CN117272772A - Evaluation method and system for water-rich refined partition of loose aquifer of mine - Google Patents
Evaluation method and system for water-rich refined partition of loose aquifer of mine Download PDFInfo
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Abstract
The invention belongs to the technical field of resource evaluation systems, and discloses an evaluation method and an evaluation system for a water-rich refined partition of a loose aquifer of a mine, wherein an evaluation index is formed by the thickness of the aquifer, the thickness of a gravel layer, lithology-thickness index, sand-ground ratio and the number of layers of the gravel layer, and an evaluation index matrix is established; unifying the variation ranges of different evaluation index data, carrying out normalization treatment to obtain a standardized evaluation matrix after treatment, and constructing a 'bottom-contained' rich water evaluation index system; combining the constructed 'bottom-contained' water-rich evaluation index system, and establishing an aquifer water-rich evaluation model through DPS software according to the principle of a projection pursuit model; performing linear projection and constructing a projection objective function in an aquifer water-rich evaluation model; optimizing a projection objective function, and determining an optimal projection direction; and (3) returning the optimal projection direction to the expression of the linear projection to obtain a projection characteristic value capable of reflecting the information of each evaluation index so as to comprehensively evaluate the evaluation object.
Description
Technical Field
The invention belongs to the technical field of resource evaluation systems, and particularly relates to an evaluation method and an evaluation system for a mine loose aquifer water-rich refined partition.
Background
At present, objectively and reasonably predicting and evaluating the water-rich property of an aquifer affecting and threatening the safe recovery of a coal seam is an important premise for developing the mine water disaster prevention and treatment work, and not only can pertinent arrangement and disposition of related prevention and treatment projects be realized, but also the water-burst (water burst) accident of a local strong water-rich area can be effectively avoided or reduced. The conventional aquifer water enrichment evaluation is often carried out around a fracture aquifer in bedrock, a karst aquifer in limestone, and the like, and the water enrichment evaluation for a loose aquifer in new kingdom is relatively few. Most of the bottom aquifer (called as bottom containing) of the new kingdom in the Huabei mining area is directly covered on the coal-series stratum, when the shallow coal seam is mined, the mining fracture can be conducted on the upper bottom containing, so that the roof water inrush accident is caused. The aquifer is the material basis of the water burst of the top plate, and the water-rich range directly determines the water quantity and the duration of the water burst. Therefore, the method is of great significance in the aspects of ensuring safe and efficient recovery of the coal seam in the shallow part of the mine, protecting the groundwater resources and the like.
The sediment characteristics are the most basic control factors for the formation of the water-bearing layer and the occurrence of groundwater, the thickness, lithology structure and sand space distribution characteristics of the sediment formed in different sediment environments are different, the water-rich property is obviously different, and the complex control mechanism and the nonlinear characteristics are shown. In the prior art, for the water-rich property evaluation of the aquifer, a plurality of methods or models are adopted to calculate the weight and the comprehensive value of each evaluation index, and a linear relation between the water-rich property of the aquifer and each evaluation index is established, but useful information of a nonlinear part between the water-rich property of the aquifer and each evaluation index is ignored, so that the accuracy of the water-rich property evaluation result is affected. Meanwhile, the traditional multi-factor comprehensive analysis method is based on the assumption that the overall evaluation index data meets the normal distribution, but in reality, many high-dimensional data does not meet the assumption of the high-dimensional normal distribution. The evaluation index data in the water-bearing layer water-rich evaluation problem has the characteristics of high dimension, nonlinearity and not necessarily conforming to normal distribution, so that many excellent models and methods cannot be practically applied to the calculation of the water-rich evaluation, and a robust or nonparametric method is needed to solve the problem.
Through the above analysis, the problems and defects existing in the prior art are as follows: the aquifer water-rich property evaluation in the prior art is carried out around a fracture aquifer in bedrock, a karst aquifer in limestone and the like, so that the research on the water-rich property of a new-world loose aquifer is relatively less, and no mature water-rich property evaluation method is provided for objectively, reasonably and accurately predicting and evaluating the water-rich property of 'bottom-contained'.
Disclosure of Invention
Aiming at the problems existing in the prior art, the invention provides a method and a system for evaluating the water-rich refined partition of a loose aquifer of a mine.
The invention discloses an evaluation method of a mine loose aquifer water-rich refined partition, which comprises the following steps of:
s101, forming an evaluation index by the thickness of the aquifer, the thickness of the gravel layer, lithology-thickness index, sand-ground ratio and the number of layers of the gravel layer, and establishing an evaluation index matrix;
s102, unifying the variation ranges of different evaluation index data, carrying out normalization processing on the evaluation index with larger and better numerical value and the index with smaller and better numerical value to obtain a normalized standardized evaluation matrix, and constructing a 'bottom-contained' rich water evaluation index system;
s103, establishing an aquifer water-rich evaluation model through DPS software according to the principle of a projection pursuit model by combining the constructed 'bottom-contained' water-rich evaluation index system;
s104, performing linear projection and constructing a projection objective function in an aquifer water-rich evaluation model;
s105, optimizing a projection objective function, and determining an optimal projection direction;
s106, bringing the optimal projection direction back to the expression of the linear projection to obtain a projection characteristic value capable of reflecting the information of each evaluation index;
s107, comprehensively evaluating the evaluation object according to the distribution characteristics and the size of the projection characteristic values.
Further, the aquifer thickness, gravel layer thickness, lithologic structure index, and sand-to-ground ratio in S101 are all positive indicators that affect the aquifer water enrichment, and the number of layers of gravel layers is a negative indicator that affects the water enrichment.
Further, in S105, the projection objective function is optimized by adopting a complex shape method to perform an optimization solution on the projection objective function.
Further, in S106, the absolute value of each component in the optimal projection direction essentially reflects the contribution degree of each evaluation index to the bottom rich water evaluation result, and the larger the absolute value of each component is, the greater the influence degree of the corresponding evaluation index on the bottom rich water is, and conversely, the smaller is.
Further, the projection characteristic value in S107 can be obtained into a contour map of the projection characteristic value with rich water after the visualization processing.
Further, the magnitude of the projection characteristic value in S107 reflects the degree of the water-rich property of the bottom, that is, the larger the projection characteristic value is, the stronger the water-rich property of the bottom is.
Another object of the present invention is to provide an evaluation system for a mine loose aquifer water-rich refined partition for implementing the evaluation method for a mine loose aquifer water-rich refined partition, the evaluation system for a mine loose aquifer water-rich refined partition comprising:
the evaluation index module is used for determining an evaluation index;
the evaluation index system establishment module is connected with the evaluation index module and is used for establishing an evaluation index system;
the projection tracking module is used for providing a projection tracking model;
the aquifer water-rich evaluation module is connected with the evaluation index system establishment module and the projection tracking module and is used for establishing an aquifer water-rich evaluation model by combining data of the evaluation index system establishment module and a model of the projection tracking module through DPS software.
It is a further object of the present invention to provide a computer device comprising a memory and a processor, the memory storing a computer program which, when executed by the processor, causes the processor to perform the steps of the method of evaluating a water-rich refined partition of a loose aquifer of a mine.
Another object of the present invention is to provide a computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method for evaluating a water-rich refined partition of a loose aquifer of a mine.
The invention further aims at providing an information data processing terminal which is used for realizing an evaluation system for the water-rich fine partition of the loose aquifer of the mine.
In combination with the technical scheme and the technical problems to be solved, the technical scheme to be protected has the following advantages and positive effects:
firstly, objective and reasonable predictive evaluation of the water-bearing layer water-rich property affecting and threatening the safe recovery of the mine coal seam is an important precondition for developing mine water-controlling work, related water-controlling engineering can be arranged and arranged in a targeted manner, and the water-inrush accident of a local strong water-rich area can be effectively avoided or reduced. At present, aiming at the problem of evaluating the water-rich property of the aquifer which influences the coal seam exploitation, a great deal of effective research is carried out by expert scholars at home and abroad, and the evaluation method mainly comprises 3 categories, namely a geophysical prospecting method (such as a transient electromagnetic method, a direct current method, a mine audio perspective method and the like), a water pumping and draining test method and a multi-factor comprehensive analysis method. The geophysical prospecting method has the problems of large workload, high cost and the like, has multiple resolvability, and interprets geophysical prospecting results to a certain extent depending on experience and technical level of interpretation staff; the water-rich characteristic of the aquifer of the mine can be visually reflected by the unit water inflow (q value) obtained by the water pumping (discharging) test, but the quantity of the water pumping (discharging) tests carried out is very limited because the water geological exploration degree of most mining areas in China is low, the requirement of the water-rich distribution rule of the aquifer cannot be met in detail, accurate evaluation and reasonable partitioning of the water-rich property of the aquifer are difficult to realize, and the water-rich property of the aquifer is not comprehensive enough to be evaluated only by the q value because of the large differences among the coalbed occurrence conditions, the mine geology and the water geological conditions of different mining areas. In contrast, the multi-factor comprehensive analysis method is a simple and effective method, and the comprehensive and accurate evaluation of the water-rich property of the aquifer can be realized by fully excavating and utilizing multi-source information affecting the water-rich property of the aquifer by means of a large amount of existing geological survey drilling data. The invention provides a mature water-rich evaluation method for objectively, reasonably and accurately predicting and evaluating the water-rich property of 'bottom-contained'.
Secondly, the method is still further optimized in the aspects of the water-rich fine evaluation of the aquifer and the selection of a proper evaluation model. The prior aquifer water-rich evaluation model research based on the multi-factor fusion analysis angle is mostly developed around fracture aquifers in bedrock, and the study on loose pore aquifer water-rich refined evaluation is relatively few. In addition, in the past researches, quantitative evaluation of the water-bearing layer water-rich property is mostly carried out by adopting a plurality of methods to calculate the weight and the comprehensive value of the parameter evaluation index, and a linear relation between the water-rich property and the evaluation value is established, but useful information of a nonlinear part between the water-rich property and the evaluation index is ignored, so that the accuracy of an evaluation result is influenced. Meanwhile, the traditional multi-factor comprehensive analysis method for the water-rich property is based on the assumption that the overall index data is subjected to normal distribution, however, the evaluation index data influencing the water-rich property has the characteristics of high dimension, nonlinearity and not necessarily accords with the normal distribution, so that many excellent models and methods cannot be suitable for quantitative evaluation calculation of the water-rich property.
The method is not influenced by high-dimensional, nonlinear and non-normal distribution evaluation index data, and breaks through the limitation that the traditional water-rich and water-rich comprehensive evaluation method can only be generally used for normal distribution data processing. The model is based on a linear projection of the data, but a nonlinear structure in the linear projection is sought, so it can be used to solve the nonlinear problem.
The invention searches the optimal projection direction completely according to the structural characteristics of the data, avoids the artificial subjectivity in weight setting, reduces the interference of artificial factors, ensures that the evaluation result can reflect the characteristics of the original data to the greatest extent, and improves the scientificity and the accuracy of the evaluation result. The invention can eliminate the interference of variables which are irrelevant or have little relation with the data structure and the characteristics. The projection characteristic value is used as a basis for evaluating the degree of the rich water, so that the magnitude of the rich water of each region can be intuitively compared. The method can realize accurate evaluation of the water-rich property of the mine aquifer, and the model is relatively simple, visual and easy to understand. The method has strong operability and effectiveness, and has good application value in the field of aquifer water enrichment evaluation. The invention provides a novel evaluation method and thought for the multi-factor aquifer water enrichment evaluation.
Thirdly, as inventive supplementary evidence of the claims of the present invention, the following important aspects are also presented:
(1) The expected benefits and commercial values after the technical scheme of the invention is converted are as follows:
the accurate prediction of the aquifer of the mine aquifer has important significance for guaranteeing the safe and efficient stoping of the coal seam, and each mine needs to develop water-rich research on the aquifer affecting the safe production before the working face arrangement and the coal seam stoping are carried out. If the water enrichment of the aquifer is detected by adopting a geophysical prospecting method or the water pumping and draining test method (hydrogeological drilling) is adopted to obtain the unit water inflow (q value), the workload is large, the cost is high, and the detection area is a small area, the production cost of a mine is obviously increased. If the technical scheme of the invention is converted, the method can be widely applied to the water-rich evaluation work of the aquifer of each mine in a plurality of mining areas in China, saves high cost required by carrying out geophysical prospecting work, water pumping test work and the like, effectively reduces the production cost of the coal mine, and has great commercial value.
(2) The technical scheme of the invention fills the technical blank in the domestic and foreign industries: the prior aquifer water-rich evaluation model research based on the multi-factor fusion analysis angle is mostly developed around fracture aquifers in bedrock, and the study on loose pore aquifer water-rich refined evaluation is relatively few. The invention provides a method suitable for fine evaluation of the water-rich property of a loose aquifer.
(3) Whether the technical scheme of the invention solves the technical problems that people want to solve all the time but fail to obtain success all the time is solved: in the past researches, quantitative evaluation of the water-bearing stratum water-rich property is mostly carried out by adopting a plurality of methods to calculate the weight and the comprehensive value of the parameter evaluation index, and a linear relation between the water-rich property and the evaluation value is established, but useful information of a nonlinear part between the water-rich property and the evaluation index is ignored, so that the accuracy of an evaluation result is influenced. Meanwhile, the traditional multi-factor comprehensive analysis method for the water-rich property is based on the assumption that the overall index data is subjected to normal distribution, however, the evaluation index data influencing the water-rich property has the characteristics of high dimension, nonlinearity and not necessarily conforming to the normal distribution, so that a plurality of excellent models and methods cannot be applied to quantitative evaluation calculation of the water-rich property. The invention establishes the evaluation model and the method which can effectively reflect the nonlinear characteristics between the rich water and the evaluation index and have high inclusion on the data structure characteristics.
Fourth, the invention provides an evaluation method for evaluating the fine partition of the water-rich nature of the loose aquifer of the mine. The method is mainly characterized by comprising the following steps of:
s101: the evaluation index matrix is established by the evaluation index composed of the water-bearing layer thickness, the gravel layer thickness, the lithology-thickness index, the sand-to-ground ratio and the number of the gravel layers. Establishing an evaluation index matrix is a first step in evaluating mine water enrichment. This includes assessing key indicators of the thickness of the aquifer, the thickness of the gravel layer, the lithology versus thickness, and the sand to ground ratio and the number of layers of gravel.
S102: unifying the variation ranges of different evaluation index data, carrying out normalization processing on the evaluation index with larger and better numerical value and the index with smaller and better numerical value to obtain a normalized standardized evaluation matrix, and constructing a 'bottom-contained' rich water evaluation index system. This step is mainly to normalize different evaluation indexes so as to unify the variation ranges of the respective indexes. This allows the individual metrics to be compared at the same scale for better overall evaluation.
S103: and establishing an aquifer water-rich evaluation model through DPS software according to the principle of the projection pursuit model by combining the constructed bottom water-rich evaluation index system. An evaluation model is constructed by utilizing the projection pursuit model principle and DPS software. The model can be combined with an evaluation index system to perform more accurate aquifer water enrichment evaluation.
S104: and performing linear projection and constructing a projection objective function in an aquifer water-rich evaluation model. In the evaluation model, linear projection and construction of projection objective functions are employed to determine the best evaluation strategy.
S105: and optimizing the projection objective function, and determining the optimal projection direction. By optimizing the projection objective function, an optimal projection direction is determined. This direction can reflect information of the evaluation index to the maximum extent.
S106: and (3) bringing the optimal projection direction back to the expression of the linear projection to obtain a projection characteristic value capable of reflecting the information of each evaluation index. This step brings the optimal projection direction back into the linear projection expression, thereby obtaining a projection characteristic value capable of reflecting each evaluation index information. These feature values enable the importance level of each evaluation index to be quantified.
S107: and comprehensively evaluating the evaluation object according to the distribution characteristics and the size of the projection characteristic values. And finally, comprehensively evaluating the evaluation object according to the distribution characteristics and the size of the projection characteristic values. The step can synthesize each evaluation index, so that a final aquifer water-rich evaluation result is obtained.
The method has the remarkable technical progress that a plurality of evaluation indexes are combined, and a more accurate aquifer water-rich evaluation result is obtained through normalization processing and projection pursuit model.
Drawings
FIG. 1 is a flow chart of an evaluation method of a mine loose aquifer water-rich refined partition provided by an embodiment of the invention.
FIG. 2 is a block diagram of an evaluation system for water-rich refined partition of a loose aquifer of a mine, which is provided by the embodiment of the invention.
FIG. 3 is an illustration of the best projection direction of a "bottom-in" rich aqueous projection tracking model provided by an embodiment of the present invention.
FIG. 4 is a contour plot of the "bottom-contained" rich water projection characteristic values of a study area provided by an embodiment of the present invention.
FIG. 5 is a plot of a "bottom-in" rich water partition of a research area provided by an embodiment of the present invention.
Fig. 6 is a Xu mine "bottom-in" deposition phase distribution provided by an embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the following examples in order to make the objects, technical solutions and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
As shown in fig. 1, the evaluation method of the water-rich refined partition of the loose aquifer of the mine comprises the following steps:
s101, forming an evaluation index by the thickness of the aquifer, the thickness of the gravel layer, lithology-thickness index, sand-ground ratio and the number of layers of the gravel layer, and establishing an evaluation index matrix;
s102, unifying the variation ranges of different evaluation index data, carrying out normalization processing on the evaluation index with larger and better numerical value and the index with smaller and better numerical value to obtain a normalized standardized evaluation matrix, and constructing a 'bottom-contained' rich water evaluation index system;
s103, establishing an aquifer water-rich evaluation model through DPS software according to the principle of a projection pursuit model by combining the constructed 'bottom-contained' water-rich evaluation index system;
s104, performing linear projection and constructing a projection objective function in an aquifer water-rich evaluation model;
s105, optimizing a projection objective function, and determining an optimal projection direction;
s106, bringing the optimal projection direction back to the expression of the linear projection to obtain a projection characteristic value capable of reflecting the information of each evaluation index;
s107, comprehensively evaluating the evaluation object according to the distribution characteristics and the size of the projection characteristic values.
The specific algorithm steps of the evaluation method for the water-rich refined partition of the loose aquifer of the mine provided by the invention are as follows:
(1) Establishing an evaluation index matrix
Let the sample capacity of the sample set to be evaluated be n, the index number of the evaluation index set be p, and the j-th evaluation index value of the i-th sample beThen the total index data of all samples to be evaluated can be represented by an n X p matrix X * The representation is:
(2) Normalization processing
In order to eliminate the influence of different dimensions, unifying the change ranges of different evaluation index data, carrying out normalization processing on the evaluation index with larger and better numerical value and the index with smaller and better numerical value according to the formula (2) and the formula (3) respectively:
wherein:respectively are provided withThe maximum value and the minimum value of the j index; x is x ij Is normalized data.
Thereby, normalized n×p normalized evaluation matrix X is obtained:
X＝(x ij ) n×p (4)
(3) Linear projection
By observing the data of the sample from different angles, the best projection direction capable of fully mining the data information and reflecting the data features to the greatest extent is found, the high-dimensional data is reduced to a low-dimensional data, which is essentially p-dimensional data (x ij ) (i=1, 2, …, n; j=1, 2, …, p) to 1-dimensional vector a= (a) 1 ,a 2 ,a 3 ,…,a p ) Projection value z of projection direction i ：
The invention uses a projection pursuit model, but seeks a nonlinear structure in linear projection, though based on linear projection of data, so can be used to solve nonlinear problems.
(4) Constructing a projection objective function
According to the classification principle, the distribution characteristics of the projection values should meet the following conditions as much as possible: the local projection points should be as dense as possible, preferably agglomerated into clusters; the projected clusters should be scattered as a whole, i.e. the inter-class distance S should be such that the p-dimensional data is spread in 1-dimensional space z And intra-class density D z At the same time, the projection objective function Q (a) is expressed as S z And D z As shown in formula (6):
Q(a)＝S z ·D z (6)
wherein: s is S z Representing the distance between classes, numerically equal to z i Standard deviation of (2); d (D) z Represents z i Is referred to as the local density or intra-class density. S is S z And D z Calculated according to the formula (7) and the formula (8):
wherein:for the sequence (z) i I=1, 2,3, …, n), n being the sample size; r is the radius of the partial density window, the value is required to ensure that the average number of projection points contained in the window cannot be too small, the excessive deviation of the moving average is avoided, the increase of the R along with the increase of n cannot be excessively high, and R=alpha.S is taken in the actual operation z Alpha is based on the projection point z i The distribution among the areas is properly adjusted, 0.1,0.01,0.001 and the like can be taken, and more than 0.1 is taken; r is (r) ij ＝|z i -z j I, distance between samples; u (u) t Is a unit step function, is a random ij Monotonic density function decreasing with increasing (R-R) when t= (R-R) ij ) When the value is more than or equal to 0, the value is equal to 1; when t= (R-R ij ) When <0, the value is equal to 0.
(5) Optimizing projection objective function, determining optimal projection direction
The different projection directions indicate different characteristics of the data structure, namely the optimal projection direction can fully mine data information and expose the projection direction of a certain characteristic structure of high-dimensional data to the greatest extent. For a given sample set index value, Q (a) is only related to the change in projection direction, so that under certain constraints (s.t.), it can be optimized using objective function maximization, thereby estimating the optimal projection direction. The maximization objective function is shown in formula (9):
formula (9) is a j To optimize the complex nonlinear optimization problem of variables, the phase in mathematical software such as MATLAB, DPS and the like is currently adoptedThe module can realize the optimization of the projection objective function. The invention applies DPS software to solve the optimal projection direction and the projection value through a nonlinear optimization algorithm.
(6) Establishing a comprehensive evaluation model
The optimum projection direction can be obtained from (9)The value can reflect the contribution degree of each evaluation index to the research object; will->Substituting (5) to obtain the optimal projection value +.>According to projection value +.>And (3) comprehensively evaluating the original evaluation object by the distribution characteristics and the size of the original evaluation object.
(7) Finely dividing aquifer water-rich grade
And (3) classifying and evaluating the projection characteristic value by adopting a natural intermittent classification method according to the projection characteristic value obtained by the comprehensive evaluation model, fully considering the extremely non-uniformity of the 'bottom water-rich property', and further classifying the weak water-rich property into weaker water-rich property, weak water-rich property and extremely weak water-rich property, namely dividing the projection characteristic value into 4 natural stages which are respectively a medium water-rich region, a weak water-rich region and an extremely weak water-rich region by adopting the natural intermittent classification method.
In S101, in the embodiment of the invention, the comprehensive water-rich degree of "bottom-containing" is objectively reflected and evaluated, and on the basis of deposition characteristics such as the development thickness of "bottom-containing", lithology combined structure and the like and deposition phase analysis, based on a deposition water control law, the thickness of an aquifer, the thickness of a gravel layer, lithology-thickness index, sand-land ratio and the number of layers of the gravel layer (total number of layers of gravels and sand) are selected as main control factors of the water-rich degree of "bottom-containing", an evaluation index system consisting of the above 5 main control factors is constructed, and the water-rich degree of "bottom-containing" is quantitatively evaluated. The relationship between each main control factor and the water-rich property of the aquifer is as follows, wherein the thickness of the aquifer, the thickness of the gravel layer, the lithology structure index and the sand-to-ground ratio are all positive indexes for influencing the water-rich property of the aquifer, and the number of the gravel layers is a negative index for influencing the water-rich property.
In S105, the projection objective function is optimized by using a complex shape method to perform an optimization solution on the projection objective function. The complex shape method is an optimization algorithm which is most effective in processing and solving the problem of medium and small scale optimization, has global convergence, can rapidly calculate and obtain an optimal projection direction value, and can be used as an auxiliary optimizing tool of a projection pursuit method.
In S106, the absolute value of each component in the optimal projection direction essentially reflects the contribution degree (influence degree) of each evaluation index to the "bottom" rich water evaluation result, and the larger the absolute value of each component is, the larger the influence degree of the corresponding evaluation index on the "bottom" rich water is, and conversely, the smaller is.
In S107, the projection characteristic value can obtain a contour map of the 'bottom-contained' water-rich projection characteristic value after the visualization processing. The magnitude of the projected characteristic value reflects the degree of "bottom" water-rich, i.e., the greater the projected characteristic value, the greater the "bottom" water-rich. The projection characteristic value is used as the evaluation basis of the 'bottom-contained' water-rich range, so that the water-rich strength of each region can be intuitively compared, and the method has certain scientificity and operability.
As shown in fig. 2, the evaluation system for the water-rich refined partition of the loose aquifer of the mine comprises:
the evaluation index module is used for determining an evaluation index;
the evaluation index system establishment module is connected with the evaluation index module and is used for establishing an evaluation index system;
the projection tracking module is used for providing a projection tracking model;
the aquifer water-rich evaluation module is connected with the evaluation index system establishment module and the projection tracking module and is used for establishing an aquifer water-rich evaluation model by combining data of the evaluation index system establishment module and a model of the projection tracking module through DPS software.
The evaluation method of the mine loose aquifer water-rich refined partition provided by the application embodiment of the invention is applied to computer equipment, wherein the computer equipment comprises a memory and a processor, the memory stores a computer program, and when the computer program is executed by the processor, the processor executes the steps of the evaluation method of the mine loose aquifer water-rich refined partition.
The evaluation method of the mine loose aquifer water-rich refined partition provided by the application embodiment of the invention is applied to an information data processing terminal, and the information data processing terminal is used for realizing an evaluation system of the mine loose aquifer water-rich refined partition.
It should be noted that the embodiments of the present invention can be realized in hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or special purpose design hardware. Those of ordinary skill in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The device of the present invention and its modules may be implemented by hardware circuitry, such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., as well as software executed by various types of processors, or by a combination of the above hardware circuitry and software, such as firmware.
Example 1:
the present invention was used to evaluate aquifer water enrichment over a large study area.
And (3) establishing a model:
aiming at the characteristic that the water-bearing layer rich water quality evaluation index data has high-dimensional, nonlinear and non-normal distribution, a projection pursuit model which can effectively reflect the nonlinear characteristics between rich water quality and the evaluation index and has high inclusion property on the structural characteristics of the data is introduced to comprehensively evaluate the 'bottom-bearing' rich water quality, thereby breaking through the limitation that the traditional comprehensive evaluation method can only be used for normal distribution data processing generally, and overcoming the defects of larger subjectivity and the like in the weight determination in the general evaluation method. The projection pursuit model can fully reflect the internal structural characteristics of the original data, eliminates the interference of irrelevant variables and the like and the influence of subjective factors, and has more objectivity in the evaluation result.
And combining the constructed 'bottom-contained' water-rich evaluation index system, carrying out normalization processing on 384 groups of drilling data of the research area according to the projection pursuit model principle, and establishing an aquifer water-rich evaluation model through DPS software. And adopting a complex shape method to carry out optimization solution on the projection objective function. The complex shape method is an optimization algorithm which is most effective in processing and solving the problem of medium and small scale optimization, has global convergence, can rapidly calculate and obtain an optimal projection direction value, and can be used as an auxiliary optimizing tool of a projection pursuit method.
After the optimization, the maximum projection index function Q (a) = 2017.4179 is obtained, and the optimal projection direction is a= (0.4665,0.5963,0.5901,0.2795,0.0235), as shown in fig. 3. The absolute value of each component in the optimal projection direction essentially reflects the contribution degree (influence degree) of each evaluation index to the 'bottom' rich water evaluation result, and the larger the absolute value of each component is, the larger the influence degree of the corresponding evaluation index to the 'bottom' rich water is, and conversely, the smaller the influence degree is. Although the obtained optimal projection direction is essentially different from the weight value of the evaluation index, there is a relationship and commonality between the two, that is, both reflect the influence degree of each evaluation index on the result and the internal relationship of the original data, and the difference between the two is that the sum of the optimal projection direction values of each evaluation index is not 1, and the sum of the weight values of each evaluation index is 1.
The optimal projection direction a= (0.4665,0.5963,0.5901,0.2795,0.0235) shows that the influence degree of the gravel layer thickness, lithology-thickness index, water-bearing layer thickness, sand-ground ratio and sand layer number on the 'bottom-contained' water-rich property of a research area is sequentially reduced, wherein the sand-gravel layer thickness, lithology-thickness index and water-bearing layer thickness are the most main factors influencing the 'bottom-contained' water-rich property of the research area, and the influence of the sand-gravel layer number is the smallest.
Bringing the obtained optimal projection direction a into the formula (5) to obtain a projection characteristic value z capable of reflecting each evaluation index information i As shown in formula (10) and expressed in z i As the evaluation basis, analyzing and determining the evaluation result. And (3) carrying out visual processing on the projection characteristic values to obtain a contour map of the 'bottom-contained' rich water projection characteristic values, which is shown in fig. 4. The magnitude of the projected characteristic value reflects the degree of "bottom" water-rich, i.e., the greater the projected characteristic value, the greater the "bottom" water-rich. The projection characteristic value is used as the evaluation basis of the 'bottom-contained' water-rich range, so that the water-rich strength of each area of the research area can be intuitively compared, and the method has certain scientificity and operability. As can be seen from fig. 4, the north part of the study area has larger "bottom-contained" water-rich projection characteristic values, and the south part is smaller, and the overall trend is gradually reduced from the south to the north.
Rich water partition evaluation:
the size range of the 'bottom-contained' water-rich projection characteristic value of the research area is larger, which shows that the 'bottom-contained' water-rich characteristic value is unevenly distributed and has larger difference. In order to further objectively and quantitatively quantify the spatial distribution characteristics of the 'bottom-contained' rich water, a natural intermittent grading method is adopted to carry out grading evaluation on projection characteristic values. The method is favorable for finely characterizing the water-rich strength grade condition of the aquifer, refining the internal difference of the water-rich property of the aquifer and defining a key target area for preventing and controlling 'bottom water-containing' water damage of the mine. The projection characteristic value representing the water enrichment of the aquifer reflects the natural attribute of the aquifer, the natural discontinuous grading method is based on the natural grouping of the data, the natural breaking points are identified by selecting the maximum similarity value in the group or the maximum difference between the groups, the emphasis is that the natural breaking points and the grouping are emphasized, and the influence of human intervention is reduced, so that the natural breaking point grading method is selected for grading reasonably and scientifically.
In mine production practice, the water-rich grade of the mine aquifer is generally divided according to the water inflow amount of a drilling unit and the division standard in the rule of water control for coal mines. Through analyzing the drilling data of 15 'bottom contained' water pumping (injecting) tests in the range of a research area, the unit water inflow value is found to be 0.00062-0.33580L/(s.m), the water richness is in weak-medium grade, wherein the water richness accounts for 66.67% of the drilling with weak water richness, the water richness accounts for 33.33% of the drilling with medium water richness, the water pumping drilling data with extremely strong water richness and strong water richness are not found, but the unit water inflow value change range is quite large and is different by hundreds of times. In order to more objectively reflect the relative intensity of the 'bottom' water-rich property, and simultaneously, in order to make the water-rich partition prediction result more convenient for the development of mine control water work, the extremely non-uniformity of the 'bottom' water-rich property is fully considered, the level of the weak water-rich property is further divided into weaker water-rich property, weak water-rich property and extremely weak water-rich property, namely, a projection characteristic value is divided into 4 natural levels by using a natural discontinuous classification method, namely, a medium water-rich region (the projection characteristic value is > 0.5101), a weaker water-rich region (the projection characteristic value is 0.3155-0.5101), a weak water-rich region (the projection characteristic value is 0.1821-0.3155) and an extremely weak water-rich region (the projection characteristic value is < 0.1821), and a research region 'bottom' water-rich property partition diagram is drawn, and is shown in fig. 5. As can be seen from fig. 5, the "bottom-contained" water-rich property of the research area generally shows a tendency of gradually weakening from north to south, wherein the medium water-rich region is distributed in the north part of the mine and the vicinity of the south side of the fault village, the middle part of the mine is mainly a weaker water-rich region and a weak water-rich region, and the south part of the mine is mainly an extremely weak water-rich region.
In conjunction with the sedimentary phase analysis (fig. 6), the south "bottom" is mainly a palea-residuum phase sediment with very weak water-rich properties; the bottom-contained sediment in the middle part and the north part is mainly formed by gradually stacking multi-stage flood fan-phase sediment from east to west and from north to south, the water-rich overall is stronger than the slope-residual phase sediment, but the plane and vertical phases are fast due to the overlapping of different deposition sub-phases/micro-phases, the lithology structure is complex, the water-rich is nonuniform, and the water-rich is weak-medium water-rich. The results of the rich water assessment partition reflect the control of sediment relative to "bottom" rich water.
Verification of a water-rich evaluation model:
the unit water inflow is the most direct criterion for the water-rich nature of the aquifer. And (3) checking the reliability of the water-rich evaluation model according to the water inflow value of the drilling unit of 15 'bottom contained' water pumping (injecting) tests in the range of the research area. The distribution of pumping test drilling holes corresponding to each water-rich partition is shown in Table 1, 5 unit water inflow drilling holes are shared in the medium water-rich partition, wherein the water inflow ranges of the 4 holes of 62-4, 10-water 1, 11-water 2 and 66-68-4 are 0.13690-0.30330L/(s.m), the water-rich partition is divided into medium water-rich levels according to relevant specifications, the water-rich levels are matched with the judging result, and only 06-viewing 2 holes (q is 0.01111L/(s.m)), and the mistakes are judged; 6 holes with unit water inflow are drilled in the weaker water-rich area, wherein the unit water inflow ranges of 5 holes of 06-viewing 1, 10-water 2, 2019-water 1, 11-water 1 and 2013-water 1 are 0.00752-0.03317L/(s.m), the q value is obviously smaller than the q value in the medium water-rich area, and only 70-71-3 holes (q is 0.33580L/(s.m)) are judged to be wrong; 2 unit water inflow drill holes are drilled in the weak water-rich area, the unit water inflow ranges are respectively 2, 2015-2, 0.00349-0.00600L/(s.m), and q values are smaller than q values in the weaker water-rich area; 2 unit water inflow drill holes are formed in the extremely weak water-rich area, the unit water inflow ranges are 2019-water 2 and 74-75-6, the unit water inflow ranges are 0.00062-0.00253L/(s.m), and q values are smaller than q values in the extremely weak water-rich area.
Table 1 evaluation of zonal results and determination of drilling distribution in Water Pump test
Through the verification of water pumping (injecting) test drilling data, the unit water inflow value of the water pumping (injecting) drilling holes contained in the medium water-rich area, the weak water-rich area and the extremely weak water-rich area divided by the method sequentially has quantitative differences (only 70-71-3 holes and 06-viewing 2 are judged to be wrong), the q value of the medium water-rich area is more than 0.1L/(s.m), the q value of the weaker water-rich area, the weak water-rich area and the extremely weak water-rich area is less than 0.1L/(s.m), and the q value of the extremely weak water-rich area is less than the q value of the weaker water-rich area is less than 0.1L/(s.m). The evaluation model has higher coincidence degree of the judging result of the relative water-rich property and the result of the water-rich property grade judged according to the unit water inflow, the weak water-rich property grade is further finely divided, the water-rich property evaluation result is consistent with the sediment phase distribution and sediment water control rule of the bottom-containing, the influence of human factors is avoided in the whole process, and the model evaluation result is ideal.
Taking the 'bottom-contained' of the Xu mine in the Huaibei mining area as an example, the invention is applied to the 'bottom-contained' water-rich evaluation of the Xu mine, finely dividing the 'bottom-contained' water-rich grade and the subarea, and defining the key target area for preventing and controlling the 'bottom-contained' water hazard of the Xu mine, thereby ensuring that the Xu mine is influenced by the 'bottom-contained' water hazard to be 3 2 The coal seam is mined safely, and the control cost of the water damage of the bottom of the mine is effectively reduced.
The following are two specific embodiments and implementation schemes, and the evaluation method based on the mine loose aquifer water-rich refined partition is as follows:
embodiment one:
evaluation object: aquifer of a mine
Step 1: establishing an evaluation index matrix
Thickness of the aquifer: the actual thickness of the aquifer (in meters) was measured.
Gravel layer thickness: the actual thickness of the gravel layer (in meters) was measured.
Lithology-thickness index: parameters used to describe lithology are related to aquifer thickness.
Sand-to-land ratio: the ratio of the gravel layer thickness to the total aquifer thickness.
Number of layers of gravel layer: the number of layers of gravel was counted.
Step 2: normalization processing
And carrying out normalization processing on each evaluation index, and ensuring that the index with the larger and better numerical value and the index with the smaller and better numerical value are on the same scale.
Step 3: establishing a rich water evaluation model
And establishing an aquifer water-rich evaluation model based on the principle of the projection pursuit model by using DPS software.
The linear projection is performed in a model and a projection objective function is constructed.
Step 4: optimizing projection objective functions
And determining the optimal projection direction by optimizing the projection objective function so as to reflect the information of each evaluation index to the greatest extent.
Step 5: calculating projection characteristic values
And (3) bringing the optimal projection direction back to the expression of the linear projection, and calculating the projection characteristic value capable of reflecting the information of each evaluation index.
Step 6: comprehensive evaluation
And comprehensively evaluating the aquifer of the mine according to the distribution characteristics and the size of the projection characteristic values. The evaluation results include a water-rich grade or score to help mine managers better understand the hydrologic characteristics of the aquifer.
Embodiment two:
evaluation object: aquifer of another mine
Step 1: establishing an evaluation index matrix
The same evaluation criteria as in example one were used, including aquifer thickness, gravel layer thickness, lithology-thickness index, sand to ground ratio, number of layers of gravel layer.
Step 2: normalization processing
And carrying out normalization processing on each evaluation index, and ensuring that the index with the larger and better numerical value and the index with the smaller and better numerical value are on the same scale.
Step 3: establishing a rich water evaluation model
And establishing an aquifer water-rich evaluation model based on the principle of the projection pursuit model by using DPS software.
The linear projection is performed in a model and a projection objective function is constructed.
Step 4: optimizing projection objective functions
And determining the optimal projection direction by optimizing the projection objective function so as to reflect the information of each evaluation index to the greatest extent.
Step 5: calculating projection characteristic values
And (3) bringing the optimal projection direction back to the expression of the linear projection, and calculating the projection characteristic value capable of reflecting the information of each evaluation index.
Step 6: comprehensive evaluation
And comprehensively evaluating the aquifer of the mine according to the distribution characteristics and the size of the projection characteristic values, and providing Guan Fu water-based information.
These two examples demonstrate how the same method can be used to evaluate the water enrichment according to different mine and aquifer conditions, but the evaluation index and parameters can be adjusted according to the actual conditions. This approach helps to more accurately understand the hydrologic condition of the loose aquifer,
the foregoing is merely illustrative of specific embodiments of the present invention, and the scope of the invention is not limited thereto, but any modifications, equivalents, improvements and alternatives falling within the spirit and principles of the present invention will be apparent to those skilled in the art within the scope of the present invention.
Claims (10)
1. A method for evaluating the water-rich fine partition of a loose aquifer of a mine is characterized by combining a plurality of evaluation indexes to establish a standardized evaluation matrix, utilizing the principle of a projection pursuit model to establish a water-rich evaluation model through DPS software, and determining the optimal projection direction through linear projection and optimization of a projection objective function, so that the projection characteristic value of each evaluation index information is accurately reflected, and a more accurate and systematic method is provided for comprehensive evaluation.
2. The method for evaluating the water-rich refined partition of the loose aquifer of the mine according to claim 1, comprising the following steps:
s101, forming an evaluation index by the thickness of the aquifer, the thickness of the gravel layer, lithology-thickness index, sand-ground ratio and the number of layers of the gravel layer, and establishing an evaluation index matrix;
s102, unifying the variation ranges of different evaluation index data, carrying out normalization processing on the evaluation index with larger and better numerical value and the index with smaller and better numerical value to obtain a normalized standardized evaluation matrix, and constructing a 'bottom-contained' rich water evaluation index system;
s103, establishing an aquifer water-rich evaluation model through DPS software according to the principle of a projection pursuit model by combining the constructed bottom water-rich evaluation index system;
s104, performing linear projection and constructing a projection objective function in an aquifer water-rich evaluation model;
s105, optimizing a projection objective function, and determining an optimal projection direction;
s106, bringing the optimal projection direction back to the expression of the linear projection to obtain a projection characteristic value capable of reflecting the information of each evaluation index;
s107, comprehensively evaluating the evaluation object according to the distribution characteristics and the size of the projection characteristic values.
3. The method for evaluating the water-rich fine partition of the loose aquifer of the mine according to claim 2, wherein the aquifer thickness, the gravel layer thickness, the lithology structure index and the sand-to-land ratio in the S101 are all positive indexes for influencing the water-rich property of the aquifer, and the number of the gravel layers is a negative index for influencing the water-rich property.
4. The method for evaluating a water-rich refined partition of a loose aquifer of claim 2, wherein in S105, the projection objective function is optimized by adopting a complex method to perform an optimization solution on the projection objective function.
5. The method for evaluating the water-rich fine partition of the loose aquifer of claim 2, wherein in S106, the absolute value of each component of the optimal projection direction essentially reflects the contribution degree of each evaluation index to the evaluation result of the water-rich bottom, and the larger the absolute value of each component is, the larger the influence degree of the corresponding evaluation index on the water-rich bottom is, and vice versa.
6. The method for evaluating the water-rich refined partition of the loose aquifer of the mine according to claim 2, wherein the projection characteristic value in S107 can be obtained into a contour map of the water-rich projection characteristic value after the visualization processing.
7. The method for evaluating the water-rich refined partition of the loose aquifer of claim 2, wherein the magnitude of the projection characteristic value in S107 reflects the water-rich degree of the bottom, that is, the larger the projection characteristic value, the stronger the water-rich degree of the bottom.
8. An evaluation system for a mine loose aquifer water-rich refined partition implementing the evaluation method for a mine loose aquifer water-rich refined partition according to any one of claims 1-7, characterized in that the evaluation system for a mine loose aquifer water-rich refined partition comprises:
the evaluation index module is used for determining an evaluation index;
the evaluation index system establishment module is connected with the evaluation index module and is used for establishing an evaluation index system;
the projection tracking module is used for providing a projection tracking model;
the aquifer water-rich evaluation module is connected with the evaluation index system establishment module and the projection tracking module and is used for establishing an aquifer water-rich evaluation model by combining data of the evaluation index system establishment module and a model of the projection tracking module through DPS software.
9. A computer readable storage medium storing a computer program which, when executed by a processor, causes the processor to perform the steps of the method of evaluating a water-rich refined partition of a loose aquifer of a mine as claimed in any one of claims 1 to 7.
10. An information data processing terminal, wherein the information data processing terminal is used for realizing the evaluation system of the mine loose aquifer water-rich refined partition according to claim 8.
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