Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine in Shandong, China: 1. Geological Analysis

Liu, Chunping; Peng, Bo; Qin, Jianxin

doi:10.1007/s10230-007-0004-6

Cited by 8 publications

(7 citation statements)

References 6 publications

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“…(9), and the boundary coefficients (a 1 ) and (a 2 ) in Equations (3), and (6) (in Liu et al (2007). These parameters are defined as the vector of k = {T,h,a}.…”

Section: Parameter Estimationmentioning

confidence: 99%

“…Boundary conditions of the ground water flow model are expressed by Eq. (3), (6), and (7) (in Liu et al (2007), which can be solved by FEM if the parameters in these equations can be determined. It is a nonlinear equation due to the unconfined water term in Eq.…”

Section: Modeling the Ground Water Movementmentioning

confidence: 99%

“…5; the base of the III 2 and III 3 zones can be regarded as horizontal, with an inferring elevation of -700 m (see Fig. 5 in Liu et al 2007). Because we hope to establish a two-dimensional model of ground water movement for both the horizontal and slope basement, the X-axis of the coordinate system was assumed to align with the base of each water-bearing zone in the southeast direction (i.e., the direction of the exploration line or the dip of the F 1 in plane projection), and the Y-axis to be perpendicular to the X-axis of each zone in the northeast direction (i.e., the trend of the F 1 in plane projection).…”

Section: Simplification Of Hydrogeological Conditionsmentioning

confidence: 99%

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Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine: 2. Simulation and Prediction of Mine Discharges

2007

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A two-dimensional model is presented as a way to hydrogeologically characterize the controlling factors in the Sanshandao Gold Mine. The finite element method was first applied to simulate the ground water system of the current operation, using leakage data and the calculated recharge. An inverse model was applied to the observed data (e.g., head and discharge) to verify and calibrate the ground water simulation model and to estimate the hydrogeological parameters for the water-bearing zones. Nonlinear mathematic programming was used to solve the inverse model and to estimate the model parameters in 17 districts with different hydrogeological characteristics. The finite element equations were solved by means of a large non-symmetrical sparse equation. The results were in agreement with what is currently observed in the mine. The models and the estimated parameters were then applied to predict the mine water discharge for drifts extending to depths of -330 to -600 m during the next development stage. In order to improve the predicted accuracy of the numerical model, an iterative element mesh was added in the districts near the drainage drifts so that the computed discharges that flowed into the drifts would approach the recharges that flow into the borders of the mine. The model was also used to understand how the mine discharge would be influenced by factors such as unsteady ground water flow and the construction of hydraulic barriers to restrict ground water from entering the pits.

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“…(9), and the boundary coefficients (a 1 ) and (a 2 ) in Equations (3), and (6) (in Liu et al (2007). These parameters are defined as the vector of k = {T,h,a}.…”

Section: Parameter Estimationmentioning

confidence: 99%

Section: Modeling the Ground Water Movementmentioning

confidence: 99%

Section: Simplification Of Hydrogeological Conditionsmentioning

confidence: 99%

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Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine: 2. Simulation and Prediction of Mine Discharges

2007

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“…Therefore, no chemical precipitations were produced in the mixing process. In this case, a ternary hybrid model that composed of seawater, brine, and atmospheric precipitation was established to evaluate their possible proportions in the mine discharge (Qin and Ma 2005;Liu et al 2007). In calculating the mixture ratios, the accuracy and reliability Assume the TDS and d 18 O of a seepage point is measured as m and -n%, and the composition of seawater, brine, and atmospheric precipitation count for a%, b% and c% respectively.…”

Section: Determination Of the Mixing Proportionsmentioning

confidence: 99%

Investigating the characteristics of mine water in a subsea mine using groundwater geochemistry and stable isotopes

Zhao

Guo

2015

Environ Earth Sci

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Investigation were conducted in the Xinli subsea mine from 2006 to 2011, which is the largest subsea mine in China and threatened by the overlying Quaternary aquifer and seawater. Hydrochemical and stable isotopic (d 2 H and d 18 O) analyses were used to study the relationships between various waters. Hydrochemical results indicated that the seepage water in the mine tunnels had higher EC, TDS, and concentrations of most elements than the seawater and saline groundwater. Water analyses indicated the mine discharge was a mixture of the seawater, brine, and atmospheric precipitation. The proportions of the three different sources were calculated based on hydrochemical and isotopic analyses. The seepage water were more isotopically enriched than the seawater but less than the brine. In addition, the isotope mixing calculation indicated that the average proportions of mine water from seawater, brine and atmospheric precipitation were about 38.5, 46, and 15.5 % respectively for the entire mine in 2006. However, the concentrations of these analyses decreased and the proportion of the seawater increased 21.1 % after 5 years of exploitation in 2011. These changes demonstrated that the surrounding rock mass underwent a certain extent of deformation and failure because of the mining disturbance, which enhanced the permeability of the surrounding rock mass.

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“…Traditional water quality and hydrochemical analysis have evolved into more advanced techniques for identifying water sources. For example, the isotope method could be used to track the source of mine water and determine the connectivity of groundwater aquifers based on the composition of mine water and the ratio of measured isotope [5,6];…”

Section: Introductionmentioning

confidence: 99%

Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush

Liu

Shen

et al. 2021

Geofluids

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In order to explore the law of groundwater evolution, the water source connection between faults and aquifers and the main sources of mine water inrush in the deep mining area of Yangcheng Coal Mine in Jining City, 40 groups of hydrochemical samples were collected and analyzed by Piper Diagram and Durov Diagram. The results showed that the fluidity of groundwater developing to the deep became weaker, the value of total dissolved solids (TDS) became larger. So, the roof and floor of coal seam were more similar in water quality types due to the conduction of faults. Using principal component analysis (PCA) to the raw data, two principal components were extracted, and the principal component scores were used as clustering variables for hierarchical cluster analysis (HCA), 5 groups of abnormal water samples were eliminated and 3 clustering groups M1, M2 and M3 were obtained from the other water samples on the tree diagram. The results showed that the combination of HCA and hydrochemical analysis was more effective in screening water samples, and the 3 clustering groups could be qualified samples to represent 3 major aquifers (Taiyuan Formation limestone aquifer, Shanxi Formation sandstone aquifer and Ordovician limestone aquifer). Finally, taking M1, M2 and M3 as grouping variables, the discriminant functions f 1 , f 2 and f 3 of the 3 aquifers were obtained, the results of stepwise discrimination analysis (SDA) showed that the discrimination model established by using 25 groups of standard water samples could discriminate the known water samples with the correct rate of 96%, 10 groups of unknown water samples collected at the fault are identified as Taiyuan Formation limestone water samples, which was consistent with the classification results of HCA, proving that the water inrush of fault DF53 was from Taiyuan Formation limestone aquifer, while the fault had little influence on Ordovician limestone aquifer.

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Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine in Shandong, China: 1. Geological Analysis

Cited by 8 publications

References 6 publications

Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine: 2. Simulation and Prediction of Mine Discharges

Geological Analysis and Numerical Modeling of Mine Discharges for the Sanshandao Gold Mine: 2. Simulation and Prediction of Mine Discharges

Investigating the characteristics of mine water in a subsea mine using groundwater geochemistry and stable isotopes

Application of Clustering and Stepwise Discriminant Analysis Based on Hydrochemical Characteristics in Determining the Source of Mine Water Inrush

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