CN110826762A - Mine water disaster evolution trend prediction method suitable for complex groundwater environment - Google Patents
Mine water disaster evolution trend prediction method suitable for complex groundwater environment Download PDFInfo
- Publication number
- CN110826762A CN110826762A CN201910886318.7A CN201910886318A CN110826762A CN 110826762 A CN110826762 A CN 110826762A CN 201910886318 A CN201910886318 A CN 201910886318A CN 110826762 A CN110826762 A CN 110826762A
- Authority
- CN
- China
- Prior art keywords
- water
- ions
- information
- inrush
- groundwater environment
- 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.)
- Withdrawn
Links
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/04—Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem"
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01D—MEASURING NOT SPECIALLY ADAPTED FOR A SPECIFIC VARIABLE; ARRANGEMENTS FOR MEASURING TWO OR MORE VARIABLES NOT COVERED IN A SINGLE OTHER SUBCLASS; TARIFF METERING APPARATUS; MEASURING OR TESTING NOT OTHERWISE PROVIDED FOR
- G01D21/00—Measuring or testing not otherwise provided for
- G01D21/02—Measuring two or more variables by means not covered by a single other subclass
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
- G01N33/1813—Water specific cations in water, e.g. heavy metals
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
- G01N33/18—Water
- G01N33/182—Water specific anions in water
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Systems or methods specially adapted for specific business sectors, e.g. utilities or tourism
- G06Q50/06—Electricity, gas or water supply
-
- 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
- Y02A20/00—Water conservation; Efficient water supply; Efficient water use
- Y02A20/152—Water filtration
Abstract
A mine water disaster evolution trend prediction method suitable for a complex groundwater environment comprises the following steps: (1) establishing a multi-point and multi-dimensional chart type database with water quality information as a main variable; (2) performing static analysis on hydrogeological information by using the multipoint-multidimensional mapping type database established in the step (1); (3) combining the multipoint-multidimensional mapping type database established in the step (1) to carry out dynamic analysis and prediction on the water inrush process; (4) and formulating a subsequent water prevention and control technical scheme according to the prediction result. The method has remarkable information anti-interference capability and low application threshold, can be used for preparing in daily water control work, can accurately judge a water inrush source before water inrush occurs, and has great guiding significance for controlling water damage of a large water mining area with complex groundwater environment.
Description
Technical Field
The invention relates to a method for predicting mine water disaster evolution trend, in particular to a method for predicting mine water disaster evolution trend suitable for complex groundwater environment, and belongs to the technical field of coal mine water prevention and control.
Background
At present, water source analysis methods for coal mines after water inrush mainly fall into two categories, namely traditional test analysis methods and mathematical statistics analysis methods. The traditional test analysis method comprises the steps of conventional water quality total analysis, trace element analysis, organic matter content analysis, isotope analysis, underground water dynamic analysis, radioactive element analysis and the like, and mainly identifies a water source through manual analysis; the mathematical statistical analysis method is mainly used for constructing a hydrogeological database based on hydrogeological information and performing water source analysis by means of statistical analysis, nonlinear analysis and the like.
The traditional test analysis method is only suitable for the conditions that the water quality difference is obvious and the hydraulic connection between water-containing layers is weak; the mathematical statistics analysis method has complex model construction and long research period, and is difficult to carry out quick and effective early warning before a water inrush event happens but the water inrush event is not developed into a disaster.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a mine water disaster evolution trend prediction method suitable for a complex groundwater environment, which has obvious information anti-interference capability and low application threshold, can carry out preparation work in daily water prevention and control work, can accurately judge a water inrush source before water inrush occurs, and has great guiding significance for early warning and prevention and control of water disasters in a large water mine area with a complex groundwater environment.
In order to achieve the purpose, the invention provides a mine water disaster evolution trend prediction method suitable for a complex groundwater environment, which comprises the following steps:
(1) establishing a multi-point and multi-dimensional chart type database with water quality information as a main variable:
establishing a coordinate system with time as a horizontal axis and a water quality information index as a vertical axis, and drawing water quality information and other hydrogeological information data of different aquifers in the coordinate system by horizontal lines according to the numerical values of the water quality information and the other hydrogeological information data;
sampling and analyzing immediately after water inrush occurs, and sequentially drawing water sample information of water inrush positions into a chart according to the time sequence of information acquisition; the interval time of water sample collection can be adjusted at any time according to the change condition so as to control the development trend as the standard.
(2) Performing static analysis on hydrogeological information by using the multipoint-multidimensional mapping table database established in the step (1), wherein the static analysis comprises the steps of finding out differences and relations among different water quality indexes of different aquifers, finding out sensitive ions with the highest water source identification sensitivity and finding out effective identification domains capable of independently identifying water sources;
(3) performing dynamic analysis and prediction on a water bursting process by combining the multipoint-multidimensional mapping table database established in the step (1), wherein the water quality characteristics of water bursting points in the water bursting process show dynamic evolution characteristics, and when an information curve tends to be stable and enters an effective identification domain, the water source type can be determined;
(4) and (3) formulating a subsequent water prevention and control technical scheme according to the prediction result:
and (4) according to the water inrush source type determined in the step (3), a water prevention and control technical scheme matched with the water source type can be formulated, and the engineering technical investment is determined according to different water damage types and threat degrees thereof.
Further, in the step (1), the same aquifers drawn into the coordinate system are marked by specific colors and line types, and the colors and the line types of different aquifers are obviously different; the water quality information comprises potassium ions, sodium ions, calcium ions, magnesium ions, chloride ions, sulfate ions, bicarbonate ions and mineralization degree; other hydrogeological information data includes water volume, water temperature, water level at the water outlet point or observation point.
In step (2), the sensitive ions are ions whose water quality can be distinguished according to their content.
Further, in the step (2), the effective identification area refers to a non-overlapping area in the graph established in the step (1) where different water qualities can be distinguished.
The invention relates to a method for forecasting the water disaster evolution trend of a mine, which comprises the steps of establishing a multipoint-multidimensional chart type database with water quality information as a main variable, finding out differences and relations among different water quality indexes of different aquifers through static analysis, finding out sensitive ions with the highest water source identification sensitivity and effective identification domains capable of identifying water sources independently, forecasting the water disaster evolution trend through dynamic analysis, determining the water source type, and making a corresponding water prevention and control technical scheme according to the determined water source type.
Drawings
FIG. 1 is a schematic diagram of a multi-point-multi-dimensional graph design according to the present invention;
FIG. 2 is a diagram showing the variation trend of the content of potassium and sodium ions in the water inrush process of the present invention;
FIG. 3 is a graph showing the trend of the content of calcium ions in the water inrush process according to the present invention;
FIG. 4 is a diagram showing the trend of the change of the chloride ion content during the water inrush process according to the present invention;
FIG. 5 is a graph showing the variation of the magnesium ion content during the water inrush process according to the present invention;
FIG. 6 is a graph showing the trend of the sulfate ion content in the water inrush process according to the present invention;
FIG. 7 is a graph showing the trend of the bicarbonate ion content during water bursting according to the present invention;
FIG. 8 is a graph showing the trend of the salinity content during water inrush according to the present invention.
Detailed Description
The invention will be further explained with reference to the drawings.
A mine water disaster evolution trend prediction method suitable for a complex groundwater environment comprises the following steps:
(1) establishing a multi-point and multi-dimensional chart type database with water quality information as a main variable:
establishing a coordinate system with time as a horizontal axis and a water quality information index as a vertical axis, and drawing water quality information and other hydrogeological information data of different aquifers in the coordinate system by horizontal lines according to the numerical values of the water quality information and the other hydrogeological information data;
sampling and analyzing immediately after water inrush occurs, and sequentially drawing water sample information of water inrush positions into a chart according to the time sequence of information acquisition;
(2) performing static analysis on hydrogeological information by using the multipoint-multidimensional mapping table database established in the step (1), wherein the static analysis comprises the steps of finding out differences and relations among different water quality indexes of different aquifers, finding out sensitive ions with the highest water source identification sensitivity and finding out effective identification domains capable of independently identifying water sources;
(3) performing dynamic analysis and prediction on a water bursting process by combining the multipoint-multidimensional mapping table database established in the step (1), wherein the water quality characteristics of water bursting points in the water bursting process show dynamic evolution characteristics, and when an information curve tends to be stable and enters an effective identification domain, the water source type can be determined;
(4) and (3) formulating a subsequent water prevention and control technical scheme according to the prediction result:
and (4) according to the water inrush source type determined in the step (3), a water prevention and control technical scheme matched with the water source type can be formulated, and the engineering technical investment is determined according to different water damage types and threat degrees thereof.
In order to distinguish different aquifers, the same aquifer drawn into a coordinate system adopts specific color and line type marks, and the colors and the line types of different aquifers are obviously different; the water quality information comprises potassium ions, sodium ions, calcium ions, magnesium ions, chloride ions, sulfate ions, bicarbonate ions and mineralization degree; the other hydrogeological information data comprise water quantity, water temperature and water level of a water outlet point or an observation point, and the reliability of the chart type database is higher when the information quantity of the chart type database is larger.
In the step (2), the sensitive ions refer to ions capable of distinguishing water quality according to the content of the sensitive ions, as shown in fig. 2, 5 and 6, corresponding intervals of the sandstone water quality, the taigrey water and the aogrey water are not overlapped, so that the sandstone water, the taigrey water and the aogrey water can be distinguished by using the content of potassium, sodium ions, magnesium ions and sulfate ions; in addition, it can be found from FIG. 6 that the sulfate ion content in Taigrey water and Ordovician grey water is 330mg/L, and the sulfate ion content in sandstone water and Taigrey water is 200mg/L, so that the three water qualities can be preliminarily distinguished by the sulfate ion. The sulfate ions can be used as sensitive ions of sandstone water, Taigrey water and Ordovician water in the ore area.
As shown in fig. 1 to 8, for a complex groundwater environment, the water quality of different aquifers may be very similar, which results in data information overlapping in a graph, at this time, the overlapping interval cannot effectively identify the water quality data, which is called as an invalid identification domain, and a relatively independent range can distinguish different types of water quality, which is called as an effective identification domain, and the effective identification domain reflects the water quality difference of different aquifers, so that the water source of the water inrush can be analyzed by this method after the water quality curve enters these non-overlapping areas.
After the multi-point-multi-dimension chart type database is used for static analysis, the information of the water inrush point sample is continuously monitored for dynamic analysis, and the dynamic analysis in the application refers to a reasonable explanation of the fluctuation condition of an information curve after water inrush by combining hydrogeological conditions, and determines whether the water quality of a water channel is polluted to form short-term fluctuation or whether the channel and the water inrush scale are further activated to form a disaster phenomenon. When the sample information curve begins to enter the effective identification domain, the aquifer can be determined to be the water inrush source, trend lines shown in fig. 5, 6 and 8 all enter the effective identification domain, so that the Aohui water participates in the current water inrush, the water inrush source is determined, a water prevention and control technical scheme matched with the water source type can be formulated subsequently, and the engineering technical investment is determined according to different water damage types and threat degrees thereof.
The mine water damage evolution trend prediction method suitable for the complex groundwater environment has the advantages that ① data compatibility is good, a multipoint-multidimensional chart-type database can be compatible with various discrete hydrogeological data information, an intuitive background value database is easy to construct, ② reliability is high, preliminary analysis, namely static analysis, can be carried out when only a few single samples exist after water inrush occurs, secondary analysis, namely dynamic analysis, is carried out by using development trend lines of water inrush information when the number of samples gradually increases, reliability deficiency caused by single water sample analysis can be avoided, misjudgment is formed, ③ application range is wide, analysis by using the trend lines of water inrush information has strong anti-interference capacity, the method is suitable for a water-bearing stratum system with large water quality difference and is more suitable for underground water inrush source analysis with complex groundwater environment, ④ technical threshold is low, use value is high, no complex mathematical calculation and research and development investment is needed, and a real-time and reliable water damage prediction method is provided for production technicians on the line.
Claims (4)
1. A mine water disaster evolution trend prediction method suitable for a complex groundwater environment is characterized by comprising the following steps:
(1) establishing a multi-point and multi-dimensional chart type database with water quality information as a main variable:
establishing a coordinate system with time as a horizontal axis and a water quality information index as a vertical axis, and drawing water quality information and other hydrogeological information data of different aquifers in the coordinate system by horizontal lines according to the numerical values of the water quality information and the other hydrogeological information data;
sampling and analyzing immediately after water inrush occurs, and sequentially drawing water sample information of water inrush positions into a chart according to the time sequence of information acquisition;
(2) performing static analysis on hydrogeological information by using the multipoint-multidimensional mapping table database established in the step (1), wherein the static analysis comprises the steps of finding out differences and relations among different water quality indexes of different aquifers, finding out sensitive ions with the highest water source identification sensitivity and finding out effective identification domains capable of independently identifying water sources;
(3) performing dynamic analysis and prediction on a water bursting process by combining the multipoint-multidimensional mapping table database established in the step (1), wherein the water quality characteristics of water bursting points in the water bursting process show dynamic evolution characteristics, and determining the type of a water source after an information curve tends to be stable and enters an effective identification domain;
(4) and (3) formulating a subsequent water prevention and control technical scheme according to the prediction result:
and (4) according to the water inrush source type determined in the step (3), making a water prevention and control technical scheme matched with the water source type.
2. The method for predicting the evolution trend of the mine water disaster applicable to the complex groundwater environment as claimed in claim 1, wherein in the step (1), the same aquifers drawn into the coordinate system are marked by specific colors and line types, and the colors and the line types of different aquifers are obviously different; the water quality information comprises potassium ions, sodium ions, calcium ions, magnesium ions, chloride ions, sulfate ions, bicarbonate ions and mineralization degree; other hydrogeological information data includes water volume, water temperature, water level at the water outlet point or observation point.
3. The method for predicting the evolution trend of the water damage of the mine suitable for the complex groundwater environment as claimed in claim 1 or 2, wherein in the step (2), the sensitive ions refer to ions which can be distinguished according to the content of the sensitive ions.
4. The method for predicting the evolution trend of the mine water damage suitable for the complex groundwater environment according to claim 1 or 2, wherein in the step (2), the effective identification domain refers to a non-overlapping region in the graph established in the step (1) where different water qualities can be distinguished.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910886318.7A CN110826762A (en) | 2019-09-19 | 2019-09-19 | Mine water disaster evolution trend prediction method suitable for complex groundwater environment |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201910886318.7A CN110826762A (en) | 2019-09-19 | 2019-09-19 | Mine water disaster evolution trend prediction method suitable for complex groundwater environment |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN110826762A true CN110826762A (en) | 2020-02-21 |
Family
ID=69548064
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201910886318.7A Withdrawn CN110826762A (en) | 2019-09-19 | 2019-09-19 | Mine water disaster evolution trend prediction method suitable for complex groundwater environment |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN110826762A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113361213A (en) * | 2021-06-08 | 2021-09-07 | 华北科技学院(中国煤矿安全技术培训中心) | Water source identification method based on coupling of hydraulics and hydrochemistry |
| CN115327061A (en) * | 2022-08-15 | 2022-11-11 | 山东清锦环保科技有限公司 | Water heavy metal detection method, device, equipment and storage medium |
Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103899356A (en) * | 2014-02-21 | 2014-07-02 | 北京华安奥特科技有限公司 | Integrated information system for monitoring, early warning, management and control of mine water disasters |
| CN106246224A (en) * | 2016-08-11 | 2016-12-21 | 山东科技大学 | Mine water disaster at-once monitor early warning system |
-
2019
- 2019-09-19 CN CN201910886318.7A patent/CN110826762A/en not_active Withdrawn
Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103899356A (en) * | 2014-02-21 | 2014-07-02 | 北京华安奥特科技有限公司 | Integrated information system for monitoring, early warning, management and control of mine water disasters |
| CN106246224A (en) * | 2016-08-11 | 2016-12-21 | 山东科技大学 | Mine water disaster at-once monitor early warning system |
Non-Patent Citations (1)
| Title |
|---|
| 牟林: "水质动态曲线预测在突水水源判别中的应用", 《煤田地质与勘探》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113361213A (en) * | 2021-06-08 | 2021-09-07 | 华北科技学院(中国煤矿安全技术培训中心) | Water source identification method based on coupling of hydraulics and hydrochemistry |
| CN115327061A (en) * | 2022-08-15 | 2022-11-11 | 山东清锦环保科技有限公司 | Water heavy metal detection method, device, equipment and storage medium |
| CN115327061B (en) * | 2022-08-15 | 2023-08-22 | 山东清锦环保科技有限公司 | Water quality heavy metal detection method, device, equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| WO2019042483A2 (en) | Tbm boring rock state real-time sensing system and method | |
| CN102926810B (en) | Forecasting method of coal and gas outburst | |
| CN109993459B (en) | Method for identifying water bursting source of complex multi-aquifer mine | |
| CN102930253B (en) | Coal and rock identification method based on image discrete multi-wavelet transform | |
| CN110826762A (en) | Mine water disaster evolution trend prediction method suitable for complex groundwater environment | |
| CN114660254A (en) | In-situ layered online monitoring system and prediction method for field groundwater pollution | |
| CN205193004U (en) | Colliery gushing water water source identification system | |
| CN103615236A (en) | Method for real-time monitoring of formation pressure by means of remote mud logging information | |
| CN204789440U (en) | Soil detecting device | |
| CN116658246A (en) | Coal mine water damage monitoring and early warning system and method | |
| CN107942383A (en) | Roof sandstone watery grade prediction technique | |
| CN112983405A (en) | Natural gamma logging method for rock debris | |
| CN113917558A (en) | Mine water source rapid distinguishing method, hydrological monitoring system, device and storage medium | |
| CN110873904B (en) | Fluid identification method and device | |
| Jin et al. | Application of distance discriminant analysis method to headstream recognition of water-bursting source | |
| CN112784706B (en) | Oil testing test operation area safety control method based on image intelligent identification | |
| CN110836790A (en) | Multi-channel automatic measuring device and method for centralized control room of in-situ leaching uranium mining area | |
| CN104297308A (en) | Device for rapidly distinguishing water inrush source of mine | |
| CN110130885A (en) | A kind of single-well crude oil bearing analysis device and analysis method | |
| CN203941096U (en) | A kind of multiparameter water quality analyzer | |
| CN115759351A (en) | Slurry shield tunneling comprehensive early warning method and system and storage medium | |
| CN104990963A (en) | On-line water quality monitoring system | |
| CN104018883A (en) | On-line/off-line coal bed gas pressure monitoring and analyzing system | |
| CN204789326U (en) | Non - hydrocarbon CO2 gas analysis appearance of oil gas exploration process mid ir | |
| You et al. | The research of coal and gas outburst warning based on logistic regression and geographic information system |
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 | ||
| WW01 | Invention patent application withdrawn after publication | ||
| WW01 | Invention patent application withdrawn after publication |
Application publication date: 20200221 |