Exploration of Ordovician limestone aquifer heterogeneity with tomographic water releasing tests

• Published in: Journal of hydrology (Amsterdam) 2022-05, Vol.608, p.127655, Article 127655
• Main Authors: Ma, Min, Liu, Zaibin, Ma, Xinmin, Zhao, Ruijue, Mao, Deqiang
• Format: Article
• Language: English
• Subjects: Dongtan coal mine; Heterogeneity; Hydraulic tomography; Parameter estimation; Water inrush
• ISSN: 0022-1694; 1879-2707
• DOI: 10.1016/j.jhydrol.2022.127655

•Water releasing tests were performed in deep confined aquifers.•HT technique can depict aquifer parameters in details over dozens of kilometers.•Artificial injection well was included to handle identified recharge channels.•Results is physically consistent with borehole chemistry and drilling fluid losses. Water inrush is a typical geological disaster in the process of underground mining. It is crucial to depict potential water inrush areas for mining safety. In this study, mining activity in Dongtan coal mine is under the water inrush threat from deep Ordovician limestone confined aquifers. Tomographic water releasing tests and simultaneous successive linear estimator (SimSLE) were conducted to characterize aquifer heterogeneity by stimulating hundreds of square kilometers. An artificial injection well was firstly introduced to alleviate the influence from identified recharge channels. The estimated parameter distributions indicated that the study area was divided into two separately hydrogeological compartments. Transmissivity (T) and storativity (S) in the north were relatively higher due to water-conducting structures, and more attention should be paid to this region which may develop into water inrush incidents. The southern area is occupied with lower T and S, which indicated relatively worse flow conditions. Auxiliary drawdown recovery data, borehole chemistry variations, drilling fluid losses, and existing geological features further confirmed the estimated parameter distributions. In the end, we concluded that Hydraulic Tomography technique (HT) could obtain aquifer parameter information in large scales and provide supports to formulate reasonably effective water prevention and control schemes before mining deep coal seams.