Coal Geology & Exploration
Abstract
“Coal and uranium exploration” and “oil and uranium exploration” are current research hotspots. Using logging data of coal and oilfield drilling to further evaluate uranium resources remains a difficult problem. Taking the Pengyang uranium deposit in the Ordos Basin as an example, this article explores the method of evaluating uranium resources based on natural gamma logging data. According to the remarkable features of the natural gamma anomaly response in the sandstone-type uranium reservoirs in the study area, the natural gamma logging regression model of the quantitative gamma logging value of the uranium deposit in the Pengyang area was studied by comparative analysis of the quantitative gamma logging data in nine verification holes and the natural gamma logging data in the oilfield boreholes, and a program for screening and calculating the amount of uranium per square meter of the deposit was developed. Such studies addressed the issue that it is difficult to efficiently use conventional oil and coal field logging data for uranium deposit identification and grade evaluation, and a regional uranium deposit identification and grade evaluation method based on natural gamma logging information has been preliminarily established. The accuracy of the results is consistent with the measured data, which can provide effective technical support for the investigation and potential evaluation of uranium resources in the Ordos Basin.
Keywords
evaluation of uranium resource, natural gamma logging, quantitative gamma logging, empirical model, grade, quantity of uranium per square meter, Ordos Basin
DOI
10.12363/issn.1001-1986.21.10.0560
Recommended Citation
YU Reng’an, SUN Dapeng, ZHOU Xiaoxi,
et al.
(2022)
"Preliminary investigation of uranium resource evaluation method based on natural gamma logging data:A case study of the Pengyang uranium deposit in Ordos Basin,"
Coal Geology & Exploration: Vol. 50:
Iss.
5, Article 19.
DOI: 10.12363/issn.1001-1986.21.10.0560
Available at:
https://cge.researchcommons.org/journal/vol50/iss5/19
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