none 10.1190/INT-2020-0197.1 Society of Exploration Geophysicists Society of Exploration Geophysicists 186 126274946 226307 2021070203032700070 10.1190 2021-09-22T13:41:48Z 2021-04-23T07:26:11Z 3 Interpretation Interpretation 2324-8858 2324-8866 08 01 2021 9 3 Zhangqing Sun Jilin University, College of Geoexploration Science and Technology, Changchun 130026, China.. https://orcid.org/0000-0002-3898-6544 Xingguo Huang Jilin University, College of Instrumentation and Electrical Engineering, Changchun 130026, China.(corresponding author). https://orcid.org/0000-0001-9719-6297 Hongliang Li New Energy Development Company of Liaohe Petroleum Exploration Bureau, Panjin 124010, China.. Anguai Lei Liaohe Oilfield Company, CNPC, Panjin 124010, China.. Nuno Vieira da Silva Formerly Imperial College London, Department of Earth Science and Engineering, South Kensington Campus, London SW7 2AZ, UK; presently Total E&P UK, Tarland Road, Westhill, Aberdeen AB32 6JZ, UK.. Fuxing Han Jilin University, College of Geoexploration Science and Technology, Changchun 130026, China.. Minqiang Cao New Energy Development Company of Liaohe Petroleum Exploration Bureau, Panjin 124010, China.. Wei Da Liaohe Oilfield Company, CNPC, Panjin 124010, China.. The concern over climate change and a transition away from fossil fuels has reinvigorated interest in using nuclear energy in producing electricity. Uranium is the principal fuel used in nuclear power plants, and mineral deposits containing this element are of strategic importance. The successful development of sandstone uranium deposits benefits from 3D geophysical characterization of sand bodies in uranium reservoirs. In view of this, we have evaluated a method based on 3D geostatistical resistivity inversion. First, we analyze the application of that method to the problem at hand and introduce a workflow for analyzing the data. Second, through petrophysical sensitivity analysis, we identify the logging parameters that can characterize sandstone in this context and geostatistical inversion to estimate those parameters. We then use 3D geostatistical resistivity inversion to map a sandstone uranium reservoir and find it to provide accurate results. Finally, the 3D data of inversion are applied to 3D spatial characterization of a sand body in the Sifangtai uranium reservoir inverting a field data set in the western of Songliao Basin in China. We believe this geostatistical inversion method to be useful in determining the location of drilling wells for exploration and development of sandstone uranium deposits. 07 01 2021 08 01 2021 T809 T819 10.1190/INT-2020-0197.1 1 10.1190/crossmark-policy library.seg.org true 2020-09-22 2021-02-06 2021-04-06 2021-07-01 National Key RD Program of China 2018YFC0604200 IGCP-675 Scientific Research and Technology R&D project of CNPC 10.1190/INT-2020-0197.1 https://library.seg.org/doi/10.1190/INT-2020-0197.1 https://library.seg.org/doi/pdf/10.1190/INT-2020-0197.1 https://pubs.geoscienceworld.org/interpretation/article/9/3/t809/605922/3d-spatial-characterization-of-sand-body-for 10.2118/23565-PA 10.1190/1.3535433 10.1190/1.3386676 10.1190/1.1845100 10.3997/1365-2397.1994034 10.1190/geo2019-0644.1 10.4208/cicp.OA-2018-0143 Acta Sedimentologica Sinica Jiao Y. Q. 23 2005 10.1111/1755-6724.13026 Geological Science and Technology Information Jiao Y. Q. 26 2007 10.12029/gc20170201 Acta Geological Sinica Jin R. S. 90 2016 10.1190/geo2012-0117.1 Coal Geology of China Kang Y. 28 2016 10.1016/j.cageo.2010.08.001 Li, C., C. Q. Yu, F. J. Nie, Y. Zhou, P. Chen, and W. Tian, 2017a, Study on the application of well seismic joint inversion technology in the prospecting of sandstone type uranium deposits: Proceedings of the China Geoscience Union Annual Meeting, 517–518 (in Chinese). World Nuclear Geoscience Li Z. W. 34 2017 10.1111/1755-6724.14518 10.1190/1.2369748 Qiu, Y., C. Q. Yu, C. Li, and X. J. Zheng, 2018, Prediction of sandstone type uranium reservoir in Kunbei area of Qaidam Basin based on well seismic joint inversion: Proceedings of the China Geoscience Union Annual Meeting, 557–558 (in Chinese). 10.1016/j.oregeorev.2019.02.036 10.1190/1.2135135 0079-628X Progress in Geophysics Shen H. T. 32 2017 China Mining Magazine Wang Q. Q. 24 2015 10.1190/geo2011-0488.1 10.1016/j.oregeorev.2019.03.003 Zhu, Y. P., X. Y. Lu, S. Y. Xu, E. Liu, M. A. Payne, and C. X. Zhan, 2013, Method for generating anisotropic resistivity volumes from seismic and log data using a rock physics model: U. S. Patent 8,473,213 B2.