CN104899358B - The Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles - Google Patents
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Abstract
The invention discloses a kind of Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles, comprise: first determine and the closely-related index of Ordovician limestone karst crevice water network distribution, then the index raw data of the down-hole Ordovician karst water literary composition drill hole having geophysical exploration is gathered, core principle component model is set up to the index raw data gathered, extract new major component, then fuzzy standardization is carried out, with the number of principal components after fuzzy standardization according to forming sample set with geophysical exploration Ordovician limestone karst Exception Type, set up the forecast model of genetic algorithm optimization SVM; Utilize the model established, Austria's ash exceptions area type of the down-hole Ordovician karst water literary composition drill hole not having geophysical exploration is predicted; Finally draw the distribution plan of grey exceptions area difficult to understand type, judge Ordovician limestone karst exceptions area type distributes scope, and analyze Ordovician limestone karst crevice water network seepage field direction.Design concept of the present invention is reliable, and Forecasting Methodology is simple, and precision of prediction is high, prediction environmental friendliness.
Description
Technical field
The present invention relates to a kind of Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles, especially a kind of Forecasting Methodology for North China type coalfield Ordovician limestone karst crevice water network cross direction profiles.
Background technology
Mine Stope Water Inrush is ubiquitous problem in coal production, now become one to be related to energy industry and to develop key subjects urgently to be resolved hurrily, because stope sill gushing water problem has extremely complicated mechanism, add the disguise of ground water movement, can not directly observe, therefore research difficulty is larger.But with regard to the occurrence condition of underground water, there is the rule of himself, can Qualitative and Quantitative research.The immediate cause of stope sill gushing water is that below base plate also exists groundwater network, and what do not have groundwater network just large water inrush accident can not occur.China's North China type coalfield is through the exploitation of nearly half a century, most mine enters deep mining, generally be subject to the threat that Ordovician karst water is outstanding, therefore determine that the space distribution rule of groundwater network is key issue and the top priority of grey water-inrush prevention work difficult to understand.Relevant scholar is more for the longitudinal research of growing of Ordovician limestone karst both at home and abroad, and achieves some important achievement, but less for the research of Ordovician limestone karst cross direction profiles.In the prior art, mainly roughly determine the position of groundwater network master pulse by the technological means such as developmental state, tracer test, drilling core of outflow test, Water Inrush point position, Genesis of Karst Subsided Column distribution situation, tomography, but but comprehensively do not analyze, quantitative research, and various research technique both expensive, testing site are less, the growth point of projective water point position and Genesis of Karst Subsided Column is also extremely limited, for the prediction of Ordovician limestone karst crevice water network cross direction profiles, there are no the report utilizing quantization parameter to set up quantitative model in prior art.Therefore be necessary that searching is a kind of can economize on the use of funds and the method for concentrated expression Karst-fissure water network developmental factors can be collected in most region to predict the cross direction profiles of Ordovician limestone karst crevice water network, for the prediction of the big-and-middle-sized projective water point position of seat earth and the gushing water water yield provides foundation.
Karst-fissure water network is on the basis of structural fissured water network, by the effect of local ground watering vector seepage field, constantly develops, and this network system possesses Karst Fissures passage and abundant underground water.And Karst Fissures space distribution is mainly by the control of the various structured fault zone of structure destruction effect formation.Therefore, by the research of the effect of influencing each other to tectonic fissure development degree, Karst corridor and Ordovician karst water degree of water-rich 3 factor, the space distribution of Ordovician limestone karst crevice water network can be got clear.Easily to obtain if can collect and abundant index quantification evaluates this 3 factors, build rationally forecast model reliably, then can determine the distribution of Ordovician limestone karst crevice water network.Tectonic movement is in the solid rock of underground, form the combination of large-scale tectonic faults, fold and numerous rimalas, the developing of groundwater network depends on tectonic fissure, the Spatial Coupling in these cracks defines the initial crevice water network system, and composite fault factor of influence, tomography fractal dimension value, fold fractal dimension value can quantitative evaluation tectonic fissure development degrees.The abnormal control being obviously subject to areal structure and major fault of Temperature Field, if near surface and shallow place low temperature underground water are caused deep by ground water circulation passage, then water temperature reduces, if because Deep Groundwater rises along tomography, then water temperature raises, and therefore ground water temperature extremely can as judging that whether tectonic fissure is the important indicator of Karst corridor.And the division of grey degree of water-rich difficult to understand is mainly according to " mine geological hazards regulation ", divide according to boring specific capacity (q) value, this criteria for classifying has science in theory, but objectively only utilize q value to divide the watery poor operability in water-bearing zone, normally the field with "nine squares" exploration stage obtains for main because q value, quantity is extremely limited, is secondly that q value obtains the large length consuming time of investment; Also have some to be studied by the maximum wastage of drilling fluid and boring and coring, but be not that each boring can get core and the maximum wastage of statistics washing fluid; And along with pit mining expanded range, down-hole Ordovician karst water literary composition borehole data is more and more abundanter, and down-hole hydrology boring acquisition is bore flooding quantity, the watery in water-bearing zone can be reflected to a certain extent, water burst value is larger, and show that the watery in water-bearing zone is relatively better, connectedness is better.On the other hand, in water-bearing zone, rich water obtains good Effect on Detecting extremely and in the detection of water-bearing structure in geophysical exploration, but be not that each down-hole Ordovician karst water literary composition drill hole all has geophysical exploration, therefore, be necessary to find a kind of accurate method, utilize the desired value and result of detection that have the hydrology drill hole of geophysical exploration to obtain to predict other karst abnormal conditions not having geophysical exploration region, for mine floor water-inrush prevention provides strong foundation.
Summary of the invention
The object of the invention is for overcoming above-mentioned the deficiencies in the prior art, a kind of Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles is provided, the method can meet the demand of North China type coalfield coal industry sustainable development, choose can economize on the use of funds and can collect in most region with the closely-related factor of Ordovician limestone karst crevice water network distribution, comprehensive utilization geophysical exploration grey exceptions area difficult to understand achievement, the blindness avoiding judging that groundwater network distributes and subjectivity, its design concept is reliable, Forecasting Methodology is simple, precision of prediction is high, prediction environmental friendliness.
For achieving the above object, the present invention adopts following technical proposals:
A Forecasting Methodology for Ordovician limestone karst crevice water network cross direction profiles, comprises the following steps:
(1) determine and the closely-related index of Ordovician limestone karst crevice water network distribution, then gather the index raw data of the down-hole Ordovician karst water literary composition drill hole having geophysical exploration;
(2) the Ordovician limestone karst exceptions area prediction model of KPCA-Fuzzy-GA-SVM is set up: core principle component model (KPCA) is set up to the index raw data gathered, extract new major component, then fuzzy standardization (Fuzzy) is carried out, with the number of principal components after fuzzy standardization according to forming sample set with geophysical exploration Ordovician limestone karst exceptions area type, set up the forecast model of genetic algorithm (GA) Support Vector Machines Optimized (SVM);
(3) gather the index raw data of the down-hole Ordovician karst water literary composition drill hole not having geophysical exploration, utilize the KPCA – Fuzzy-GA-SVM model prediction grey exceptions area difficult to understand type established;
(4) draw the distribution plan of grey exceptions area difficult to understand type, judge Ordovician limestone karst exceptions area type distributes scope;
(5) Ordovician limestone karst crevice water network seepage field direction is analyzed.
Described step (1) with the closely-related index of Ordovician limestone karst crevice water network distribution, refer to the index that can reflect Karst Fissures development degree, Karst corridor and Austria's ash degree of water-rich, specifically comprise tomography factor of influence, tomography fractal dimension value, fold fractal dimension value, Ordovician karst water temperature abnormality changing value and down-hole Ordovician karst water literary composition bore flooding quantity 5 indexs.
Wherein Ordovician karst water temperature abnormality changing value computing formula is as follows:
ΔT＝|T-t|，
In formula: Δ T is water temperature abnormality changing value, unit DEG C; T is this some actual measurement water temperature, unit DEG C; T is the normal temperature according to ground temperature gradient calculation, unit DEG C; Wherein t is by following formulae discovery:
In formula: t ' is zone of constant temperature, study area temperature, unit DEG C; H is grey top elevation difficult to understand, unit m; H is zone of constant temperature absolute altitude, unit m; Δ t is study area underground temperature gradient, unit DEG C/100m.
Described step (2) set up core principle component model, comprise the following steps:
1. there are 5 index raw data of the down-hole Ordovician karst water literary composition drill hole of geophysical exploration to be designated as one (l × 5) dimension raw data matrix A by the l collected;
2. Nonlinear Mapping is passed through
raw data matrix A is mapped to high-dimensional feature space, and calculates nuclear matrix K, K=(k
ij)
l × l, k
ij=K (x
i, x
j), (i, j=1,2 ..., l), l is index number; Wherein Nonlinear Mapping
kernel function be Gaussian radial basis function;
3. according to equation l λ α=K α, the eigenvalue λ of nuclear matrix K is asked for
1≤ λ
2≤ ...≤λ
lwith characteristic of correspondence vector α
1, α
2..., α
l, and by orthogonalization method unit orthogonalized eigenvectors, obtain normalized proper vector α '
1, α '
2..., α '
l;
4. according to formula
choose m eigenvalue of maximum λ
1, λ
2..., λ
mand characteristic of correspondence vector α '
1, α '
2..., α '
m; Wherein, 0<m<l;
5. the proper vector Y=K α ' of raw data gained after KPCA dimensionality reduction is calculated, wherein α '=[α '
1, α '
2..., α '
m], Y is the sample data matrix after dimensionality reduction;
The fuzzy standardization of described step (2), standardization formula is:
The geophysical exploration Ordovician limestone karst exceptions area type of described step (2), comprise intense anomaly district, weak anomaly district and district without exception, intense anomaly district sample label is set to 1, weak anomaly district sample label is set to 0, and district without exception sample label is set to-1.
The determination methods of the Ordovician limestone karst exceptions area type distributes scope of described step (4) refers to, Austria's ash exceptions area Map of Distributions of Types drawn, wherein intense anomaly district, weak anomaly district, district without exception uses 1 respectively, 0,-1 represents, utilize Ke Like intermediate interpolated method, draw the separatrix I (0.5 line) in intense anomaly district and weak anomaly district, and the separatrix II (-0.5 line) in weak anomaly district and district without exception, the region being then positioned at > 0.5 line is Ordovician limestone karst crevice water network distribution region, region between 0.5 line ~-0.5 line is crevice water network distribution region, the region being positioned at <-0.5 line is karst and agensis region, crack.
The method of the analysis Ordovician limestone karst crevice water network seepage field basic orientation of described step (5) is: draw Ordovician karst water position isoline, is pointed to direction and the seepage field basic orientation of low-water level by high water stage.
The present invention compared with prior art has the following advantages:
(1) tomography factor of influence, tomography fractal dimension value, fold fractal dimension value, Ordovician karst water temperature abnormality changing value and down-hole Ordovician karst water literary composition bore flooding quantity 5 indexs are chosen, the parameter chosen both easily obtained, had popularity, accomplish again quantification, can comprehensive evaluation Karst Fissures development degree, Karst corridor and Ordovician karst water degree of water-rich 3 factors; Comprehensive utilization geophysical exploration grey exceptions area difficult to understand achievement, the blindness avoiding judging that groundwater network distributes and subjectivity.
(2) kernel function combines with principal component analysis (PCA) by core principle component analysis, adopts nonlinear method to extract major component, improves the quality of data, effectively reduce the impact of lengthy and jumbled information, have more remarkable result than traditional principal component analysis (PCA); Core principle component analysis result is carried out fuzzy standardization, eliminates the impact that data yardstick disunity brings; Finally utilize support vector machine (SVM) disaggregated model to predict the distribution of Ordovician limestone karst crevice water network, its design concept is reliable, and Forecasting Methodology is simple, and precision of prediction is high, prediction environmental friendliness.
Accompanying drawing explanation
Fig. 1 is the inventive method particular flow sheet;
Fig. 2 optimizes the process flow diagram of the forecast model of SVM for setting up genetic algorithm (GA).
Embodiment
Below in conjunction with drawings and Examples, the present invention is further described.
As shown in Figure 1, a kind of Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles, comprises the steps:
(1) determine and the closely-related index of Ordovician limestone karst crevice water network distribution, then gather the index raw data of the down-hole Ordovician karst water literary composition drill hole having geophysical exploration.
Wherein, with the closely-related index of Ordovician limestone karst crevice water network distribution, refer to the index that can reflect Karst Fissures development degree, Karst corridor and Austria's ash degree of water-rich, specifically comprise tomography factor of influence, tomography fractal dimension value, fold fractal dimension value, Ordovician karst water temperature abnormality changing value and down-hole Ordovician karst water literary composition bore flooding quantity 5 indexs;
Ordovician karst water temperature abnormality changing value computing formula is as follows:
ΔT＝|T-t|，
In formula: Δ T is water temperature abnormality changing value, DEG C; T is this some actual measurement water temperature, DEG C; T is the normal temperature according to ground temperature gradient calculation, DEG C; Wherein t is by following formulae discovery:
In formula: t ' is zone of constant temperature, study area temperature, DEG C; H is grey top elevation difficult to understand, m; H is zone of constant temperature absolute altitude, m; Δ t is study area underground temperature gradient, DEG C/100m.
(2) the Ordovician limestone karst exceptions area prediction model of KPCA-Fuzzy-GA-SVM is set up: core principle component model (KPCA) is set up to the index raw data gathered, extract new major component, then fuzzy standardization (Fuzzy) is carried out, with the number of principal components after fuzzy standardization according to forming sample set with geophysical exploration Ordovician limestone karst exceptions area type, set up the forecast model of genetic algorithm (GA) Support Vector Machines Optimized (SVM).
Described core principle component model of setting up comprises the following steps:
1. there are 5 index raw data of the down-hole Ordovician karst water literary composition drill hole of geophysical exploration to be designated as one (l × 5) dimension raw data matrix A by the l collected;
2. Nonlinear Mapping is passed through
raw data matrix A is mapped to high-dimensional feature space, and calculates nuclear matrix K, K=(k
ij)
l × l, k
ij=K (x
i, x
j), (i, j=1,2 ..., l), l is index number; Wherein Nonlinear Mapping
kernel function be Gaussian radial basis function;
3. according to equation l λ α=K α, the eigenvalue λ of nuclear matrix K is asked for
1≤ λ
2≤ ...≤λ
lwith characteristic of correspondence vector α
1, α
2..., α
l, and by orthogonalization method unit orthogonalized eigenvectors, obtain normalized proper vector α '
1, α '
2..., α '
l;
4. according to formula
choose m eigenvalue of maximum λ
1, λ
2..., λ
mand characteristic of correspondence vector α '
1, α '
2..., α '
m; Wherein, 0<m<l;
5. the proper vector Y=K α ' of raw data gained after KPCA dimensionality reduction is calculated, wherein α '=[α '
1, α '
2..., α '
m], Y is the sample data matrix after dimensionality reduction.
Described fuzzy standardization, standardization formula is:
Described geophysical exploration Ordovician limestone karst Exception Type, comprises intense anomaly district, weak anomaly district and district without exception, and intense anomaly district sample label is set to 1, and weak anomaly district sample label is set to 0, and district without exception sample label is set to-1.
The described forecast model setting up genetic algorithm (GA) Support Vector Machines Optimized (SVM), namely first utilize genetic algorithm to be optimized the punishment parameter C of SVM model and kernel functional parameter σ (nuclear parameter of SVM model chooses RBF kernel function), then utilize optimized parameter to carry out SVM modeling.Fig. 2 is the process flow diagram of the forecast model setting up genetic algorithm (GA) Support Vector Machines Optimized (SVM), comprises the following steps:
1. sample set is arranged: to the sample set described in step (2), randomly draw the sample of 20% as test sample book, remaining sample is as training sample; Using the major component after fuzzy standardization as input vector, using geophysical exploration Ordovician limestone karst Exception Type as object vector;
2. genetic algorithm optimizing: utilize genetic algorithm to determine punishment parameter C and kernel functional parameter σ;
3. SVM training: input training sample, utilizes the optimized parameter sought to carry out SVM training, sets up support vector machine (SVM) model;
4. model testing: utilize test sample book to test to forecast model, it is that forecast model is qualified that precision of forecasting model reaches more than 85%, can apply; Precision of forecasting model is less than 85%, then re-start core principle component modeling.
(3) gather the index raw data of the down-hole Ordovician karst water literary composition drill hole not having geophysical exploration, utilize the KPCA – Fuzzy-GA-SVM model prediction grey exceptions area difficult to understand type established.
Embodiment is, first to the index raw data not having the civilian drill hole of the down-hole Ordovician karst water of geophysical exploration, the core principle component model utilizing step (2) to set up calculates number of principal components certificate, then fuzzy standardization is carried out, using the number of principal components after fuzzy standardization according to as input parameter, the forecast model of genetic algorithm (GA) Support Vector Machines Optimized (SVM) set up in input step (2), predicts grey exceptions area difficult to understand type.
(4) draw the distribution plan of grey exceptions area difficult to understand type, judge Ordovician limestone karst exceptions area type distributes scope.
Concrete determination methods is: Austria's ash exceptions area Map of Distributions of Types of drafting, wherein intense anomaly district, weak anomaly district, district without exception uses 1 respectively, 0,-1 represents, utilize Ke Like intermediate interpolated method, draw the separatrix I (0.5 line) in intense anomaly district and weak anomaly district, and the separatrix II (-0.5 line) in weak anomaly district and district without exception, the region being then positioned at > 0.5 line is Ordovician limestone karst crevice water network distribution region, region between 0.5 line ~-0.5 line is crevice water network distribution region, the region being positioned at <-0.5 line is karst and agensis region, crack.
(5) Ordovician limestone karst crevice water network seepage field direction is analyzed.
Concrete grammar is: draw Ordovician karst water position isoline, is pointed to direction and the seepage field basic orientation of low-water level by high water stage.
By reference to the accompanying drawings the specific embodiment of the present invention is described although above-mentioned; but not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various amendment or distortion that creative work can make still within protection scope of the present invention.
Claims (6)
1. a Forecasting Methodology for Ordovician limestone karst crevice water network cross direction profiles, is characterized in that, comprise the following steps:
(1) determine and the closely-related index of Ordovician limestone karst crevice water network distribution, then gather the index raw data of the down-hole Ordovician karst water literary composition drill hole having geophysical exploration;
Described with the closely-related index of Ordovician limestone karst crevice water network distribution, refer to the index that can reflect Karst Fissures development degree, Karst corridor and Austria's ash degree of water-rich, specifically comprise tomography factor of influence, tomography fractal dimension value, fold fractal dimension value, Ordovician karst water temperature abnormality changing value and down-hole Ordovician karst water literary composition bore flooding quantity 5 index raw data;
(2) the Ordovician limestone karst exceptions area prediction model of KPCA-Fuzzy-GA-SVM is set up: core principle component model and KPCA are set up to the index raw data gathered, extract new major component, then fuzzy standardization and Fuzzy is carried out, with the number of principal components after fuzzy standardization according to forming sample set with geophysical exploration Ordovician limestone karst exceptions area type, set up the forecast model of genetic algorithm and GA Support Vector Machines Optimized and SVM;
Describedly set up core principle component model, comprise the following steps:
1. there are 5 index raw data of the down-hole Ordovician karst water literary composition drill hole of geophysical exploration to be designated as one (l × 5) dimension raw data matrix A by the l collected;
2. Nonlinear Mapping is passed through
raw data matrix A is mapped to high-dimensional feature space, and calculates nuclear matrix K, K=(k
ij)
l × l, k
ij=K (x
i, x
j), (i, j=1,2 ..., l), l is index number; Wherein Nonlinear Mapping
kernel function be Gaussian radial basis function;
3. according to equation l λ α=K α, the eigenvalue λ of nuclear matrix K is asked for
1≤ λ
2≤ ...≤λ
lwith characteristic of correspondence vector α
1, α
2..., α
l, and by orthogonalization method unit orthogonalized eigenvectors, obtain normalized proper vector α '
1, α '
2..., α '
l;
4. according to formula
choose m eigenvalue of maximum λ
1, λ
2..., λ
mand characteristic of correspondence vector α '
1, α '
2..., α '
m; Wherein, 0<m<l;
5. the proper vector Y=K α ' of raw data gained after KPCA dimensionality reduction is calculated, wherein α '=[α '
1, α '
2..., α '
m], Y is the sample data matrix after dimensionality reduction;
(3) gather the index raw data of the down-hole Ordovician karst water literary composition drill hole not having geophysical exploration, utilize the KPCA – Fuzzy-GA-SVM model prediction grey exceptions area difficult to understand type established;
(4) draw the distribution plan of grey exceptions area difficult to understand type, judge Ordovician limestone karst exceptions area type distributes scope;
(5) Ordovician limestone karst crevice water network seepage field direction is analyzed.
2. the Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles as claimed in claim 1, it is characterized in that, wherein Ordovician karst water temperature abnormality changing value computing formula is as follows:
ΔT＝|T-t|，
In formula: Δ T is water temperature abnormality changing value, unit DEG C; T is this some actual measurement water temperature, unit DEG C; T is the normal temperature according to ground temperature gradient calculation, unit DEG C; Wherein t is by following formulae discovery:
In formula: t ' is zone of constant temperature, study area temperature, unit DEG C; H is grey top elevation difficult to understand, unit m; H is zone of constant temperature absolute altitude, unit m; Δ t is study area underground temperature gradient, unit DEG C/100m.
3. the Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles as claimed in claim 1, it is characterized in that, the fuzzy standardization of described step (2), standardization formula is:
4. the Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles as claimed in claim 1, it is characterized in that, the geophysical exploration Ordovician limestone karst exceptions area type of described step (2), comprise intense anomaly district, weak anomaly district and district without exception, intense anomaly district sample label is set to 1, weak anomaly district sample label is set to 0, and district without exception sample label is set to-1.
5. the Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles as claimed in claim 1, it is characterized in that, the determination methods of the Ordovician limestone karst exceptions area type distributes scope of described step (4) refers to, Austria's ash exceptions area Map of Distributions of Types drawn, wherein intense anomaly district, weak anomaly district, district without exception uses 1 respectively, 0,-1 represents, utilize Ke Like intermediate interpolated method, draw separatrix I i.e. 0.5 line in intense anomaly district and weak anomaly district, and the separatrix II in weak anomaly district and district without exception i.e.-0.5 line, the region being then positioned at > 0.5 line is Ordovician limestone karst crevice water network distribution region, region between 0.5 line ~-0.5 line is crevice water network distribution region, the region being positioned at <-0.5 line is karst and agensis region, crack.
6. the Forecasting Methodology of Ordovician limestone karst crevice water network cross direction profiles as claimed in claim 1, it is characterized in that, the method of the analysis Ordovician limestone karst crevice water network seepage field basic orientation of described step (5) is: draw Ordovician karst water position isoline, is pointed to direction and the seepage field basic orientation of low-water level by high water stage.
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