CN102243319B - Method and device for detecting underground discontinuous body - Google Patents

Abstract

An embodiment of the present invention provides a method and device for detecting an underground discontinuity. The method includes: acquiring seismic data; selecting the size of the calculation time window according to the geological structure corresponding to the seismic data; selecting a time length longer than the calculation time window the time range; use the coherent algorithm, the pre-selected calculation time window and the pre-selected time range to obtain the curvature of each data point to be measured in the seismic data; obtain the entire seismic data according to the curvature of each data point to be measured The volume curvature of the whole seismic data is used to detect underground fractures and faults. In this method, the calculation process of body curvature is direct, the error is small, and the efficiency is high, which can greatly improve the recognition ability of discontinuities.

Description

A kind of detection method of underground discontinuum and device

Technical field

The present invention relates to the seismic exploration technique field, be specifically related to a kind of detection method and device of underground discontinuum, be particularly related to the new method of the multiple dimensioned seismic volume curvature of a kind of calculating in seismic data interpretation attribute, new multiple dimensioned earthquake curvature attribute can be applied in the oil exploration and development fields, identifies fracture and the crack of different brackets.

Background technology

Earthquake curvature attribute and subterranean fracture etc. are in close relations.At present, earthquake curvature computing method commonly used have two kinds: a kind of curvature of face computing method that are based on layer bit data; Another kind is to calculate first reflection inclination angle, stratum and orientation, asks for the computing method of body curvature by coordinate transform again.

The curvature of face computing method based on layer bit data of prior art at first are described.In order to calculate curvature more specific on the curved surface, need the quadric surface of a part of match, in Fig. 1, eight points adjacent with it with current point (z5) come quadric surface of match in least squares sense.Adopt 3 * 3 grid methods, this local secondary curve surface definition is as follows:

z＝ax ²+by ²+cxy+dx+ey+f， (1)

Wherein

$a=\frac{1}{2}\frac{{\∂}^2}{\∂x}\frac{z}{2}=\frac{z1+z3+z4+z6+z7+z9}{6\mathrm{\Δ}{x}^2}-\frac{z2+z5+z8}{3\mathrm{\Δ}{x}^2},---\left(2\right)$

$b=\frac{1}{2}\frac{{\&PartialD;}^{2}z}{{\&PartialD;\mathrm{<figure-callout\; id="2"\; label="y"\; filenames="HSA00000123211900041.png"\; state="\{\{state\}\}">y</figure-callout>}}^2}=\frac{z1+z2+z3+z7+z8+z9}{6\mathrm{\&Delta;}{y}^2}-\frac{z4+z5+z6}{3\mathrm{\&Delta;}{\mathrm{<figure-callout\; id="2"\; label="y"\; filenames="HSA00000123211900041.png"\; state="\{\{state\}\}">y</figure-callout>}}^2},---\left(3\right)$

$c=\frac{1}{2}\frac{{\&PartialD;}^{2}z}{\&PartialD;x\&PartialD;y}=\frac{z3+z7-z1-z9}{4\mathrm{\&Delta;x\&Delta;y}},---\left(4\right)$

$d=\frac{1}{2}\frac{\&PartialD;z}{\&PartialD;x}=\frac{z3+z6+z9-z1-z4-z7}{6\mathrm{\&Delta;x}},---\left(5\right)$

$e=\frac{1}{2}\frac{\&PartialD;z}{\&PartialD;y}=\frac{\mathrm{<figure-callout\; id="1"\; label="z"\; filenames="HSA00000123211900031.png,HSA00000123211900041.png"\; state="\{\{state\}\}">z</figure-callout>}1+\mathrm{<figure-callout\; id="2"\; label="z"\; filenames="HSA00000123211900041.png"\; state="\{\{state\}\}">z</figure-callout>}2+z3-z7-z8-z9}{6\mathrm{\&Delta;y}},---\left(6\right)$

$f=\frac{2(z2+z4+z6+z8)-(z1+z3+z7+z9)+5z5}{9},---\left(7\right)$

Maximum positive curvature computing formula is

K _pos＝(a+b)+[(a-b) ²+c ²] ^1/2. (8)

Wherein, z1 to z9 be curved surface in the value (as shown in Figure 1) at grid node place, Δ x and Δ y are the x direction of grid node and the interval on the y direction, by the coefficient a in the equation (1), b, c, d, e, f can calculate the curvature of current sampling point.Also can adopt large grid node, for example 5 * 5, but this needs the larger system of equations of solution, needs more calculated amount.Grid cell is fewer, and the calculating of curvature is faster, and the local feature of the curvature that obtains is more obvious.Above-mentioned curvature of face computing method those skilled in the art can be with reference to such as Publication about Document: Robert A.Curvature attributes and their application to 3D interpreted horizons.First Break, 2001,19 (2): 85～100.

The computing method of body curvature of the prior art below are described.Al-Dossary and Marfurt (2006) propose computing method (the Al-Dossary S.and Marfurt K.J.3D volumetricmultispectral estimates of reflector curvature and rotation.Geophysics of body curvature, 2006,71 (5): 41～51), this method is calculated first inclination angle, reflection horizon and bearing data, obtains body curvature through rotation of coordinate with different differentiate formula again.The method specifically comprises:

Suppose to have the inclination data body:

$u(z,x,y)=p(z,x,y)\hat{X}+q(z,x,y)\hat{Y},---\left(9\right)$

Wherein p and q are the components at inclination angle, With

Be the vector of unit length in the Cartesian coordinate system, Al-Dossary and Marfurt are decomposed into two parts with it from mathematics

$\mathrm{div}\left(u\right)=\&PartialD;p/\&PartialD;x+\&PartialD;q/\&PartialD;y,---\left(10\right)$

With

$r_z=\&PartialD;p/\&PartialD;y-\&PartialD;q/\&PartialD;x,---\left(11\right)$

Use reflection inclination data p and the q of input, at the x=y=0 place, the coefficient in the equation (1) becomes:

D _x(D _xz)＝2a＝D _xp， (12)

D _y(D _yz)＝2b＝D _yq， (13)

D _xq+D _yp＝2c， (14)

Wherein, operator D _xAnd D _yCan be equation (15), differentiate formula arbitrarily in (16) and (18).By selecting coordinate system, obtain the coefficient in the equation (1), calculate body curvature.

Adoptable differentiate formula is as follows:

$\frac{\mathrm{du}\left(x\right)}{\mathrm{dx}}=\frac{\frac{2}{3}u(x+h)-\frac{2}{3}u(x-h)-\frac{1}{12}u(x+2h)+\frac{1}{12}u(x-2h)}{h},---\left(15\right)$

$D23=\frac{1}{2\mathrm{\&mu;}}[F(-x)-F\left(x\right)],---\left(16\right)$

Wherein F (x) is:

$\frac{F\left(x\right)}{A}=\cos \mathrm{\&phi;exp}(-\frac{\mathrm{\&alpha;x}}{\mathrm{\&eta;\&mu;}})-\cos (\frac{\mathrm{\&gamma;x}}{\mathrm{\&eta;\&mu;}}+\mathrm{\&phi;})\exp (-\frac{\mathrm{\&beta;x}}{\mathrm{\&eta;\&mu;}})+\frac{\mathrm{\&eta;}}{\mathrm{\&alpha;}}C\left(\mathrm{\&phi;}\right)\sin \left(\frac{x}{\mathrm{\&mu;}}\right)\exp (-\frac{x}{\mathrm{\&mu;}}).---\left(17\right)$

$F(\&PartialD;u/\&PartialD;x)=-i{k}_{x}F\left[u\left(x\right)\right].---\left(18\right)$

The inventor finds in realizing process of the present invention, and prior art has the following disadvantages at least:

For the curvature of face computing method of prior art one, need to before carrying out curvature calculating, know first layer position (curved surface) data, the precision of this method easily is subject to the impact of the picking errors in the interpretation process of layer position.

Body curvature computing method for prior art two, the body Curvature Methods that Al-Dossary and Marfurt propose is too complicated: at first need to calculate the inclination data body, then utilize the inclination data body to obtain coefficient in the equation (1) by differentiate, after again coordinate system suitably being rotated, just obtain at last body curvature.But not a direct method for Scale Decomposition.

To sum up, adopt these two kinds of computing method to identify the precision of the discontinuums such as subterranean fracture lower.

Summary of the invention

The purpose of the embodiment of the invention is, a kind of detection method and device of underground discontinuum is provided, to improve recognition capability and the detection efficiency to underground discontinuum.

On the one hand, the embodiment of the invention provides a kind of detection method of underground discontinuum, and described method comprises: obtain geological data; The tectonic structure corresponding according to described geological data chosen the size of computation window; Access time, length was greater than the time range of described computation window; The computation window of utilize coherent algorithm, choosing in advance reaches the time range of choosing in advance, obtains the curvature of each testing data point in the described geological data; According to the curvature of each testing data point, obtain the body curvature of whole geological data; Body curvature according to described whole geological data detects underground crack and tomography.

On the other hand, the embodiment of the invention provides a kind of pick-up unit of underground discontinuum, and described device comprises: data capture unit is used for obtaining geological data; The time window choose the unit, be used for the tectonic structure corresponding according to described geological data, choose the size of computation window; Time range is chosen the unit, is used for access time length greater than the time range of described computation window; The curvature acquiring unit is used for the computation window that utilizes coherent algorithm, chooses in advance and the time range of choosing in advance, obtains the curvature of each testing data point in the described geological data; Body curvature acquiring unit is used for the curvature according to each testing data point, obtains the body curvature of whole geological data; The discontinuum detecting unit is used for the body curvature according to described whole geological data, and underground crack and tomography are detected.

The technique scheme of the confession of the embodiment of the invention, having overcome prior art calculates the impact that the middle level bit data picked up and causes the precision to reduce in the curvature of face, and the deficiency of the aspect such as body curvature computation process is loaded down with trivial details, complicated, make the computation process of body curvature more straightforward, error is little, precision is high, counting yield is high, thereby can greatly improve recognition capability and the detection efficiency of discontinuum.

Description of drawings

In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, the below will do one to the accompanying drawing of required use in embodiment or the description of the Prior Art and introduce simply, apparently, accompanying drawing in the following describes only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.

Fig. 1 is 3 * 3 grid method schematic diagram of prior art;

Fig. 2 is the overall flow figure of the detection method of 1 one kinds of underground discontinuums of the embodiment of the invention;

Fig. 3 is that the embodiment of the invention 1 is according to a kind of particular flow sheet of method shown in Figure 2;

Fig. 3 A is the 3D seismic data space schematic diagram of the embodiment of the invention 1;

Fig. 4 is the 2D section of the generated data of the embodiment of the invention 1;

Fig. 5 is the maximum positive curvature attribute of 2D section among Fig. 4 of the embodiment of the invention 1;

Fig. 6 is the process flow diagram of detection method of a kind of underground discontinuum of the embodiment of the invention 2;

Fig. 7 is that the embodiment of the invention 2 is according to a kind of particular flow sheet of method shown in Figure 6;

Fig. 8 is the 2D section of the actual seismic data of the embodiment of the invention 2;

Fig. 9 is the coherence slice of the actual seismic data of the embodiment of the invention 2;

Figure 10 is the maximum positive curvature section of Whole frequency band of the actual seismic data of the embodiment of the invention 2;

Figure 11 is the maximum positive curvature section of low frequency of the actual seismic data of the embodiment of the invention 2;

Figure 12 is the maximum positive curvature section of high frequency of the actual seismic data of the embodiment of the invention 2;

Figure 13 is the functional block diagram of the pick-up unit of 3 one kinds of underground discontinuums of the embodiment of the invention;

Figure 13 A is the detailed functional block diagram of the embodiment of the invention 3 mean curvature acquiring units 140;

Figure 13 B is the detailed functional block diagram of the search subelement 141 of the embodiment of the invention 3;

Figure 14 is the concrete function block diagram of the pick-up unit of the embodiment of the invention 3 another kind of underground discontinuums;

Figure 14 A is the concrete function block diagram of the embodiment of the invention 3 multiband data capture units 240;

Figure 14 B is the concrete function block diagram of the embodiment of the invention 3 multiple dimensioned body curvature computing units 250.

Embodiment

For the purpose, technical scheme and the advantage that make the embodiment of the invention clearer, below in conjunction with the accompanying drawing in the embodiment of the invention, technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making the every other embodiment that obtains under the creative work prerequisite.

The method of the embodiment of the invention is based on following principle: suppose that subsurface reflective boundary is continuous, therefore the seismic reflection lineups of same reflecting interface are continuous, similar.In seismic data volume, the reflection line-ups at interface (events) forms a continuous curved surface, and the similarity of lineups can be calculated by coherent algorithm.In one embodiment, for the current sampling point that will calculate, at first adopt coherent algorithm to ask for a local curved surface, then utilize this local curved surface to calculate the curvature of this sampled point, then according to the curvature of each data point, obtain the body curvature of whole geological data.In another embodiment, by application window Fourier Fourier conversion (WFT) geological data is decomposed, and in conjunction with the body curvature computing method among the upper embodiment, obtain the body curvature on the different scale.

Embodiment 1:

The embodiment of the invention 1 provides a kind of detection method of underground discontinuum.Fig. 2 is the process flow diagram of detection method of a kind of underground discontinuum of the embodiment of the invention 1.As shown in Figure 2, the method comprises the steps:

S201, obtain geological data;

S202, the tectonic structure corresponding according to described geological data are chosen the size of computation window;

Particularly, the detailed process of S202 can comprise: when the complicated geological on the earthquake section, choose little computation window; Perhaps, when the tectonic structure on the earthquake section is simple, window when choosing computation.The basis for estimation of geological structural complexity is: degree and the factors such as quantity, fold morphology and formation contact according to the mature fault on the seismic section are judged.For example can choose computation window based on following principle: when the Geological Structural Forms on the seismic section of described geological data only comprises parallel laminar (parallelstratified), window when choosing computation; Perhaps, Geological Structural Forms on the seismic section of described geological data is except comprising parallel laminar, when also comprising anticline (anticline), at least a in tiltedly (syncline), tomography (fault), unconformability (unconformity) or the fold (fold), choose little computation window.For example, little computation window can be the time window less than 5 sampled points, and the time window that comprises 5 or above sampled point window when being computation, but the embodiment of the invention is not restricted to this.

S203, access time, length was greater than the default time range of described computation window;

S204, utilize coherent algorithm, the computation window chosen in advance and the time range chosen in advance, obtain the curvature of each testing data point in the described geological data;

Particularly, when obtaining the curvature of a testing data point, the process of step S204 specifically can comprise: for each the testing data point in the geological data, centered by the road at described testing data point place, on each phase neighboring trace, search in described time range according to described computation window, seek on described each phase neighboring trace based on coherent algorithm and put maximally related data point with described testing data; According to putting maximally related a plurality of data point and local curved surface of described testing data point match with described testing data on a plurality of phase neighboring traces; Calculate the curvature of described testing data point according to described local curved surface.

Particularly, when on seeking a phase neighboring trace, putting maximally related data point with described testing data, centered by the road at described testing data point place, on described phase neighboring trace, search in described time range according to described computation window, seek on the described phase neighboring trace process of putting maximally related data point with described testing data based on coherent algorithm and specifically comprise the steps:

On described phase neighboring trace, search in described time range according to computation window, obtain a plurality of coherent value based on coherent algorithm, from described a plurality of coherent value, select maximum coherent value, and the data point that the coherent value of described maximum is corresponding is defined as the relevant data points of described testing data point on described phase neighboring trace.

When obtaining a coherent value based on coherent algorithm, detailed process comprises the steps:

Choose the first data acquisition in the computation window on the road at described testing data point place; In the described time range of described phase neighboring trace, choose upper the second data acquisition in computation window of described phase neighboring trace; Described the first data acquisition and described the second data acquisition are concerned with calculating to obtain a coherent value based on coherent algorithm; After described phase neighboring trace executes once relevant calculating, the computation window on the described phase neighboring trace is moved along predetermined direction in described time range.

Repeat aforesaid operations until the computation window on the described phase neighboring trace has traveled through all data in the described time range at described phase neighboring trace: will obtain a plurality of coherent value after repeating aforesaid operations;

From described a plurality of coherent value, select maximum coherent value, and the data point that the coherent value of described maximum is corresponding is defined as the relevant data points of described testing data point on described phase neighboring trace.

Alternatively, described predetermined direction is the direction that increases along the quantity of data point, the direction that perhaps reduces along the quantity of data point.When described predetermined direction was the direction that increases along the quantity of data point, the starting point of described the second computation window was arranged at the lower limit place of described default time range; Perhaps, when described predetermined direction was the direction that reduces along the quantity of data point, the starting point of described the second computation window was positioned at the upper vault of described default time range.

Particularly, according to putting in the process of maximally related a plurality of data point and a local curved surface of described testing data point match with described testing data on a plurality of phase neighboring traces, if adopt " 3 * 3 " gridding method, this local curved surface is to put the local curved surface that maximally related 8 data points consist of by described testing data point and with described testing data, certainly, the embodiment of the invention is not restricted to this, as adopting " 5 * 5 " gridding method, then this local curved surface is to put the local curved surface that maximally related 24 data points consist of by described testing data point and with described testing data.Adopt the grid node of other scale can realize equally.In the process of the curvature of calculating described testing data point according to described local curved surface, the method for calculating the curvature of testing data point can see also formula (1) to formula (8).

S205, according to the curvature of each data point, obtain the body curvature of whole geological data;

Particularly, the detailed process of S205 can comprise: according to the curvature of each the testing data point on the road at described testing data point place, obtain the curvature in this road; According to every curvature together, obtain the body curvature of whole geological data.Described body curvature comprises maximum positive curvature.The embodiment of the invention is not restricted to this, and the detailed process of S205 also can comprise: calculate the curvature of current data point, like this each point of the whole data volume of cycle calculations is just entirely shaken the body curvature of data.

S206, according to the body curvature of described whole geological data, underground crack and tomography are detected.

Particularly, the place that body curvature absolute value is large is corresponding to underground crack and tomography.Can detect or identify underground crack and tomography according to this principle.

Particularly, in the flow process shown in Figure 2 based on coherent algorithm can be first generation calculation of coherence cube algorithm, second generation calculation of coherence cube algorithm or third generation calculation of coherence cube algorithm.Below further specify the coherent algorithm of using in the embodiment of the invention method shown in Figure 2.

The embodiment of the invention has adopted coherent algorithm to seek local curved surface in the algorithm that calculates curvature.Relevant is the mathematical measure of two signal similar degree, has at present three kinds of methods to calculate coherent body.Preferably adopt third generation coherent body technique C3 method in the embodiment of the invention.C3 coherent algorithm those skilled in the art can list of references: Gersztenkorn A.and Marfurt K.J.Eigenstructure-basedcoherence computations as an aid to 3D structural and stratigraphic mapping.Geophysics, 1999,64 (5): 1446～1479.

The detailed description of C3 coherent algorithm below is provided.In the 3D geological data, the window data body that analyze is a little 3D cube, comprises the J road, and per pass has N sampled point.The amplitude of each sampled point in this cube is arranged in a matrix D in order, and wherein the index of sampled point is N, and the index of Taoist monastic name is J:

Its covariance matrix is E=D ^TD.The mark of covariance matrix E is:

$\mathrm{Tr}\left(E\right)=\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{e}_{\mathrm{jj}}=\underset{j=1}{\overset{J}{\mathrm{\&Sigma;}}}{\mathrm{\&lambda;}}_j---\left(20\right)$

λ j (j=1 ..., J) be the eigenwert of covariance matrix E.Relevant being expressed as:

$C=\frac{{\mathrm{\&lambda;}}_1}{\mathrm{Tr}\left(E\right)},---\left(21\right)$

Wherein, λ ₁It is the eigenvalue of maximum of covariance matrix E.

Method shown in Figure 2 below is described in further detail by way of example.

Fig. 3 is that the embodiment of the invention 1 is according to a kind of particular flow sheet of method shown in Figure 2.As shown in Figure 3, the method comprises the steps:

S301, for the architectonic complexity on the seismic section, choose suitable computation window size; For complex structure, choose little computation window, for simple structure, window when choosing computation.

Particularly, computation window refers to that to need selected time range, its purposes be the sampling number certificate in the window in order to obtain in order to calculate.

S302, for the current sampling point that calculates, be the center of computation window; Centered by the road at current sampling point place, choose the default time range on the phase neighboring trace, adopt coherent algorithm to calculate on the phase neighboring trace and the maximally related point of current sampling point.

The implication in road refers to the geological data that records on the single acceptance point.This road refers to the current road that calculates.Because the road of geological data distributes as net shape on the plane, the phase neighboring trace is the road with the value difference 1 of the main profile in this road and/or cross-track.

S303, on the phase neighboring trace repeating step S302, obtain current 8 maximally related points on the phase neighboring trace; Utilize these 9 points to come fit equation (1) based on " 3 * 3 " gridding method, obtain each coefficient (for example a, b, c, d, e, f) of equation (1), then calculate the curvature value of current point according to each coefficient of obtaining and equation (8).

S304, on whole road repeating step S302 and step S303, obtain the result of calculation in this road.

The process of S305, repeating step S304 is obtained every result of calculation together, to obtain the curvature result of whole data volume.

Below describe among above-mentioned steps S302 and the S303 search procedure based on coherent algorithm in detail:

Fig. 3 A is the 3D seismic data space schematic diagram of the embodiment of the invention 1.Please in conjunction with consulting Fig. 3 A, suppose that 3D seismic data has L bar survey line, the M road is arranged on the every survey line, have N data point on the per pass, form a 3D seismic data space representation and be: L * M * N, wherein L, M and N are positive integer; Suppose that the current positional representation of data point in described 3D seismic data space to be calculated is (i, j, k), the positional representation of road, current data point place (hereinafter to be referred as current road) in described 3D seismic data space is (i, j), and a plurality of phase neighboring traces that road, current data point place is corresponding are expressed as respectively (i-1 in the position in 3D seismic data space, j-1), (i-1, j), (i-1, j+1), (i, j-1), (i, j+1), (i+1, j-1), (i+1, j), (i+1, j+1), wherein, i ∈ [1, L], j ∈ [1, M], k ∈ [1, N].

The lengths table of supposing the computation window chosen is shown l, and then described current data point k is set to the center of described computation window l, and chooses the data that are positioned at the computation window l centered by described current data point k on the described current road (i, j).

Preset Time scope on each phase neighboring trace is set as [k-r, k+r], and chooses computation window at each phase neighboring trace, its lengths table is shown l, wherein, and r 〉=l/2;

Respectively at the described Preset Time scope [k-r of each phase neighboring trace, k+r] in, choose the phase neighboring trace upper in computation window l data and described current road (i, j) on choose be positioned at computation window l data, based on the coherent algorithm calculating that is concerned with, obtain a coherent value.Wherein, the starting point of the computation window l of described phase neighboring trace is from k-r, every execution once is concerned with after the calculating, make computation window l at Preset Time scope [k-r, k+r] interior data point of starting point increase, and in whole Preset Time scope [k-r, k+r] the interior repeatedly relevant process of calculating of execution that circulates, i.e. continuous window l during mobile computing on each phase neighboring trace, and choose on the phase neighboring trace on data in the computation window l after mobile and the current road calculating that is concerned with of the data in the computation window l, until described computation window l has traveled through all data points in the described whole Preset Time scope [k-r, k+r].

Carry out repeatedly at each phase neighboring trace and relevantly to calculate obtaining a plurality of coherent value, and choose sampled point corresponding to coherent value maximum in described a plurality of coherent value, as on the described phase neighboring trace with the maximally related data point of described current data point.

Particularly, if find maximum coherence value on the phase neighboring trace, then the center of the computation window that this maximum coherence value is corresponding is as maximally related data point.

Further, the proof procedure that the embodiment of the invention 1 is carried out the method for body curvature calculating based on coherent algorithm below is described.

Fig. 4 is the 2D section of the generated data of the embodiment of the invention 1.Generated data is the data that theoretical formula calculates, the data that geological data in general sense refers to construct and collects.As shown in Figure 4, in this synthetic curved surface geological data, curved surface left-half shape is the arched roof of a projection, the right half part shape be one recessed hollow, calculate the body curvature (maximum positive curvature) of these earthquake data with the coherent algorithm of the embodiment of the invention.Two dimensional cross-section such as Fig. 4 along arched roof summit and hollow low spot, the maximum positive curvature attribute of this two dimensional cross-section as shown in Figure 5, Fig. 5 is the maximum positive curvature attribute of 2D section among Fig. 4 of the embodiment of the invention 1, as shown in Figure 5, the value of maximum positive curvature attribute has been portrayed the morphological feature of this two dimensional cross-section exactly: on the occasion of the expression protuberance, negative value represents depression, and the curvature attribute just/extreme point of negative value is corresponding consistent with the arched roof summit of structure and hollow low spot, has verified thus the correctness of embodiment of the invention algorithm.

In embodiment of the invention Fig. 2 and the method shown in Figure 3, use coherent algorithm can effectively computable to go out the body curvature of geological data, the algorithm explicit physical meaning, principle is simple, travelling speed is fast, can Effective Raise to recognition capability and the detection efficiency of underground discontinuum.

Embodiment 2:

The embodiment of the invention 2 provides the detection method of another kind of underground discontinuum.Before carrying out detection, calculate first multiple dimensioned earthquake curvature attribute, this process is mainly by application window Fourier conversion, geological data is decomposed into different frequency bands, then the geological data behind the frequency division is calculated respectively its corresponding body curvature, to obtain the body curvature of different scale.In the process of calculating body curvature, also be based on coherent algorithm.

Fig. 6 is the process flow diagram of detection method of a kind of underground discontinuum of the embodiment of the invention 2.As shown in Figure 6, the method comprises the steps:

S601, obtain geological data;

S602, described geological data is carried out spectrum analysis, determine the frequency band range of described geological data;

S603, according to the frequency band range of described geological data, application window Fourier Fourier conversion is decomposed into geological data in the different sub-band scopes with described geological data;

Particularly, by data are carried out spectrum analysis, obtain the whole frequency band range of data at S602.In the process of S603, can be as required, whole frequency band range is divided at least two different sub-band scopes (i.e. less frequency band range), thereby be selected the first input parameter of window Fourier conversion, be about to the first input parameter that described at least two different sub-band scopes are chosen to be window Fourier conversion; Then the described geological data that obtains is chosen to be the second input parameter of window Fourier conversion; Then, according to described the first input parameter and described the second input parameter, window based Fourier conversion obtains to correspond respectively to the geological data of at least two different sub-band scopes.After carrying out said process, the Output rusults of window Fourier conversion is the geological data corresponding to the different frequency bands parameter, and whole geological data is broken down into the geological data in the different frequency band ranges thus.

For example, one group of frequency band parameter comprises high frequency value and the low frequency value of frequency band, again for example, by given many group frequency band parameters, geological data can be decomposed into geological data in the different frequency bands by window Fourier conversion.

S604, calculate respectively the body curvature corresponding to geological data of each frequency band based on coherent algorithm, to obtain the body curvature of different scale.

Particularly, the detailed process of S604 can comprise: carry out respectively curvature based on the geological data of coherent algorithm after to frequency division and calculate.Computation process specifically can comprise: adopt coherent algorithm to obtain 9 points (as shown in Figure 1) on the local curved surface, calculate the curvature of current point, this process of iteration can obtain multiple dimensioned curvature attribute.And please those skilled in the art's combination consult the method shown in the embodiment of the invention 1.

Fig. 7 is a kind of particular flow sheet of the embodiment of the invention 2 foundations method shown in Figure 6, and as shown in Figure 7, the method comprises the steps:

S701, obtain geological data; The same S601 of this step repeats no more.

S702, described geological data is carried out spectrum analysis, to determine the frequency range of described geological data; The same S602 of this step repeats no more.

S703, judge whether to carry out frequency division, when judged result enters step S704 for need to carry out frequency division the time, otherwise, enter step S706.

S704, according to the frequency range of described geological data, application window Fourier Fourier conversion is decomposed into different frequency bands with described geological data; The same S603 of this step repeats no more, and enters S705 after the S704.

S705, calculate respectively the body curvature corresponding to geological data of each frequency band based on coherent algorithm, to obtain the body curvature of different scale.The same S604 of this step repeats no more.

Particularly, the size of yardstick image study object.The geological data of the corresponding high frequency band of the curvature attribute of small scale, vice versa.

S706, calculate the body curvature corresponding to geological data of Whole frequency band based on coherent algorithm, to obtain full range belt body curvature.Particularly, the method for institute's foundation is also based on coherent algorithm in the computation process of full range belt body curvature.

Alternatively, S703 not necessarily also can both calculate multiple dimensioned body curvature according to concrete research needs, also calculated full range belt body curvature.The purpose of calculating full range belt body curvature is to compare with the curvature of other yardsticks, can provide more fully information for seismic interpretation.

Below describe further by a concrete example and real data to be carried out multiple dimensioned body curvature is calculated and the processing procedure of full range belt body flexometer calculation.

At first, calculate maximum positive curvature (body curvature) attribute of this earthquake data Whole frequency band.

Fig. 8 is a two-dimension earthquake longitudinal profile of the embodiment of the invention 2, and the straight line of locating in 1.8 seconds has marked the time location (1.8s) of the time slice (Fig. 9 to Figure 12) of getting, and the longitudinal axis represents the time among Fig. 8, and transverse axis represents Taoist monastic name.Section from Fig. 8 can find out, locates to have passed through two shatter belts (as shown in elliptical section is divided among Fig. 8) and a tomography (shown in square frame part among Fig. 8) in 1.8 seconds.As everyone knows, coherence properties can be identified the discontinuum in the geological data well, such as tomography and crack etc.Fig. 9 is the horizontal coherence slice of the actual seismic data of the embodiment of the invention 2, and as shown in Figure 9, coherence properties section has clearly reflected the information of two shatter belts and tomography.Figure 10 is the maximum positive curvature section of Whole frequency band of the actual seismic data of the embodiment of the invention 2, and as shown in figure 10, maximum positive curvature attribute section has also clearly reflected the information of two shatter belts and tomography.This explanation curvature attribute is the same with coherence properties, can be used for identifying the discontinuums such as tomography and crack, and good correlativity is arranged between curvature attribute and fold, tomography, anticline and the shatter belt.

Then, geological data being carried out multiple dimensioned body curvature calculates.

Because the frequency band of this geological data is not wide, only its (geological data) is decomposed into two data volumes of high and low frequency with window Fourier conversion, these two data volumes are calculated respectively maximum positive curvature (body curvature) attribute.The low-frequency band of geological data is geology result's background, and the high frequency band of geological data has reflected little architectonic feature.Therefore the curvature (such as Figure 11 and shown in Figure 12) of different scale has reflected the different characteristic of geologic structure.Wherein, Figure 11 is the maximum positive curvature section of low frequency of the actual seismic data of the embodiment of the invention 2; Figure 12 is the maximum positive curvature section of high frequency of the actual seismic data of the embodiment of the invention 2.

At last, the curvature of the curvature of the curvature of comparative analysis Whole frequency band data, low-frequency band data, high frequency band data.

Particularly, compare with the curvature (as shown in figure 10) of Whole frequency band data, the curvature of low-frequency data (as shown in figure 11) has comprised less information, only portrayed architectonic background characteristics, for example, rectangular area among contrast Figure 10 and Figure 11 can find out that information is few in the curvature of Figure 11 medium and low frequency data, has only portrayed architectonic background characteristics; The curvature of high-frequency data (as shown in figure 12) can demonstrate more little architectonic feature, therefore can reflect better little geologic feature, for example, the rectangular area among contrast Figure 10 and Figure 12 can find out that the curvature of Figure 12 High-frequency Data can show more little geologic body feature.Confirmed that thus the multi-dimension curvature attribute can disclose different geologic features, can improve the resolution of explaining, disclosed the more information in the data.

The curvature of face computing method based on layer bit data of prior art, the information (curved surface data) of necessary known layer bit data before calculating, namely use the layer bit data that provides as input, the precision of this method easily is subject to the impact of the picking errors in the interpretation process of layer position.And the method for the embodiment of the invention is for being input as whole geological data, by finding a local curved surface based on coherent algorithm in seismic data volume, and utilizes the data of this local curved surface to carry out curvature and calculates, and precision is higher, error is less.And the embodiment of the invention is towards the multiple dimensioned earthquake curvature attribute acquisition methods based on coherent algorithm of seismic data interpretation, and use coherent algorithm energy effectively computable goes out the body curvature of geological data, the algorithm explicit physical meaning, and principle is simple, and travelling speed is fast.And application window Fourier conversion can obtain multiple dimensioned body curvature attribute, and this new multi-dimension curvature attribute can greatly improve the recognition capability of the geologic bodies such as crack.

Embodiment 3:

The embodiment of the invention also provides a kind of pick-up unit of underground discontinuum.

Figure 13 is the functional block diagram of pick-up unit of a kind of underground discontinuum of the embodiment of the invention 3.Such as Figure 13 institute method, this device comprises:

Data capture unit 110 is used for obtaining geological data;

The time window choose unit 120, be used for the tectonic structure corresponding according to described geological data, choose the size of computation window;

Particularly, window selected cell 120 when described specifically can be used for when the Geological Structural Forms on the seismic section of described geological data only comprises parallel laminar window when choosing computation; Perhaps, the Geological Structural Forms on the seismic section of described geological data when also comprising anticline, at least a in oblique, tomography, unconformability or the fold, is chosen little computation window except comprising parallel laminar.

Time range is chosen unit 130, is used for access time length greater than the time range of described computation window;

Curvature acquiring unit 140 is used for the computation window that utilizes coherent algorithm, chooses in advance and the time range of choosing in advance, obtains the curvature of each testing data point in the described geological data;

Body curvature acquiring unit 150 is used for the curvature according to each testing data point, obtains the body curvature of whole geological data;

Particularly, described body curvature acquiring unit 150 specifically can be used for the curvature according to each the testing data point on the road at described testing data point place, obtains the curvature in this road; And according to every curvature together, obtain the body curvature of whole geological data.

Discontinuum detecting unit 160 is used for the body curvature according to described whole geological data, and underground crack and tomography are detected.

Figure 13 A is the detailed functional block diagram of the curvature acquiring unit 140 of the embodiment of the invention 3.As shown in FIG. 13A, curvature acquiring unit 140 comprises: search subelement 141, surface fitting subelement 142 and curvature computation subunit 143;

Described search subelement 141, be used for centered by the road at described testing data point place, on each phase neighboring trace, search in described time range according to described computation window, seek on described each phase neighboring trace based on coherent algorithm and put maximally related data point with described testing data;

Described surface fitting subelement 142 is used for according to putting maximally related a plurality of data point and local curved surface of described testing data point match with described testing data on a plurality of phase neighboring traces;

Described curvature computation subunit 143 is for the curvature of calculating described testing data point according to described local curved surface.

Alternatively, described local curved surface comprises: put the local curved surface that maximally related 8,15 or 24 data points consist of by described testing data point and with described testing data.Described coherent algorithm comprises the first generation, the second generation or third generation calculation of coherence cube algorithm.Described body curvature comprises maximum positive curvature.

Particularly, described search subelement 141, specifically can be used on described phase neighboring trace, searching in described time range according to computation window, obtain a plurality of coherent value based on coherent algorithm, from described a plurality of coherent value, select maximum coherent value, and the data point that the coherent value of described maximum is corresponding is defined as the relevant data points of described testing data point on described phase neighboring trace.

Figure 13 B is the detailed functional block diagram of the search subelement 141 of the embodiment of the invention 3.Shown in Figure 13 B, search subelement 141 comprises: the first data acquisition is chosen module 1411, the second data acquisition is chosen module 1412, relevant computing module 1413 and computation window mobile module 1414;

Described the first data acquisition is chosen module 1411, for the first data acquisition in the computation window on the road of choosing described testing data point place;

Described the second data acquisition is chosen module 1412, is used for choosing upper the second data acquisition in computation window of described phase neighboring trace in the described time range of described phase neighboring trace;

Described relevant computing module 1413 is used for described the first data acquisition and described the second data acquisition are concerned with calculating to obtain a coherent value based on coherent algorithm;

Described computation window mobile module 1414 is used for after described phase neighboring trace executes once relevant calculating the computation window on the described phase neighboring trace being moved along predetermined direction in described time range.

Alternatively, described predetermined direction is the direction that increases along the quantity of data point, the direction that perhaps reduces along the quantity of data point.When described predetermined direction was the direction that increases along the quantity of data point, the starting point of described the second computation window was arranged at the lower limit place of described default time range; Perhaps, when described predetermined direction was the direction that reduces along the quantity of data point, the starting point of described the second computation window was positioned at the upper vault of described default time range.

Particularly, when on seeking a phase neighboring trace, putting maximally related data point with described testing data, the first data acquisition is chosen module 1411, the second data acquisition chooses module 1412, relevant computing module 1413 and computation window mobile module 1414 will repeat multi-pass operations until computation window has traveled through all data in the described time range, will obtain a plurality of coherent value after above-mentioned functions unit 1411-1414 repeats repeatedly aforesaid operations;

Then, described search subelement 141 is selected maximum coherent value from described a plurality of coherent value, and the data point that the coherent value of described maximum is corresponding is defined as the relevant data points of described testing data point on described phase neighboring trace.

Figure 14 is the concrete function block diagram of pick-up unit of the another kind of underground discontinuum of the embodiment of the invention 3.As shown in figure 14, this device 20 comprises:

Data capture unit 210 is used for obtaining geological data; Its function is with data capture unit 110.

Spectral analysis unit 220 is used for described geological data is carried out spectrum analysis, determines the frequency band range of described geological data;

Multiband data capture unit 240 is used for the frequency band range according to described geological data, and application window Fourier Fourier conversion is decomposed into geological data in the different sub-band scopes with described geological data; Multiple dimensioned body curvature computing unit 250 is for body curvature corresponding to geological data of calculating respectively each sub-band scope based on coherent algorithm, to obtain the body curvature of different scale.

Discontinuum detecting unit 270 is used for according to the body curvature that obtains different scale underground crack and tomography being detected.

Figure 14 A is the concrete function block diagram of the multiband data capture unit 240 of the embodiment of the invention 3.Shown in Figure 14 A, described multiband data capture unit 240 can comprise that band decomposition subelement 241, the first input parameter are chosen subelement 242, the second input parameter is chosen subelement 243 and window Fourier varitron unit 244;

Described band decomposition subelement 241 can be used for the frequency band range of described geological data is divided at least two different sub-band scopes; Described the first input parameter is chosen subelement 242, can be used for described at least two different sub-band scopes are chosen to be the first input parameter of window Fourier conversion; Described the second input parameter is chosen subelement 243, can be used for the described geological data that obtains is chosen to be the second input parameter of window Fourier conversion; Described window Fourier varitron unit 244 can be used for according to described the first input parameter and described the second input parameter, and window based Fourier conversion obtains to correspond respectively to the geological data of at least two different sub-band scopes.

Alternatively, pick-up unit 20 can further include:

Frequency division judging unit 230 is connected with band decomposition unit 240 with spectral analysis unit 220, is used for judging whether geological data to be decomposed into different frequency ranges.And,

Full range belt body flexometer is calculated unit 260, be connected with discontinuous detecting unit 270 with frequency division judging unit 230, be used for when the judged result of frequency division judging unit 230 when not needing frequency division, based on the body curvature corresponding to geological data of coherent algorithm calculating Whole frequency band, with acquisition full range belt body curvature.

Above-mentioned discontinuum detecting unit 270 can also be used for according to the result of calculation of multiple dimensioned body curvature computing unit 250 and full range belt body flexometer calculation unit 260 underground discontinuum being detected.

Particularly, full range belt body flexometer calculate unit 260 function can by time window selected cell 120, time range shown in Figure 13 choose unit 130, curvature acquiring unit 140 and body curvature acquiring unit 150 common complete with.

Figure 14 B is the concrete function block diagram of multiple dimensioned body curvature computing unit 250 among the embodiment of the invention 3 Figure 14.As shown in Figure 14B, multiple dimensioned body curvature computing unit 250 can further comprise the first yardstick body curvature computing unit 251, the second yardstick body curvature computing unit 252 and the 3rd yardstick body curvature computing unit 253, is respectively applied to calculate corresponding the first body curvature, second body curvature and the trisome curvature of data of the first frequency band, the second frequency band and the 3rd frequency band.Wherein the function of the first above-mentioned yardstick body curvature computing unit 251, the second yardstick body curvature computing unit 252 and the 3rd yardstick body curvature computing unit 253 all can adopt time window among Figure 13 choose unit 120, time range choose unit 130, curvature acquiring unit 140, and body curvature acquiring unit 150 realize, accordingly, the data of above-mentioned each functional unit 120-150 processing are the data from the first frequency band, the second frequency band or the 3rd frequency band.

The detailed functions of each functional unit shown in embodiment of the invention Figure 13-Figure 14 B, and the device principle of work in aforesaid embodiment of the method, describe, therefore do not repeat them here.

The described pick-up unit of the embodiment of the invention, use coherent algorithm energy effectively computable goes out the body curvature of geological data, the algorithm explicit physical meaning, principle is simple, and travelling speed is fast.And application window Fourier conversion can obtain multiple dimensioned body curvature attribute, and this new multi-dimension curvature attribute can greatly improve the recognition capability of the geologic bodies such as crack.

One of ordinary skill in the art will appreciate that all or part of flow process that realizes in above-described embodiment method, to come the relevant hardware of instruction to finish by computer program, described program can be stored in the computer read/write memory medium, this program can comprise the flow process such as the embodiment of above-mentioned each side method when carrying out.Wherein, described storage medium can be magnetic disc, CD, read-only store-memory body (Read-OnlyMemory, ROM) or random store-memory body (Random Access Memory, RAM) etc.

Above embodiment only in order to the technical scheme of the embodiment of the invention to be described, is not intended to limit; Although with reference to previous embodiment the embodiment of the invention is had been described in detail, those of ordinary skill in the art is to be understood that: it still can be made amendment to the technical scheme that aforementioned each embodiment puts down in writing, and perhaps part technical characterictic wherein is equal to replacement; And these modifications or replacement do not make the essence of appropriate technical solution break away from the spirit and scope of each embodiment technical scheme of the embodiment of the invention.

Claims (16)

1. a detection method of underground discontinuity, is characterized in that, described method comprises: Get seismic data; According to the geological structure corresponding to the seismic data, select the size of the calculation time window; wherein, according to the geological structure corresponding to the seismic data, the selection of the size of the calculation time window includes: when the geological structure on the seismic section of the seismic data When the structural form only includes parallel layers, select a large calculation time window; or, when the geological structure on the seismic section of the seismic data includes not only parallel layers, but also includes anticlines, synclines, faults, and unconformity or at least one of folds, choose a small calculation time window; Selecting a time range whose time length is greater than the calculation time window; Obtain the curvature of each data point to be measured in the seismic data by using a coherent algorithm, a preselected calculation time window and a preselected time range; According to the curvature of each data point to be measured, the volume curvature of the entire seismic data is obtained; Subsurface fractures and faults are detected based on the volume curvature of the entire seismic data. 2. The method according to claim 1, wherein, when obtaining the curvature of a data point to be measured, comprising: Taking the track where the data point to be measured is located as the center, search on each adjacent track within the time range according to the calculation time window, and search for the data point on each adjacent track that is related to the test point based on a coherent algorithm. the data point with which the data point is most relevant; fitting a local surface according to a plurality of data points most relevant to the data points to be measured on a plurality of adjacent tracks and the data points to be measured; The curvature of the data point to be measured is calculated according to the local curved surface. 3. The method according to claim 2, wherein, when looking for the data point most relevant to the data point to be measured on an adjacent track, specifically comprising: Search in the time range according to the calculation time window on the adjacent track, obtain a plurality of coherence values based on the coherence algorithm, select the largest coherence value from the plurality of coherence values, and store the largest coherence value The corresponding data point is determined as the most relevant data point of the data point to be measured on the adjacent track. 4. The method according to claim 3, wherein when a coherent value is obtained based on a coherent algorithm, it specifically comprises: Selecting the first data set within the calculation time window on the track where the data point to be measured is located; Within the time range of the adjacent track, select a second data set located in the calculation time window on the adjacent track; performing coherence calculation on the first data set and the second data set based on a coherence algorithm to obtain a coherence value; After a coherent calculation is performed on the adjacent track, the calculation time window on the adjacent track is moved along a predetermined direction within the time range. 5. The method according to claim 4, wherein the predetermined direction is along a direction in which the number of data points increases, or along a direction in which the number of data points decreases. 6. The method of claim 5, wherein, When the predetermined direction is along the direction in which the number of data points increases, the starting point of the calculation time window is set at the lower limit of the preset time range; or, When the predetermined direction is along a direction in which the number of data points decreases, the starting point of the calculation time window is located at the upper limit of the preset time range. 7. The method according to claim 1, characterized in that, after said acquiring seismic data, said method further comprises: Perform frequency spectrum analysis on the seismic data to determine the frequency band range of the seismic data; Decomposing the seismic data into seismic data within different sub-frequency bands by applying windowed Fourier transform according to the frequency band range of the seismic data; Based on the coherent algorithm, the volume curvature corresponding to the seismic data in each sub-band range is calculated separately to obtain volume curvatures of different scales. 8. The method according to claim 7, characterized in that, according to the frequency band range of the seismic data, the application window Fourier transform is used to decompose the seismic data into seismic data in different sub-frequency band ranges; comprising: dividing the frequency band range of seismic data into at least two different sub-frequency band ranges; selecting the at least two different sub-band ranges as first input parameters for windowed Fourier transform; Selecting the acquired seismic data as the second input parameter of the windowed Fourier transform; Seismic data respectively corresponding to at least two different sub-frequency band ranges are obtained based on the windowed Fourier transform according to the first input parameter and the second input parameter. 9. The method according to any one of claims 1-8, wherein the volume curvature of the entire seismic data is obtained according to the curvature of each data point; comprising: According to the curvature of each data point to be measured on the trace where the data point to be measured is located, the curvature of the trace is obtained; according to the curvature of each trace, the volume curvature of the entire seismic data is obtained. 10. A detection device for an underground discontinuity, characterized in that the device comprises: a data acquisition unit, configured to acquire seismic data; The time window selection unit is used to select the size of the calculation time window according to the geological structure corresponding to the seismic data; the time window selection unit is specifically used when the geological structure on the seismic profile of the seismic data only includes parallel When layered, select a large calculation time window; or, when the geological structure on the seismic section of the seismic data includes not only parallel layers, but also includes at least one of anticlines, synclines, faults, unconformities, or folds When one is selected, select a small calculation time window; a time range selection unit, configured to select a time range whose time length is greater than the calculation time window; a curvature acquisition unit, configured to acquire the curvature of each data point to be measured in the seismic data by using a coherent algorithm, a pre-selected calculation time window and a pre-selected time range; a volume curvature acquisition unit, configured to obtain the volume curvature of the entire seismic data according to the curvature of each data point to be measured; The discontinuity detection unit is configured to detect underground fractures and faults according to the volume curvature of the entire seismic data. 11. The device according to claim 10, wherein the curvature acquisition unit includes a search subunit, a surface fitting subunit and a curvature calculation subunit; The search subunit is configured to center on the track where the data point to be measured is located, search on each adjacent track within the time range according to the calculation time window, and search for each track based on a coherent algorithm. The data point most relevant to the data point to be measured on the adjacent track; The surface fitting subunit is used to fit a local surface according to a plurality of data points most relevant to the data points to be measured and the data points to be measured on a plurality of adjacent lanes; The curvature calculation subunit is configured to calculate the curvature of the data point to be measured according to the local curved surface. 12. The apparatus of claim 11, wherein: The search subunit is specifically configured to search in the time range according to the calculation time window on the adjacent track, obtain a plurality of coherence values based on a coherence algorithm, and select the largest coherence value from the plurality of coherence values , and determine the data point corresponding to the largest coherence value as the most relevant data point of the data point to be measured on the adjacent track. 13. The device according to claim 12, wherein the search subunit comprises: a first data set selection module, a second data set selection module, a coherent calculation module and a calculation time window movement module; The first data set selection module is used to select the first data set within the calculation time window on the track where the data point to be measured is located; The second data set selection module is configured to select a second data set on the adjacent track within the calculation time window within the time range of the adjacent track; The coherent calculation module is configured to perform coherent calculation on the first data set and the second data set based on a coherent algorithm to obtain a coherent value; The calculation time window moving module is configured to move the calculation time window on the adjacent track along a predetermined direction within the time range after a coherent calculation is performed on the adjacent track. 14. The device according to claim 10, further comprising: a spectrum analysis unit, configured to perform spectrum analysis on the seismic data to determine the frequency band range of the seismic data; The multi-band data acquisition unit is used to decompose the seismic data into seismic data in different sub-frequency bands by applying windowed Fourier transform according to the frequency band range of the seismic data; The multi-scale volume curvature calculation unit is configured to separately calculate the volume curvature corresponding to the seismic data in each sub-frequency range based on a coherent algorithm, so as to obtain volume curvatures of different scales. 15. The apparatus of claim 14, wherein: The multi-band data acquisition unit includes a frequency band decomposition subunit, a first input parameter selection subunit, a second input parameter selection subunit and a window Fourier transformation subunit; The frequency band decomposition subunit is configured to divide the frequency band range of the seismic data into at least two different sub-frequency band ranges; The first input parameter selection subunit is used to select the at least two different sub-band ranges as the first input parameters of the windowed Fourier transform; The second input parameter selection subunit is used to select the acquired seismic data as the second input parameter of windowed Fourier transform; The windowed Fourier transform subunit is configured to obtain seismic data respectively corresponding to at least two different sub-frequency band ranges based on windowed Fourier transform according to the first input parameter and the second input parameter. 16. The device according to any one of claims 10-15, characterized in that, The volume curvature acquisition unit is specifically configured to obtain the curvature of the track according to the curvature of each data point to be measured on the track where the data point to be measured is located; and obtain the volume curvature of the entire seismic data according to the curvature of each track.

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