CN107367756A - A kind of quantitative analysis method of multilayer near surface Seismology and Geology complexity - Google Patents
A kind of quantitative analysis method of multilayer near surface Seismology and Geology complexity Download PDFInfo
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Abstract
The invention provides a kind of method of multilayer near surface Seismology and Geology complexity quantitative analysis, accurate Characterization of this method using boundary element near surface structure geometric properties, study the influence of relief surface and irregular geology interface to seimic wave propagation, characterize boundary element by Gauss numeric integral in borderline exterior normal derivative by elementary solution influences on the wave field of node, not only describe influencing each other between any two points, the influence of boundary shape feature is also features simultaneously, quantitative analysis relatively accurately can be carried out to multilayer near surface Seismology and Geology complexity.
Description
Technical field
The present invention relates to technical field of geophysical exploration, the earthquake money in more particularly to a kind of seismic acquisition processing
Expect mass analysis technique.
Background technology
Selection of the earth's surface complexity to earthquake imaging method, the data of the processing and surface relief of seismic data intricately
Collection is respectively provided with directive significance, however, earth's surface complexity is qualitative evaluation mostly at present, it is difficult to commented with quantitative method
Estimate.
Western part of China and southern area near surface complexity are big, and the geological data signal to noise ratio of collection is extremely low, has a strong impact on ground
The quality of imaging is shaken, is embodied in：Massif is precipitous, ravines and guillies criss-cross, discrepancy in elevation great disparity, abnormal when the original earthquake data of collection is walked
Become, cause serious static correction problem；Old stratum strong deformation, inverse punching, which pushes away, covers crop out, causes violent near-surface velocity
Change and high steep structure；The weathering and erosion of exposure rock stratum is serious, and top layer is loose, causes serious frequency dispersion effect and high-frequency absorption.
So complicated near surface seismic geological codition brings extreme difficulties to seismic data acquisition processing, causes to excite
Condition of acceptance and seismic wavelet (waveform, energy, frequency) uniformity extreme difference.
For surface seismic exploration, the maximum influence of complicated near surface is the strong scattering work to all deep reflex ripples
With plus the serious absorption of near surface and frequency dispersion, forming semi-random half relevant near surface strong scattering background noise, diffuse whole
Big gun collection, deep reflex signal is flooded, caused significant wave wave breaking, wave dispersionization is serious, and it is preferable to be hardly visible same phasic property
Significant wave group.
Therefore, the complexity of near surface is serious restriction deep structure the main reason for causing seismic data Arctic ice area
The seismic imaging effect made, it is the bottleneck problem of complex area oil exploration, and the difficulty that oil exploration both at home and abroad is tackled key problems for a long time
Topic.
All ground observation wave fields of complicated near surface scatter attenuation, it is mainly shown as focusing, defocuses and shape transformation, with
The roughness of relief surface and the correlation length of near surface random medium are closely related.Near surface how is researched and analysed and evaluates to answer
Polygamy and its influence to seimic wave propagation, always seismographic study hotspot, the major part of prior art are ground for a long time
Study carefully work and be concentrated mainly on complicated near-surface seismic Numerical Simulation, use large scale irregular obstacle body structure+inside mostly
The rate pattern of random medium, stress simulation algorithm research, and the analysis to wave field complexity is less.
Exist in the prior art and near surface scattering mechanism is studied using seismic full-field shape method for numerical simulation, but it is not
Scattering and roughness of ground surface and the correlation of near surface random medium parameter can intuitively be understood, and be related to magnanimity simulation and calculate,
Although substantial amounts of parsing/semi-analytic method arises at the historic moment, due to the limitation of approximation accuracy, these methods can not be applicable completely
Scatter and characterize in complicated near surface.
In a word, near surface strong scattering is noise for seismic exploration, how to quantify the scattering noise intensity of earthquake big gun collection,
Always surface seismic exploration, i.e. oil exploration an open question, this and near-surface velocity cross directional variations and structure inclination angle divide
Cloth is closely related.
Due to random fluctuation earth's surface and internal heterogeneous extremely strong randomness, it is difficult to find that at present a set of effective
Near surface complexity quantization signifying method, e.g., Ashford etc. more systematically gives landform inclination angle and relative elevation and earthquake
Correlation between ripple type, wavelength, incidence angle；Chou is defined with a varied topography based on relief surface data characteristics
Degree；Chinese patent CN200810105063 discloses a kind of underground non-uniform medium seismic investigation complexity quantitative analysis method,
It is based on the heterogeneous spectrum of complex dielectrics geology (lateral variation in velocity and stratigraphic dip change heterogeneous spectrum) and seismic spread operator
The interaction of angular spectrum；Fu proposes a kind of complex dielectrics complexity concept and its computational methods, and is applied to Ku Cheao
The complexity quantitative analysis and the description of complicated Submarine Geomorphic Features of high-dip structure are fallen into, however, the quantitative analysis method can not fit
Quantitative analysis for earth's surface complexity.
In the prior art, the quantitative analysis method for earth's surface complexity is not yet set up, therefore, it is necessary to develops one
Kind for multilayer near surface Seismology and Geology complexity quantitative approach, and based on this may be selected appropriate seismic imaging method,
The processing method of seismic wave data and the collecting method of surface relief complex area etc., so as to instruct geological prospecting.
The content of the invention
In order to solve the above problems, present inventor has performed studying with keen determination, as a result find：With form line and geology line of demarcation
For starting point, based on fluctuating integral equation by border, the complexity of wave field is characterized with Green's function, in conjunction with the complexity of wave field
Property, influence of the boundary element to wave field at different nodes of different occurrences is characterized with Gauss numeric integral, forms matrix, then with
Scattered amplitude matrix is obtained based on the matrix formed, by the summation of scattered amplitude matrix element and the ratio of the ratio between matrix dimension
It is worth as the coefficient for characterizing multilayer near surface Seismology and Geology complexity, uses it to quantitative analysis multilayer near surface Seismology and Geology complexity
Property, and appropriate seismic imaging method, the processing method of seismic data and surface relief complex area may be selected based on this
Collecting method etc., so as to instruct geological prospecting, so as to complete the present invention.
It is an object of the invention to provide one kind with multilayer near surface scattered amplitude matrix come quantitative analysis multilayer near surface
The method of Seismology and Geology complexity, this method comprise the following steps：
(1) form line and geology line of demarcation are obtained, the form line and the progress of geology line of demarcation to acquisition are discrete, obtain border
Unit, determines the locus coordinate of each boundary element end points, and determines the locus of respective nodes on each boundary element
Coordinate；
(2) side that the node that any one step 1 of selection determines determines as present node, any one step 1 of selection
Boundary's unit characterizes present node with working as current border unit with exterior normal derivative of the Green's function on current border unit
Influencing each other between arbitrfary point on front border unit；
(3) current whole influence of the boundary element to wave field at present node is characterized with integration；
(4) repeat step 2 and step 3, until being characterized with integration mutual between all nodes and all boundary elements
Influence, form the first matrix H；
(5) based on the first matrix H obtained in step 4, corresponding scattered amplitude coefficient matrix is formedAnd it will dissipate
Penetrate peak factor matrixElement summation and the ratio of matrix dimension be expressed as multilayer near surface Seismology and Geology Complexity Coefficient,
Realize multilayer near surface Seismology and Geology complexity quantitative analysis.
Brief description of the drawings
Fig. 1 shows multilayer near surface Seismology and Geology complexity quantitative analysis method FB(flow block) of the present invention；
Fig. 2 shows the border fluctuation IEM model schematic diagram comprising source point；
Fig. 3 shows that mountain peak is highly 160m model；
Fig. 4 shows that mountain peak is highly 240m model；
Fig. 5 shows that mountain peak is highly 320m model；
Fig. 6 shows that mountain peak is highly 400m model；
Fig. 3 that Fig. 7 shows to be obtained with inventive method shows that model is correspondingMatrix；
Fig. 4 that Fig. 8 shows to be obtained with inventive method shows that model is correspondingMatrix；
Fig. 5 that Fig. 9 shows to be obtained with inventive method shows that model is correspondingMatrix；
Fig. 6 that Figure 10 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 11 shows the model that the mountain peak gradient is 25 °；
Figure 12 shows the model that the mountain peak gradient is 35 °；
Figure 13 shows the model that the mountain peak gradient is 45 °；
Figure 14 shows the model that the mountain peak gradient is 65 °；
Figure 11 that Figure 15 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 12 that Figure 16 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 13 that Figure 17 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 14 that Figure 18 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 19 shows the model that horizontal span is 2000m；
Figure 20 shows the model that horizontal span is 1500m；
Figure 21 shows the model that horizontal span is 1000m；
Figure 22 shows the model that horizontal span is 500m；
Figure 19 that Figure 23 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 20 that Figure 24 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 21 that Figure 25 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 22 that Figure 26 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 27 shows the model that mountain peak number is 1；
Figure 28 shows the model that mountain peak number is 2；
Figure 29 shows the model that mountain peak number is 3；
Figure 30 shows the model that mountain peak number is 4；
Figure 27 that Figure 31 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 28 that Figure 32 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 29 that Figure 33 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 30 that Figure 34 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 35 models that illustratively number of plies is 1 layer；
Figure 36 models that illustratively number of plies is 2 layers；
Figure 37 models that illustratively number of plies is 3 layers；
Figure 38 models that illustratively number of plies is 4 layers；
Figure 35 that Figure 39 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 36 that Figure 40 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 37 that Figure 41 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 38 that Figure 42 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 43 shows the model that frequency of seismic wave is 10Hz；
Figure 44 shows the model that frequency of seismic wave is 35Hz；
Figure 45 shows the model that frequency of seismic wave is 50Hz；
Figure 46 shows the model that frequency of seismic wave is 65Hz；
Figure 43 that Figure 47 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 44 that Figure 48 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 45 that Figure 49 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 46 that Figure 50 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 51 shows the model that subdivision unit number is 80；
Figure 52 shows the model that subdivision unit number is 150；
Figure 53 shows the model that subdivision unit number is 230；
Figure 54 shows the model that subdivision unit number is 535；
Figure 51 that Figure 55 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 52 that Figure 56 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 53 that Figure 57 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 54 that Figure 58 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 59 shows practically to descend velocity structure model；
Figure 60 shows practically to descend model of the velocity structure model after earth's surface is smooth；
Figure 60 that Figure 61 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 61 that Figure 62 shows to be obtained with inventive method shows that model is correspondingMatrix；
Figure 59 and Figure 60 that Figure 63 shows to be obtained with the inventive method show the Complexity Coefficient curve of model, wherein,
Model shown in the corresponding diagram 59 of curve 1；
Model shown in the corresponding diagram 60 of curve 2；
Figure 64 shows the Complexity Coefficient curve that 1~experimental example of experimental example 5 and experimental example 7 obtain；
Figure 65 shows the Complexity Coefficient curve that experimental example 6 obtains.
Embodiment
Below by the present invention is described in detail, the features and advantages of the invention will become more with these explanations
To be clear, clear and definite.
Special word " exemplary " is meant " being used as example, embodiment or illustrative " herein.Here as " exemplary "
Illustrated any embodiment should not necessarily be construed as preferred or advantageous over other embodiments.
The present invention described below.
According to the quantitative analysis method of multilayer near surface Seismology and Geology complexity provided by the invention, as shown in figure 1, including
Following steps：
Step 1, form line and geology line of demarcation are obtained, the form line and the progress of geology line of demarcation to acquisition are discrete, obtain
Boundary element, determines the locus coordinate of each boundary element end points, and determines the space of respective nodes on each boundary element
Position coordinates.
In the present invention, the information gathered not only includes earth's surface terrain information, while also includes subsurface geology and demarcate
Face information, i.e. analysis method provided by the invention considers comprehensively, to not only allow for earth's surface landform to multilayer near surface Seismology and Geology
The influence of complexity, influence of the subsurface geology interface to the overall situation is also contains, analysis method is more comprehensive, objective, science.
In the present invention, the method for obtaining form line and geology interface information is not specially limited, can used existing
There is the method that any one in technology obtains form line and geology interface information, as geology infers method, well logging method and/or earthquake
Probe method etc..
Preferably, form line and geology line of demarcation are numbered, are easy to the identification of computer.In the present invention, over the ground
The number order in shape line and geology line of demarcation is not specially limited, it is only necessary to is assigned every form line and geology line of demarcation unique
Numbering.
In the present invention, the form line to acquisition and geology line of demarcation are carried out discrete with constant element, i.e., node is taken on border
The midpoint of unit, and the functional value of arbitrfary point is equal to the functional value at node on each boundary element, so as to obtain s phase
Mutually independent boundary element, and the locus coordinate of above-mentioned boundary element end points is determined, and then it is determined that each border is single
The correspondingly locus coordinate of node in member.
The present invention defines multilayer near surface Seismology and Geology complexity based on the border fluctuation integral equation comprising source point
Property coefficient, to evaluate and analyze multilayer near surface Seismology and Geology complexity.
Shown in the described fluctuation of the border comprising source point integral equation such as following formula (1), it turns the differential equation in region
Change borderline integral equation into, describe the synthesis wave field formed after source point disturbance, be that seismic wave passes in uniform dielectric
The governing equation broadcast,
Wherein,
Equal sign left side Section 1 and Section 2 represent boundary scattering field and source wave field successively, i.e., total wave field u (r) is by this two
Divide and together decide on.
The border fluctuation integral equation comprising source point can be described by model as shown in Figure 2：
Uniform dielectricIt is made up of irregular obstacle body Γ and interior zone Ω two parts,
R, r' and r0ForOn arbitrfary point,
Focus S (ω) is located at r0Place,
The π f of ω=2 are circular frequency,
F is frequency of seismic wave,
For the Green's function in two-dimensional background medium,
For Hankel function,
k0=ω/v0For background wave number,
v0For background velocity of wave,
The π of C (r)=θ (r)/2 is constant relevant with boundary geometry at boundary point r, by the border tangent plane of r points
ToAngle theta (r) determine, for smooth boundary, C (r)=0.5.
Because the border fluctuation integral equation (1) comprising source point is in whole zoningUpper establishment, therefore can be by r points
Moved to r' points on border, will equation left side Section 1 split after move on the right of equation so that borderline function u (r') and
Its normal derivativeSeparation, is easy to individually handle, then above formula is converted into following formula (2)
It is easy for narration, make the above formula equal sign left side be equal to M, then obtain following formula (3)
Border constant element is discrete, i.e., node is taken at the midpoint of boundary element, and arbitrfary point on each boundary element
Functional value is equal to the functional value at node, then above formula (3) can discrete be following formula (4) (for constant element C (r)=0.5),
Wherein,
u(rj') it is boundary element ΓjUpper arbitrfary point rj' place functional value；
I, j=1,2 ..., s is boundary element sequence number；
S is boundary element sum.
Step 2, the node that any one step 1 of selection determines is any to select what a step 1 determined as present node
Boundary element as current border unit, with exterior normal derivative of the Green's function on current border unit characterize present node with
Influencing each other between arbitrfary point on current border unit.
In step 2 of the present invention, the locus coordinate of each node obtained based on step 1 and each boundary element end
The locus coordinate of point, the node that any one step 1 of selection determines arbitrarily select a step 1 true as present node
Fixed boundary element calculates its lattice with arbitrfary point on current border unit as current border unit since selected node
Woods function, and exterior normal derivative of the Green's function for asking to obtain on current border unit, with this come characterize present node with work as
Influencing each other between arbitrfary point on front border unit.
Shown in described Green's function such as following formula (5),
Wherein,
For 0 rank Hankel function of the first kind,
k0=ω/v0For background wave number,
ω is circular frequency, v0For background velocity of wave,
R is present node position,
R' is arbitrfary point position on boundary element,
I and j represents boundary element sequence number, i.e. i, j=1,2 ..., s.
Step 3, current whole influence of the boundary element to wave field at present node is characterized with integration.
In the present invention, the exterior normal derivative that step 2 obtains is integrated, current whole side is characterized with obtained integration
Influence of boundary's unit to wave field at present node, wherein, shown in the expression formula such as following formula (6) of described integration,
Wherein,
ΓjFor serial number j boundary element,
N is ΓjOuter normal direction.
In the present invention, due to being form line and geology line of demarcation to be carried out with constant element discrete, therefore there are u (rj')
=u (rj), then above formula (6) can further be turned to
From formula (6), the integral term on the right of above formula (7) equal sign is to integrateThen have
Above formula (8) represented for current calculate node i, need to by its with all boundary elements (including unit sheet where node i
Body) once integrated, for there is the border of s node, need to calculate altogether s times integration, for present node i calculate terminate after according to
It is secondary to shift to next node, completed until all nodes calculate, total mark number is s2。
The present inventors have noted that in above formula (8), to all i, j=1,2 ..., s, occur once in j cyclic processes
I=j situation, now there are u (ri)=u (rj), it can be merged intoTherefore, redefine
Wherein,
For Kronecker functions, then M in formula (8)iCan abbreviation be further
Above formula (10) is applied to all boundary elements, then can obtainsIndividual equation, being write as matrix form is
So as to characterize influence of the boundary element of different occurrences in whole model to wave field at different nodes.
The quantitative analysis method of multilayer near surface Seismology and Geology complexity provided by the invention, mainly utilizes above-mentioned matrix side
The coefficient matrix of journey, i.e. the first matrix H are scattered analysis of complexity.Wherein,
The first described matrix H is,
Wherein,
Each element H of matrixijIt is calculated by following formula (13),
Wherein,
lijFor node riTo arbitrfary point rj' distance,
ForFirst derivative；
x1, y1And x1, y2It is boundary element ΓjThe actual coordinate of two end points；
K represents Gauss integration points；
ξkRepresent point position；
wkRepresent point weight coefficient；
likRepresent boundary element ΓiUpper node riWith boundary element ΓjUpper Gauss integration point ξkThe distance between.
Step 4, repeat step 2 and step 3, until characterizing the phase between all nodes and all boundary elements with integration
Mutually influence, form the first matrix H.
In the present invention, repeat step 2 and step 3, so as to calculate the lattice between all nodes and all boundary elements
Woods function, and exterior normal derivative of the Green's function on its boundary element is correspondingly tried to achieve, and then accumulated with correspondingly Gauss numerical value
Point characterize influencing each other between wave field caused by each node, i.e. characterize the complexity of wave field, now form first
Matrix H.
In step 4 of the present invention, influencing each other between each node and all boundary elements can be calculated one by one
Arrive, obtained information is comprehensive and careful.
Step 5, based on the first matrix H obtained in step 4, correspondingly scattered amplitude coefficient matrix is formedAnd
By scattered amplitude coefficient matrixElement summation and the ratio of matrix dimension be expressed as multilayer near surface Seismology and Geology complexity
Coefficient, realize multilayer near surface Seismology and Geology complexity quantitative analysis.
Because H-matrix is a complex matrix, its dimension represents the sum of boundary element, and each element can be recognized in matrix
The distance between to be to propagate component outside the wave field node boundary on the scene for node of showing up in normal direction from source node, it is with node,
Relative position and the geometric shape on border where node are closely related, and to each element modulus on the basis of plural H-matrix, will
Matrix H is converted into amplitude matrixIt can be easy to describe the problem in real number field, multilayer near surface Seismology and Geology is answered so as to realize
Polygamy quantitative analysis.
The numerical value for the multilayer near surface Seismology and Geology Complexity Coefficient that step 5 obtains is complicated with multilayer near surface Seismology and Geology
Property correlation, i.e. its numerical value it is bigger explanation multilayer near surface Seismology and Geology complexity it is stronger.
In the present invention, according to the multilayer near surface Seismology and Geology Complexity Coefficient selection seismic imaging obtained in step 5
Collecting method of method, the processing method for instructing seismic data and/or selection surface relief complex area etc., is such as utilized
Frequency domain migration side, when dominant frequency is in 30Hz, in general, when multilayer near surface Seismology and Geology Complexity Coefficient is less than
When 0.04, Fourier's seismic imaging method is walked using row；When multilayer near surface Seismology and Geology Complexity Coefficient between 0.04~
When 0.08, using single order variables separation seismic imaging method；When multilayer near surface Seismology and Geology Complexity Coefficient is more than 0.08,
Using Fourier-modal method seismic imaging method.
Therefore, in step 5 of the present invention, scattered amplitude coefficient is calculated on the basis of the first matrix H obtained in step 4
MatrixSo as to which complex field wave field is converted into real number field peak factor, to obtain scalar complexity factor, wherein,Matrix
Calculation such as following formula (14) shown in：
In the present invention, because the complexity of whole model is together decided on by the correlation between all boundary elements,
Therefore a scalar factor comp is defined, carrys out Direct Analysis multilayer according to the distribution characteristics of above-mentioned matrix element, the present inventor
Near surface Seismology and Geology complexity, shown in the defined formula such as following formula (15) of the scalar factor comp,
Wherein,
Comp represents multilayer near surface Seismology and Geology Complexity Coefficient；
I and j represents boundary element sequence number, i.e. i, j=1,2 ..., s；
|Hij| represent scattered amplitude coefficient matrixElement；
S represents scattered amplitude coefficient matrixDimension.
In the present invention, with scattered amplitude coefficient matrixDimension s carry out boundary element division numbers pair in removal process 1
Influenceed caused by multilayer near surface Seismology and Geology Complexity Coefficient, and then, the Complexity Coefficient of different scales model can be entered
Row compares.
According to the quantitative analysis method of multilayer near surface Seismology and Geology complexity provided by the invention, have below beneficial to effect
Fruit：
(1) complexity of whole model is together decided on by the correlation between all boundary elements；
(2) for same model, the seismic wave that can be directed to different frequency provides different complexity factors, realized
Scaling down processing；
(3) this method be particularly suitable for use in earth's surface seriously rise and fall and subsurface geology situation complex region, including mountain region, plateau,
Basin etc., can structural complexity evaluating that is relatively accurate and meticulously providing different models；
(4) to the collection of geological data, denoising, migration imaging in seismic data process have very important actual meaning
Justice；
(5) method provided by the invention, elementary solution between any two points and its is passed through in borderline exterior normal derivative
Cross what Gauss numeric integral was calculatedMatrix, scattering influence caused by all-pair present node on border is described, its
Advantage is to contain boundary geometrical shape information, is analyzed near surface structural complexity and provide possibility.
Experimental example
The mountain peak landform model of the different height of experimental example 1
In this experimental example, setting mountain peak is highly respectively 160m, 240m, 320m and 400m four models, is remembered respectively
For model (a), model (b), model (c) and model (d), as shown in Fig. 3~Fig. 6, the horizontal span of four models is
2000m, boundary element number are 200, and using its complexity of method quantitative analysis provided by the invention, its is correspondingMatrix is as schemed
Shown in 7~Figure 10, its gray value is incremented by with the increase of mountain peak height, its Complexity Coefficient as shown in curve 1 in Figure 64,
It is to be incremented by with the increase of mountain peak height, incremental Complexity Coefficient, which reflects complexity, to be increased and increase with relative relief.
The mountain peak landform model of the different gradient of experimental example 2
In this experimental example, four models gradually increasing of the setting mountain peak gradient, its gradient be respectively 25 °, 35 °, 45 ° and
65 °, model (a), model (b), model (c) and model (d) are designated as respectively, as shown in Figure 11~Figure 14, are provided using the present invention
Method quantitative analysis its complexity, its is correspondingMatrix is as shown in Figure 15~Figure 18, and its gray value is with the increasing of the mountain peak gradient
Add and be incremented by, its Complexity Coefficient is incremented by as shown in curve 2 in Figure 64, and with the increase of the mountain peak gradient.
The landform model of the varying level span of experimental example 3
In this experimental example, the landform model of four model varying level spans of setting, respectively 2000m, 1500m,
1000m and 500m, model (a), model (b), model (c) and model (d) are designated as respectively, as shown in Figure 19~Figure 22, utilize this
Its complexity of the method quantitative analysis of invention offer, its is correspondingMatrix is as shown in Figure 23~Figure 26, and its gray value is with level
The increase of span and successively decrease, its Complexity Coefficient is smaller from curve in Figure 64 3, horizontal span as shown in curve 3 in Figure 64
Complexity is stronger, i.e., when mountain peak is constant and horizontal component infinitely extends, the influence on mountain peak will gradually weaken.
The different mountain peak exponential models of experimental example 4
In this experimental example, the landform model of four model difference mountain peak numbers of setting, respectively 1,2,3 and 4
It is individual, it is designated as model (a), model (b), model (c) and model (d) respectively, height, span and the side on each mountain peak in four models
Boundary's unit number is respectively 360m, 2000m and 200, as shown in Figure 27~Figure 30, using method quantitative analysis provided by the invention its
Complexity, its is correspondingAs shown in Figure 31~Figure 34, its gray value acutely increases matrix with the increase of mountain peak number, reflection
Multimodal relief surface has very strong complexity, and this scattering very strong with multimodal relief surface in actual ground seismological observation makes an uproar
Sound is consistent, and its Complexity Coefficient is as shown in curve 4 in Figure 64.
The Different Strata exponential model of experimental example 5
In this experimental example, the landform model of four differently numbers of plies of setting, earth's surface and the equal random fluctuation of strata interface,
Layer in be uniform dielectric, as shown in Figure 35~Figure 38, the ground number of plies is followed successively by 1 layer, 2 layers, 3 layers and 4 layers, be designated as respectively model (a),
Model (b), model (c) and model (d), wherein stain represent the node of boundary element, wherein,
Figure 35 undergrounds are uniform dielectric model, and Figure 36, Figure 37 and Figure 38 the ground number of plies are respectively 2 layers, 3 layers and 4 layers, each mould
Type form line, geology interface form and border partition patterns are identical.
From Figure 35~Figure 38, with the increase of the irregularly number of plies, model becomes increasingly complex.
Using its complexity of method quantitative analysis provided by the invention, its is correspondingMatrix is as shown in Figure 39~Figure 42.
In this experimental example, the border motif of model is in irregular spread state, therefore correspondingMatrix distribution shows
More confusion is obtained, can not be according to its feature evaluation Construction of A Model characteristic.
The multilayer near surface Seismology and Geology complexity of Figure 35~Figure 38 institutes representation model is calculated using method provided by the invention
Coefficient, and four results are depicted as curve 5 in Figure 64, from curve in Figure 64 5, the Complexity Coefficient point of first three model
Not Wei 0.015144,0.031128,0.046847, three linearly increases trend substantially because form line and two it is non-
The form of Trap evaluation interface has similitude, and stratum average thickness is also not present caused by notable difference；And the 4th kind of mould
The Complexity Coefficient of type be 0.073751, from Figure 64 it can be seen that the slope over 10 significantly increase, cause the change it is main because
Element is the difficult point that the steep dip Angle Position of the trap layer in model, especially bottom and boundaries on either side is imaging, while is also aggravation
The principal element of complexity, this is consistent with theoretical prediction.
The earthquake wave pattern of the different frequency of experimental example 6
In this experimental example, four model landform of setting are identical, are taken from the first layer of the model in experimental example 5
With third layer geology interface, but frequency of seismic wave parameter is different, respectively 10Hz, 35Hz, 50Hz and 65Hz, is designated as mould respectively
Type (a), model (b), model (c) and model (d), as shown in Figure 43~Figure 46.
Identical geological model shows different complexities for the seismic wave of different frequency, and theory deduces that frequency is got over
Height, wavelength is smaller, and seismic wave is easier to be influenceed by construction, and model complexity is relatively also bigger.
Using its complexity of method quantitative analysis provided by the invention, its is correspondingMatrix as shown in Figure 47~Figure 50,Square
The distribution of battle array nonzero element is identical, and this is due to the result using same model；And the difference of element value then embodies
Influence caused by different frequency, can be seen that from Figure 47~Figure 50The gray value of matrix becomes larger, and can tentatively sentence
Disconnected overall complexity is in increase trend.
The multilayer near surface Seismology and Geology that Figure 65 accurately gives the model obtained using method provided by the invention is complicated
The result of property coefficient, from Figure 65, as frequency increases, complexity substantially rises, and slope of a curve and frequency interval
It is approximately positive correlation.
The different boundary discrete model of experimental example 7
Four models shown in Figure 51~Figure 54 are identical with Figure 50 institutes representation models, and difference is the fine journey of border subdivision
Degree (discrete after gained boundary element number) is gradually incremented by, and the boundary element number difference obtained by subdivision is larger, respectively 80,150,
230 and 535, model (a), model (b), model (c) and model (d) are designated as respectively, for testing border subdivision to complexity coefficient
The influence of calculating.
The error that model is discrete to be required between boundary element and actual boundary is as far as possible small, is used in the violent place of fluctuations
Small and more boundary element, and the gentle place that rises and falls is then with long and few boundary element, it is ensured that discrete model reflects reality substantially
The principal character of border model.
Using its complexity of method quantitative analysis provided by the invention, its is correspondingMatrix is as shown in Figure 55~Figure 58.
Using the Complexity Coefficient that method provided by the invention obtains as shown in curve 6 in Figure 64, Complexity Coefficient is basic
0.073 or so is maintained, influence of the border subdivision to result is very small.
Experimental example 8 practically descends velocity structure model
Figure 59 shows practically to descend velocity structure model, and its complexity is mainly manifested in two aspects：The landform seriously to rise and fall
With the near surface structure of complexity.
The complicated geology of this area is analyzed and evaluated with method provided by the invention.
Master stratum line of demarcation is sketched the contours of according to VELOCITY DISTRIBUTION first, recycles constant element to form line and stratum line of demarcation
Carry out discrete, the label of node and boundary element follows principle from left to right and from top to bottom.
Discrete results are as shown in figure 50, form 14 borders and 445 boundary elements altogether, and wherein black line represents border, black
Point represents boundary element end points.In addition, for comparative analysis, increase the confidence level of result, on the basis of realistic model over the ground
Shape line moves smoothly, so as to reduce influence of the landform to whole model complexity, and is used beyond actual elevation region
Neighborhood velocity of wave fills, and to ensure the integrality of former velocity structure, has eventually formed the contrast model shown in Figure 60.
Obviously, the geologic structure after form line is smooth is simpler, with same method division and divergent boundary, number of boundary
Amount is still 14, and boundary element is reduced to 265 with the dechirped of form line.
Method provided by the invention is applied to the two models, obtainedMatrix respectively as shown in Figure 61 and Figure 62, by
It is stronger in the randomness of this experimental example mesorelief and interface,Matrix lacks clear and definite correlation marker, therefore is only difficult to sense organ
Accurately distinguish both complexity difference.Selection frequency 10Hz, 35Hz, 50Hz and 65Hz calculate both Complexity Coefficients respectively,
As a result as shown in Figure 63,
Corresponding diagram 59 and Figure 60 obtain Complexity Coefficient respectively for curve 1 and curve 2 in Figure 63, can be seen that from Figure 63
Curve 1 in the top of curve 2, thus illustrates in the case of frequency parameter identical completely, is drawn with method provided by the invention
Complexity factor, practically descend velocity structure model really more complicated than the model after smooth surface, moreover, with seismic wave
The increase of frequency, the complexity of two models increase simultaneously, and this point equally matches with theory.
It can also be seen that, the smooth entire effect to whole model of earth's surface curve is not very big in this experimental example, but
Method provided by the invention shows the response good to structure change from both difference has numerically been accurately reflected.
Experimental example 9 draws Complexity Coefficient curve
By the Complexity Coefficient Drawing of Curve that 1~experimental example of experimental example 8 obtains on Figure 64, wherein,
Curve 1 represents the Complexity Coefficient that experimental example 1 obtains；
Curve 2 represents the Complexity Coefficient that experimental example 2 obtains；
Curve 3 represents the Complexity Coefficient that experimental example 3 obtains；
Curve 4 represents the Complexity Coefficient that experimental example 4 obtains；
Curve 5 represents the Complexity Coefficient that experimental example 5 obtains；
Curve 6 represents the Complexity Coefficient that experimental example 7 obtains.
From Figure 64, model features shown in 1~experimental example of experimental example 3, Complexity Coefficient corresponding to its complexity increase
It is almost identical to be incremented by slope, shows that the influence of these complicated sexual factors belongs to same magnitude.
In addition, the initial value of curve 1 to curve 3 gradually rises in Figure 64, illustrate flat mountain peak landforms complexity be weaker than it is narrow and
High mountain peak landforms.
The present invention is described in detail above in association with embodiment and exemplary example, but these explanations are simultaneously
It is not considered as limiting the invention.It will be appreciated by those skilled in the art that without departing from the spirit and scope of the invention,
A variety of equivalencing, modification or improvement can be carried out to technical solution of the present invention and embodiments thereof, these each fall within the present invention
In the range of.Protection scope of the present invention is determined by the appended claims.
Claims (9)
- A kind of 1. method of multilayer near surface Seismology and Geology complexity quantitative analysis, it is characterised in that this method includes following step Suddenly：(1) form line and geology line of demarcation are obtained, the form line and the progress of geology line of demarcation to acquisition are discrete, obtain border list Member, determines the locus coordinate of each boundary element end points, and determines that the locus of respective nodes on each boundary element is sat Mark；(2) for the node that any one step 1 of selection determines as present node, the border that any one step 1 of selection determines is single Member is used as current border unit, characterizes present node with exterior normal derivative of the Green's function on current border unit and works as front Influencing each other between arbitrfary point on boundary's unit；(3) influence of the current border unit to wave field at present node is characterized with integration；(4) repeat step 2 and step 3, until influencing each other between all nodes and all boundary elements is characterized with integration, Form the first matrix H；(5) based on the first matrix H obtained in step 4, corresponding scattered amplitude coefficient matrix is formedAnd scattering is shaken Width coefficient matrixElement summation and the ratio of matrix dimension be expressed as multilayer near surface Seismology and Geology Complexity Coefficient, realize Multilayer near surface Seismology and Geology complexity quantitative analysis.
- 2. according to the method for claim 1, it is characterised in that in step 1, form line and geology line of demarcation to acquisition Carried out with constant element discrete.
- 3. according to the method for claim 1, it is characterised in that in step 2,Shown in the relational expression of the Green's function such as following formula (5),Wherein,For 0 rank Hankel function of the first kind,k0=ω/v0For background wave number,ω is circular frequency, v0For background velocity of wave,R is present node position,R' is arbitrfary point position on boundary element,I and j represents boundary element sequence number, i.e. i, j=1,2 ..., s.
- 4. according to the method for claim 1, it is characterised in that in step 3, expression formula such as following formula (6) institute of the integration Show,Wherein,ΓjFor serial number j boundary element,N is ΓjOuter normal direction.
- 5. according to the method for claim 1, it is characterised in that in step 4, the first described matrix H is,Wherein,Each element H of matrixijThe Gauss numeric integral as shown in following formula (13) obtains,Wherein,lijFor node riTo arbitrfary point rj' distance,ForFirst derivative；x1, y1And x2, y2It is boundary element ΓjThe actual coordinate of two end points；K represents Gauss integration points；ξkRepresent point position；wkRepresent point weight coefficient；likRepresent boundary element ΓiUpper node riWith boundary element ΓjUpper Gauss integration point ξkThe distance between.
- 6. according to the method for claim 1, it is characterised in that described in step 5Shown in matrix such as following formula (14)：。
- 7. according to the method for claim 1, it is characterised in that in step 5, multilayer near surface Seismology and Geology Complexity Coefficient As shown in following formula (15),Wherein,Comp represents multilayer near surface Seismology and Geology Complexity Coefficient；I and j represents boundary element sequence number, i.e. i, j=1,2 ..., s；|Hij| represent scattered amplitude coefficient matrixElement；S represents scattered amplitude coefficient matrixDimension.
- 8. according to the method for claim 1, it is characterised in that the multilayer near surface Seismology and Geology complexity that step 5 obtains The numerical value of coefficient and multilayer near surface Seismology and Geology complexity correlation.
- 9. according to the method for claim 1, it is characterised in that further comprising the steps of：According to the multilayer obtained in step 5 Near surface Seismology and Geology Complexity Coefficient, to select desired seismic imaging method, seismic data processing method, surface relief The collecting method of complex area.
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