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Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China

[Image: see text] Accurate and reliable evaluations of potential groundwater areas are of significance in the hydrogeological assessments of coalfields because water inrush disasters may be caused by unclear groundwater potential. A three-dimensional geological model of porosity based on determinist...

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Autores principales: Li, Liyao, Qu, Juan, Wei, Jiuchuan, Xia, Fei, Gao, Jindong, Liu, Chao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Chemical Society 2021
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153666/
https://www.ncbi.nlm.nih.gov/pubmed/34056157
http://dx.doi.org/10.1021/acsomega.0c06166
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author Li, Liyao
Qu, Juan
Wei, Jiuchuan
Xia, Fei
Gao, Jindong
Liu, Chao
author_facet Li, Liyao
Qu, Juan
Wei, Jiuchuan
Xia, Fei
Gao, Jindong
Liu, Chao
author_sort Li, Liyao
collection PubMed
description [Image: see text] Accurate and reliable evaluations of potential groundwater areas are of significance in the hydrogeological assessments of coalfields because water inrush disasters may be caused by unclear groundwater potential. A three-dimensional geological model of porosity based on deterministic modeling and a facies-controlled method are used to determine the groundwater potential of the coal measure aquifer. The modeling processes are as follows: based on the interlayer and discontinuity (faults) data extracted from boreholes and geological maps, an integrated sequence framework model is developed. Using the results of sedimentary microfacies identification and the method of deterministic modeling, a sedimentary microfacies model is successfully established. Finally, based on facies-controlled and sequential Gaussian methods, an effective porosity model is established that can predict the groundwater potential. The predicted results show that sandstones sedimented in channel, point bar, and batture environments possess high effective porosity and strong groundwater potential; however, the sandstones sedimented in interdistributary bays, flood plains, and sand sheets possess low effective porosity. Model validation was performed based on the hydrological pumping test data collected from observation boreholes, drainage water inflow data from dewatered boreholes in the tunnel around workface, and the mine water inflow in tunnels and the workfaces. The validation analysis results show that the effective porosity and sedimentary facies were correlated with the actual flux. The predicted results are consistent with the actual flux data, validating the predicted model.
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spelling pubmed-81536662021-05-27 Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China Li, Liyao Qu, Juan Wei, Jiuchuan Xia, Fei Gao, Jindong Liu, Chao ACS Omega [Image: see text] Accurate and reliable evaluations of potential groundwater areas are of significance in the hydrogeological assessments of coalfields because water inrush disasters may be caused by unclear groundwater potential. A three-dimensional geological model of porosity based on deterministic modeling and a facies-controlled method are used to determine the groundwater potential of the coal measure aquifer. The modeling processes are as follows: based on the interlayer and discontinuity (faults) data extracted from boreholes and geological maps, an integrated sequence framework model is developed. Using the results of sedimentary microfacies identification and the method of deterministic modeling, a sedimentary microfacies model is successfully established. Finally, based on facies-controlled and sequential Gaussian methods, an effective porosity model is established that can predict the groundwater potential. The predicted results show that sandstones sedimented in channel, point bar, and batture environments possess high effective porosity and strong groundwater potential; however, the sandstones sedimented in interdistributary bays, flood plains, and sand sheets possess low effective porosity. Model validation was performed based on the hydrological pumping test data collected from observation boreholes, drainage water inflow data from dewatered boreholes in the tunnel around workface, and the mine water inflow in tunnels and the workfaces. The validation analysis results show that the effective porosity and sedimentary facies were correlated with the actual flux. The predicted results are consistent with the actual flux data, validating the predicted model. American Chemical Society 2021-04-08 /pmc/articles/PMC8153666/ /pubmed/34056157 http://dx.doi.org/10.1021/acsomega.0c06166 Text en © 2021 The Authors. Published by American Chemical Society Permits non-commercial access and re-use, provided that author attribution and integrity are maintained; but does not permit creation of adaptations or other derivative works (https://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Li, Liyao
Qu, Juan
Wei, Jiuchuan
Xia, Fei
Gao, Jindong
Liu, Chao
Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title_full Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title_fullStr Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title_full_unstemmed Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title_short Facies-Controlled Geostatistical Porosity Model for Estimation of the Groundwater Potential Area in Hongliu Coalmine, Ordos Basin, China
title_sort facies-controlled geostatistical porosity model for estimation of the groundwater potential area in hongliu coalmine, ordos basin, china
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8153666/
https://www.ncbi.nlm.nih.gov/pubmed/34056157
http://dx.doi.org/10.1021/acsomega.0c06166
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