CN103869358A - Histogram equalization-based fault identification method and equipment - Google Patents

Abstract

The invention provides a histogram equalization-based fault identification method and equipment. The method comprises the steps of collecting seismic data; conventionally processing the seismic data to obtain a post-stack three-dimensional (3D) seismic data volume; determining the third-generation coherence property of the post-stack 3D seismic data volume; performing histogram equalization processing on the post-stack 3D seismic data volume according to the third-generation coherence property to obtain a post-stack 3D seismic data volume subjected to the histogram equalization processing; performing fault identification according to the post-stack 3D seismic data volume subjected to the histogram equalization processing. By taking the coherence property as a data foundation and enhancing the contrast of the line features of a large-sized fault and a medium-sized crack and a background in a coherence result, the aims of digging a hidden fault and improving the resolution ratio of dominant fault/crack information are achieved.

Description

A kind of fault recognizing method and apparatus based on histogram equalization

Technical field

The present invention, about oil-gas exploration technical field, particularly about the recognition technology of tomography, is a kind of method and apparatus of the fault recognizing based on histogram equalization concretely.

Background technology

Tomography, crack, solution cavity etc. are the important component parts of slit formation hydrocarbon-bearing pool (equal reservoir as non-in carbonate), and they play an important role in Hydrocarbon Formation Reservoirs process.Mature fault situation is one of key factor of controlling reservoir hydrocarbons " life, storage, lid, circle, fortune, guarantor ", and therefore, many large-scale oil pools are all closely related with mature fault in the world.Solution cavity is the geologic body jointly being formed by the geologic function such as tectonic movement, karst, has oil gas pooling function in carbonate reservoir, is one of important exploration targets in China Tarim Oilfield.Crack is important hydrocarbon migration channel, and its existence can either be linked up the reservoir space of dispersion as the reservoir of solution cavity System forming scale, can provide necessary permeability for each reservoir space inside again.Therefore, carry out the work of high-precision tomography/Crack Detection to support the follow-up exploratory development such as crack modeling, reservoir simulation research, significant.

The Typical Representative of tomography/Crack Detection technology is relevant series technique.Coherent technique results from the nineties in last century, has developed at present three generations's algorithm.First generation algorithm (being called for short C1 algorithm) based on simple crosscorrelation is to be proposed in nineteen ninety-five by Bahorich and Frmer, the second generation algorithm (being called for short C2 algorithm) that utilizes multiple tracks similarity is to be equaled to propose for 1998 by Marfurt, and the third generation coherent algorithm (being called for short C3 algorithm) based on feature structure is to be proposed by Gersztenkorn and Marfurt.

Wherein, the application precondition of C1 algorithm is comparatively harsh, and the defect of C2 algorithm is responsive and insensitive to the variation of lateral amplitude of vibration to waveform.Comparatively speaking, C3 algorithm has made up the two deficiency, in its 3-D data volume after skew, each sampling point is tried to achieve and the coherence of ambient data, forms a 3-D data volume that characterizes coherence, i.e. data coherency in computation window.So both can suppress continuity, and give prominence to uncontinuity, and can reflect quantitatively again the horizontal change of seismic signature, acquired results is more directly perceived than the geologic interpretation of seismic horizontal slice.The method is mainly used in more objective, finer fault interpretation, river course, sand body and crack prediction.But generally speaking, the noiseproof feature of coherence properties technology is not good, is easily subject to noise pollution, therefore often has the too low situation of tomography/crack and background contrasts around, this causes result images clear not to portraying of tomography/crack, even affects the judgement of explanation personnel to fault interpretation.For example, the mature fault region forming in time tectonic movement of many phases, migration parameter arranges the improper fault boundary energy that causes to be disperseed, and causes fault information to present cloud distribution etc.

Summary of the invention

Portraying in order to overcome the coherent technique that exists in prior art the defect that is subject to noise pollution aspect tomography/crack, the invention provides a kind of method and apparatus of the fault recognizing based on histogram equalization, take coherence properties as data basis, by large scale tomography, the line feature in mesoscale crack and the contrast of background in the dry and hard fruit of hardening constituent, realize the object of excavating Invisible fault, improving dominant tomography/crack information resolution.

One of object of the present invention is, a kind of method of the fault recognizing based on histogram equalization is provided, and comprising: acquiring seismic data; Described geological data is carried out to conventional processing, obtain poststack 3-d seismic data set; Determine the third generation coherence properties of described poststack 3-d seismic data set; According to described third generation coherence properties, described poststack 3-d seismic data set is carried out to histogram equalization processing, obtain histogram equalization poststack 3-d seismic data set after treatment; Carry out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.

One of object of the present invention is, a kind of equipment of the fault recognizing based on histogram equalization is provided, and comprising: seismic data acquisition device, for acquiring seismic data; Conventional processing device, carries out conventional processing for the geological data to described, obtains poststack 3-d seismic data set; Coherence properties determining device, for determining the third generation coherence properties of described poststack 3-d seismic data set; Histogram equalization treating apparatus, for described poststack 3-d seismic data set being carried out to histogram equalization processing according to described third generation coherence properties, obtains histogram equalization poststack 3-d seismic data set after treatment; Fault recognizing device, for carrying out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.

Beneficial effect of the present invention is, a kind of method and apparatus of the fault recognizing based on histogram equalization is provided, histogram equalization analysis in processing based on image, be applicable to strengthen the precision of poststack coherence properties fracture identification, take coherence properties as data basis, by large scale tomography in the dry and hard fruit of hardening constituent, the line feature in mesoscale crack and the contrast of background, realize and excavate Invisible fault, improve the object of dominant tomography/crack information resolution, can be used for improving the global contrast of image, situation the about especially contrast of valid data in image quite being approached, the tool effect that improves significantly.

For above and other object of the present invention, feature and advantage can be become apparent, preferred embodiment cited below particularly, and coordinate appended graphicly, be described in detail below.

Accompanying drawing explanation

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

The process flow diagram of the method for a kind of fault recognizing based on histogram equalization that Fig. 1 provides for the embodiment of the present invention;

Fig. 2 is the particular flow sheet of the step S104 in Fig. 1;

The structured flowchart of the equipment of a kind of fault recognizing based on histogram equalization that Fig. 3 provides for the embodiment of the present invention;

Fig. 4 is the structured flowchart of histogram equalization treating apparatus 400 in the equipment of a kind of fault recognizing based on histogram equalization provided by the invention;

Fig. 5 is X work area coherence properties time slice;

Fig. 6 is that X work area tomography/crack strengthens result;

Fig. 7 is Y work area coherence properties time slice;

Fig. 8 is that Y work area tomography/crack strengthens result.

Embodiment

Below in conjunction with the accompanying drawing in the embodiment of the present invention, the technical scheme in the embodiment of the present invention is clearly and completely described, obviously, described embodiment is only the present invention's part embodiment, rather than whole embodiment.Based on the embodiment in the present invention, those of ordinary skills, not making the every other embodiment obtaining under creative work prerequisite, belong to the scope of protection of the invention.

The Typical Representative of tomography/Crack Detection technology is relevant series technique.Third generation coherent algorithm (being called for short C3 algorithm) based on feature structure is to be proposed by Gersztenkorn and Marfurt.In its 3-D data volume after skew, each sampling point is tried to achieve and the coherence of ambient data, form a 3-D data volume that characterizes coherence, i.e. data coherency in computation window.So both can suppress continuity, and give prominence to uncontinuity, and can reflect quantitatively again the horizontal change of seismic signature, acquired results is more directly perceived than the geologic interpretation of seismic horizontal slice.The method is mainly used in more objective, finer fault interpretation, river course, sand body and crack prediction.But generally speaking, the noiseproof feature of coherence properties technology is not good, is easily subject to noise pollution, therefore often has the too low situation of tomography/crack and background contrasts around, this causes result images clear not to portraying of tomography/crack, even affects the judgement of explanation personnel to fault interpretation.For example, the mature fault region forming in time tectonic movement of many phases, migration parameter arranges the improper fault boundary energy that causes to be disperseed, and causes fault information to present cloud distribution etc.

Because above-mentioned technical matters, the present invention proposes a kind of method of the fault recognizing based on histogram equalization, the particular flow sheet that Fig. 1 is the method, and as shown in Figure 1, described method comprises:

S101: acquiring seismic data.In concrete embodiment, can adopt conventional method of seismic prospecting acquiring seismic data.

S102: described geological data is carried out to conventional processing, obtain poststack 3-d seismic data set.In concrete embodiment, conventional processing generally comprises the steps such as pre-service (comprise and separate volume, road editor, gain process, geometry definition), denoising and consistance processing, static correction (static correction and residual static correction), deconvolution, velocity analysis, normal moveout correction, stack, skew.Geological data is carried out to conventional processing and obtain poststack 3-d seismic data set, form is SEGY.Geological data is generally organized take seismic trace as unit, adopts SEGY stored in file format.

S103: the third generation coherence properties of determining described poststack 3-d seismic data set.In concrete embodiment, the third generation coherence properties (based on Eigenvalues Decomposition) of calculating poststack 3-D data volume can be carried out in the following way: extraction three-dimensional element grid, extraction time section, structure covariance matrix, calculating covariance matrix eigenwert, structure coherent value, loop iteration complete calculating;

S104: according to described third generation coherence properties, described poststack 3-d seismic data set is carried out to histogram equalization processing, obtain histogram equalization poststack 3-d seismic data set after treatment.Fig. 2 is the particular flow sheet of step S104.As shown in Figure 2, this step specifically comprises:

S201: extract two-dimensional time section along the isochronous surface of described third generation coherence properties.In concrete embodiment, the two-dimensional time section of extracting along the isochronous surface of third generation coherence properties can be passed through U _irepresent, wherein i is time-sampling number, and the concrete value of i can be set according to actual conditions, such as i=1, and .2 ... NTsmaple, NTsmaple is geological data maximum time hits, this step is extracted U altogether ₁to U _iindividual two-dimensional time section, U _icodomain domain of walker be [0,1].

S202: the codomain normalized of described two-dimensional time section, in the scope in gray scale territory, is obtained to the two-dimensional time section after normalized.

In concrete embodiment, by the two-dimensional time U that cuts into slices _icodomain normalized in [0, the 255] scope in gray scale territory, realize by formula (1):

$U_i\_\mathrm{new}=\mathrm{ronud}(\frac{U_i-U_i\_\min }{U_i\_\max -U_i\_\min }\×255)---\left(1\right)$

Wherein, U _ifor two-dimensional time section, i is time-sampling number, and ronud is the operational symbol that rounds up, U _i_ min is two-dimensional time section U _iminimum value, U _i_ max is two-dimensional time section U _imaximal value, U _i_ new is the two-dimensional time section after normalized.

S203: add up the number of times that in the two-dimensional time section after described normalized, same grayscale value occurs.In concrete embodiment, the two-dimensional time section U after statistics normalized _ithe number of times that in the matrix element of _ new, same grayscale value j occurs, is made as n _j.

S204: determine the probability that same grayscale value occurs.In concrete embodiment, add up the probability that gray-scale value j occurs, realize by following formula (2):

$p\left(j\right)=\frac{n_j}{n},j\∈\mathrm{0,1},...,L-1---\left(2\right)$

Wherein, U _ifor two-dimensional time section, j is that same grayscale value is at U _ithe serial number of middle appearance, n _jfor U _iin the number of times that occurs of j gray-scale value, n is U _igray scale element sum, P (j) is the probability that j gray-scale value occurs, L is U _iin do not repeat the number of gray-scale value.S205: determine the cumulative probability function that described probability is corresponding.

In concrete embodiment, the cumulative probability function that probability is corresponding is realized by formula (3):

$c\left(j\right)=\underset{k=0}{\overset{j}{\mathrm{\Σ}}}P\left(k\right)---\left(3\right)$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, k is the cumulative sequence number of probability, and P (k) is the probability that certain same grayscale value occurs, and c (j) is j the cumulative probability function that gray-scale value is corresponding.

S206: the two-dimensional time section after described normalized is carried out to histogram equalization processing, obtain equalization result.

In concrete embodiment, the following formula of foundation (4) is to the two-dimensional time section U after normalized _iin _ new, all sample points carry out histogram equalization processing:

$\mathrm{Ui}\_\mathrm{final}\left(l\right)=\mathrm{round}(\frac{c\left(l\right)-c_{\min }}{n-c_{\min }}\×(2^8-1))---\left(4\right)$

Wherein, Ui_final (l) is equalization result, and l is two-dimensional time section U _ithe subscript of middle element, ronud is the operational symbol that rounds up, c _minfor the two-dimensional time section U after normalized _ithe minimum value of Accumulation of Elements probability function in _ new, c (l) is the two-dimensional time section U after normalized _ithe corresponding cumulative probability of currentElement in _ new, 2 ⁸-1 is number of greyscale levels.

S207: adjust the gray threshold of described equalization result, obtain histogram equalization poststack 3-d seismic data set after treatment.

In concrete embodiment, adjust the gray threshold (generally take 20 as boundary) of equalization result Ui_final (l), to distinguish tomography/crack and background.Each two-dimensional time section Ui in poststack 3-d seismic data set is carried out to step S103, and each i time slice is write to new SEGY destination file, form histogram equalization poststack 3-d seismic data set after treatment.

As shown in Figure 1, the method also comprises:

S105: carry out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.Utilize to strengthen result and carry out fault recognizing mode and coherence properties is as good as, as qualitative identification tomography, plane fault are explained etc., but enhancing result is more clear aspect portraying at tomography, and multi-solution is few, uses convenient.

Be as mentioned above the method for a kind of fault recognizing based on histogram equalization provided by the invention, be intended to be concerned with and predict the outcome as basis, by strengthening the otherness of local tomography/crack area and environment value, further excavate the connotative fault/crack information in target area.

The present invention also proposes a kind of equipment of the fault recognizing based on histogram equalization, the structured flowchart that Fig. 3 is this equipment, and as shown in Figure 3, described equipment comprises:

Seismic data acquisition device 100, for acquiring seismic data.In concrete embodiment, can adopt conventional method of seismic prospecting acquiring seismic data.

Conventional processing device 200, carries out conventional processing for the geological data to described, obtains poststack 3-d seismic data set.In concrete embodiment, conventional processing generally comprises the steps such as pre-service (comprise and separate volume, road editor, gain process, geometry definition), denoising and consistance processing, static correction (static correction and residual static correction), deconvolution, velocity analysis, normal moveout correction, stack, skew.Geological data is carried out to conventional processing and obtain poststack 3-d seismic data set, form is SEGY.Geological data is generally organized take seismic trace as unit, adopts SEGY stored in file format.

Coherence properties determining device 300, for determining the third generation coherence properties of described poststack 3-d seismic data set.In concrete embodiment, the third generation coherence properties (based on Eigenvalues Decomposition) of calculating poststack 3-D data volume can extract in the following way three-dimensional element grid, extraction time section, builds covariance matrix, calculates covariance matrix eigenwert, builds coherent value, loop iteration completes calculating;

Histogram equalization treating apparatus 400, for described poststack 3-d seismic data set being carried out to histogram equalization processing according to described third generation coherence properties, obtains histogram equalization poststack 3-d seismic data set after treatment.Fig. 4 is the concrete structure block diagram of histogram equalization treating apparatus.As shown in Figure 4, histogram equalization treating apparatus specifically comprises:

Two-dimensional time section extraction module 401, extracts two-dimensional time section for the isochronous surface of the third generation coherence properties along described.In concrete embodiment, the two-dimensional time section of extracting along the isochronous surface of third generation coherence properties can be passed through U _irepresent, wherein i is time-sampling number, and the concrete value of i can be set according to actual conditions, such as i=1, and .2 ... NTsmaple, NTsmaple is geological data maximum time hits, this step is extracted U altogether ₁to U _iindividual two-dimensional time section, U _icodomain domain of walker be [0,1].

Normalized module 402, for by the codomain normalized of described two-dimensional time section to the scope in gray scale territory in, the two-dimensional time obtaining after normalized is cut into slices.

In concrete embodiment, by the two-dimensional time U that cuts into slices _icodomain normalized in [0, the 255] scope in gray scale territory, realize by formula (1):

$U_i\_\mathrm{new}=\mathrm{ronud}(\frac{U_i-U_i\_\min }{U_i\_\max -U_i\_\min }\×255)---\left(1\right)$

Wherein, U _ifor two-dimensional time section, i is time-sampling number, and ronud is the operational symbol that rounds up, U _i_ min is two-dimensional time section U _iminimum value, U _i_ max is two-dimensional time section U _imaximal value, U _i_ new is the two-dimensional time section after normalized.

Number of times statistical module 403, the number of times occurring for the two-dimensional time section same grayscale value of adding up after described normalized.In concrete embodiment, the two-dimensional time section U after statistics normalized _ithe number of times that in the matrix element of _ new, same grayscale value j occurs, is made as n _j.

Same grayscale value probability determination module 404, for the probability of determining that same grayscale value occurs.In concrete embodiment, add up the probability that gray-scale value j occurs, realize by following formula (2):

$p\left(j\right)=\frac{n_j}{n},j\∈\mathrm{0,1},...,L-1---\left(2\right)$

Wherein, U _ifor two-dimensional time section, j is that same grayscale value is at U _ithe serial number of middle appearance, n _jfor U _iin the number of times that occurs of j gray-scale value, n is U _igray scale element sum, P (j) is the probability that j gray-scale value occurs, L is U _iin do not repeat the number of gray-scale value.Cumulative probability function determination module 405, for determining cumulative probability function corresponding to described probability.

In concrete embodiment, the cumulative probability function that probability is corresponding is realized by formula (3):

$c\left(j\right)=\underset{k=0}{\overset{j}{\mathrm{\Σ}}}P\left(k\right)---\left(3\right)$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, k is the cumulative sequence number of probability, and P (k) is the probability that certain same grayscale value occurs, and c (j) is j the cumulative probability function that gray-scale value is corresponding.

Histogram equalization processing module 406, carries out histogram equalization processing for the two-dimensional time section to after described normalized, obtains equalization result.

In concrete embodiment, the following formula of foundation (4) is to the two-dimensional time section U after normalized _iin _ new, all sample points carry out histogram equalization processing:

$\mathrm{Ui}\_\mathrm{final}\left(l\right)=\mathrm{round}(\frac{c\left(l\right)-c_{\min }}{n-c_{\min }}\×(2^8-1))---\left(4\right)$

Wherein, Ui_final (l) is equalization result, and l is two-dimensional time section U _ithe subscript of middle element, ronud is the operational symbol that rounds up, c _minfor the two-dimensional time section U after normalized _ithe minimum value of Accumulation of Elements probability function in _ new, c (l) is the two-dimensional time section U after normalized _ithe corresponding cumulative probability of currentElement in _ new, 2 ⁸-1 is number of greyscale levels.

Gray threshold adjusting module 407, for adjusting the gray threshold of described equalization result, obtains histogram equalization poststack 3-d seismic data set after treatment.

In concrete embodiment, adjust the gray threshold (generally take 20 as boundary) of equalization result Ui_final (l), to distinguish tomography/crack and background.Each two-dimensional time section Ui in poststack 3-d seismic data set is carried out to step S103, and each i time slice is write to new SEGY destination file, form histogram equalization poststack 3-d seismic data set after treatment.

As shown in Figure 3, this identification also comprises:

Fault recognizing device 500, for carrying out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.Utilize to strengthen result and carry out fault recognizing mode and coherence properties is as good as, as qualitative identification tomography, plane fault are explained etc., but enhancing result is more clear aspect portraying at tomography, and multi-solution is few, uses convenient.

Be as mentioned above the identification of a kind of fault recognizing based on histogram equalization provided by the invention, be intended to be concerned with and predict the outcome as basis, by strengthening the otherness of local tomography/crack area and environment value, further excavate the connotative fault/crack information in target area.

Below in conjunction with specific embodiment, introduce in detail technical scheme of the present invention.Domestic certain X work area, the three-dimensional poststack data in Y work area are carried out experimental crack and strengthened analysis.

Fig. 5 is X work area coherence properties time slice, and as shown in Figure 5, in X work area, principal fault distribution trend is comparatively clear, but the borders such as secondary fault, solution cavity are smudgy.Method and apparatus through a kind of fault recognizing based on histogram equalization provided by the invention strengthens after processing, obtains the X work area tomography shown in Fig. 6/crack and strengthens result, and as shown in Figure 6, tomography/cracks at different levels information all obtains lifting in various degree.

Fig. 7 is Y work area coherence properties time slice, as shown in Figure 7, Y work area mature fault and broken serious, there is cloud fuzzy region in relevant result (after threshold value adjustment), and inner tomography distribution is portrayed unclear.The method and apparatus of a kind of fault recognizing based on histogram equalization provided by the invention strengthens after processing, obtain the Y work area tomography shown in Fig. 8/crack and strengthen result, as shown in Figure 8, result is including cloud region, and the resolution of tomography/crack, work area information is obviously promoted.

Above-mentioned facts have proved, the present invention is take seismic coherence attribute as data basis, be treated to master with histogram equalization, coordinate the means such as threshold value setting, can give prominence to the linear structure of tomography/crack information, the otherness of strengthening tomography/crack information and background, possesses the ability that simultaneously promotes dominant, recessive tomography/crack identification precision.

In sum, useful achievement of the present invention is: the method and apparatus that a kind of fault recognizing based on histogram equalization is provided, this technology can be used for improving the global contrast of image, situation the about especially contrast of valid data in image quite being approached, the tool effect that improves significantly.The present invention, take coherence properties as data basis, by large scale tomography, the line feature in mesoscale crack and the contrast of background in the dry and hard fruit of hardening constituent, realizes the object of excavating Invisible fault, improving dominant tomography/crack information resolution.

The method and apparatus of a kind of fault recognizing based on histogram equalization provided by the invention, its core connotation is:

(1) noise immunity is strong.Coherence properties after histogram equalization is processed, can removal of images in nebulous tomography fuzzy region, highlight the wire fault structure of this intra-zone;

(2) computation process is simple, is easy to realize, and can promote in real time two dimensional surface internal fissure precision of prediction, and easily to three-dimensional extended, supports the follow-up works such as tomography automatic tracing;

(3) possesses the ability of excavating part connotative fault/crack information.

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

Those skilled in the art can also recognize that the various functions that the embodiment of the present invention is listed are to realize by hardware or software the designing requirement of depending on specific application and whole system.Those skilled in the art can, for every kind of specific application, can make in all sorts of ways and realize described function, but this realization should not be understood to exceed the scope of embodiment of the present invention protection.

In the present invention, applied specific embodiment principle of the present invention and embodiment are set forth, the explanation of above embodiment is just for helping to understand method of the present invention and core concept thereof; , for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention meanwhile.

Claims (12)

1. a method for the fault recognizing based on histogram equalization, is characterized in that, described method specifically comprises:

Acquiring seismic data;

Described geological data is carried out to conventional processing, obtain poststack 3-d seismic data set;

Determine the third generation coherence properties of described poststack 3-d seismic data set;

According to described third generation coherence properties, described poststack 3-d seismic data set is carried out to histogram equalization processing, obtain histogram equalization poststack 3-d seismic data set after treatment;

Carry out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.

2. method according to claim 1, is characterized in that, according to described third generation coherence properties, described poststack 3-d seismic data set is carried out to histogram equalization processing, obtains histogram equalization poststack 3-d seismic data set after treatment and specifically comprises:

Extract two-dimensional time section along the isochronous surface of described third generation coherence properties;

The codomain normalized of described two-dimensional time section, in the scope in gray scale territory, is obtained to the two-dimensional time section after normalized;

Add up the number of times that in the two-dimensional time section after described normalized, same grayscale value occurs;

Determine the probability that same grayscale value occurs;

Determine the cumulative probability function that described probability is corresponding;

Two-dimensional time section after described normalized is carried out to histogram equalization processing, obtain equalization result;

Adjust the gray threshold of described equalization result, obtain histogram equalization poststack 3-d seismic data set after treatment.

3. method according to claim 2, is characterized in that, by the codomain normalized of described two-dimensional time section, in the scope in gray scale territory, the two-dimensional time section after the normalized obtaining is:

$U_i\_\mathrm{new}=\mathrm{ronud}(\frac{U_i-U_i\_\min }{U_i\_\max -U_i\_\min }\×255)$

Wherein, U _ifor two-dimensional time section, i is time-sampling number, and ronud is the operational symbol that rounds up, U _i_ min is two-dimensional time section U _iminimum value, U _i_ max is two-dimensional time section U _imaximal value, U _i_ new is the two-dimensional time section after normalized.

4. method according to claim 2, is characterized in that, the probability that the same grayscale value of determining occurs is:

$p\left(j\right)=\frac{n_j}{n},j\∈\mathrm{0,1},...,L-1$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, U _ifor two-dimensional time section, n _jfor U _iin the number of times that occurs of j gray-scale value, n is U _igray scale element sum, P (j) is the probability that j gray-scale value occurs, L is U _iin do not repeat the number of gray-scale value.

5. method according to claim 2, is characterized in that, cumulative probability function corresponding to described probability of determining is:

$c\left(j\right)=\underset{k=0}{\overset{j}{\mathrm{\Σ}}}P\left(k\right)$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, k is the cumulative sequence number of probability, and P (k) is the probability that certain same grayscale value occurs, and c (j) is j the cumulative probability function that gray-scale value is corresponding.

6. method according to claim 2, is characterized in that, the two-dimensional time section after described normalized is carried out to histogram equalization processing, and the equalization result obtaining is:

$\mathrm{Ui}\_\mathrm{final}\left(l\right)=\mathrm{round}(\frac{c\left(l\right)-c_{\min }}{n-c_{\min }}\×(2^8-1))$

Wherein, Ui_final (l) is equalization result, and l is two-dimensional time section U _ithe subscript of middle element, ronud is the operational symbol that rounds up, c _minfor the two-dimensional time section U after normalized _ithe minimum value of Accumulation of Elements probability function in _ new, c (l) is the two-dimensional time section U after normalized _ithe corresponding cumulative probability of currentElement in _ new, 2 ⁸-1 is number of greyscale levels.

7. an equipment for the fault recognizing based on histogram equalization, is characterized in that, described equipment specifically comprises:

Seismic data acquisition device, for acquiring seismic data;

Conventional processing device, carries out conventional processing for the geological data to described, obtains poststack 3-d seismic data set;

Coherence properties determining device, for determining the third generation coherence properties of described poststack 3-d seismic data set;

Histogram equalization treating apparatus, for described poststack 3-d seismic data set being carried out to histogram equalization processing according to described third generation coherence properties, obtains histogram equalization poststack 3-d seismic data set after treatment;

Fault recognizing device, for carrying out fault recognizing according to described histogram equalization poststack 3-d seismic data set after treatment.

8. equipment according to claim 7, is characterized in that, described histogram equalization treating apparatus specifically comprises:

Two-dimensional time section extraction module, extracts two-dimensional time section for the isochronous surface of the third generation coherence properties along described;

Normalized module, for by the codomain normalized of described two-dimensional time section to the scope in gray scale territory in, the two-dimensional time obtaining after normalized is cut into slices;

Number of times statistical module, the number of times occurring for the two-dimensional time section same grayscale value of adding up after described normalized;

Same grayscale value probability determination module, for the probability of determining that same grayscale value occurs;

Cumulative probability function determination module, for determining cumulative probability function corresponding to described probability;

Histogram equalization processing module, carries out histogram equalization processing for the two-dimensional time section to after described normalized, obtains equalization result;

Gray threshold adjusting module, for adjusting the gray threshold of described equalization result, obtains histogram equalization poststack 3-d seismic data set after treatment.

9. equipment according to claim 8, is characterized in that, the two-dimensional time section after the normalized that described normalized module obtains is:

$U_i\_\mathrm{new}=\mathrm{ronud}(\frac{U_i-U_i\_\min }{U_i\_\max -U_i\_\min }\×255)$

Wherein, U _ifor two-dimensional time section, i is time-sampling number, and ronud is the operational symbol that rounds up, U _i_ min is two-dimensional time section U _iminimum value, U _i_ max is two-dimensional time section U _imaximal value, U _i_ new is the two-dimensional time section after normalized.

10. equipment according to claim 8, is characterized in that, the probability that certain same grayscale value that described same grayscale value probability determination module is determined occurs is:

$p\left(j\right)=\frac{n_j}{n},j\∈\mathrm{0,1},...,L-1$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, n _jfor U _iin the number of times that occurs of j gray-scale value, n is U _igray scale element sum, P (j) is the probability that j gray-scale value occurs, L is U _iin do not repeat the number of gray-scale value.

11. equipment according to claim 8, is characterized in that, cumulative probability function corresponding to described probability that described cumulative probability function determination module is determined is:

$c\left(j\right)=\underset{k=0}{\overset{j}{\mathrm{\Σ}}}P\left(k\right)$

Wherein, j is that same grayscale value is at U _ithe serial number of middle appearance, k is the cumulative sequence number of probability, and P (k) is the probability that certain same grayscale value occurs, and c (j) is j the cumulative probability function that gray-scale value is corresponding.

12. equipment according to claim 8, is characterized in that, the equalization result that described histogram equalization processing module obtains is:

$\mathrm{Ui}\_\mathrm{final}\left(l\right)=\mathrm{round}(\frac{c\left(l\right)-c_{\min }}{n-c_{\min }}\×(2^8-1))$

Wherein, Ui_final (l) is equalization result, and l is two-dimensional time section U _ithe subscript of middle element, ronud is the operational symbol that rounds up, c _minfor the two-dimensional time section U after normalized _ithe minimum value of Accumulation of Elements probability function in _ new, c (l) is the two-dimensional time section U after normalized _ithe corresponding cumulative probability of currentElement in _ new, 2 ⁸-1 is number of greyscale levels.

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