CN113932877B - Karst water level prediction method for mining area and terminal equipment - Google Patents
Karst water level prediction method for mining area and terminal equipment Download PDFInfo
- Publication number
- CN113932877B CN113932877B CN202111163921.6A CN202111163921A CN113932877B CN 113932877 B CN113932877 B CN 113932877B CN 202111163921 A CN202111163921 A CN 202111163921A CN 113932877 B CN113932877 B CN 113932877B
- Authority
- CN
- China
- Prior art keywords
- water level
- karst
- mining area
- layering
- mining
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- XLYOFNOQVPJJNP-UHFFFAOYSA-N water Substances O XLYOFNOQVPJJNP-UHFFFAOYSA-N 0.000 title claims abstract description 240
- 238000005065 mining Methods 0.000 title claims abstract description 136
- 238000000034 method Methods 0.000 title claims abstract description 48
- 238000012544 monitoring process Methods 0.000 claims abstract description 35
- 230000035699 permeability Effects 0.000 claims description 15
- 238000004590 computer program Methods 0.000 claims description 14
- 238000003860 storage Methods 0.000 claims description 13
- 238000012549 training Methods 0.000 claims description 8
- 238000001556 precipitation Methods 0.000 claims description 5
- 238000001704 evaporation Methods 0.000 claims description 4
- 230000008020 evaporation Effects 0.000 claims description 4
- 230000008595 infiltration Effects 0.000 claims description 4
- 238000001764 infiltration Methods 0.000 claims description 4
- 238000010276 construction Methods 0.000 claims description 3
- 239000013589 supplement Substances 0.000 claims 2
- 230000002452 interceptive effect Effects 0.000 claims 1
- BVKZGUZCCUSVTD-UHFFFAOYSA-L Carbonate Chemical compound [O-]C([O-])=O BVKZGUZCCUSVTD-UHFFFAOYSA-L 0.000 description 7
- 239000011435 rock Substances 0.000 description 7
- 238000010586 diagram Methods 0.000 description 5
- 230000008569 process Effects 0.000 description 5
- 230000004044 response Effects 0.000 description 4
- 238000004364 calculation method Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000001514 detection method Methods 0.000 description 3
- 230000000694 effects Effects 0.000 description 3
- 230000006870 function Effects 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 230000004888 barrier function Effects 0.000 description 2
- 238000004891 communication Methods 0.000 description 2
- 230000003993 interaction Effects 0.000 description 2
- 230000002093 peripheral effect Effects 0.000 description 2
- 238000011002 quantification Methods 0.000 description 2
- 230000001502 supplementing effect Effects 0.000 description 2
- 230000009471 action Effects 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 238000003491 array Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000015572 biosynthetic process Effects 0.000 description 1
- 238000004422 calculation algorithm Methods 0.000 description 1
- 229910001748 carbonate mineral Inorganic materials 0.000 description 1
- 238000011217 control strategy Methods 0.000 description 1
- 230000007797 corrosion Effects 0.000 description 1
- 238000005260 corrosion Methods 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000004090 dissolution Methods 0.000 description 1
- 238000009826 distribution Methods 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 239000003673 groundwater Substances 0.000 description 1
- 150000002500 ions Chemical class 0.000 description 1
- 238000002955 isolation Methods 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000035515 penetration Effects 0.000 description 1
- 239000011148 porous material Substances 0.000 description 1
- 238000002360 preparation method Methods 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000002352 surface water Substances 0.000 description 1
- 239000011800 void material Substances 0.000 description 1
- 239000002349 well water Substances 0.000 description 1
- 235000020681 well water Nutrition 0.000 description 1
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01F—MEASURING VOLUME, VOLUME FLOW, MASS FLOW OR LIQUID LEVEL; METERING BY VOLUME
- G01F23/00—Indicating or measuring liquid level or level of fluent solid material, e.g. indicating in terms of volume or indicating by means of an alarm
-
- E—FIXED CONSTRUCTIONS
- E21—EARTH OR ROCK DRILLING; MINING
- E21F—SAFETY DEVICES, TRANSPORT, FILLING-UP, RESCUE, VENTILATION, OR DRAINING IN OR OF MINES OR TUNNELS
- E21F17/00—Methods or devices for use in mines or tunnels, not covered elsewhere
- E21F17/18—Special adaptations of signalling or alarm devices
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
- G06F17/10—Complex mathematical operations
- G06F17/15—Correlation function computation including computation of convolution operations
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A10/00—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE at coastal zones; at river basins
- Y02A10/40—Controlling or monitoring, e.g. of flood or hurricane; Forecasting, e.g. risk assessment or mapping
Landscapes
- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Mathematical Analysis (AREA)
- Theoretical Computer Science (AREA)
- Mining & Mineral Resources (AREA)
- Mathematical Physics (AREA)
- Data Mining & Analysis (AREA)
- Pure & Applied Mathematics (AREA)
- Computational Mathematics (AREA)
- Mathematical Optimization (AREA)
- Life Sciences & Earth Sciences (AREA)
- Computing Systems (AREA)
- Geology (AREA)
- Algebra (AREA)
- Geochemistry & Mineralogy (AREA)
- General Life Sciences & Earth Sciences (AREA)
- Databases & Information Systems (AREA)
- Software Systems (AREA)
- General Engineering & Computer Science (AREA)
- Fluid Mechanics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
- Management, Administration, Business Operations System, And Electronic Commerce (AREA)
Abstract
The application is applicable to the technical field of mines, and provides a karst water level prediction method and terminal equipment for a mining area, wherein the method comprises the following steps: acquiring water level monitoring data, and generating initial water level values of all layers according to the water level monitoring data; acquiring boundary factors to determine boundary information of each layer; acquiring the influence value of the interference factors on each layering; the karst water level of each layering is determined based on the karst water level prediction model of the mining area, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering, and the karst water level in each layering of the mining area is predicted through the karst water level prediction model of the mining area and the relevant information, so that the karst water level information under the current condition can be accurately analyzed, guidance is provided for mining work, disaster occurrence is reduced, and mining safety is improved.
Description
Technical Field
The application belongs to the technical field of mines, and particularly relates to a karst water level prediction method and terminal equipment for a mining area.
Background
The karst mining area forms karst in various forms due to the corrosion effect generated by surface water and underground water, and the penetration resistance and the damage capability of the rock are greatly reduced due to the existence of karst channels. When the karst water level is too high, disasters such as water burst, mud burst, ground collapse, river water backflow and the like can easily occur in the mine exploitation process. In order to reduce the occurrence of the disasters, the mining enterprises can monitor the karst water level in the mining area at present, however, the karst water level condition cannot be predicted in advance, and early warning cannot be performed in advance.
Disclosure of Invention
The embodiment of the application provides a karst water level prediction method and terminal equipment for a mining area, which can accurately predict the condition of the karst water level in the mining area.
In a first aspect, an embodiment of the present application provides a karst water level prediction method for a mining area, including:
acquiring water level monitoring data, and generating initial water level values of all layers according to the water level monitoring data;
acquiring boundary factors to determine boundary information of each layer;
acquiring the influence value of the interference factors on each layering;
and determining the karst water level of each layering based on the karst water level prediction model of the mining area, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering.
In a possible implementation manner of the first aspect, the method for constructing a three-dimensional model of a geological structure of a mining area further includes:
constructing a karst water level prediction model of a mining area;
and training the mining area karst water level prediction model based on the historical karst water level data to obtain a trained mining area karst water level prediction model.
In a possible implementation manner of the first aspect, the mining area karst water level prediction model is:
wherein S is s For water storage rate, K xx Is the permeability coefficient of the opposite main direction of the X axis, K yy Is the permeability coefficient, K of the opposite main direction of the Y axis zz Is the permeability coefficient of the opposite main direction of the Z axis, H is the water head value of a point (x, y, Z) at the moment t, W is the influence value of an interference factor, t is time, H is the water level value, omega is the calculation domain, H 0 (x,y,z,t 0 ) The initial water level value of the point (x, y, z) is q (x, y, z, t) is the supply quantity of unit area on the general water head boundary, cos (n, x), cos (n, y) and cos (n, z) are respectively the cosine of the included angle between the normal direction and the coordinate axis direction outside the water-proof boundary, mu is the saturation difference or the water supply degree, q w Is the sum of the air rainfall infiltration supplementing quantity and the underground water evaporation quantity on the unit area of the free surface Γ 2 Is a general head boundary Γ 3 Is a water-proof boundary.
In a possible implementation manner of the first aspect, the acquiring water level monitoring data and generating initial water level values of each layer according to the water level monitoring data includes:
splitting the mining area according to the hydrogeologic structure characteristics of the mining area to obtain each layering of the mining area;
an initial water level value for each of the tiers is determined based on the water level monitoring data.
In a possible implementation manner of the first aspect, obtaining the impact value of the interference factor on each layer includes:
obtaining interference factors;
and quantifying the interference factors to obtain the influence value of each layering.
In a possible implementation manner of the first aspect, the karst water level prediction method of a mining area further includes:
and generating a corresponding exploitation strategy according to the predicted karst water level condition.
In a possible implementation manner of the first aspect, the method for constructing a three-dimensional model of a geological structure of a mining area further includes:
and sending the mining strategy to a client.
In a second aspect, an embodiment of the present application provides a terminal device, including:
the first acquisition unit is used for acquiring water level monitoring data and generating initial water level values of all layers according to the water level monitoring data;
a second acquiring unit configured to acquire boundary information of each layer determined by boundary factors;
the third acquisition unit is used for acquiring the influence value of the interference factors on each layering;
and the prediction unit is used for determining the karst water level of each layering based on the karst water level prediction model of the mining area, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering.
In a third aspect, an embodiment of the present application provides a terminal device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, where the processor implements the steps of the karst water level prediction method of a mining area according to any one of the first aspects when the computer program is executed by the processor.
In a fourth aspect, embodiments of the present application provide a computer readable storage medium storing a computer program which, when executed by a processor, implements the steps of the karst water level prediction method of a mining area as defined in any one of the first aspects above.
In a fifth aspect, embodiments of the present application provide a computer program product which, when run on a server, enables the server to perform the karst water level prediction method of a mining area according to any one of the first aspects above.
Compared with the prior art, the embodiment of the application has the beneficial effects that:
according to the karst water level prediction method and the terminal equipment for the mining area, the karst water level in each layer of the mining area is predicted through the karst water level prediction model for the mining area, the initial water level value of each layer of the mining area, the boundary information of each layer and the influence value of each layer, the karst water level information under the current condition can be accurately analyzed, guidance is provided for mining work, occurrence of disasters is reduced, and mining safety is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the following description will briefly introduce the drawings that are needed in the embodiments or the description of the prior art, it is obvious that the drawings in the following description are only some embodiments of the present application, and that other drawings may be obtained according to these drawings without inventive effort for a person skilled in the art.
FIG. 1 is a schematic diagram of an implementation flow of a karst water level prediction method for a mining area according to an embodiment of the present application;
FIG. 2 is a schematic flow chart of another method for predicting karst water level in a mining area according to an embodiment of the present disclosure;
FIG. 3 is a schematic flow chart of another method for predicting karst water level in a mining area according to an embodiment of the present disclosure;
fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present application;
fig. 5 is a schematic structural diagram of another terminal device according to an embodiment of the present application.
Detailed Description
In the following description, for purposes of explanation and not limitation, specific details are set forth, such as particular system configurations, techniques, etc. in order to provide a thorough understanding of the embodiments of the present application. It will be apparent, however, to one skilled in the art that the present application may be practiced in other embodiments that depart from these specific details. In other instances, detailed descriptions of well-known systems, devices, circuits, and methods are omitted so as not to obscure the description of the present application with unnecessary detail.
It should be understood that the terms "comprises" and/or "comprising," when used in this specification and the appended claims, specify the presence of stated features, integers, steps, operations, elements, and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and/or groups thereof.
It should also be understood that the term "and/or" as used in this specification and the appended claims refers to any and all possible combinations of one or more of the associated listed items, and includes such combinations.
As used in this specification and the appended claims, the term "if" may be interpreted as "when..once" or "in response to a determination" or "in response to detection" depending on the context. Similarly, the phrase "if a determination" or "if a [ described condition or event ] is detected" may be interpreted in the context of meaning "upon determination" or "in response to determination" or "upon detection of a [ described condition or event ]" or "in response to detection of a [ described condition or event ]".
In addition, in the description of the present application and the appended claims, the terms "first," "second," "third," and the like are used merely to distinguish between descriptions and are not to be construed as indicating or implying relative importance.
Reference in the specification to "one embodiment" or "some embodiments" or the like means that a particular feature, structure, or characteristic described in connection with the embodiment is included in one or more embodiments of the application. Thus, appearances of the phrases "in one embodiment," "in some embodiments," "in other embodiments," and the like in the specification are not necessarily all referring to the same embodiment, but mean "one or more but not all embodiments" unless expressly specified otherwise. The terms "comprising," "including," "having," and variations thereof mean "including but not limited to," unless expressly specified otherwise.
The karst water level analysis method has great significance in guaranteeing safe and efficient mining of mines, reducing and preventing various geological disasters.
The soluble carbonate rock is eroded to form a void which can be connected from a tiny karst hole to a huge karst hole to form a single karst area channel or a grid-like karst body.
The formation of karst region channels mainly results from the dissolution of carbonate rock, and under the action of polar molecular charge and potentiodynamic conditions of water, ions in carbonate mineral lattices are separated from original positions and transferred into water, so that cavities are formed. The runoff of the karst pipeline is smooth, the flow speed and the flow rate are large, once the karst pipeline is revealed, water and mud burst of a pit are caused, and great potential safety hazards are brought to mining. Therefore, the water level of the karst is predicted in advance before exploitation, and the karst exceeding the safe water level is subjected to necessary water control strategies during exploitation, so that the safe development of exploitation work is ensured.
The embodiment of the application provides a karst water level prediction method for a mining area, which predicts the karst water level in each layering of the mining area through a mining area karst water level prediction model, an initial water level value of each layering of the mining area, boundary information of each layering and influence values of each layering, can accurately analyze the karst water level information under the current condition, provides guidance for mining work, reduces occurrence of disasters and improves mining safety.
The karst water level prediction method for the mining area provided by the embodiment of the application is described below with reference to the accompanying drawings:
referring to fig. 1, fig. 1 is a flowchart of a karst water level prediction method for a mining area according to an embodiment of the present application. As shown in fig. 1, the karst water level prediction method for a mining area may include S101 to S104, which are described in detail as follows:
s101: and acquiring water level monitoring data, and generating initial water level values of all layers according to the water level monitoring data.
In the embodiment of the present application, the water level monitoring data is historically obtained water level monitoring data. For example, water level monitoring data obtained at a plurality of water level monitoring points previously set in a mining area may be used as an initial water level value of a mining area karst water level prediction model, and for example, a karst water level value obtained by monitoring on the 12 th 2017 month 31 day may be obtained as the water level monitoring data.
In a specific application, each monitored karst water level value can be uploaded to a server, and the terminal equipment acquires the water level monitoring data by sending a data acquisition request to the server. For example, the terminal device may send a data acquisition request for acquiring the karst water level value monitored in 12 months 31 in 2017 to the server storing the historical water level monitoring data, and after receiving the data acquisition request, the server acquires the corresponding karst water level value and sends the corresponding karst water level value to the terminal device, so that the terminal device acquires the water level monitoring data. Of course, the terminal device may also send a data acquisition request not including the specified date to the server, and the server randomly extracts water level monitoring data of a certain day and transmits the water level monitoring data to the terminal device, so that the terminal device acquires the water level monitoring data.
In an embodiment of the present application, the step S101 includes:
splitting the mining area according to the hydrogeologic structure characteristics of the mining area to obtain each layering of the mining area;
an initial water level value for each of the tiers is determined based on the water level monitoring data.
In the embodiment of the application, the mining area can be split according to the hydrogeological structure characteristics of the mining area. The whole mining area is divided into 300 multiplied by 200 rectangular unit grids on a plane, and the rectangular unit grids are respectively expressed as a fourth series of loose rock pore aquifer, a Hutian group carbonate rock first water-weakly permeable layer, a Hutian group carbonate karst cave first water-containing channel, a Hutian group carbonate rock second water-weakly permeable layer, a Hutian group carbonate karst cave second water-containing channel and a Hutian group carbonate rock third water-weakly permeable layer with the elevation above-50 m from top to bottom in the vertical direction.
After each of the tiers is partitioned, an initial water level value for each tier is determined based on the water level monitoring data.
Specifically, the initial water level value of each layer can be determined in a linear interpolation mode by utilizing surfer software.
S102: the acquired boundary factors determine boundary information for each tier.
In the embodiment of the application, according to actual geology and hydrogeology characteristics of a mining area, the bottom boundary of the calculated domain is a water isolation boundary, and the four sides are generalized to be a general water head boundary.
Specifically, in the horizontal direction, the eastern, southern and western parts are bounded by the peripheral mining weight license range, the north part is bounded by the peripheral mining weight license range to the north latitude 2779044.33 geodetic coordinates, and the four sides are generalized as general water head boundaries. The top of the calculation area receives the supply of atmospheric rainfall on one hand and is a supply boundary; on the other hand, the ground water evaporates through the water-tight barrier, and the bottom is a water-tight barrier.
S103: and obtaining the influence value of the interference factors on each layering.
In the embodiment of the application, since natural precipitation, exploitation well, drainage well and the like in the mining area can influence the karst water level, the natural precipitation, exploitation well water inflow and drainage well drainage are taken as interference factors, and the influence values of the interference factors on the karst water level of each layering can be determined by quantifying the interference factors. It should be noted that, the quantification of natural precipitation, water inflow of the production well and drainage of the drainage well can be achieved based on the existing quantification method, and this application will not be repeated.
S104: and determining the karst water level of each layering based on the karst water level prediction model of the mining area, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering.
In specific application, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering are input into the mining area karst water level prediction model, so that the karst water level corresponding to each layering can be obtained. The mining area karst water level prediction model is a trained mining area karst water level prediction model.
In an embodiment of the present application, referring to fig. 2, the method for predicting karst water level in a mining area further includes:
s105: constructing a karst water level prediction model of a mining area;
s106: and training the mining area karst water level prediction model based on the historical karst water level data to obtain a trained mining area karst water level prediction model.
In a specific application, the mining area karst water level prediction model is a three-dimensional unsteady flow model.
In an embodiment of the present application, the mining area karst water level prediction model is:
wherein S is s For water storage rate, K xx Is the permeability coefficient of the opposite main direction of the X axis, K yy Is the permeability coefficient, K of the opposite main direction of the Y axis zz Is the permeability coefficient of the opposite main direction of the Z axis, H is the water head value of a point (x, y, Z) at the moment t, W is the influence value of an interference factor, t is time, H is the water level value, omega is the calculation domain, H 0 (x，y，z，t 0 ) The initial water level value of the point (x, y, z) is q (x, y, z, t) is the unit surface on the boundary of the general water headThe supply quantity of the product, cos (n, x), cos (n, y) and cos (n, z) are respectively the cosine of the included angle between the external normal direction of the waterproof boundary and the coordinate axis direction, mu is the saturation difference or the water supply degree, q w Is the sum of the air rainfall infiltration supplementing quantity and the underground water evaporation quantity on the unit area of the free surface Γ 2 Is a general head boundary Γ 3 Is a water-proof boundary.
In practical application, the water storage rate S s Permeability coefficient K of opposite main direction of water supply mu and X axis xx Permeability coefficient K of opposite main direction of Y axis yy Permeability coefficient K of opposite main direction of Z axis zz May be determined based on empirical values, as this application is not limited.
In the embodiment of the application, the created model can be trained and checked by utilizing historical data to obtain the mining area karst water level prediction model with prediction accuracy higher than an accuracy threshold, the trained mining area karst water level prediction model is pre-configured in the terminal equipment, and the terminal equipment can call the mining area karst water level prediction model when the karst water level of the mining area needs to be predicted. Of course, the trained karst water level prediction model of the mining area can be stored in the server, and when the terminal equipment needs to predict the karst water level of the mining area, a calling application is sent to the server so as to call the karst water level prediction model of the mining area to predict the water level.
Referring to fig. 3, another method for predicting karst water level in a mining area according to the embodiment of the present application may further include, after S104, the following steps:
s107: and generating a corresponding exploitation strategy according to the predicted karst water level condition.
In the embodiment of the application, different mining strategies can be set corresponding to the karst water level conditions, for example, when the water levels of the karst in all the layers are lower than the safe water level, the corresponding mining strategies are set so as not to need water control measures; when a karst channel exceeding a safe water level exists in a certain layer, the corresponding mining strategy is to drain the karst channel exceeding the safe water level in the layer; when karst passages exceeding a safe water level exist in each of the plurality of layers, the whole mining area is drained and the like.
It should be noted that the mining strategies corresponding to the karst water level conditions may be varied in a rich manner, and the above are merely examples and not limitations.
In practical applications, after determining the mining strategy, the mining strategy needs to be sent to a client (terminal equipment on the mining personnel side) so that mining personnel can perform mining preparation for the mining strategy.
From the above, it can be seen that according to the karst water level prediction method for the mining area provided by the embodiment of the application, the karst water level in each layer of the mining area is predicted through the initial water level value of each layer of the mining area karst water level prediction model and each layer of the mining area, the boundary information of each layer and the influence value of each layer, the karst water level information under the current condition can be accurately analyzed, a corresponding exploitation strategy can be generated, guidance is provided for exploitation work, occurrence of disasters is reduced, and exploitation safety is improved.
Fig. 4 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 4, the terminal device includes:
the first obtaining unit 401 is configured to obtain water level monitoring data, and generate initial water level values of each layer according to the water level monitoring data.
The second acquisition unit 402 is configured to acquire boundary information that determines each layer by boundary factors.
The third obtaining unit 403 is configured to obtain an impact value of the interference factor on each hierarchy.
The prediction unit 404 is configured to determine a karst water level of each of the strata based on the mining area karst water level prediction model, an initial water level value of each of the strata, boundary information of each of the strata, and an influence value of each of the strata.
In an embodiment of the present application, the terminal device further includes a construction unit and a training unit.
The construction unit is used for constructing a karst water level prediction model of the mining area;
the training unit is used for training the mining area karst water level prediction model based on the historical karst water level data to obtain the trained mining area karst water level prediction model.
In one embodiment of the present application, the first obtaining unit 401 is specifically configured to split the mining area according to the hydrogeological structure feature of the mining area, so as to obtain each layering of the mining area; an initial water level value for each of the tiers is determined based on the water level monitoring data.
In one embodiment of the present application, the third obtaining unit 403 is specifically configured to obtain an interference factor; and quantifying the interference factors to obtain the influence value of each layering.
In an embodiment of the present application, the terminal device further includes a mining policy generating unit and a transmitting unit.
The exploitation strategy generation unit is used for generating a corresponding exploitation strategy according to the predicted karst water level condition.
The sending unit is used for sending the mining strategy to the client.
It can be seen that, according to the terminal device provided by the embodiment of the application, the karst water level in each layer of the mining area can be predicted through the karst water level prediction model of the mining area, the initial water level value of each layer of the mining area, the boundary information of each layer and the influence value of each layer, the karst water level information under the current condition can be accurately analyzed, a corresponding exploitation strategy can be generated, guidance is provided for exploitation work, occurrence of disasters is reduced, and exploitation safety is improved.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
Fig. 5 is a schematic structural diagram of a terminal device according to an embodiment of the present application. As shown in fig. 5, the terminal device 5 of this embodiment includes: at least one processor 50 (only one shown in fig. 5), a memory 51 and a computer program 52 stored in the memory 51 and executable on the at least one processor 50, the processor 50 implementing the steps in any of the karst water level prediction method embodiments of a mine as described above when executing the computer program 52.
It will be appreciated by those skilled in the art that fig. 5 is merely an example of the terminal device 5 and is not meant to be limiting as the terminal device 5, and may include more or fewer components than shown, or may combine certain components, or different components, such as may also include input-output devices, network access devices, etc.
The processor 50 may be a central processing unit (Central Processing Unit, CPU), the processor 50 may also be other general purpose processors, digital signal processors (Digital Signal Processor, DSP), application specific integrated circuits (Application Specific Integrated Circuit, ASIC), off-the-shelf programmable gate arrays (Field-Programmable Gate Array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, or the like. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The memory 51 may in some embodiments be an internal storage unit of the terminal device 5, such as a hard disk or a memory of the terminal device 5. The memory 51 may in other embodiments also be an external storage device of the terminal device 5, such as a plug-in hard disk, a Smart Media Card (SMC), a Secure Digital (SD) Card, a Flash memory Card (Flash Card) or the like, which are provided on the terminal device 5. Further, the memory 51 may also include both an internal storage unit and an external storage device of the terminal device 5. The memory 51 is used for storing an operating system, application programs, boot loader (BootLoader), data, other programs, etc., such as program codes of the computer program. The memory 51 may also be used to temporarily store data that has been output or is to be output.
The embodiment of the application also provides a computer readable storage medium, wherein the computer readable storage medium stores a computer program, and the computer program can realize the steps in the karst water level prediction method embodiment of any mining area when being executed by a processor.
The embodiment of the application provides a computer program product, which when run on a terminal device, causes the terminal device to execute to implement the steps in the karst water level prediction method embodiment of any one of the mining areas.
It should be noted that, because the content of information interaction and execution process between the above devices/units is based on the same concept as the method embodiment of the present application, specific functions and technical effects thereof may be referred to in the method embodiment section, and will not be described herein again.
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-described division of the functional units and modules is illustrated, and in practical application, the above-described functional distribution may be performed by different functional units and modules according to needs, i.e. the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-described functions. The functional units and modules in the embodiment may be integrated in one processing unit, or each unit may exist alone physically, or two or more units may be integrated in one unit, where the integrated units may be implemented in a form of hardware or a form of a software functional unit. In addition, specific names of the functional units and modules are only for convenience of distinguishing from each other, and are not used for limiting the protection scope of the present application. The specific working process of the units and modules in the above system may refer to the corresponding process in the foregoing method embodiment, which is not described herein again.
In the foregoing embodiments, the descriptions of the embodiments are emphasized, and in part, not described or illustrated in any particular embodiment, reference is made to the related descriptions of other embodiments.
Those of ordinary skill in the art will appreciate that the various illustrative elements and algorithm steps described in connection with the embodiments disclosed herein may be implemented as electronic hardware, or combinations of computer software and electronic hardware. Whether such functionality is implemented as hardware or software depends upon the particular application and design constraints imposed on the solution. Skilled artisans may implement the described functionality in varying ways for each particular application, but such implementation decisions should not be interpreted as causing a departure from the scope of the present application.
In the embodiments provided in this application, it should be understood that the disclosed karst water level prediction method for a mine may be implemented in other manners. For example, the above-described apparatus/server embodiments are merely illustrative, e.g., the division of the modules or units is merely a logical functional division, and there may be additional divisions in actual implementation, e.g., multiple units or components may be combined or integrated into another system, or some features may be omitted, or not performed. Alternatively, the coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection via interfaces, devices or units, which may be in electrical, mechanical or other forms.
The units described as separate units may or may not be physically separate, and units shown as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.
The above embodiments are only for illustrating the technical solution of the present application, and are not limiting; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit and scope of the technical solutions of the embodiments of the present application, and are intended to be included in the scope of the present application.
Claims (7)
1. A karst water level prediction method for a mining area, comprising:
acquiring water level monitoring data, and generating initial water level values of all layers according to the water level monitoring data; splitting the mining area according to the hydrogeologic structure characteristics of the mining area to obtain each layering of the mining area, wherein each layering is distributed vertically from top to bottom;
acquiring boundary factors to determine boundary information of each layer;
acquiring the influence value of the interference factors on each layering; taking natural precipitation, water inflow of a exploitation well and drainage of a drainage well as interference factors;
determining karst water levels of all layers based on a karst water level prediction model of a mining area, initial water level values of all layers, boundary information of all layers and influence values of all layers;
generating a corresponding exploitation strategy according to the predicted karst water level condition, wherein the exploitation strategy comprises the following steps: when the water levels of karst in all the layers are lower than the safe water level, setting a corresponding exploitation strategy to be free from water control measures; when karst channels exceeding the safe water level exist in one layer, the corresponding mining strategy is to drain the karst channels exceeding the safe water level in the layer; when karst channels exceeding a safe water level exist in the multiple layers, the whole mining area is drained;
the method further comprises the steps of:
constructing a karst water level prediction model of a mining area;
training the mining area karst water level prediction model based on the historical karst water level data to obtain a trained mining area karst water level prediction model;
the mining area karst water level prediction model is as follows:
wherein,for the water storage rate->Is the permeability coefficient of the opposite main direction of the X axis,>is the permeability coefficient of the opposite main direction of the Y axis, < >>Is the permeability coefficient of the opposite main direction of the Z axis, H is the point +.>At->The water head value at moment, W is the influence value of interference factors, t is time, h is water level value, +.>For calculating the domain +.>For->Is%>For the supply of unit area on the boundary of the general head, < >>、/>、/>Cosine of the included angle between the external normal direction of the waterproof boundary and the coordinate axis direction, and +.>Is saturation difference or water supply degree->Is the sum of the air rainfall infiltration supplement quantity and the underground water evaporation quantity on the unit area of the free surface, +.>Is a general head boundary, < >>Is a water-proof boundary.
2. The method of karst water level prediction for a mine of claim 1, wherein the acquiring water level monitoring data and generating initial water level values for each of the strata based on the water level monitoring data comprises:
an initial water level value for each of the tiers is determined based on the water level monitoring data.
3. The method of karst water level prediction for a mine of claim 1, wherein obtaining a value of influence of an interfering factor on each of the strata comprises:
obtaining interference factors;
and quantifying the interference factors to obtain the influence value of each layering.
4. The method for predicting the karst water level in a mine of claim 1, further comprising:
and sending the mining strategy to a client.
5. A terminal device, comprising:
the first acquisition unit is used for acquiring water level monitoring data and generating initial water level values of all layers according to the water level monitoring data; splitting the mining area according to the hydrogeologic structure characteristics of the mining area to obtain each layering of the mining area, wherein each layering is distributed vertically from top to bottom;
a second acquiring unit configured to acquire boundary information of each layer determined by boundary factors;
the third acquisition unit is used for acquiring the influence value of the interference factors on each layering; taking natural precipitation, water inflow of a exploitation well and drainage of a drainage well as interference factors;
the prediction unit is used for determining the karst water level of each layering based on the karst water level prediction model of the mining area, the initial water level value of each layering, the boundary information of each layering and the influence value of each layering;
the mining strategy generation unit is used for generating a corresponding mining strategy according to the predicted karst water level condition and comprises the following steps: when the water levels of karst in all the layers are lower than the safe water level, setting a corresponding exploitation strategy to be free from water control measures; when karst channels exceeding the safe water level exist in one layer, the corresponding mining strategy is to drain the karst channels exceeding the safe water level in the layer; when karst channels exceeding a safe water level exist in the multiple layers, the whole mining area is drained;
the construction unit is used for constructing a karst water level prediction model of the mining area;
the training unit is used for training the mining area karst water level prediction model based on the historical karst water level data to obtain a trained mining area karst water level prediction model; the mining area karst water level prediction model is as follows:
wherein,for the water storage rate->Is the permeability coefficient of the opposite main direction of the X axis,>is the permeability coefficient of the opposite main direction of the Y axis, < >>Is the opposite main of Z axisDirection permeability coefficient, H is the point +.>At->The water head value at moment, W is the influence value of interference factors, t is time, h is water level value, +.>For calculating the domain +.>For->Is%>For the supply of unit area on the boundary of the general head, < >>、/>、/>Cosine of the included angle between the external normal direction of the waterproof boundary and the coordinate axis direction, and +.>Is saturation difference or water supply degree->Is the sum of the air rainfall infiltration supplement quantity and the underground water evaporation quantity on the unit area of the free surface, +.>Is a general-purpose head boundary and,/>is a water-proof boundary.
6. A terminal device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, carries out the steps of the karst water level prediction method of a mining area according to any one of claims 1 to 4.
7. A computer readable storage medium storing a computer program, characterized in that the computer program when executed by a processor implements the steps of the karst water level prediction method of a mining area according to any one of claims 1 to 4.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111163921.6A CN113932877B (en) | 2021-09-30 | 2021-09-30 | Karst water level prediction method for mining area and terminal equipment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111163921.6A CN113932877B (en) | 2021-09-30 | 2021-09-30 | Karst water level prediction method for mining area and terminal equipment |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113932877A CN113932877A (en) | 2022-01-14 |
| CN113932877B true CN113932877B (en) | 2023-12-22 |
Family
ID=79277662
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111163921.6A Active CN113932877B (en) | 2021-09-30 | 2021-09-30 | Karst water level prediction method for mining area and terminal equipment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113932877B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115394057B (en) * | 2022-07-13 | 2024-05-10 | 北京市轨道交通学会 | A method, device and system for monitoring and warning water level and water pressure of tunnel structure |
| CN117726045B (en) * | 2024-02-07 | 2024-05-10 | 山东大学 | Water inflow prediction method and system based on inversion of hydrological field along tunnel |
Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201193536Y (en) * | 2008-03-13 | 2009-02-11 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | Soil discharging apparatus for sump |
| KR101013182B1 (en) * | 2010-08-10 | 2011-02-10 | 한국지질자원연구원 | A computer-readable recording medium recording a program for executing the groundwater pumping method, the water level sensor and the pumping method using the groundwater level change. |
| CN102261262A (en) * | 2010-08-13 | 2011-11-30 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | High-performance foam mortar filling method for mine stope |
| WO2012045936A2 (en) * | 2010-09-27 | 2012-04-12 | Total Sa | Karstification simulation |
| EA201171238A1 (en) * | 2011-09-07 | 2013-03-29 | Открытое Акционерное Общество "Белгорхимпром" (Оао "Белгорхимпром") | METHOD OF PREVENTION OF FLOODING OF POTASSIUM MINES DURING BREAKTHROUGHES IN THE MINE OF UNDERGROUND WATER FROM GEOLOGICAL DISORDERS |
| CN103226732A (en) * | 2013-03-21 | 2013-07-31 | 中南大学 | GMS (groundwater modeling system)-based forecast method for ground water seepage fields at different mining levels of mining area |
| US10053985B1 (en) * | 2017-03-24 | 2018-08-21 | China University Of Mining & Technology-Beijing | Real-time water-level monitoring system for dumping site of open-pit coal mine, and methods of establishment and use of the same |
| CN109190854A (en) * | 2018-10-29 | 2019-01-11 | 六盘水师范学院 | A kind of method of the multifactor analogy prediction work face water yield of bottom plate water-filling |
| CN109271675A (en) * | 2018-08-24 | 2019-01-25 | 中煤科工集团西安研究院有限公司 | The critical level of ground water dynamic prediction method of Single-Index Model ecology of mining areas and device |
| CN110163416A (en) * | 2019-04-23 | 2019-08-23 | 水利部牧区水利科学研究所 | A kind of groundwater management method and device |
| CN110837701A (en) * | 2019-11-12 | 2020-02-25 | 中南大学 | Mining area bottom plate fault water inrush quantitative evaluation method based on full-coupling analysis |
| CN110874976A (en) * | 2019-11-29 | 2020-03-10 | 济南大学 | A simulation method for groundwater dynamics of karst springs |
| CN111577382A (en) * | 2020-04-14 | 2020-08-25 | 河北昕佳工程勘查设计有限公司 | Water damage prevention and comprehensive water resource utilization method for karst big water iron mine in Hebei Handan chen region |
| CN111798052A (en) * | 2020-07-03 | 2020-10-20 | 安徽大学 | A dynamic prediction method of three-dimensional spatial information in high-water-level coal mining subsidence water area |
| CN111927555A (en) * | 2020-08-14 | 2020-11-13 | 南京大学 | A dynamic prediction method of coal mine working face water inflow under mining disturbance conditions |
| CN113217043A (en) * | 2021-05-28 | 2021-08-06 | 中煤科工集团西安研究院有限公司 | Efficient and rapid plugging method and construction method for water source with water inrush fault water guide zone |
| CN113374440A (en) * | 2021-05-28 | 2021-09-10 | 中煤科工集团西安研究院有限公司 | Rapid plugging method and construction method for water inrush channel of hidden collapse column |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20060020408A1 (en) * | 2003-08-14 | 2006-01-26 | Cole George M | Methodology for prediction of shallow groundwater levels |
-
2021
- 2021-09-30 CN CN202111163921.6A patent/CN113932877B/en active Active
Patent Citations (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN201193536Y (en) * | 2008-03-13 | 2009-02-11 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | Soil discharging apparatus for sump |
| KR101013182B1 (en) * | 2010-08-10 | 2011-02-10 | 한국지질자원연구원 | A computer-readable recording medium recording a program for executing the groundwater pumping method, the water level sensor and the pumping method using the groundwater level change. |
| CN102261262A (en) * | 2010-08-13 | 2011-11-30 | 深圳市中金岭南有色金属股份有限公司凡口铅锌矿 | High-performance foam mortar filling method for mine stope |
| WO2012045936A2 (en) * | 2010-09-27 | 2012-04-12 | Total Sa | Karstification simulation |
| EA201171238A1 (en) * | 2011-09-07 | 2013-03-29 | Открытое Акционерное Общество "Белгорхимпром" (Оао "Белгорхимпром") | METHOD OF PREVENTION OF FLOODING OF POTASSIUM MINES DURING BREAKTHROUGHES IN THE MINE OF UNDERGROUND WATER FROM GEOLOGICAL DISORDERS |
| CN103226732A (en) * | 2013-03-21 | 2013-07-31 | 中南大学 | GMS (groundwater modeling system)-based forecast method for ground water seepage fields at different mining levels of mining area |
| US10053985B1 (en) * | 2017-03-24 | 2018-08-21 | China University Of Mining & Technology-Beijing | Real-time water-level monitoring system for dumping site of open-pit coal mine, and methods of establishment and use of the same |
| CN109271675A (en) * | 2018-08-24 | 2019-01-25 | 中煤科工集团西安研究院有限公司 | The critical level of ground water dynamic prediction method of Single-Index Model ecology of mining areas and device |
| CN109190854A (en) * | 2018-10-29 | 2019-01-11 | 六盘水师范学院 | A kind of method of the multifactor analogy prediction work face water yield of bottom plate water-filling |
| CN110163416A (en) * | 2019-04-23 | 2019-08-23 | 水利部牧区水利科学研究所 | A kind of groundwater management method and device |
| CN110837701A (en) * | 2019-11-12 | 2020-02-25 | 中南大学 | Mining area bottom plate fault water inrush quantitative evaluation method based on full-coupling analysis |
| CN110874976A (en) * | 2019-11-29 | 2020-03-10 | 济南大学 | A simulation method for groundwater dynamics of karst springs |
| CN111577382A (en) * | 2020-04-14 | 2020-08-25 | 河北昕佳工程勘查设计有限公司 | Water damage prevention and comprehensive water resource utilization method for karst big water iron mine in Hebei Handan chen region |
| CN111798052A (en) * | 2020-07-03 | 2020-10-20 | 安徽大学 | A dynamic prediction method of three-dimensional spatial information in high-water-level coal mining subsidence water area |
| CN111927555A (en) * | 2020-08-14 | 2020-11-13 | 南京大学 | A dynamic prediction method of coal mine working face water inflow under mining disturbance conditions |
| CN113217043A (en) * | 2021-05-28 | 2021-08-06 | 中煤科工集团西安研究院有限公司 | Efficient and rapid plugging method and construction method for water source with water inrush fault water guide zone |
| CN113374440A (en) * | 2021-05-28 | 2021-09-10 | 中煤科工集团西安研究院有限公司 | Rapid plugging method and construction method for water inrush channel of hidden collapse column |
Non-Patent Citations (5)
| Title |
|---|
| 基于FEFLOW和GIS技术的矿区地下水动态模拟及预测;李彩梅等;《干旱区地理》;第38卷(第02期);第359-367页 * |
| 汪磊.但家庙矿泉水富集成因与开采方案研究.《中国优秀硕士学位论文全文数据库 基础科学辑》.2017,(第12期),第A011-198页. * |
| 马志敬等.黑龙洞泉域岩溶地下水水质运移模拟分析.《科学技术与工程》.2020,第20卷(第36期),第14838-14846页. * |
| 马青山等.矿井涌水量预测三维数值模拟.《西安科技大学学报》.2015,第35卷(第2期),第236-241页. * |
| 骆祖江等.矿井涌水量预测数值模拟研究.《煤炭科学技术》.2015,第43卷(第1期),第33-36页. * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113932877A (en) | 2022-01-14 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Cheng et al. | Flood risk zoning by using 2D hydrodynamic modeling: A case study in Jinan City | |
| Macdonald et al. | Groundwater flooding within an urbanised flood plain | |
| CN113932877B (en) | Karst water level prediction method for mining area and terminal equipment | |
| Elmahdy et al. | Groundwater potential modelling using remote sensing and GIS: a case study of the Al Dhaid area, United Arab Emirates | |
| Mazi et al. | Intensively exploited Mediterranean aquifers: resilience to seawater intrusion and proximity to critical thresholds | |
| Elmahdy et al. | Natural hazards susceptibility mapping in Kuala Lumpur, Malaysia: an assessment using remote sensing and geographic information system (GIS) | |
| CN103226732A (en) | GMS (groundwater modeling system)-based forecast method for ground water seepage fields at different mining levels of mining area | |
| Pareta et al. | Landslide modeling and susceptibility mapping of Giri river watershed, Himachal Pradesh (India) | |
| Dong et al. | Optimization of mine drainage capacity using FEFLOW for the No. 14 Coal Seam of China’s Linnancang Coal Mine | |
| El Bastawesy et al. | Detection and assessment of the waterlogging in the dryland drainage basins using remote sensing and GIS techniques | |
| CN110489928B (en) | Method and system for predicting development height of water-flowing fractured zone in shallow coal seam mining area | |
| US10598818B2 (en) | Method for determining geological caves | |
| Park et al. | Debris flow hazard zonation by probabilistic analysis (Mt. Woomyeon, Seoul, Korea) | |
| CN110738378B (en) | A method and system for predicting debris flow disasters in mountainous areas | |
| Hou et al. | Effect of digital elevation model spatial resolution on depression storage | |
| Arunbabu et al. | Sedimentation and internal phosphorus loads in Krishnagiri Reservoir, India | |
| Xie et al. | Hydrogeological model for groundwater prediction in the Shennan mining area, China | |
| CN105046060B (en) | A kind of seat earth high artesian underground single hole dredges drop optimization method | |
| CN108062447B (en) | Method for predicting influence of diving precipitation on building settlement | |
| CN108133108B (en) | Method for predicting influence of confined water precipitation on building settlement | |
| 박경미 et al. | Strategies for an effective artificial recharge in alluvial stream-aquifer systems undergoing heavy seasonal pumping | |
| CN115062461A (en) | Anti-floating defense water level value taking system and method considering underground structure blocking effect | |
| CN116227710A (en) | Method and system for predicting variation degree of ecological water level under coal seam mining in ecologically fragile areas | |
| CN113920259A (en) | A three-dimensional model construction method and terminal equipment of a mining area geological structure | |
| CN116776517A (en) | Underground resource exploitation optimization method and device, computer equipment and storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |