scholarly journals Research on a Numerical Simulation and Prediction Model of Floor Mining Failure Depth in the Chenghe Mining Area

Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-14
Author(s):  
Ang Li ◽  
Qian Mu ◽  
Wenzhong Zhang ◽  
Chaoyang Liu ◽  
Feng Wang ◽  
...  
Keyword(s):  
Water Pressure ◽  
Mining Area ◽  
Small Error ◽  
Empirical Formulas ◽  
Mining Operations ◽  
Nonlinear Fitting ◽  
Mining Depth ◽  
Floor Failure ◽  
Mining Width ◽  
Failure Depth

Ordovician limestone water on the floor is a serious threat to the safety of coal mine production in the Weibei coalfield, and prediction of the floor failure depth is the key for evaluating the mining conditions under pressure. This paper combines the hydrogeological conditions of the no. 5 coal seam and uses the FLAC3D program to determine the floor failure depth under two-factor (mining depth and width) and multifactor (mining depth, width, and height) conditions via numerical calculations and analysis. We obtain the fitting formula for the floor failure depth and analyze the influence of various factors on it. The results show that when the mining width does not exceed 200 m, the mining width has the greatest influence on the floor failure depth, followed by mining depth and mining height. In this paper, the working face floor failure depths measured values of 18 flat seams in China are taken as samples for comparison with the values calculated via empirical formulas and fitting formulas, and the maximum and minimum absolute errors and relative errors are analyzed. The nonlinear fitting regression formulas offered in this paper are found to provide strong predictive value, high accuracy, and a relatively small error range. The reliability and rationality of the models are further verified, thus providing a reference for future mining operations under safe aquifer water pressure conditions in the Weibei coalfield.

Justification of engineering safety criteria for undermining of water-proof layer in the Upper Kama Salt Deposit

2021 ◽  
pp. 57-63
Author(s):  
A. A. Baryakh ◽  
L. O. Tenison
Keyword(s):  
Water Soluble ◽  
Russian Science ◽  
Mining Operations ◽  
Subsidence Trough ◽  
Safety Criterion ◽  
Mining Depth ◽  
Mine Sites ◽  
Main Thing ◽  
Water Proof

Safety of a water-proof pillar between the stoping void and the aquifers defines the key feature of water-soluble mineral mining. In this regard, the most important element of geomechanical supervision of mining operations, especially, at the mine project stage, is the engineering safety criteria aimed at the adequate valuation of safe undermining of water-proof strata (WPS). The WPS safety procedures now in force calculate only maximal sagging of undermined beds and disregard deformation in the edge area of WPS. In the meanwhile, the edges of WPS are the areas of localization of maximal horizontal strains, and the hazard of vertical jointing is the highest in these areas. In this connection, in the capacity of the index of the manmade load on WPS, it is proposed to use the maximal slope of the edge area of the subsidence trough. The evaluations were carried out in 6 Uralkali’s mine sites selected from the mathematical modeling and geophysical survey data which exhibited considerable damage of WPS. Based on the implemented research and justifications, it is recommended to use the generalized safety criterion for undermining of WPS as a maximal subsidence/mining depth ratio which is directly proportional to the ground slope. This engineering procedure describes more adequately the fracture mechanism in WPS rocks, in particular, damage localization in edge areas of the subsidence trough, or influence of mining depth on WPS stability and, which is main thing, is based on the criteria derived from the long-term observations and measurements performed in the Upper Kama deposit. The study was supported by the Russian Science Foundation, Grant No. 19-77-30008.

A Robust Method to Predict Fluid Properties Based on Big Data and Machine Learning Algorithms

2021 ◽  
Author(s):  
Yingxian Liu ◽  
Cunliang Chen ◽  
Hanqing Zhao ◽  
Yu Wang ◽  
Xiaodong Han
Keyword(s):  
Machine Learning ◽  
Physical Properties ◽  
Learning Algorithm ◽  
Direct Method ◽  
Learning Algorithms ◽  
Small Error ◽  
Machine Learning Algorithms ◽  
Well Test ◽  
Empirical Formulas ◽  
Fluid Properties

Abstract Fluid properties are key factors for predicting single well productivity, well test interpretation and oilfield recovery prediction, which directly affect the success of ODP program design. The most accurate and direct method of acquisition is underground sampling. However, not every well has samples due to technical reasons such as excessive well deviation or high cost during the exploration stage. Therefore, analogies or empirical formulas have to be adopted to carry out research in many cases. But a large number of oilfield developments have shown that the errors caused by these methods are very large. Therefore, how to quickly and accurately obtain fluid physical properties is of great significance. In recent years, with the development and improvement of artificial intelligence or machine learning algorithms, their applications in the oilfield have become more and more extensive. This paper proposed a method for predicting crude oil physical properties based on machine learning algorithms. This method uses PVT data from nearly 100 wells in Bohai Oilfield. 75% of the data is used for training and learning to obtain the prediction model, and the remaining 25% is used for testing. Practice shows that the prediction results of the machine learning algorithm are very close to the actual data, with a very small error. Finally, this method was used to apply the preliminary plan design of the BZ29 oilfield which is a new oilfield. Especially for the unsampled sand bodies, the fluid physical properties prediction was carried out. It also compares the influence of the analogy method on the scheme, which provides potential and risk analysis for scheme design. This method will be applied in more oil fields in the Bohai Sea in the future and has important promotion value.

The Characteristics of Collapse Columns in Duanwang Minefield and their Influences on Gas Emission Quantities of Coal Faces

2013 ◽  
Vol 634-638 ◽  
pp. 3537-3540
Author(s):  
Xin Xian Zhai ◽  
Xiao Ju Li ◽  
Yan Wei Zhai
Keyword(s):  
Coal Mine ◽  
Production Capacity ◽  
Mining Area ◽  
Mine Safety ◽  
Shanxi Province ◽  
Free Form ◽  
Karst Collapse ◽  
Coal Face ◽  
Gas Emission ◽  
Mining Depth

Duanwang Coal Mine is located at north of Qinshui coalfield in Shanxi province, China, which gently inclined and thick seams have been mined. Authorized production capacity of the coal mine is 1.8Mt/a. With the increase of mining depth, the mine gas emission quantity increased. Karst collapse columns are very developed in the minefield, and the phenomenon of abnormal gas emission always occurred at the coal face and driving gateway around the collapse columns, then the mine became high gassy one from low gassy mine. Using field measurement and theoretical analysis methods, the following conclusion can be drawn. Karst collapse columns have significant influences on gas emission of the coal face and driving gateway. Here are large amount of free form gas into and around the collapse columns, the collapse columns were disclosure while driving gateway, a large amount of the free gas into collapse column would be instantly released, which caused abnormal gas emission at driving gateway, even leading to gas density exceeding limitation by Coal Mine Safety Regulation of China. However, during mining area of the collapse columns, gas emission quantity at coal face was relatively smaller.

scholarly journals Annual production enhancement at deep mining

2019 ◽  
Vol 123 ◽  
pp. 01043 ◽  
Author(s):  
Nataliia Shvaher ◽  
Tetiana Komisarenko ◽  
Serhii Chukharev ◽  
Svitlana Panova
Keyword(s):  
Iron Ore ◽  
Underground Mine ◽  
Annual Production ◽  
Direct Proportion ◽  
Operating Life ◽  
Mining Operations ◽  
Deep Mining ◽  
Second Stage ◽  
Mining Depth ◽  
Mining Enterprise

The article aims at determining possible annual production considering mining and technical capabilities of the underground mine. Deepening of mining operations at Kryvyi Rih iron ore basin reduces considerably annual production of the useful mineral which results in increased mining costs. To maintain annual production, it is reasonable to build the second stage of opening the depth of which depends on production volumes. When determining the optimal depth of the first stage opening, it is necessary to apply a complex research method including the graphoanalytical one for determining the underground mine’s annual production and the industrial one for adjusting the methods considering technical conditions of the enterprise. It has been determined that annual production is influenced not only by mining and geological but also by mining and technical conditions. It has been proved that annual production of an underground mine decreases in direct proportion to the increased depth of mining. The speed of skips in the shaft is greatly impacted by the length of the main opening and its operating life. With the increase of the shaft operating life the skip speed decreases from 12 to 6 – 8 m/s. When designing the flowchart of further opening of underlying levels, it is necessary to consider both mining capabilities and technical conditions of the shaft and headgear, mining depth and the main opening operating life as well as the strategy of the mining enterprise. Consideration of the above mentioned factors enables maintaining the required annual production when mining iron ores at great depths. Under conditions of Kryvyi Rih iron ore basin, it has been determined reasonable to apply the main vertical shaft flowchart when mining reserves to the depth of 1650 m.

scholarly journals Water Preservation and Conservation above Coal Mines Using an Innovative Approach: A Case Study

Energies ◽  
2020 ◽  
Vol 13 (11) ◽  
pp. 2818
Author(s):  
Yujun Xu ◽  
Liqiang Ma ◽  
Yihe Yu
Keyword(s):  
Coal Mining ◽  
Water Conservation ◽  
Large Scale ◽  
Influencing Factor ◽  
Mining Area ◽  
Mining Operations ◽  
Narrow Strip ◽  
Geological Conditions ◽  
The Impact

To better protect the ecological environment during large scale underground coal mining operations in the northwest of China, the authors have proposed a water-conservation coal mining (WCCM) method. This case study demonstrated the successful application of WCCM in the Yu-Shen mining area. Firstly, by using the analytic hierarchy process (AHP), the influencing factors of WCCM were identified and the identification model with a multilevel structure was developed, to determine the weight of each influencing factor. Based on this, the five maps: overburden thickness contour, stratigraphic structure map, water-rich zoning map of aquifers, aquiclude thickness contour and coal seam thickness contour, were analyzed and determined. This formed the basis for studying WCCM in the mining area. Using the geological conditions of the Yu-Shen mining area, the features of caved zone, water conductive fractured zone (WCFZ) and protective zone were studied. The equations for calculating the height of the “three zones” were proposed. Considering the hydrogeological condition of Yu-Shen mining area, the criteria were put forward to evaluate the impact of coal mining on groundwater, which were then used to determine the distribution of different impact levels. Using strata control theory, the mechanism and applicability of WCCM methods, including height-restricted mining, (partial) backfill mining and narrow strip mining, together with the applicable zone of these methods, were analyzed and identified. Under the guidance of “two zoning” (zoning based on coal mining’s impact level on groundwater and zoning based on applicability of WCCM methods), the WCCM practice was carried out in Yu-Shen mining area. The research findings will provide theoretical and practical instruction for the WCCM in the northwest mining area of China, which is important to reduce the impact of mining on surface and groundwater.

scholarly journals Study on the mechanism of water inrush in the arid western mining area

2019 ◽  
Vol 118 ◽  
pp. 03008
Author(s):  
Chao Zheng ◽  
Lan Yu ◽  
Jiangyi He ◽  
Fengfeng Yang ◽  
Jufeng Zhang
Keyword(s):  
Large Scale ◽  
Water Pressure ◽  
Water Inrush ◽  
Hydrodynamic Pressure ◽  
Mining Area ◽  
Mining Areas ◽  
Isolation Layer ◽  
Working Face ◽  
Combined Action ◽  
Tension Fracture

The analysis found that the coal mining process in the western mining area has the mining loss and disaster effect of the water-rich aquifer of the coal seam roof, which is mainly manifested by the overburden water in the roof. On this basis, the formation and development of the separation water of the roof is proposed, and the mechanism of the water inrush from the layer is revealed. It is found that there is hydrostatic pressure and hydrodynamic pressure in the separated water, under the combined action of bed separation water pressure, the mining-induced fracture and water-isolation layer tension fracture are connected, which causes water inrushing in the coal working face of the mine, and provides a theoretical guarantee for the large-scale development of coal resources in western mining areas.

Prediction of Top-Coal Caving and Drawing Characteristics Using Artificial Neural Networks in Extremely Thick Coal Seam

2015 ◽  
Vol 743 ◽  
pp. 612-616 ◽  
Author(s):  
J.H. Yu ◽  
De Bing Mao
Keyword(s):  
Neural Networks ◽  
Artificial Neural Networks ◽  
Coal Seam ◽  
Network Model ◽  
Mining Area ◽  
Software Training ◽  
Thick Coal Seam ◽  
Mining Depth ◽  
Training Samples ◽  
Artificial Neural

Based on the feature of large thickness and poor drawing characteristics in extremely thick coal seam top-coal caving method, combined with numerous practical examples analyses, the primarily six factors influence the drawing characteristics were found out which are mining depth, coal seam strength, joint crack development, parting thickness in top-coal, caving ratios, immediate roof filling coefficient. According to 45 typical top-coal caving in extremely thick coal seam samples, the prediction of top-coal caving and drawing characteristics based on artificial neural networks was established and training samples and testing samples was determined. Use SPSS statistical software training the network model. Then select No. 9 coal seam first mining area of Tiaohu mine as the application case. The drawing property was forecast according to the established network model. Application results show that the use of artificial neural networks for top-coal caving and drawing characteristic prediction is effective and feasible.

Analysis on Ground Subsidence in Underground Mining

2011 ◽  
Vol 383-390 ◽  
pp. 2201-2205
Author(s):  
Xin Xi Liu ◽  
Xue Zhi Wang
Keyword(s):  
Underground Mining ◽  
Ground Deformation ◽  
Coal Pillar ◽  
Mining Area ◽  
Ground Subsidence ◽  
Recovery Coefficient ◽  
Mining Width ◽  
Movement And Deformation ◽  
Relationship Of ◽  
The Relationship

Analysis on the characters of ground subsidence of Yangjiaping mining area, with same excavation depth and recovery coefficient, the numerical simulations to nonlinear large deformation using finite-difference method(FLAC) are achieved on the different strip extraction schemes that adopted different mining and reservation width. The result indicates that the subsidence values and horizontal deformation increases with the increasing of the strip extraction width on condition of the same recovery rate. Based on probability density function (PDF) method, the relationship of the coal pillar width, the mining width and ground deformation is acquired, which is some useful reference for using the strip extraction method to control the surface movement and deformation.

Analysis of floor failure depth by using electric profiling method in longwall gangue backfill mining

2013 ◽  
Vol 19 (3) ◽  
pp. 282-289 ◽  
Author(s):  
Sheng-Li Yang ◽  
Xin-Pin Ding ◽  
Xin Wang ◽  
Xiao-Meng Li ◽  
Li Lin
Keyword(s):  
Floor Failure ◽  
Backfill Mining ◽  
Failure Depth ◽  
Electric Profiling

Limit equilibrium analysis for the design of backfilled stope barricades made of waste rock

2011 ◽  
Vol 48 (11) ◽  
pp. 1713-1728 ◽  
Author(s):  
Li Li ◽  
Michel Aubertin
Keyword(s):  
Pore Water ◽  
Pore Water Pressure ◽  
Limit Equilibrium ◽  
Water Pressure ◽  
Waste Rock ◽  
Equilibrium Analysis ◽  
Mining Operations ◽  
Limit Equilibrium Analysis ◽  
Fill Material

Backfilling of underground stopes is commonly applied in mining operations. Barricades are required to hold the fill material in the stope during and after placement. As such barricades may be constructed with waste rock, there is a need to develop solutions to analyse their response. This paper presents a limit equilibrium analysis solution for defining the dimensions of waste rock barricades. The proposed solution applies to drained (without pore-water pressure) and submerged (with pore-water pressure) conditions. The solutions are presented and applied to sample cases.

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