CN115615980A - Method and device for predicting typical ion concentration of mine water and computer equipment - Google Patents
Method and device for predicting typical ion concentration of mine water and computer equipment Download PDFInfo
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Abstract
The invention provides a method, a device and computer equipment for predicting typical ion concentration of mine water, wherein the method comprises the following steps: s10, respectively determining the water inflow Q of the mining working face and the water inflow Q of the goaf Air conditioner And the water inflow Q of the excavation roadway Digging machine (ii) a S20, respectively determining main ions in a mining working face, a goaf and a mine water sample of a driving roadway and detecting the concentration of the main ions; s30, respectively determining typical ions in a mining working face, a goaf and a water sample of a driving roadway according to the main ions and the concentration thereof obtained in the S20; s40, determining the water inflow Q of the mining working face and the water inflow Q of the goaf according to the S10 Air conditioner And water inflow amount Q of tunneling roadway Digging machine And S30, determining typical ions in the mine water, and calculating the concentration of the typical ions in the mixed mine water of the unexplored coal seam.
Description
Technical Field
The invention belongs to the field of mine water prevention and control and mine water resource utilization, and particularly relates to a method and a device for predicting typical ion concentration of mine water and computer equipment.
Background
China has abundant coal resources and is an irreplaceable stable main energy source in a short period. However, from the distribution region, the coal resources and water resources in China are reversely distributed. The western region has excellent coal resources, the coal resource reserve accounts for more than 70% of the total amount of the whole country, but the western mining region belongs to a arid and semi-arid water shortage region, and the water resource amount accounts for only 5.7% of the whole country. High intensity coal mining produces large quantities of mine water, in excess of 7.0 billion m3 of mine water per year. Direct discharge of mine water not only wastes water resources, but also destroys the ecological environment around the mining area. The mine water resource utilization is realized, and the mine water is used for production, life and ecological water after being treated, which is the main work for solving the contradiction between the shortage of water resources in coal areas and the waste of mine water resources.
The west mining areas are located in arid and semi-arid climate areas, the annual evaporation capacity is about 6 times of rainfall, the influence of evaporation and concentration is caused, and the mineralization degree of underground water and mine water is generally higher than the limit value of national GB 5749-2006 sanitary Standard for Drinking Water and GB/T14848-2017 underground Water quality Standard III class limit value by 1000mg/L. The highly mineralized mine water has bitter taste, is not suitable for direct drinking, causes salinization of soil due to no treatment and irrigation, and hinders resource utilization of the mine water due to the high mineralized degree. The mine water with high mineralization degree is mainly mixed with various ions (including K) in water + 、Na + 、Ca 2+ 、Mg 2+、 、SO 4 2- 、Cl - 、HCO 3 - ) The content is higher. The method has important significance for the treatment and resource utilization of the mine water with high mineralization degree by accurately identifying typical ions in the mine water and accurately predicting the concentration of the typical ions.
The current common methods for predicting typical ion concentration in a mine comprise two main types of neural network learning prediction methods and numerical simulation prediction methods. Although the artificial neural network has excellent characteristics of self-adaption, self-organization, self-learning and the like, a large amount of water quality data samples are needed for learning and training in the prediction process; the numerical simulation prediction mainly focuses on prediction of an ion pollution range, and is high in theoretical performance, multiple parameters are needed in the process of establishing a model, and the technical threshold is high. In summary, the above methods are difficult to be rapidly popularized and applied on site.
In actual production, the mine water sources are more, the main sources comprise mining working face water burst, goaf water burst and tunneling roadway water burst, the water quantity difference of the mine water from different sources is larger, the mine water is controlled by double control of natural factors and manual activities, the concentration of typical ions in different water sources is different, and the concentration of the typical ions in the collected mine water is directly influenced. Therefore, a typical ion concentration prediction method for coupling mine water quantity and mine water quality is developed, and a quantity and quality coupling prediction system is developed based on the typical ion concentration prediction method and is very necessary to be popularized and applied to the field.
Disclosure of Invention
Aiming at the defects in the prior art, the invention aims to provide a method for predicting the typical ion concentration in mine water, and solve the problems in the prior art.
In order to solve the technical problems, the invention adopts the following technical scheme to realize:
a method for predicting typical ion concentration in mine water is characterized by comprising the following steps:
s10, respectively determining the water inflow Q of the mining working face and the water inflow Q of the goaf Air conditioner And the water inflow Q of the excavation roadway Digging machine ；
S20, respectively determining main ions in a mining working face, a goaf and a mine water sample of a driving roadway and detecting the concentration of the main ions;
s30, respectively determining typical ions in a mining working face, a goaf and a water sample of a driving roadway according to the main ions and the concentration thereof obtained in the S20;
s40, determining the water inflow Q of the mining working face and the water inflow Q of the goaf according to the S10 Air conditioner And water inflow amount Q of tunneling roadway Digging machine And S30, determining typical ions in the mine water, and calculating the concentration of the typical ions in the mixed mine water of the unexplored coal seam.
Preferably, in S10, the water inflow of the mining face:
Q＝Q 1 +Q 2 (1)
wherein, Q is the water inflow of mining working face, unit: m is 3 /d；Q 1 Dynamic supply amount for mining working face, unit: m is 3 /d；Q 2 The unit is the static reserve of the mining working face: m is 3 D; k is the permeability coefficient, unit: m/d; m is the aquifer thickness, unit: m; h is the average head height, in units: m; s is a drainage head reduction value in units: m; r 0 To influence the radius, the unit: m; r is 0 For reference to radius, unit: m; b is 0 For adopting the working face trend length, unit: m; b is the working face inclination width, unit: m; eta is the influence coefficient of pit shape。
Preferably, the water inflow Q of the goaf is determined in the step S10 Air conditioner Water inflow quantity Q of driving tunnel Digging machine Collecting water inflow data of the mined goaf and the tunneling roadway in history, acquiring the water inflow change rule of the goaf and the tunneling roadway, and predicting the water inflow Q of the goaf in the unexploited area according to the water inflow increasing or attenuating rule Air conditioner And the water inflow Q of the driving tunnel Digging machine 。
Preferably, in S20, three mine water samples of a mining working face, a goaf and a driving roadway are respectively collected, and ICP-MS is adopted to respectively detect main cations K in the mine water samples + 、Na + 、Ca 2+ 、Mg 2+ Concentration and major anion SO 4 2- 、Cl - Concentration;
detection of HCO by chemical titration 3 - And (4) concentration.
Preferably, in S30, K is determined according to S20 + 、Na + 、Ca 2+ 、Mg 2+、 、SO 4 2- 、Cl - 、HCO 3 - The concentration of seven large ions is plotted in a pipe three-line graph, main anions and cations in the mine water are distinguished according to the main water chemistry type identified by the pipe three-line graph, and are defined as typical ions A, B and C.
Preferably, in S40, the concentration of typical ion a in the mixed mine water of the unexplored coal seam is predicted:
C A ＝K·C mining A +K Air conditioner ·C Null A +K Digging machine ·C Digging A (6)
Wherein K is the proportion of the water inflow of the mining working face to the total water inflow, and K is Air conditioner The ratio of the water inflow to the total water inflow in the goaf, K Digging machine The ratio of water inflow to total water inflow for the driving tunnel, C Mining A The average concentration of ions of the mining working face A is shown as the unit: mg/L; c Null A The average concentration of ions in the goaf A is shown in unit: mg/L; c Digging A Average concentration of ions A in the tunneling roadway, unit: mg/L.
Preferably, the proportion K of the water inflow of the mining working face to the total water inflow is as follows:
ratio K of water inflow to total water inflow in goaf Air conditioner ：
Ratio K of water inflow to total water inflow of excavation roadway Digging machine ：
Preferably, the average ion concentration C of the mining working face A Mining A ：
Average concentration C of ions in goaf A Null A ：
Average concentration C of A ions in excavation roadway Digging A ：
Wherein, C A1 Average concentration of a ions in the mining face sample 1, unit: mg/L; c A2 Average concentration of a ions in the mining face sample 2, unit: mg/L; c A3 Average concentration of a ions in the mining face sample 3, unit: mg/L; c An For sampling the average concentration of A ions in a working face sample nDegree, unit: mg/L; c An1 The average concentration of A ions in a goaf sample n is shown in unit: mg/L; c An2 The average concentration of A ions in a tunneling roadway sample n is shown as the following unit: mg/L; n is the number of water samples of a mining working face, a goaf and a driving roadway;
in the step S40, the concentration of typical ions B and the concentration of ions C in the mixed mine water of the unexplored coal seam are predicted together with the ions a.
An apparatus for predicting the typical ion concentration in mine water, the apparatus comprising:
the mining working face water inflow prediction module is used for acquiring the water inflow of the mining working face;
the goaf water inflow prediction module is used for acquiring the water inflow of the goaf;
the tunneling roadway water inflow prediction module is used for acquiring the water inflow of the tunneling roadway;
the mine water gushing proportion determining module is used for determining the water gushing proportion of each source mine water according to the water gushing amount of the mining working face, the goaf and the tunneling roadway, acquiring the proportion of water inflow of a mining working face to total water inflow, the proportion of water inflow of a goaf to total water inflow and the proportion of water inflow of a driving roadway to total water inflow;
the mine water typical ion distinguishing module of each source is used for obtaining main ions in mine water samples of a mining working face, a goaf and a driving roadway;
the water quality data acquisition module of each source mine is used for acquiring water quality data of each water sample of a mining working face, a goaf and a driving roadway mine;
the mine water typical ion average concentration determining module is used for determining the average concentration of typical ions in a mining working face, a goaf and a water sample of a driving tunnel according to the acquired main ions and water sample quality data in the mining working face, the goaf and the water sample of the mine of the driving tunnel;
and the concentration prediction module of the typical example of the water of the un-mined mine is used for predicting the concentration of the typical example of the water of the un-mined mine according to the proportion of the water inflow of the dynamic working face to the total water inflow, the proportion of the water inflow of the goaf to the total water inflow, the proportion of the water inflow of the excavation roadway to the total water inflow and the average concentration of typical ions.
A computer device: the system comprises a transceiver, a memory and a processor, wherein the memory stores computer readable instructions which, when executed by the processor, cause the processor to perform the method for predicting the typical ion concentration in the mine water, and the computer readable instructions, when executed by the one or more processors, cause the one or more processors to perform the method for predicting the typical ion concentration in the mine water.
Compared with the prior art, the invention has the following technical effects:
the method fully considers the source-sink process of the formation of the mine water, including the main source of the mine water, the mine water inflow amount of different sources and the mine water quality of different sources, and accurately predicts the concentration of typical ions in the mine water by coupling the mine water inflow amount and the mine water quality. The prediction method is convenient, simple and rapid, a prediction system is formed, the prediction method can be directly popularized and applied to the field, accurate data is provided for the system configuration of the high-salinity mine water treatment, and meanwhile theoretical support is provided for the utilization of high-salinity mine water resources.
Drawings
FIG. 1 is a schematic flow diagram of the present invention;
FIG. 2 (a) is a statistical chart of the historical water inflow of the gob of the present invention;
FIG. 2 (b) is a statistical chart of the historical water inflow of the excavation roadway of the invention;
FIG. 3 is a pipe trilinear diagram of the present invention;
FIG. 4 is a block diagram of the inventive apparatus;
fig. 5 is a schematic structural diagram of a computer device in an embodiment of the present invention.
The present invention will be explained in further detail with reference to examples.
Detailed Description
The following embodiments of the present invention are provided, and it should be noted that the present invention is not limited to the following embodiments, and all equivalent changes based on the technical solutions of the present invention are within the protection scope of the present invention.
Herein, TDS means Total dispersed solids, as Total dissolved solids; the mineralization degree of the mine water can be represented by TDS, and the concentration of the TDS is equal to main ion K in the mine water + 、Na + 、Ca 2+ 、Mg 2+ 、SO 4 2- 、Cl - 、HCO 3 - The total sum of main ions in the common mine water is more than 1000mg/L, and the mine water with high mineralization is obtained; ICP-MS stands for inductively coupled plasma emission spectrometer.
Example 1:
in the embodiment, hara ditch coal mine is selected to be positioned in a Liu Da test area of Shenmu city of Shaanxi province, 4.5 kilometers in the north, and is administrative affiliated to a Liu Da test area of Shenmu city. Connecting the large Liu Da well field with the Hala ditch as a boundary in south; the north is bounded by a stone Ge platform well field; east is bounded by the seven groove and shangmon boundary; west is bounded by wulanmulun river. Area of field 72.1308km 2 The capacity of the approved coal is 1600 ten thousand tons/year, and the current main coal mining layer is the Jurassic Yanan group 22 coal. In the future, 31-coal mining is expected, and the mineralization degree of mine water gradually increases along with the extension of mining to deep parts, so that the advance prediction of the typical ion concentration in 31-coal mine water is necessary for the treatment and utilization of mine water resources.
In this example, there are 4 coal faces to be mined, namely 31107 (face number), 31108, 31109 and 31110 faces. The method for predicting the water inflow of the four working faces comprises the following steps:
in the determination of the water inflow of the mining working face, the key point of the calculation of the dynamic replenishment lies in determining the permeability coefficient (K), the thickness (M) of an aquifer, the height (H) of an average water head and the water level depreciation (S) in the hydrogeology replenishment period; query for face strike length (B) from mining plan 0 ) Wide working face inclination (b); and (4) inquiring and determining the pit shape influence coefficient (eta) according to a coal mine control water manual. Specific values of the above acquisition parameters are shown in Table 1-1.
TABLE 1-1 Hara ditch coal mine hydrogeological parameters
| Working surface | B 0 | b | η | K | M | H | S |
| 31107 | 3100 | 300 | 1.11 | 0.01 | 54.00 | 45.00 | 45.00 |
| 31108 | 2791 | 300 | 1.11 | 0.01 | 54.00 | 45.00 | 45.00 |
| 31109 | 2500 | 300 | 1.11 | 0.01 | 54.00 | 45.00 | 45.00 |
| 31110 | 2400 | 300 | 1.11 | 0.01 | 54.00 | 45.00 | 45.00 |
Calculating dynamic replenishment quantity of mining working face according to the obtained parameters, taking 31107 working face as an example, substituting the parameters into a formula to calculate
R o ＝943.5+45＝988.5、
The dynamic replenishment amounts for the respective work planes 31108, 31109, 31110 were calculated, and the results are shown in tables 1-2.
TABLE 1-2 Hara gully coal mine 31107-31110 face dynamic replenishment calculation
Calculating the static reserve of the mining working face, substituting parameters such as mu d, F, M, t (which can be obtained according to mining plan) and the like into formula (3), and calculating the static reserve Q of the mining working face 2 Also, taking 31107 as an example of a work surface,
TABLE 1-3 Hara gully coal mine 31107-31110 working face static reserve calculation
Predicting the total water inflow in the stoping process of the continuous working face by using a dynamic-static reserve method, wherein the total water inflow of the mining working face is equal to the superposition of the dynamic supply amount and the static reserve amount, and the water inflow of the mining working face is obtained by Q = Q 1 +Q 2 The calculation results are shown in tables 1 to 4.
| Working surface | Dynamic replenishment quantity Q 1 (m 3 /h) | Static reserve Q 2 (m 3 /h) | Water inflow of mining working face (m 3/h) |
| 31107 | 54.68 | 4.65 | 59.33 |
| 31108 | 49.83 | 5.38 | 55.21 |
| 31109 | 45.25 | 4.22 | 49.47 |
| 31110 | 43.92 | 4.63 | 48.55 |
Water inflow Q of goaf and tunneling roadway Air conditioner And Q Digging machine The method comprises the steps of collecting and counting data of water inflow of 12 years of a coal mining face and a goaf in a 22-year coal mining seam from 2010 to 2021 (the past water inflow of the mining seam can be generally regarded as historical water inflow, and the change of the future water inflow can be predicted according to the change rule of the historical water inflow), and drawing a curve graph of the change of the water inflow along with time. Fig. 2 (a) is a time-varying graph of the goaf water inflow, and fig. 2 (b) is a time-varying graph of the heading face. According to the change data of the water inflow amount of the goaf, the total water inflow amount of the goaf basically presents a dynamic and stable state, and the water inflow amount is 220m 3 Fluctuating around/h. As can be seen from the water inflow change curve of the tunneling working face, after 2014, the water inflow of the tunneling working face is basically in a dynamic stable state, and the stable value is 20.85m 3 H is used as the reference value. Therefore, the water inflow Q of the goaf is predicted according to the prediction Air conditioner Is 220m 3 Per, water inflow quantity Q of driving tunnel Digging machine Is 20.85m 3 /h。
The main ions, the main ion concentration and the main ion concentration sum in each mine water sample are determined, and in order to predict typical ions in 31 coal mine water, 31 coal mine water main source (31 coal mining working face, 22 coal goaf and 31 coal driving working face) water samples need to be collected for detection and analysis. 10 groups of water samples are collected at the time, and Na is analyzed and detected + 、K + 、Ca 2+ 、Mg 2+ 、Cl - 、SO 4 2- 、HCO 3 - The results are shown in tables 1 to 5.
TABLE 1-5 mine Water ion concentrations from different sources (mg/L)
Determining typical ions in mine water samples
From the ion concentration data of tables 1-5, a pipe trilinear plot is plotted, as shown in FIG. 3. The major cations (Ca, mg, na + K) and anions (C1, SO) in the figure 4 ，HCO 3 ) Units of (d) are percent milliequivalents (ion milliequivalents equals concentration (mg/l) times ion valence divided by the mass of the element, a percent milliequivalents of a cation equals milliequivalents of a cation divided by the sum of milliequivalents of all cations, and a percent milliequivalents of an anion equals milliequivalents divided by the sum of milliequivalents of all anions). Each figure comprises three parts, two isosceles triangle domains are respectively arranged at the lower left and the lower right, the isosceles triangle domains are comprehensively corresponding to a diamond domain (figure 1), and the side length of each domain is read according to 100 equal parts. In the lower left isosceles triangular domain, the percent milliequivalents of the three major cations are expressed as single points on a three-line scale. In the lower right isosceles triangle, the anion is also denoted by the same method. Thus, the two single points drawn on the graph represent the relative concentrations of cations and anions in the groundwater. Rays are then taken through the two single-point parallel triangle outer edges to intersect at a point within the diamond region. This generally reflects the dominant anions and cations in the water sample, from which the water chemistry type is read. According to the principle, the water chemistry type of the mine water of the Hara ditch coal mine is mainly SO according to the figure 3 4 ·HCO 3 -Na. Ca and HCO 3 -Na form. Therefore, typical ions in the mine water are further judged to be Na, ca and HCO 3 、SO 4 And ion concentration prediction is performed using the ion concentration as a main object.
Method for determining mine water quality coupling method to predict concentration of typical ions in mixed mine water of unexploited coal bed
Calculating the proportion of the water inflow of the mining working face to the total water inflow according to the water inflow of the mining working face, the goaf and the mine of the driving working face
Proportion of water inflow to total water inflow in goaf
The ratio of water inflow to total water inflow of the excavation roadway
The results are shown in tables 1-6.
TABLE 1-6 proportionality coefficients of water burst from mines of different sources
| Source of mine water | 31107 | 31108 | 31109 | 31110 |
| 22 coal goaf K Air conditioner | 0.46 | 0.45 | 0.46 | 0.45 |
| 31 coal mining working face K | 0.04 | 0.05 | 0.04 | 0.05 |
| 31 coal driving tunnel K Digging machine | 0.50 | 0.50 | 0.50 | 0.50 |
Calculating typical ions HCO in mine water from different sources according to mining working face, goaf and driving working face mine water sample ion concentrations and formulas (10), (11) and (12) 3 、SO 4 Average concentrations of Na and Ca are shown in tables 1-7.
TABLE 1-7 typical average ion concentration (mg/L) of mine water from different sources
| Source of mine water | Na | Ca | HCO 3 | SO 4 |
| 22 coal goaf | 186.67 | 100.61 | 351.22 | 359.97 |
| 31 coal mining working face | 339.80 | 24.04 | 211.00 | 5.86 |
| 31 coal driving tunnel | 323.78 | 2.75 | 75.51 | 160.35 |
The Na, ca and HCO in the mixed mine water of the non-mined working faces 31107, 31108, 31109 and 31110 are calculated according to the formula (6) 3 、SO 4 The concentrations of four typical ions, the results are shown in tables 1-8.
TABLE 1-8 31107, 31108, 31109, 31110 prediction of typical ion concentration in mine water for working face
| Ion type | 31107 | 31108 | 31109 | 31110 | |
| Na | 261.35 | 262.88 | 261.35 | 262.88 | |
| Ca | 48.62 | 47.85 | 48.62 | 47.85 | |
| HCO 3 | 207.76 | 206.35 | 200.28 | 206.35 | |
| SO 4 | 246.00 | 242.45 | 246.00 | 242.45 |
Based on the same technical concept, the present application further provides a computer device, as shown in fig. 5, including a transceiver, a processor, and a memory, where the memory stores computer readable instructions, and the computer readable instructions, when executed by the processor, cause the processor to execute the method for predicting the typical ion concentration in the mine water in the above embodiments.
Based on the same technical concept, the present application also provides a storage medium storing computer readable instructions, which when executed by one or more processors, cause the one or more processors to execute the method for predicting the typical ion concentration in the mine water in the above embodiments.
Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present application may be embodied in the form of a software product, which is stored in a storage medium (ROM/RAM), and includes several instructions for enabling a terminal (which may be a mobile phone, a computer, a server, or a network device) to execute the methods according to the embodiments of the present application.
The embodiments of the present application have been described above with reference to the drawings, but the present application is not limited to the above-mentioned embodiments, which are only illustrative and not restrictive, and those skilled in the art can make many changes and modifications without departing from the spirit and scope of the present application and the protection scope of the claims, and all changes and modifications that come within the meaning and range of equivalency of the claims are to be embraced within their scope.
Claims (10)
1. A method for predicting typical ion concentration in mine water is characterized by comprising the following steps:
s10, respectively determining the water inflow Q of the mining working face and the water inflow Q of the goaf Air conditioner And the water inflow Q of the excavation roadway Digging machine ；
S20, respectively determining main ions in a mining working face, a goaf and a mine water sample of a driving roadway and detecting the concentration of the main ions;
s30, respectively determining typical ions in a mining working face, a goaf and a water sample of a driving roadway according to the main ions and the concentration thereof obtained in the S20;
s40, determining the water inflow Q of the mining working face and the water inflow Q of the goaf according to the S10 Air conditioner And water inflow amount Q of tunneling roadway Digging machine And S30, determining typical ions in each mine water, and calculating the concentration of the typical ions in the mixed mine water of the unexplored coal seam.
2. The method of predicting the typical ion concentration in mine water of claim 1,
in S10, the water inflow of the mining working face is as follows:
Q＝Q 1 +Q 2 (1)
wherein, Q is the water inflow of mining working face, unit: m is 3 /d；Q 1 Dynamic supply amount for mining working face, unit: m is 3 /d；Q 2 The unit is the static reserve of the mining working face: m is 3 D; k is the permeability coefficient in: m/d; m is the aquifer thickness, unit: m; h is the average head height, in units: m; s is a drainage head reduction value in units: m; r 0 To influence the radius, unit: m; r is 0 For reference to radius, unit: m; b is 0 For adopting the working face trend length, unit: m; b is the working face inclination width, unit: m; eta is the pit shape influence coefficient.
3. The method of predicting the typical ion concentration in mine water of claim 1,
and in the step S10, determining the water inflow Q of the goaf Air conditioner Water inflow quantity Q of driving tunnel Digging machine Collecting water inflow data of the mined goaf and the tunneling roadway in history, acquiring the water inflow change rule of the goaf and the tunneling roadway, and predicting the water inflow Q of the goaf in the unexploited area according to the water inflow increasing or attenuating rule Air conditioner And the water inflow Q of the driving tunnel Digging machine 。
4. The method of predicting the typical ion concentration in mine water of claim 1,
in S20, three mine water samples of a mining working face, a goaf and a driving roadway are respectively collected, and ICP-MS is adopted to respectively detect main cations K in the mine water samples + 、Na + 、Ca 2+ 、Mg 2+ Concentration and major anion SO 4 2- 、Cl - Concentration;
detection of HCO by chemical titration 3 - And (4) concentration.
5. The method of predicting the typical ion concentration in mine water of claim 4,
in S30, K is determined according to S20 + 、Na + 、Ca 2+ 、Mg 2+ 、、SO 4 2- 、Cl - 、HCO 3 - Drawing a pipe three-line graph according to the concentration of seven large ions, and distinguishing main anions and cations in the mine water according to the main water chemistry type identified by the pipe three-line graphIons are defined as typical ions A, B, c in mine water, wherein the number of the typical ions in the mine water is more than 1 and less than 7.
6. The method of predicting the typical ion concentration in mine water of claim 5,
in the step S40, the concentration of typical ions A in the mixed mine water of the unexplored coal seam is predicted:
C A ＝K·C mining A +K Air conditioner ·C Null A +K Digging machine ·C Digging A (6)
Wherein K is the proportion of the water inflow of the mining working face to the total water inflow, and K is Air conditioner The ratio of the water inflow to the total water inflow in the goaf, K Digging machine The ratio of water inflow to total water inflow for the driving tunnel, C Mining A The average concentration of ions in the mining working face A is shown as unit: mg/L; c Null A The average concentration of ions in the goaf A is shown as unit: mg/L; c Digging A Average concentration of ions A in the tunneling roadway, unit: mg/L.
7. The method of predicting the typical ion concentration in mine water of claim 6,
the proportion K of the water inflow of the mining working face to the total water inflow is as follows:
ratio K of water inflow to total water inflow in goaf Air conditioner ：
Ratio K of water inflow to total water inflow of excavation roadway Digging machine ：
8. The method of predicting the typical ion concentration in mine water of claim 7,
average concentration C of ions in mining working face A Mining A ：
Average concentration C of ions in goaf A Null A ：
Average concentration C of ions A in excavation roadway Digging A ：
Wherein, C A1 Average concentration of a ions in the mining face sample 1, unit: mg/L; c A2 Average concentration of a ions in the mining face sample 2, unit: mg/L; c A3 Average concentration of a ions in the sampling face sample 3, unit: mg/L; c An The average concentration of a ions in the sample n of the mining face is unit: mg/L; c An1 The average concentration of A ions in a goaf sample n is shown as the following unit: mg/L; c An2 The average concentration of A ions in a tunneling roadway sample n is shown as the following unit: mg/L; n is the number of water samples of a mining working face, a goaf and a driving roadway;
in the step S40, the concentration of typical ions B and the concentration of ions C in the mixed mine water of the unexplored coal seam are predicted together with the ions a.
9. An apparatus for predicting the concentration of typical ions in mine water, the apparatus comprising:
the mining working face water inflow prediction module is used for acquiring the water inflow of the mining working face;
the goaf water inflow prediction module is used for acquiring the water inflow of the goaf;
the tunneling roadway water inflow prediction module is used for acquiring the water inflow of the tunneling roadway;
the mine water gushing proportion determining module is used for determining the proportion of the water gushing of each source mine water according to the water gushing amount of the mining working face, the goaf and the driving roadway, acquiring the proportion of water inflow of a mining working face to total water inflow, the proportion of water inflow of a goaf to total water inflow and the proportion of water inflow of a driving roadway to total water inflow;
the source mine water typical ion distinguishing module is used for obtaining main ions in mine water samples of a mining working face, a goaf and a driving roadway;
the water quality data acquisition module of each source mine is used for acquiring water quality data of each water sample of a mining working face, a goaf and a driving roadway mine;
the mine water typical ion average concentration determining module is used for determining the average concentration of typical ions in the mining working face, the goaf and the water sample of the excavation roadway according to the obtained main ions and water sample water quality data in the mining working face, the goaf and the water sample of the mine of the excavation roadway;
and the concentration prediction module of the typical example of the water of the un-mined mine is used for predicting the concentration of the typical example of the water of the un-mined mine according to the proportion of the water inflow of the dynamic working face to the total water inflow, the proportion of the water inflow of the goaf to the total water inflow, the proportion of the water inflow of the excavation roadway to the total water inflow and the average concentration of typical ions.
10. A computer device, characterized by: comprising a transceiver, a memory and a processor, the memory having stored therein computer readable instructions which, when executed by the processor, cause the processor to perform the method of predicting the typical ion concentration in mine water of any of claims 1-8, the computer readable instructions, when executed by the one or more processors, cause the one or more processors to perform the method of predicting the typical ion concentration in mine water of any of claims 1-8.
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| CN116754735A (en) * | 2023-06-20 | 2023-09-15 | 北京低碳清洁能源研究院 | Method for predicting water quality components and concentration content of mine water of coal mine |
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| CN116754735A (en) * | 2023-06-20 | 2023-09-15 | 北京低碳清洁能源研究院 | Method for predicting water quality components and concentration content of mine water of coal mine |
| CN116754735B (en) * | 2023-06-20 | 2024-01-09 | 北京低碳清洁能源研究院 | Method for predicting water quality components and concentration content of mine water of coal mine |
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