction positive and negative value characteristic point sequences are respectively screened from the initial positive and negative value characteristic point sequences to form a primary frequency-reduction extreme value characteristic point sequence.

FIG. 12 is a schematic diagram of a first-order down-conversion extremum feature point sequence screened from an initial extremum feature point sequence. The curve in the figure is a seismic record waveform; the dots are characteristic points of each initial positive value; asterisks indicate characteristic points of each initial negative value; and taking each point identified by the square frame as each stage of frequency reduction extreme value characteristic point obtained by screening. And taking the position interval of the seismic record where the adjacent characteristic points in the first-stage frequency reduction extreme value characteristic point sequence are as a waveform self-adaptive window, and sequentially extracting the seismic record waveform between the position of the front end return zero point corresponding to the first initial characteristic point and the position of the rear end return zero point corresponding to the last initial characteristic point in each window as the intermediate frequency component of the seismic signal.

FIG. 13 is a schematic diagram illustrating the extraction of frequency components in seismic signals within a waveform adaptation window. The curve in the figure is a seismic record waveform; the square point is two adjacent stage down-conversion extreme characteristic points pqd1_ipqd1And pqd1_ipqd1+1The waveform adaptive window is a position interval (k _ ipqd1, k _ ipqd1_1) of the seismic record where the seismic record is located; the asterisks are the characteristic points of each initial extreme value in the waveform self-adaptive window; the circular frame mark is taken as the first initial characteristic point of the sequence, and the circular point is the corresponding front end zero point; the last initial feature point is marked by a diamond frame, and the diamond points are shown as pairsThe back end of the response returns to zero. And (3) extracting the seismic record waveform on the seismic record position interval (marked by two dotted lines) where the two zero points are located as the intermediate frequency component of the seismic signal. And in each waveform self-adaptive window, sequentially screening and supplementing initial characteristic points, and performing high-frequency component waveform reconstruction of the seismic record by utilizing a cosine function interpolation algorithm between two points.

FIG. 14 is a schematic diagram of seismic recording high frequency component waveform reconstruction within a waveform adaptation window. The thinner curve in the figure is the seismic record waveform; the square point is two adjacent stage down-conversion extreme characteristic points pqd1_ipqd1And pqd1_ipqd1+1The waveform adaptive window is a position interval (k _ ipqd1, k _ ipqd1_1) of the seismic record where the seismic record is located; the asterisks are 5 initial extreme characteristic points in a waveform adaptive window, wherein the 3 initial characteristic points with the minimum sample value absolute value are pqu2 in sequence₃、pqu2₄And pqu2₁Then according to the initial feature point pqu2 from the most front end₁And a final initial feature point pqu2₄Determining a seismic signal high-frequency component interval in the position interval of the seismic record, wherein the initial characteristic point sequence in the interval is pqu2_ipqu2(ipqu2 ═ 1,2,3,4) (identified by the circular box); dots p1-p2, p3-p4 and p5-p6 are respectively supplementary extreme characteristic points at corresponding sampling positions between two adjacent characteristic points of the sequence, and signal high-frequency component waveform reconstruction is carried out between the two adjacent characteristic points of the supplemented characteristic point sequence by utilizing a two-point cosine function interpolation algorithm; applying the first characteristic point pqu2 to the front boundary of the high frequency signal₁The waveform return-to-zero supplementation is carried out on the seismic signals between the corresponding seismic record sampling position and the corresponding front end return-to-zero point (marked by a diamond point); using the last feature point pqu2 for the high frequency signal end boundary₄The waveform return-to-zero supplementation is carried out on the seismic signals between the corresponding seismic record sampling position and the corresponding back-end return-to-zero point (marked by a triangular point); the thicker curve in the figure is the waveform of the high-frequency component of the seismic signal after waveform reconstruction in the waveform self-adaptive window.

FIG. 15 is a schematic diagram of a cosine function interpolation algorithm between two points. The curve in the figure is a seismic record waveform; the dots are each initial extreme characteristic point; square shapeThe frame mark is each stage of frequency reduction extreme value characteristic point obtained after screening; x is the number of_k0And x_k1Sampling point values of two adjacent sampling points in the first-stage frequency reduction extremum characteristic point sequence are respectively positioned at k0 and k 1; x is due to_k0And x_k1The same sign, k01 is the middle position of two sample points of k0 and k1, x_k01(identified by diamond points) as sample values supplemented at k01 (if the sample values of the other two adjacent sample points in the first-stage frequency-reduction extremum characteristic point sequence are different in sign, the sample values do not need to be supplemented); the thicker curve in the figure is the first-stage frequency reduction waveform obtained by a cosine function interpolation algorithm between two points.

In the above process, the invention provides a method for extracting and reconstructing high-frequency components in seismic signals based on time domain waveform adaptive window extremum characteristic point screening and waveform reconstruction for the first time, and realizes that complete and continuous four frequency division signals are extracted from original seismic signals according to a sequence of two-stage frequency reduction (low frequency) → one-stage frequency reduction (medium-low frequency) → one-stage frequency increase (medium frequency) → two-stage frequency increase (high frequency) (fig. 16), and response relations between the frequency division seismic signals and different-stage geological target bodies are organically established, so that a more intuitive and reasonable multi-scale seismic data body is provided for reservoir description and reservoir sedimentary facies prediction.

In connection with the specific example, the bilge-Wulya-Taiwang-south depression is a single-break dustpan-like fissured lake basin developed during the middle chalky season, which depression is early in the chalky Alzhen-Tenggel period (K)₁T6-T11 reflection interval) on the eastern gentle slope zone mainly develop many-stage superposed sediments such as lake-facies trigonoceris, slope fans, near-shore underwater fans and lake bottom fans. Fig. 17 shows a seismic data reflection energy attribute slice (T8+20ms reflection layer, corresponding to the top of altan group a four segments) newly acquired and processed in 2016, from which the plane spread characteristics, fan boundary positions, and inner curtain structure characteristics of various fans are difficult to distinguish. The sedimentary facies plane spread characteristics, phase belt relations, inner screen structures and evolution analysis of the Alshan late stage → the terminal stage are developed by using the slices of four frequency division seismic data bodies of secondary frequency reduction (low frequency), primary frequency reduction (medium-low frequency), primary frequency raising (medium frequency), secondary frequency raising (high frequency) and the like in the method. FIGS. 18a to 18b18d and FIGS. 19 a-19 d show the new divided data volume reflected energy attribute slice at k₁ba⁴Upper (late: T8+50ms) and k₁ba⁴The clear course of deplane profile change and vertical dephasing evolution during apical (end: T8+20ms) deposition with signal scale large → small (low frequency → medium-low frequency → medium frequency → high frequency): k is a radical of₁ba⁴In the upper formation stage (advanced Alshan period), four leaves (①②③④) of trigonella are developed on the gentle slope of the east side of the depression groove, the boundary contact relation of ①③④ three leaves is clearly depicted, and the obvious fan stage secondary overlapping development sequence is shown (early ① -middle ③ -late ④), the inside of each leaf is densely developed with gravel and other coarse-medium-large-size fan water channel microphase and fine-medium-small-size water channel microphase, which reflects the deposition background of sufficient supply of the current source and mainly from the south, the southwest and the southeast directions to k₁ba⁴In the stage of top formation (Alshan terminal), the development scale of four leaves of the trigonella and the large-scale fan water channels distributed on the leaves is obviously reduced, the granularity of the conglomerate becomes fine and gradually shrinks towards the south, the supply of the source is obviously reduced in the period, the main development of the leaves is the medium-small fan water channels, but the dense distribution degree is also rapidly reduced, particularly, the ①③ fan and the ② fan die in the local area.

Through the embodiment, it can be determined that the seismic signal high-frequency component reconstruction method provided by the invention can decompose and reconstruct the original seismic signal into a multi-scale, complete and continuous frequency division signal according to the distribution rule of the extreme characteristic points of the seismic record and the sequence from low frequency to high frequency (second-stage frequency reduction → first-stage frequency increase → second-stage frequency increase). The multi-scale seismic information and the original seismic record have the same waveform property at the corresponding extreme point, have strict inheritance and fidelity, can eliminate mutual superposition and interference among geologic bodies with different scales, and each single-frequency component reflects the response of a geologic target body matched with the scale. The invention is applied to the two-dimensional seismic section and the three-dimensional seismic data volume, and the frequency division seismic section and the seismic data volume with a plurality of different scales of the time domain can be directly obtained. The frequency division data can be used for carrying out the works of seismic geological fine interpretation, reservoir characteristics, sedimentary facies prediction and the like. And the reasonability, reliability and accuracy of the seismic geological interpretation result can be comprehensively improved through interactive comparison, constraint and verification among the multi-scale seismic data geological interpretation results.

Based on the same inventive concept as the method provided in the first aspect, a third aspect of the present invention provides a system for extracting frequency components from seismic signals, as shown in fig. 20, specifically including:

and the screening module 100 screens out the first-order frequency reduction extreme value characteristic points from the seismic records.

And the medium-frequency component extraction module 200 is used for extracting medium-frequency components in the seismic records based on the position of each primary frequency-reduction extreme characteristic point corresponding to the seismic record.

As shown in fig. 21, the screening module 100 includes:

an initial extreme characteristic point sequence composition module 110, which screens out initial extreme characteristic points from the seismic records and composes an initial extreme characteristic point sequence;

a first-order frequency-reduction extreme characteristic point sequence composition module 120, which is used for screening first-order frequency-reduction extreme characteristic points in the initial extreme characteristic point sequence and composing a first-order frequency-reduction extreme characteristic point sequence;

based on the same inventive concept, as shown in fig. 22, the initial extreme feature point sequence composing module 110 includes:

a first sampling point judgment unit 111, which obtains a sampling point of the first sampling point whose sampling point value is greater than that of the adjacent sampling point; the first sampling point is a sampling point of which the sampling point value in the seismic record is greater than zero;

a second sampling point determining unit 112, which obtains a sampling point of the second sampling point whose sampling point value is smaller than that of the adjacent sampling point; the second sampling point is a sampling point of which the sampling point value in the seismic record is less than zero;

the initial extreme value feature point sequence forming unit 113 uses the acquired first sampling point and second sampling point as initial extreme value feature points, and forms an initial extreme value feature point sequence by using all the initial extreme value feature points according to the sequence of the positions in the seismic record.

For the same reason, as shown in fig. 23, the first-stage down-conversion extremum feature point sequence forming module 120 includes:

a first initial extreme value feature point determining unit 121, configured to obtain a point, of the first initial extreme value feature points, where a sample point value is greater than that of an adjacent initial extreme value feature point; the first initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is greater than zero;

the second initial extreme value feature point determining unit 122 obtains a point of the second initial extreme value feature points, where the sampling point value is smaller than that of the adjacent initial extreme value feature point; the second initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is less than zero;

the first-order frequency-reduction extreme characteristic point sequence forming unit 123 uses the acquired first initial extreme characteristic point and the acquired second initial extreme characteristic point as first-order frequency-reduction extreme characteristic points, and forms a first-order frequency-reduction extreme characteristic point sequence by using all the first-order frequency-reduction extreme characteristic points according to the sequence of the positions of the first-order frequency-reduction extreme characteristic points in the seismic record.

As shown in fig. 24, for the same reason, the intermediate frequency component extraction module 200 includes:

the waveform determining unit 201 determines, as waveform adaptive windows, the position intervals of the seismic records corresponding to the two adjacent first-stage down-conversion extremum characteristic points, and determines, as position intervals of the intermediate frequency component, the interval between the positions of the seismic records corresponding to the front end return zero point corresponding to the first initial characteristic point and the rear end return zero point corresponding to the last initial characteristic point in each window;

the medium frequency component extracting unit 202 extracts a waveform in a position interval where the medium frequency component is located, where the extracted waveform is the medium frequency component in the seismic record.

The description of the embodiment can show that the system for extracting the medium-frequency components of the seismic signals can decompose the original seismic signals according to the distribution rule of extreme value characteristic points of the seismic records and the sequence from low frequency to high frequency (secondary frequency reduction → primary frequency increase → secondary frequency increase), the multi-scale seismic information and the original seismic records have the same waveform property at the corresponding extreme value points, the system has strict inheritance and fidelity, the mutual superposition and interference among geological bodies with different scales can be eliminated, and each single-frequency component reflects the response of a geological target body matched with the scale. The medium-frequency components extracted by the method can be used as one of the bases for subsequently developing the work of seismic geological fine interpretation, reservoir characteristics, sedimentary facies prediction and the like, and further, the rationality, reliability and accuracy of seismic geological interpretation results can be comprehensively improved through interactive comparison, constraint and verification among multi-scale seismic data geological interpretation results.

Further, based on the same inventive concept as the seismic signal high frequency component reconstruction method provided by the embodiment of the second aspect, a fourth aspect of the present invention provides a seismic signal high frequency component reconstruction system, specifically as shown in fig. 25, including:

And the high-frequency component waveform reconstruction module 300 is used for reconstructing the waveform of the high-frequency component in the seismic record based on the position of each primary frequency-reduction extreme characteristic point corresponding to the seismic record.

Wherein the screening module 100 includes:

for the same reason, as shown in fig. 26, the high frequency component waveform reconstruction module 300 includes:

a waveform adaptive window determining unit 301, configured to use a position interval, corresponding to a sampling point in the seismic record, of two adjacent down-conversion extremum feature points in the first-stage down-conversion extremum feature point sequence as a waveform adaptive window;

a location interval determination unit 302 for determining a location interval of the high-frequency component in the seismic record, which selects the initial extremum feature points in each waveform adaptive window based on the absolute values of the sampling point values of the initial extremum feature points in the waveform adaptive window, and determines the location interval of the high-frequency component in the seismic record according to the selected initial extremum feature points;

a set extreme feature point determining unit 303 configured to determine and supplement a plurality of set extreme feature points based on a first initial extreme feature point and a last initial extreme feature point in a position interval of each high-frequency component in the seismic record;

the waveform reconstruction unit 304 determines a waveform reconstruction interval based on the first initial extreme characteristic point, the last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record, and performs waveform reconstruction on the seismic signal in each waveform reconstruction interval.

For the same reason, as shown in fig. 27, the location section determination unit 302 for determining the location section of the high-frequency component in the seismic record includes:

a sorting unit 302a according to the absolute value of the sample point value, sorting each initial extremum feature point in a waveform adaptive window at least comprising three initial extremum feature points according to the sequence from small to large according to the absolute value of the sample point value;

according to the position forward-backward sorting unit 302b of the seismic records, screening a plurality of initial extreme value feature points arranged in front of the set position, and sorting the screened initial extreme value feature points according to the position forward-backward sequence of the corresponding seismic records;

the high-frequency component position interval determining unit 302c determines an interval between the positions of the seismic records corresponding to the first initial extremum feature point and the last initial extremum feature point in the sequence of the positions of the corresponding seismic records as a position interval of the high-frequency component in the seismic records.

Based on the same reason, the set extreme characteristic point determining unit uniformly sets a plurality of set extreme characteristic points with preset sample values in the position interval of each high-frequency component in the seismic record according to the interval length; and the preset sample point value and the position of the corresponding set extreme characteristic point in the seismic record have a set corresponding relationship.

For the same reason, as shown in fig. 28, the waveform reconstructing unit 304 includes:

the waveform reconstruction interval determining unit 304a sequences the first initial extreme characteristic point, the last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record according to the position sequence of the corresponding seismic record, and determines the interval between the positions of the seismic record corresponding to each two adjacent characteristic points as a waveform reconstruction interval;

a waveform reconstruction interval corresponding feature point determination unit 304b that determines whether the sample point values of two feature points corresponding to each waveform reconstruction interval are different in sign;

if the single-wave reconstruction unit 304c determines that the corresponding waveform is a single wave, and determines the sampling point position and the sampling point value of the reconstructed sampling point in the waveform reconstruction interval according to a cosine function difference algorithm;

if not, the complex wave reconstruction unit 304d determines that the corresponding waveform is a complex wave, sets a complementary sample point which equally divides the waveform reconstruction interval into two subintervals according to the length, and determines the sample point position and the sample point value of the reconstruction sample point in the two subintervals according to a cosine function interpolation algorithm.

Preferably, for the same reason, as shown in fig. 29, the high frequency component waveform reconstruction module 300 further includes:

a front-end waveform return-to-zero complementing unit 305 for performing waveform return-to-zero complementing on the seismic signal between the first initial characteristic point of each waveform reconstruction interval and the corresponding front-end return-to-zero point; and/or

And the back-end waveform zero-returning supplementary unit 306 is used for performing waveform zero-returning supplementary on the seismic signals between the last initial characteristic point of each waveform reconstruction interval and the corresponding back-end zero-returning point.

The systems, devices, modules or units illustrated in the above embodiments may be implemented by a computer chip or an entity, or by a product with certain functions. A typical implementation device is an electronic device, which may be, for example, a personal computer, a laptop computer, a tablet computer, a wearable device, or a combination of any of these devices.

In a typical example, the electronic device specifically comprises a memory, a processor and a computer program stored on the memory and executable on the processor, the processor implementing the method performed by the client as described above when executing the program, or the processor implementing the method performed by the server as described above when executing the program.

Referring now to FIG. 30, shown is a schematic diagram of an electronic device 600 suitable for use in implementing embodiments of the present application.

As shown in fig. 30, the electronic apparatus 600 includes a Central Processing Unit (CPU)601 that can perform various appropriate works and processes according to a program stored in a Read Only Memory (ROM)602 or a program loaded from a storage section 608 into a Random Access Memory (RAM)) 603. In the RAM603, various programs and data necessary for the operation of the system 600 are also stored. The CPU601, ROM602, and RAM603 are connected to each other via a bus 604. An input/output (I/O) interface 605 is also connected to bus 604.

The following components are connected to the I/O interface 605: an input portion 606 including a keyboard, a mouse, and the like; an output portion 607 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 608 including a hard disk and the like; and a communication section 609 including a network interface card such as a LAN card, a modem, or the like. The communication section 609 performs communication processing via a network such as the internet. The driver 610 is also connected to the I/O interface 606 as needed. A removable medium 611 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 610 as necessary, so that a computer program read out therefrom is mounted as necessary on the storage section 608.

In particular, according to an embodiment of the present invention, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the invention include a computer program product comprising a computer program tangibly embodied on a machine-readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 609, and/or installed from the removable medium 611.

The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the hardware + program class embodiment, since it is substantially similar to the method embodiment, the description is simple, and the relevant points can be referred to the partial description of the method embodiment. Although embodiments of the present description provide method steps as described in embodiments or flowcharts, more or fewer steps may be included based on conventional or non-inventive means. The order of steps recited in the embodiments is merely one manner of performing the steps in a multitude of orders and does not represent the only order of execution. When an actual apparatus or end product executes, it may execute sequentially or in parallel (e.g., parallel processors or multi-threaded environments, or even distributed data processing environments) according to the method shown in the embodiment or the figures. The terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, the presence of additional identical or equivalent elements in a process, method, article, or apparatus that comprises the recited elements is not excluded. For convenience of description, the above devices are described as being divided into various modules by functions, and are described separately. Of course, in implementing the embodiments of the present description, the functions of each module may be implemented in one or more software and/or hardware, or a module implementing the same function may be implemented by a combination of multiple sub-modules or sub-units, and the like. The above-described embodiments of the apparatus are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form. The present invention is described with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of the invention. It will be understood that each flow and/or block of the flow diagrams and/or block diagrams, and combinations of flows and/or blocks in the flow diagrams and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks. As will be appreciated by one skilled in the art, embodiments of the present description may be provided as a method, system, or computer program product. Accordingly, embodiments of the present description may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects. Furthermore, embodiments of the present description may take the form of a computer program product embodied on one or more computer-usable storage media (including, but not limited to, disk storage, CD-ROM, optical storage, and so forth) having computer-usable program code embodied therein. The embodiments in the present specification are described in a progressive manner, and the same and similar parts among the embodiments are referred to each other, and each embodiment focuses on the differences from the other embodiments. In particular, for the system embodiment, since it is substantially similar to the method embodiment, the description is simple, and for the relevant points, reference may be made to the partial description of the method embodiment. In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of an embodiment of the specification. In this specification, the schematic representations of the terms used above are not necessarily intended to refer to the same embodiment or example. Furthermore, various embodiments or examples and features of different embodiments or examples described in this specification can be combined and combined by one skilled in the art without contradiction. The above description is only an example of the embodiments of the present disclosure, and is not intended to limit the embodiments of the present disclosure. Various modifications and variations to the embodiments described herein will be apparent to those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the embodiments of the present specification should be included in the scope of the claims of the embodiments of the present specification.

Claims

1. A method for extracting frequency components in seismic signals is characterized by comprising the following steps:

screening primary frequency reduction extreme value characteristic points from the seismic records;

and extracting medium-frequency components in the seismic records based on the position of each primary frequency reduction extremum characteristic point corresponding to the seismic records.

2. The extraction method according to claim 1, wherein the step of screening the first-order downconversion extremum feature points from the seismic records comprises:

screening initial extreme value characteristic points from the seismic records and forming an initial extreme value characteristic point sequence;

and screening primary frequency reduction extreme characteristic points in the initial extreme characteristic point sequence, and forming a primary frequency reduction extreme characteristic point sequence.

3. The extraction method according to claim 2, wherein the step of screening initial extreme feature points from the seismic records and forming an initial extreme feature point sequence comprises:

acquiring sampling points of which the sampling point values are larger than those of adjacent sampling points in the first sampling points; the first sampling point is a sampling point of which the sampling point value in the seismic record is greater than zero;

acquiring sampling points of which the sampling point values are smaller than those of adjacent sampling points in the second sampling points; the second sampling point is a sampling point of which the sampling point value in the seismic record is less than zero;

and taking the obtained first sampling point and the second sampling point as initial extreme characteristic points, and forming an initial extreme characteristic point sequence by all the initial extreme characteristic points according to the front and back sequence of the positions of the initial extreme characteristic points in the seismic record.

4. The method of claim 2, wherein the step of filtering the first-order down-conversion extremum feature points from the initial extremum feature point sequence and forming a first-order down-conversion extremum feature point sequence comprises:

acquiring points of which the sampling point values are larger than the adjacent initial extreme value characteristic points in the first initial extreme value characteristic points; the first initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is greater than zero;

obtaining points of which the sampling point values are smaller than the adjacent initial extreme value characteristic points in the second initial extreme value characteristic points; the second initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is less than zero;

and taking the obtained first initial extreme value characteristic point and the second initial extreme value characteristic point as primary frequency reduction extreme value characteristic points, and forming a primary frequency reduction extreme value characteristic point sequence by all the primary frequency reduction extreme value characteristic points according to the front and back sequence of the positions of the primary frequency reduction extreme value characteristic points in the seismic record.

5. The extraction method according to claim 1, wherein the extracting the medium frequency component from the seismic record based on each one-level down-conversion extremum characteristic point corresponding to the position of the seismic record comprises:

taking the position interval of the two adjacent primary frequency reduction extreme value characteristic points corresponding to the seismic records as a waveform self-adaptive window, and determining the interval between the positions of the front end return zero point corresponding to the first initial characteristic point and the rear end return zero point corresponding to the last initial characteristic point in each window, which correspond to the seismic records, as the position interval of the intermediate frequency component;

and extracting the waveform in the position interval where the medium-frequency component is located, wherein the extracted waveform is the medium-frequency component in the seismic record.

6. A seismic signal high frequency component reconstruction method, comprising:

and performing waveform reconstruction on high-frequency components in the seismic records based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

7. The method of claim 6, wherein the screening of first order downconversion extremum feature points from the seismic records comprises:

8. The reconstruction method according to claim 7, wherein the step of screening the initial extreme feature points from the seismic records and forming the initial extreme feature point sequence comprises:

9. The reconstruction method according to claim 7, wherein the first-order down-conversion extreme feature points screened from the initial extreme feature point sequence and forming a first-order down-conversion extreme feature point sequence comprises:

10. The reconstruction method according to claim 6, wherein the waveform reconstructing the high frequency component in the seismic record based on the position of the seismic record corresponding to each first-order down-conversion extremum characteristic point comprises:

taking the position interval of the two adjacent frequency reduction extremum characteristic points in the primary frequency reduction extremum characteristic point sequence corresponding to the sampling points in the seismic record as a waveform self-adaptive window;

screening the initial extreme value characteristic points in each waveform self-adaptive window based on the absolute value of the sampling point value of the initial extreme value characteristic points in each waveform self-adaptive window, and determining the position interval of the high-frequency component in the seismic record according to the screened initial extreme value characteristic points;

determining and supplementing a plurality of set extreme value feature points based on a first initial extreme value feature point and a last initial extreme value feature point in a position interval of each high-frequency component in the seismic record;

and determining a waveform reconstruction interval based on the first initial extreme characteristic point, the last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record, and performing waveform reconstruction on the seismic signal in each waveform reconstruction interval.

11. The reconstruction method according to claim 10, wherein the step of screening the initial extremum feature points in each waveform adaptive window based on the absolute value of the sampling point values of the initial extremum feature points in the waveform adaptive window and determining the location interval of the high frequency component in the seismic record according to the screened initial extremum feature points comprises:

sequencing each initial extreme characteristic point in a waveform self-adaptive window at least comprising three initial extreme characteristic points according to the sequence of the absolute values of sample point values from small to large;

screening a plurality of initial extreme value characteristic points arranged in front of a set position, and sequencing the screened initial extreme value characteristic points according to the front and back sequence of the positions of the corresponding seismic records;

and determining the interval between the positions of the seismic records corresponding to the first initial extreme characteristic point and the last initial extreme characteristic point in the sequence of the positions of the corresponding seismic records as the position interval of the high-frequency component in the seismic records.

12. The reconstruction method according to claim 10, wherein the determining of the supplementary sets of extreme characteristic points based on the first initial extreme characteristic point and the last initial extreme characteristic point in the location interval of each high frequency component in the seismic records comprises:

13. The reconstruction method according to claim 10, wherein the determining waveform reconstruction intervals based on the first initial extreme feature point, the last initial extreme feature point and a plurality of set extreme feature points in the position interval of each high frequency component in the seismic record, and performing waveform reconstruction on the seismic signal in each waveform reconstruction interval comprises:

sequencing a first initial extreme value characteristic point, a last initial extreme value characteristic point and a plurality of set extreme value characteristic points in the position interval of each high-frequency component in the seismic record according to the position sequence of the corresponding seismic record, and determining the interval between the positions of the seismic record corresponding to each two adjacent characteristic points as a waveform reconstruction interval;

judging whether the sampling point values of the two characteristic points corresponding to each waveform reconstruction interval are different in sign;

if so, determining the sampling point position and the sampling point value of the reconstructed sampling point in the waveform reconstruction interval according to a cosine function difference algorithm;

if not, setting supplementary sample points which equally divide the waveform reconstruction interval into two subintervals according to the length, and respectively determining the sample point position and the sample point value of the reconstruction sample point in the two subintervals according to a cosine function interpolation algorithm.

14. The reconstruction method according to claim 10, wherein the waveform reconstructing the high frequency component in the seismic record based on the location of the seismic record corresponding to each first-order down-conversion extremum characteristic point, further comprises:

performing waveform return-to-zero supplementation on the seismic signals between the first initial characteristic point of each waveform reconstruction interval and the corresponding front end return-to-zero point; and/or

And performing waveform return-to-zero supplementation on the seismic signals between the last initial characteristic point of each waveform reconstruction interval and the corresponding back-end return-to-zero point.

15. A seismic signal intermediate frequency component extraction system, comprising:

the screening module screens out primary frequency reduction extreme value characteristic points from the seismic records;

and the medium-frequency component extraction module is used for extracting medium-frequency components in the seismic record based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

16. The extraction system according to claim 15, wherein the screening module comprises:

the initial extreme value characteristic point sequence composition module is used for screening initial extreme value characteristic points from the seismic records and forming an initial extreme value characteristic point sequence;

and the primary frequency reduction extreme value characteristic point sequence forming module is used for screening primary frequency reduction extreme value characteristic points in the initial extreme value characteristic point sequence and forming a primary frequency reduction extreme value characteristic point sequence.

17. The extraction system according to claim 16, wherein the initial extreme feature point sequence composition module comprises:

the first sampling point judging unit is used for acquiring sampling points of which the sampling point values are larger than those of adjacent sampling points in the first sampling points; the first sampling point is a sampling point of which the sampling point value in the seismic record is greater than zero;

the second sampling point judging unit is used for acquiring sampling points of which the sampling point values are smaller than those of the adjacent sampling points in the second sampling points; the second sampling point is a sampling point of which the sampling point value in the seismic record is less than zero;

and the initial extreme value characteristic point sequence forming unit is used for forming an initial extreme value characteristic point sequence by taking the acquired first sampling point and the acquired second sampling point as initial extreme value characteristic points and forming all the initial extreme value characteristic points according to the front and back sequence of the positions of the initial extreme value characteristic points in the seismic record.

18. The extraction system according to claim 16, wherein the first-order down-conversion extreme feature point sequence composing module comprises:

the first initial extreme value characteristic point judging unit is used for acquiring points, of which the sampling point values are greater than those of adjacent initial extreme value characteristic points, in the first initial extreme value characteristic points; the first initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is greater than zero;

the second initial extreme value characteristic point judgment unit acquires points, of which the sampling point values are smaller than those of adjacent initial extreme value characteristic points, in the second initial extreme value characteristic points; the second initial extreme characteristic point is a point of which the sampling point value in the initial extreme characteristic point sequence is less than zero;

and the first-stage frequency reduction extreme value characteristic point sequence forming unit is used for forming a first-stage frequency reduction extreme value characteristic point sequence by taking the acquired first initial extreme value characteristic point and the acquired second initial extreme value characteristic point as first-stage frequency reduction extreme value characteristic points and forming the first-stage frequency reduction extreme value characteristic point sequence by all the first-stage frequency reduction extreme value characteristic points according to the front and back sequence of the positions of the first-stage frequency reduction extreme value characteristic points in the seismic record.

19. The extraction system according to claim 15, wherein the intermediate frequency component extraction module includes:

the waveform determining unit is used for taking the position intervals of the seismic records corresponding to the two adjacent first-stage frequency reduction extreme value characteristic points as waveform self-adaptive windows, and determining the interval between the positions of the seismic records corresponding to the front end return zero point corresponding to the first initial characteristic point and the rear end return zero point corresponding to the last initial characteristic point in each window as the position interval of the intermediate frequency component;

and the medium-frequency component extraction unit is used for extracting the waveform in the position interval where the medium-frequency component is located, wherein the extracted waveform is the medium-frequency component in the seismic record.

20. A system for reconstructing high frequency components of a seismic signal, comprising:

and the high-frequency component waveform reconstruction module is used for reconstructing the waveform of the high-frequency component in the seismic record based on the position of each primary frequency reduction extreme value characteristic point corresponding to the seismic record.

21. The reconstruction system of claim 20 wherein the filtering module comprises:

22. The reconstruction system of claim 21, wherein the initial extreme feature point sequence composition module comprises:

23. The reconstruction system of claim 21, wherein the first-order down-conversion extreme feature point sequence composition module comprises:

24. The reconstruction system of claim 21, wherein the high frequency component waveform reconstruction module comprises:

the waveform self-adaptive window determining unit is used for taking a position interval of the corresponding sampling point in the seismic record of the two adjacent frequency reduction extremum characteristic points in the primary frequency reduction extremum characteristic point sequence as a waveform self-adaptive window;

the device comprises a position interval determining unit for the high-frequency component in the seismic record, a sampling point value calculating unit and a sampling point value calculating unit, wherein the position interval determining unit is used for screening initial extreme value characteristic points in each waveform self-adaptive window based on the absolute value of the sampling point value of the initial extreme value characteristic point in each waveform self-adaptive window and determining the position interval of the high-frequency component in the seismic record according to the screened initial extreme value characteristic points;

a set extreme characteristic point determining unit which determines and supplements a plurality of set extreme characteristic points based on a first initial extreme characteristic point and a last initial extreme characteristic point in a position interval of each high-frequency component in the seismic record;

and the waveform reconstruction unit determines a waveform reconstruction interval based on the first initial extreme characteristic point, the last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record, and performs waveform reconstruction on the seismic signal in each waveform reconstruction interval.

25. The reconstruction system according to claim 24, wherein the location interval determination unit of the high frequency component in the seismic recording includes:

the sorting unit sorts each initial extreme characteristic point in the waveform self-adaptive window at least comprising three initial extreme characteristic points according to the absolute value of the sample point from small to large;

screening a plurality of initial extreme value characteristic points arranged in front of a set position according to a position front-back ordering unit of the seismic record, and ordering the screened initial extreme value characteristic points according to the position front-back order of the corresponding seismic record;

and the high-frequency component position interval determining unit is used for determining an interval between the positions of the seismic records corresponding to the first initial extreme characteristic point and the last initial extreme characteristic point in the sequence of the positions of the corresponding seismic records as the position interval of the high-frequency component in the seismic records.

26. The reconstruction system according to claim 24, wherein the set extremum feature point determining unit uniformly sets a plurality of set extremum feature points having preset sample values in a position interval of each high frequency component in the seismic record according to an interval length; and the preset sample point value and the position of the corresponding set extreme characteristic point in the seismic record have a set corresponding relationship.

27. The reconstruction system according to claim 24, wherein the waveform reconstruction unit includes:

the waveform reconstruction interval determining unit is used for sequencing a first initial extreme characteristic point, a last initial extreme characteristic point and a plurality of set extreme characteristic points in the position interval of each high-frequency component in the seismic record according to the position sequence of the corresponding seismic record, and determining the interval between the positions of the two adjacent characteristic points corresponding to the seismic record as a waveform reconstruction interval;

the waveform reconstruction interval corresponding characteristic point judging unit judges whether the sampling point values of two characteristic points corresponding to each waveform reconstruction interval are different in sign;

if the single-wave reconstruction unit judges that the waveform reconstruction interval is positive, determining the sampling point position and the sampling point value of a reconstructed sampling point in the waveform reconstruction interval according to a cosine function difference algorithm;

and if not, the complex wave reconstruction unit equally divides the waveform reconstruction interval into two subintervals according to the length, and determines the sampling point position and the sampling point value of the reconstruction sampling point in the two subintervals according to a cosine function interpolation algorithm.

28. The reconstruction system of claim 24, wherein the high frequency component waveform reconstruction module further comprises:

the front-end waveform return-to-zero supplementing unit is used for performing waveform return-to-zero supplementation on the seismic signals between the first initial characteristic point of each waveform reconstruction interval and the corresponding front-end return-to-zero point; and/or

And the rear-end waveform return-to-zero supplementing unit is used for performing waveform return-to-zero supplementation on the seismic signals between the last initial characteristic point of each waveform reconstruction interval and the corresponding rear-end return-to-zero point.

29. An electronic device comprising a memory, a processor and a computer program stored on the memory and executable on the processor, wherein the processor when executing the program implements the steps of the method of extracting frequency components in seismic signals according to any one of claims 1 to 5; alternatively, the processor implements the seismic signal high frequency component reconstruction method according to any one of claims 6 to 14 when executing the program.

30. A computer-readable storage medium on which a computer program is stored, the computer program, when being executed by a processor, implementing the steps of the method for extracting frequency components in seismic signals according to any one of claims 1 to 5; alternatively, the computer program when executed by a processor implements the seismic signal high frequency component reconstruction method of any of claims 6 to 14.