CN100547438C - A kind of oil-gas exploration method and system - Google Patents
A kind of oil-gas exploration method and system Download PDFInfo
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Abstract
The invention provides a kind of oil-gas exploration method and system, be used to solve the problem of space flight or the oil-gas exploration of aviation high-spectrum remote-sensing.Said method comprising the steps of: utilize ground object spectrum data in the ground light spectrometer measurement Research district; Utilize digital camera to gather ground atural object data of description in the study area; Gather face of land sample data and measuring condition data; Utilize portable GPS to gather the tested atural object coordinate data in ground in the study area; Generate ground ground Object Spectra DataBase in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data; The hyperspectral imager that utilizes satellite or aircraft to carry is gathered atural object high-spectrum remote sensing data in the study area; Data and atural object high-spectrum remote sensing data to described ground ground Object Spectra DataBase are handled, and obtain oil-gas exploration target area data.
Description
Technical field
The present invention is about the oil-gas exploration technology, and particularly the technology of carrying out high-spectrum remote-sensing oil-gas exploration about the study area that has the little seepage phenomenon of oil gas on the face of land is a kind of oil-gas exploration method and system concretely.
Background technology
High spectrum resolution remote sensing technique is the remote sensing technology of new generation that grows up on traditional multispectral romote sensing technology basis the eighties in 20th century.Over more than 20 year, by the development of remote sensor technology and a large amount of space flight, airborne remote sensing experiments, make this technology progressively ripe, enter the application stage at present, obtained using widely at numerous areas such as reconnaissance geological survey and resource exploration, military surveillance, environmental change monitoring, precision agriculture, forest resourceies investigation.
By means of conventional gas and oil method of exploration (earthquake, gravity, magnetic force, electrical method and other materialization spy methods), the preparatory reconnaissance borehole success ratio is only about 30%; And whenever beat a bite disused well less, in northwest China, can save 1,000,000 prospecting prime cost at least.Therefore, one of technology that in hydrocarbon resources today in short supply day by day, that oil-gas exploration method efficiently becomes is very crucial, demand urgently developing.
In the prior art, the pilot study of aviation or the oil-gas exploration of space flight high-spectrum remote-sensing and practice begin; Yet still there is not the validity that case shows the oil-gas exploration of space flight high-spectrum remote-sensing.
Summary of the invention
The invention provides a kind of oil-gas exploration method and system, be used to solve the problem of aviation or the oil-gas exploration of space flight high-spectrum remote-sensing.Technical scheme of the present invention is:
A kind of oil-gas exploration method said method comprising the steps of: utilize ground object spectrum data in the ground light spectrometer measurement Research district; Utilize digital camera to gather ground atural object data of description, face of land sample data and measuring condition data in the study area; Utilize portable GPS to gather the tested atural object coordinate data in ground in the study area; Generate ground ground Object Spectra DataBase in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data; Utilize that satellite or aircraft carry hyperspectral imager gather atural object high-spectrum remote sensing data in the study area; Data and atural object high-spectrum remote sensing data to described ground ground Object Spectra DataBase are handled, and obtain oil-gas exploration target area data.
A kind of oil-gas exploration system, described system comprises: the ground light spectrometer is used for object spectrum data in ground in the measurement Research district; Digital camera is used to gather ground atural object data of description in the study area; Gather face of land sample data, face of land sample data and measuring condition data simultaneously; Portable GPS is used to gather the tested atural object coordinate data in ground in the study area; Portable computer is used for generating field ground feature spectra database in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data; The hyperspectral imager that satellite or aircraft carry is used to gather atural object high-spectrum remote sensing data in the study area; The oil gas anacom is used for the data and the atural object high-spectrum remote sensing data of described ground Object Spectra DataBase are handled, and obtains oil-gas exploration target area data.
Beneficial effect of the present invention is: the existence and the form of expression thereof that help to determine the little seepage phenomenon of study area oil gas by higher signal to noise ratio (S/N ratio) of open-air measured spectra and spectrally resolved power, guarantee the accurate extraction of the spectral signature of the relevant surface interference of oil gas, thereby finally set up the little seepage characteristic spectrum of study area oil gas model; Hyperion (the high spectrum of space flight) the higher spatial resolution of data helps to guarantee the surface interference that obtained by the high spectrum image analysis that satellite or aircraft carry continuity preferably on space distribution, then in conjunction with GEOLOGICAL INTERPRETATION, provide the space distribution rule of surface interference better.The present invention utilizes above-mentioned two kinds of data sources to analyze and research respectively, finally carries out analysis-by-synthesis, obtains the oil-gas exploration target area efficiently.
Description of drawings
Fig. 1 is an embodiment of the invention system construction drawing;
Fig. 2 is an embodiment of the invention ground survey equipment synoptic diagram;
Fig. 3 is an embodiment of the invention data base logic structural drawing;
Fig. 4 is embodiment of the invention high spectrum image analysis process figure;
Fig. 5 is pretreatment process figure;
Fig. 6 is the band process flow diagram;
Fig. 7 chooses GCP point process flow diagram;
Fig. 8 is a small echo PCA mixing dimensionality reduction process flow diagram;
Fig. 9 is a small echo Fisher feature extraction process flow diagram;
Figure 10 is based on small echo PCA classification process figure;
Figure 11 is based on small echo Fisher classification process figure;
Figure 12 is based on the little seepage diagnostic of oil gas local feature taxonomic structure block diagram;
Figure 13 is a prediction exploration target area process flow diagram.
Embodiment
Below in conjunction with description of drawings the specific embodiment of the present invention.As shown in Figure 1, a kind of oil-gas exploration system of the embodiment of the invention comprises: the ground light spectrometer is used for object spectrum data in ground in the measurement Research district; Digital camera is used to gather ground atural object data of description in the study area; Gather face of land sample data and measuring condition data simultaneously; Portable GPS is used to gather the tested atural object coordinate data in ground in the study area; Portable computer is used for generating field ground feature spectra database in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data; The hyperspectral imager that satellite or aircraft carry is used to gather atural object high-spectrum remote sensing data in the study area; The oil gas anacom is used for the data and the atural object high-spectrum remote sensing data of described ground Object Spectra DataBase are handled, and obtains oil-gas exploration target area data.
The ground light spectrometer of the embodiment of the invention is a FieldSpec Pro FR spectrometer, and the hyperspectral imager that satellite or aircraft carry is the high spectrometer of Hyperion of going up lift-launch that EO-1 satellite or aircraft carry.Open-air spectral measurement of the invention process fully takes into account the influence of factors such as cloud amount, sun altitude, illumination, and is true in order to the complete sum that guarantees open-air measured spectra data; And Hyperion is at present unique at the collection high spatial of rail and the commercial space borne imagery spectrometer of high spectral resolution power.Unusually have a higher spatial resolution by what the Hyperion high-spectral data obtained, and then can obtain the unusual distribution of the little seepage symbiosis of more reliable oil gas.
As shown in Figure 2, utilize the spectral value of ground light spectrometer, can adopt the equipment listed as table 1 to the various cover types of open-air (synchronously) mensuration.Table 1
| Title | Quantity (platform) |
| The open-air spectro-metre of ASD | 2 |
| Handhold GPS | 2 |
| Digital camera | 2 |
| Notebook computer | 3 |
| Mitsubishi's offroad vehicle | 2 |
Wherein, FieldSpec Pro FR spectrometer correlation technique parameter is as shown in table 2:
Table 2
Wherein, the high spectrometer correlation technique of Hyperion parameter is as shown in table 3:
Table 3
When ground survey, the following measurement scheme of selectable employing: each measuring point is gathered 5 ground object target data, and 5 on-gauge plate data are carried out detailed geologic description and record to each measuring point, gather each 1 in distant view and close shot photo, and measuring point is sampled according to actual conditions and needs.
Surveying work is chosen, and weather fine, that cloud amount is little is carried out the work, or the overcast to clear back sky brightness period big, that solar illumination is more stable carries out.Carry out data preparation, be about to institute's photometry spectrum and photo and be organized into electronic document, guarantee the order of mass data by survey line, measuring point.And eyeball and sampled point pressed coordinate projection to design drawing, make real material figure.
Carry out the analysis of mineral X-ray diffraction for pedotheque and (wherein choose the sample of 1/5 underground 1m in the study area collection, be used for comparing intensity of anomaly) with face of land sample, by statistical study for chemical analysis (X-ray diffraction analysis) result, can determine whether study area exists the little seepage phenomenon of oil gas, and it is in the form of expression on the face of land.
Utilize C# and Access to set up ground Object Spectra DataBase.Wherein: data, ground feature spectral measurement data, sample data etc. examined in the field geology accent carry out centralized stores, management, inquiry; The conceptual model of spectra database design is made of data entity, database function (management, processing, analysis and application model etc.) and database application.According to the invention demand, its data processing mainly adopts ENVI, therefore, must set up seamless link with ENVI to the interface of database.
Data base logic structure and physical arrangement are seen Fig. 3, have in it:
1) ground object target is measured description list
When being used for record, to the general description of all atural object general character, as locus (longitude and latitude, height above sea level), measuring position, surveying instrument etc. to the atural object target measurement.
2) object spectrum record sheet
Only the spectroscopic data of sample measured in record, and spectral signature is described.
3) sample attribute description table
Face of land sample barment tag is described, as structure, structure, geologic time, alteration features etc.
4) atural object physics constitutes table
Describe the formation of institute's geodetic thing, the component of its number percent is to be obtained by the sample chemical analysis.
5) measuring equipment parameter list
Institute's instrument that uses and technical indicator parameter thereof when being recorded in open-air spectral measurement.
6) measurement environment parameter list
As shown in Figure 4, during measurement target, the atmospheric parameter of record object background, the parameter extraction when being used for that the Hyperion remotely-sensed data carried out radiant correction.
Hyperion is a push-broom sensor.It has 220 independently spectrum channels, and spectral coverage is 356～2577nm.Level 1R spoke brightness data has 242 spectral coverages, wherein 198 spectral coverages are through calibration, because visible light/near infrared (VNIR) and short-wave infrared (SWIR) two sensors focal plane wave band have part to overlap, so have 196 autonomous channels, comprise that the yNIR interval is 8～57 spectral coverages, and the SWIR interval is 79～224 spectral coverages.The reason that the part spectral coverage fails to calibrate is that detector is too low in the response of those several spectral coverages.The spectrally resolved power of the spectral coverage of Hyperion data is 10nm, and spatial resolution is 30m, is well suited for the needs of geological prospecting.
Remote sensing digital image is made up of a series of pixels, and each pixel is represented with a numerical value (DN, Digital Number), is called the brightness value or the gray-scale value of pixel.
The storage format of high-spectral data is divided into BSQ (Band Sequential Format), BIL (Band Interleaved by Line Format), BIP (Band Interleaved by PixelFormat).As Fig. 4, shown in Figure 5, this chapter at first saves as ENVI standard format BIL with Hyperion L1R data, selects wherein effective 196 wave bands then, next carry out the pre-service of Hyperion data, comprise and remove dead pixel row, removal band noise, denoising, radiant correction etc.Why Hyperion image preconditioning technique thinking is placed on noise reduction after the radiant correction as shown in Figure 5, is because radiant correction can amplify noise usually, reduce signal to noise ratio (S/N ratio).(rotation angle is about 12 °) the inevitable original spectrum information that change high-spectral data greatly has influence on follow-up image classification precision for the resampling of original DN value in the geometry correction of Hyperion data.Therefore, the geometry correction of present embodiment is not carried out in pre-service, but the one-tenth diagram data after atmosphere radiation correction, classification, information extraction is proofreaied and correct.
Because final goal of the present invention is that the faint oil gas symbiosis in the extraction study area face of land is unusual, and the spatial resolution of Hyperion image is 30m, large-area homogenizing makes hydrocarbon characteristic fainter, therefore in the design of the image Preprocessing Algorithm of present embodiment, must assurance accurately remove noise, reduce the loss of useful information as far as possible; That is: can not be that cost is finished noise reduction process to sacrifice useful information.
In 196 available spectral coverages of Hyperion data, there is bad detection unit in individual channels, causes its corresponding sampled pixel row not respond, and the DN value is zero.These pixel columns that do not respond are called the dead pixel row.
In 196 available spectral coverages of Hyperion data, B94-col 92 (94 spectral coverages, 92 row, down together), B99-col 91, B116-col 137, B165-col 147, B190-col 112, B200-col 7, B201-col 7, B 203-col 114 are the dead pixel row.If remove at the pretreatment stage pixel column of not checkmating, then these row are bound to be used as unusually when feature extraction and graphical analysis and extract, and this is with the classification results of serious interfere with subsequent.
Because the spectrally resolved power of Hyperion data is higher, be 10nm, the variation of DN value can be similar to and regard linear change as between the spectral coverage of front and back, so present embodiment has adopted the spectrum approach based on linear interpolation---will exist the spectral coverage of dead pixel row to proofread and correct spectral coverage as need, utilize the DN value that needs to proofread and correct spectral coverage front and back spectral coverage, carry out linear interpolation arithmetic, to dead pixel row pixel assignment.
For the Hyperion image, also can adopt the method for spatial neighborhood interpolation, promptly the DN values of two row about need correction spectral coverage dead pixel row are carried out linear interpolation arithmetic, realize the assignment of dead pixel row.
The band noise is a kind ofly periodically to repeat noise phenomenon in image in spatial domain, mainly be since in the spectrometer the aging and sensor of inconsistent, some small faults of data system target decided at the higher level but not officially announced of the response function of each CCD in the spectral response district, instrument and element several main causes such as random fluctuation of signal response are caused.
The arrangement mode of CCD is perpendicular to the flight path direction in the Hyperion spectrometer system, and adopts the earth observation mode of push-broom type.Under the condition of same spectra amount of incident,, promptly be listed as to the band noise because the spectral response value difference of each sensor in each row has caused occurring perpendicular striped on each spectral coverage.
Band noise remove method adopts: the filtering method of gain and deviation algorithm, histogram matching method, polynomial fitting method, principal component transform method, square matching method, space-frequency domain etc., wherein:
Present embodiment adopts gain and deviation algorithm, gain is the response heterogeneity of coming each detection unit of tuning detector array by calculated gains and deviation with deviation algorithm, algorithm is selected a reference value (Reference Value), make the average of each row and standard deviation all more near reference value, thereby reach the purpose of removing the band noise.
Present embodiment selects for use near the average of the neighborhood that some row are constituted the pending row and standard deviation as with reference to value, makes behind the removal band, and new DN value is more near near pixel value it, thereby farthest recovers original DN value, is the part and removes strip coating method.
Based on the statistical study for VNIR in the Hyperion data and SWIR wave band, find: the band noise among the former independent one is listed now usually, and the common several row of the band noise among the latter occur continuously and present a band noise block.Thus, carry out the part when going the bar tape handling, adopt the neighborhood of different in width to come the statistical-reference value for the data of two wave bands.Obviously the width neighborhood of SWIR wave band should be wideer.
The a few pixels row have very significantly band feature in the image simultaneously, and are not the dead pixel row, and the existence of these row brings than mistake for the statistics of reference value.These row are called remarkable band, and utilize the threshold value of formula (1) definition that it is detected, by the intermediate value of neighborhood that adjacent several row constitute it is adjusted then; In addition, several row on border, the image left and right sides often have big noise, because it is positioned at the border of spectral coverage image, carries out the part and remove band so can't get the neighborhood of its several row in left and right sides, adopt the gain and the deviation of overall strip coating method statistics that it is revised:
In the formula, μ
jAnd σ
jBe respectively each column mean and standard deviation, l
Med(μ
j) and l
Med(σ
j) be respectively adjacent several row the constitute average of neighborhood and the intermediate value of standard deviation.
Polynomial fitting method is that based on the statistics to each row column mean of spectral coverage, the method for employing fitting of a polynomial obtains immediate matched curve.The column mean after the match and the difference of former column mean are as correcting action, and each pixel of this spectral coverage deducts the correcting action of its column, and that has promptly realized this spectral coverage image goes the bar tape handling.
When this method is suitably chosen the fitting of a polynomial number of times, can be when further removing band noise (showing as burr and sudden change on the column mean curve), keep well or recover original gradation of image distributed intelligence.
So far, what present embodiment had been set up the Hyperion data goes the band flow process, as Fig. 6.It should be noted that if the high cloud of gray-scale value occurs on the image perhaps water body in large that gray-scale value is extremely low and Yun Yingshi must consider their influences to the integral image gray-scale value separately, can not handle so that conventional method is unified.Fairly simple feasible method is, utilizes mask (being that MASK covers layer) technology, makes the pixel that characterizes this type of material not participate in statistics, in order to avoid make and go gradation of image distribution distortion after the bar tape handling.
The remote sensor (Hyperion) that carries from satellite or aircraft extracts the information on the face of land itself received atmosphere of big pneumatic jack and face of land mixed signal, this process is called as the atmosphere radiation correction.Have only the earth surface reflection rate that obtains through atmosphere radiation correction accurately, just can be used as the intrinsic parameters of reflection terrestrial materials The Nomenclature Composition and Structure of Complexes; This earth surface reflection rate really is independent of the sun and atmospheric condition, becomes the basis of further applied research.
Carrying out the atmosphere radiation timing of remotely-sensed data, utilize the special modality or the combination of channels of the high spectral information that same remote sensor (Hyperion) obtains, extract such as necessary input parameters of atmosphere radiation transmission course such as atmosphere vapour content, atmospheric ozone content, atmospheric aerosol optical thicknesses, utilize the radiation delivery model that observation data is carried out accurate radiation again and proofread and correct.The characteristics of this disposal route are: the atmospheric optics characterisitic parameter that is used for the atmosphere radiation correction comes from the inverting of measurement data simultaneously of same sensor, has very high timing tracking accuracy; Simultaneously, can obtain the space distribution of the frequent atmosphere vapour content of change in time and space, improve the atmosphere radiation correction accuracy greatly by pixel ground inverting atmosphere vapour content.
The signal to noise ratio (S/N ratio) of Hyperion data is according to the spectral coverage difference and the difference great disparity.At the VNIR wave band, its signal to noise ratio (S/N ratio) can reach 190: 1, and at the SWIR wave band, its signal to noise ratio (S/N ratio) is lower than 40: 1.Except aforesaid band noise, also there are system noise and random noise in the Hyperion data; Simultaneously, atmosphere radiation is proofreaied and correct the noise that must bring some.
Wavelength band of the present invention is the minimum SWIR zone of signal to noise ratio (S/N ratio), present embodiment adopts EFFORT (Empirical Flat Field Optimized ReflectanceTransformation) algorithm to remove system noise, adopt MNF (Minimum NoiseFraction) algorithm to remove random noise then, at last atmosphere radiation is proofreaied and correct the more spectral coverage of residual error that is produced and remove (this spectral coverage is usually located at the water vapor absorption wave band), thereby selected 155 spectral coverages (seeing Table 4) have finally been finished the pre-service of Hyperion data.
Table 4 is the finally selected wave band of pre-service:
Table 4
Owing to be subjected to the restriction of the correction accuracy in measuring method, sensor, used model and the data handling procedure, in high spectrum reflection rate data, system noise or error can occur usually.These cumulative errors may only account for several percentage points of each spectral coverage, but but can cause the realistic accuracy of the absolute precision of entire emission rate data well below raw data.When measuring with the appropriateness finishing, adopt the EFFORT algorithm to carry out the reflectivity conversion, thereby make the wave spectrum curve be similar to the wave spectrum curve of true atural object more reflectivity data.
The MNF algorithm is twice stacked principal component transform in essence.Conversion for the first time (based on the noise covariance matrix of estimating) is used for separating and readjusting the noise of data; Second step was the standard principal component transform to the noise whitening data.Thus, data space is divided into two parts: a part is big eigenwert characteristic of correspondence image, and other parts then are the noise images of less eigenwert correspondence.Because the data signal to noise ratio (S/N ratio) difference of Hyperion data VNIR and SWIR wave band is very big, thus in the MNF noise reduction process, both are handled respectively, and then it is synthesized.
Remote sensing images comprise serious geometry deformation usually.The systematicness geometry deformation is regular and foreseeable, but so the mathematical formulae or the model of application simulation remote-sensing flatform and remote sensor internal modification predict.Present embodiment adopts the polynomial expression bearing calibration to carry out geometry correction to the Hyperspectral imaging of 8 scape Hyperion.Target data is the one-tenth diagram data (ground pixel resolving power is 30m) after atmosphere radiation correction, classification, information extraction.Choose ground control point during geometry correction on the ASTER satellite image, every scape Hyperion image is chosen 20～30 reference mark, chooses 160～240 ground control points in the whole workspace; The distribution of reference mark on topomap is more even.Its process is as shown in Figure 7:
Utilize the remote sensing images of distortion and the GCP corresponding point between the benchmark image (ASTER), try to achieve this geometric distortion model (least square method quadratic polynomial calibration model), utilize this model to carry out the correction of geometric distortion then.The concrete reason that distorts is not considered in this correction, and only considers how to utilize distortion model to come correcting image.
During image mosaic, if can find that to the image direct splicing line of cut (being splicing line) transition is obvious, the difference of both sides brightness is fairly obvious.This is the condition difference of obtaining owing to remote sensing image, and different scape images exist in some aspects than big-difference, as color, brightness etc.In order to make the continuity of mosaic image be enhanced, weaken near the notable difference of line of cut, adopt various seamless transitions algorithms, emergence line of cut peripheral region during image mosaic mostly.Algorithm commonly used is: median filtering method, Wavelet Transform, weighting smoothing method etc.
What present embodiment adopted is the weighting smoothing method: (x is y) by the gray-scale value DN of corresponding point in two width of cloth images for gray values of pixel points DN in the image overlap area
1(x, y) and DN
2(x, y) weighted mean obtains, that is:
DN(x，y)＝k×DN
1(x，y)+(1-k)×DN
2(x，y) (2)
Wherein k is the gradual change factor, satisfies condition: 0＜k＜1.In the certain limit of the line of cut left and right sides, set smooth region, in the zone point go up k value by from line of cut apart from and gradual change, the k value is 0.5 on line of cut.Realized thus in the overlapping region by left-to-right level and smooth splicing.
Because the Hyperion image that uses is long narrow rectangle, the overlapping region between two scapes is all comparatively long narrow, and the width size variation is bigger up and down.Therefore, improve for the weighting smoothing method.Get between each the most left point of row of image overlap district and the rightest point (being spaced apart L) and do linear weighted function and smoothly sprout wings when handling, its smooth region has been contained image overlap area substantially.
This method representation is:
Wherein, x ', the x x ' that " is respectively two endpoint locations that y lists the overlapping region, L=x ".
When carrying out feature extraction, the algorithm that present embodiment adopted is that the pairing spectrum of each pixel in the image is carried out wavelet transform, and this not merely can reduce data volume, also can keep trickle spectral signature difference simultaneously.Extract the demand of faint hydrocarbon characteristic at Hyperion data characteristic and the present invention, concrete algorithm flow is seen Fig. 8.
At first, choose suitable wavelet basis.This paper selects for use multiple wavelet basis to compare, and each original spectrum is carried out n layer wavelet decomposition.Because the details wavelet coefficient overwhelming majority after first and second layer decomposition is a noise information, so ignore.Approximation wavelet coefficients (low-frequency information) after keeping the n layer and decomposing and the l～n (n=4 herein, the details wavelet coefficient (high-frequency information) after l=3) layer decomposes.
Then the wavelet coefficient that remains is carried out the decorrelation of spectral information between spectral coverage, promptly carry out the PCA computing; According to the needs of nicety of grading, need to select the major component number of reservation.
The sharpest edges of mixing transformation are to be that final classification considers the local spatial information between adjacent class pixel, this be use merely the small echo dimensionality reduction can not provide.Another advantage that wavelet decomposition combines with PCA can reduce the high-spectral data dimension exactly greatly, reduces calculated amount, improves counting yield.
Present embodiment is selected suitable parameter (as wavelet basis, the decomposition number of plies and approximation characteristic number etc.), to realize small echo Fisher feature extraction/SFF feature selecting system.Its implementation procedure as shown in Figure 9.Concrete steps are as follows:
At first, the original spectrum signal is carried out n layer wavelet decomposition, keep the approximation wavelet coefficients after the n layer decomposes, and l is to the detail signal (because the high-frequency information after first and second layer decomposition mainly shows as noise, so give up) of n layer.N=4 herein, l=3.
Secondly, the approximate information and the detailed information that remain are carried out Fisher ' s linear identification, but can keep c-1 recognition feature (c is the classification number of actual atural object) at most.But keep c-1 recognition feature.
Once more, calculate the autocorrelation value of m approximation wavelet coefficients, obtain m autocorrelation characteristic.
At last, but m approximation characteristic originally, a m autocorrelation characteristic are combined with c-1 recognition feature, form the proper vector that contains 2m+c-1 feature.Use above-mentioned SFF feature selection approach that 2m+c-1 feature carried out the feature screening, generate the optimal characteristics collection.
Assorting process based on small echo PCA is seen Figure 10, and concrete steps are as follows:
1) target image is carried out rough segmentation, utilize method rough segmentation 6～7 class atural objects of K-average automatic cluster, obtain K-average classification chart.
2) the rough segmentation result is analyzed.Observe the distribution situation of all kinds of atural objects on the classification chart,, from image, directly choose all kinds of ground object sample in conjunction with tone corresponding on the colored composite diagram with all kinds of atural objects.
3) characteristic image (preceding 5 major components that keep after the feature extraction) is carried out maximum likelihood classification, i.e. Subdividing Processing.Analyze the spectral characteristic and the geographical geological condition of all kinds of atural objects, determine merging or segmentation relation between all kinds of atural objects, choose region of interest then and cover layer processing (being mask technique).
4) only region of interest is carried out automatic K-mean cluster, thereby new training sample is provided, carry out maximum likelihood classification again.
5) continuous repeating step 3), 4), when classification results is comparatively satisfied, output category figure.This figure is panorama classification chart (many atural object classification), comprises the classification results in the zone of loseing interest in.
6) owing to the objective of the invention is to obtain zone with the little seepage surface interference of the oil gas in gas field district feature similarity, so during in conjunction with the position in known gas field district and segmentation with the gas field district regional classification situation of coincideing, selected gas field district sample, and constantly change likelihood ratio, only adopt the smart branch of maximum likelihood method for this zone.
Assorting process based on small echo Fisher is seen Figure 11.
Assorting process based on the little seepage diagnostic of oil gas local feature is seen Figure 12, and concrete steps are as follows:
1) at first selects B195～B215 totally 21 spectral coverages, carry out envelope and remove;
2) extract position, the degree of depth and the area information at the spectral absorption peak of each pixel correspondence respectively;
3) obtain the pixel that the absorption peak position is positioned at (2.193,2.203,2.213 μ m);
4) the absorption peak depth characteristic of the pixel that obtains further analytical procedure 3), the bigger pixel of the output absorption peak degree of depth;
5) the absorption peak area features of the pixel that obtains analytical procedure 4 next) is exported the bigger pixel of absorption peak area, finally finishes the delineation of the clay mineral alteration exceptions area of high spectrum image.
When differentiating based on the depth characteristic of absorption peak, should be by means of the space distribution of class internal standard difference curve and pixel, the prudent minute quantity pixel (1%～2%) of investigating the degree of depth and area maximum, the error point that these pixels are normally caused by objective factor (cloud, humidity).If its corresponding class internal standard difference is very big, promptly distance is big in the class, illustrates that the each point feature difference is very big in the class, and therefore the cluster weak effect is removed it as error information.
By ground survey, there is the little seepage phenomenon of oil gas in study area, and its form of expression on the face of land is that the clay mineral alteration is unusual, the carbonate alteration is unusual, and hydrocarbons is unusual; Analysis based on 799 face of land spectrum of field actual measurement, confirm the feasibility of the spectrum ground detection that the little seepage of oil gas causes in the study area face of land symbiosis is unusual, verified the validity of the little seepage characteristic spectrum of oil gas model in the study area that comprises 3 class sorting algorithms that this paper chapter 5 proposed.
Analysis by for the 8 scape Hyperion images that cover study area proves that the little seepage phenomenon of the existing oil gas of study area can detect by the high-spectrum remote-sensing method; Set up 3 kinds of high-spectrum remote sensing categorizing systems (comprise categorizing system, based on the categorizing system of small echo Fisher and based on the categorizing system of the little seepage diagnostic of oil gas local feature), finished the preliminary delineation of the little seepage of oil gas face of land symbiosis exceptions area based on small echo PCA.Above-mentioned 3 kinds of categorizing systems have obtained to analyze with open-air measured spectra the symbiosis abnormal law of basically identical.
As previously mentioned, open-air measured spectra and Hyperion data respectively have superiority.In order to give full play to the advantage of two kinds of data sources, and mutual verification guide on analytical algorithm, the face of land symbiosis anomaly analysis result that the little seepage of the oil gas of the two is caused, in addition comprehensive, auxiliary geologic interpretation with necessity, the oil-gas exploration target area in the final forecasting research district.
Based on the data analysis result of open-air measured spectra and satellite or aircraft lift-launch, the density information of the space distribution of the symbiosis abnormity point that the little seepage of extraction oil gas causes generates comprehensively and schemes unusually; The auxiliary then geologic interpretation with necessity generates the little seepage spatial distribution map of oil gas; Final predicting oil is explored the target area, lays respectively at the northwestward and the west and south of study area, and idiographic flow is seen Figure 13.
Therefore above embodiment only is used to illustrate the present invention, but not is used to limit the present invention.
Claims (12)
1. an oil-gas exploration method is characterized in that, said method comprising the steps of:
Utilize ground object spectrum data in the ground light spectrometer measurement Research district;
Utilize digital camera to gather ground atural object data of description in the study area, gather face of land sample data and measuring condition data;
Utilize portable GPS to gather the tested atural object coordinate data in ground in the study area;
Generate ground ground Object Spectra DataBase in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data;
The hyperspectral imager that utilizes satellite or aircraft to carry is gathered atural object high-spectrum remote sensing data in the study area;
Data and atural object high-spectrum remote sensing data to described ground ground Object Spectra DataBase are handled, and obtain oil-gas exploration target area data;
Wherein, the described spectral remote sensing of object height over the ground view data is handled and is comprised:
High-spectrum remote sensing data pre-treatment step;
High-spectrum remote sensing data characteristics extraction step;
The high-spectrum remote sensing data analysis step.
2. method according to claim 1 is characterized in that, described ground ground Object Spectra DataBase comprises:
Ground object target is measured description list, is used to write down the general description of the atural object general character such as locus, measuring position, surveying instrument of ground object target;
The object spectrum record sheet be used to write down the spectroscopic data of measuring sample, and spectral signature is described;
Sample attribute description table is used to describe barment tags such as face of land structures of samples, structure, geologic time, alteration features;
Atural object physics constitutes table, describes the formation of institute's geodetic thing;
The measuring equipment parameter list, institute's instrument that uses and technical indicator parameter thereof when being used to be recorded in open-air spectral measurement;
The measurement environment parameter list is used for the atmospheric parameter of record object background, the parameter extraction the when remotely-sensed data that is used for hyperspectral imager collection that satellite or aircraft are carried is carried out radiant correction.
3. method according to claim 1 is characterized in that, described high-spectrum remote sensing data pre-treatment step comprises successively:
The high-spectrum remote sensing data are saved as the ENVI standard format, and select wherein effective wave band;
The high-spectrum remote sensing data are removed the processing of dead pixel row;
The high-spectrum remote sensing data are removed the processing of band noise;
The high-spectrum remote sensing data are carried out radiant correction to be handled;
The high-spectrum remote sensing data are carried out noise reduction process.
4. method according to claim 1 is characterized in that, described high-spectrum remote sensing data characteristics extraction step comprises:
PAC characteristic extraction step based on small echo;
Fisher characteristic extraction step based on small echo.
5. method according to claim 1 is characterized in that, described high-spectrum remote sensing data analysis step comprises:
The maximum likelihood analysis treatment step;
Local feature method analyzing and processing step.
6. method according to claim 1 is characterized in that, the data of described ground ground Object Spectra DataBase and atural object high-spectrum remote sensing data is handled comprise:
According to the data and the atural object high-spectrum remote sensing data of ground ground Object Spectra DataBase, the density information of the space distribution of the symbiosis abnormity point that the little seepage of extraction oil gas causes generates comprehensively and schemes unusually;
Explain according to corresponding geological, generate the little seepage spatial distribution map of oil gas;
Dope the oil-gas exploration target area according to described comprehensive unusual figure and the little seepage spatial distribution map of oil gas.
7. an oil-gas exploration system is characterized in that, described system comprises:
The ground light spectrometer is used for object spectrum data in ground in the measurement Research district;
Digital camera is used to gather ground atural object data of description in the study area;
Portable GPS is used to gather the tested atural object coordinate data in ground in the study area;
Portable computer is used for generating field ground feature spectra database in the study area according to described object spectrum data, atural object data of description, face of land sample data, measuring condition number and tested atural object coordinate data;
The hyperspectral imager that satellite or aircraft carry is used to gather atural object high-spectrum remote sensing data in the study area;
The oil gas anacom is used for the data and the atural object high-spectrum remote sensing data of described ground Object Spectra DataBase are handled, and obtains oil-gas exploration target area data;
Described oil gas anacom comprises:
Pretreatment unit is used for the high-spectrum remote sensing data are carried out pre-service;
Feature extraction unit is used for the high-spectrum remote sensing data are carried out feature extraction;
Data analysis unit is used for the high-spectrum remote sensing data are analyzed.
8. system according to claim 7 is characterized in that, described ground ground Object Spectra DataBase comprises:
Ground object target is measured description list, is used to write down the general description of the atural object general character such as locus, measuring position, surveying instrument of ground object target;
The object spectrum record sheet be used to write down the spectroscopic data of measuring sample, and spectral signature is described;
Sample attribute description table is used to describe barment tags such as face of land structures of samples, structure, geologic time, alteration features;
Atural object physics constitutes table, describes the formation of institute's geodetic thing;
The measuring equipment parameter list, institute's instrument that uses and technical indicator parameter thereof when being used to be recorded in open-air spectral measurement;
The measurement environment parameter list is used for the atmospheric parameter of record object background, the parameter extraction the when remotely-sensed data that is used for hyperspectral imager collection that satellite or aircraft are carried is carried out radiant correction.
9. system according to claim 7 is characterized in that, described pretreatment unit comprises:
Format converting module is used for the high-spectrum remote sensing data are saved as the ENVI standard format, and selects wherein effective wave band;
Remove dead pixel row module, be used for the high-spectrum remote sensing data are removed the processing of dead pixel row;
Remove band noise module, be used for the high-spectrum remote sensing data are removed the processing of band noise;
Correction module is used for that the high-spectrum remote sensing data are carried out radiant correction and handles;
Noise reduction module is used for the high-spectrum remote sensing data are carried out noise reduction process.
10. system according to claim 7 is characterized in that, described feature extraction unit comprises:
Small echo PAC module is used to carry out the PAC feature extraction based on small echo;
Small echo Fisher module is used to carry out the Fisher feature extraction based on small echo.
11. system according to claim 7 is characterized in that, described data analysis unit comprises:
The maximum likelihood analysis module is used to carry out maximum likelihood analysis;
The local feature method is analyzed, and is used to carry out the analysis of local feature method.
12. system according to claim 7 is characterized in that, described oil gas anacom also comprises:
Integerated analytic unit is used for data and atural object high-spectrum remote sensing data according to the ground ground Object Spectra DataBase, and the density information of the space distribution of the symbiosis abnormity point that the little seepage of extraction oil gas causes generates comprehensively and schemes unusually; And, generate the little seepage spatial distribution map of oil gas according to the corresponding geological explanation;
Oil-gas exploration target area acquiring unit is used for doping the oil-gas exploration target area according to described comprehensive unusual figure and the little seepage spatial distribution map of oil gas.
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