Application of geophysical well logs in solving geologic issues: Past, present and future prospect

Abstract

Geophysical well logs are widely used in geological fields, however, there are considerable incompatibilities existing in solving geological issues using well log data. This review critically fills the gaps between geology and geophysical well logs, as assessed from peer reviewed papers and from the authors’ personal experiences, in the particular goal of solving geological issues using geophysical well logs. The origin and history of geophysical logging are summarized. Next follows a review of the state of knowledge for geophysical well logs in terms of type of specifications, vertical resolution, depth of investigations and demonstrated applications. Then the current status and advances in applications of geophysical well logs in fields of structural geology, sedimentary geology and petroleum geology are discussed. Well logs are used in structural and sedimentary geology in terms of structure detection, in situ stress evaluation, sedimentary characterization, sequence stratigraphy division and fracture prediction. Well logs can also be applied in petroleum geology fields of optimizing sweet spots for hydraulic fracturing in unconventional oil and gas resource. Geophysical well logs are extending their application in other fields of geosciences, and geological issues will be efficiently solved via well logs with the improvements of advanced well log suits. Further work is required in order to improve accuracy and diminish uncertainties by introducing artificial intelligence. This review provides a systematic and clear descriptions of the applications of geophysical well log data along with examples of how the data is displayed and processed for solving geologic problems.

Keywords

Geophysical well logs / Sequence stratigraphy / Source rock / Unconventional oil and gas resources / Artificial intelligence

CRediT authorship contribution statement

Jin Lai: Conceptualization, Methodology, Software, Data curation, Writing – original draft, Visualization, Investigation, Writing – review & editing. Yang Su: Conceptualization, Methodology, Software, Data curation, Writing – original draft. Lu Xiao: Data curation, Writing – original draft. Fei Zhao: Data curation, Writing – original draft. Tianyu Bai: Data curation, Writing – original draft. Yuhang Li: Conceptualization, Methodology, Software. Hongbin Li: Visualization, Investigation. Yuyue Huang: Visualization, Investigation. Guiwen Wang: Conceptualization, Methodology, Software, Writing – review & editing. Ziqiang Qin: Visualization, Investigation.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgments

This work is financially supported by National Natural Science Foundation of China (Grant No. 42002133), strategic cooperation project of PetroChina and CUPB (China University of Petroleum, Beijing) (ZLZX2020-01), and Science Foundation of China University of Petroleum, Beijing (No. 2462023QNXZ010). The authors would like to express their sincere thanks to the PetroChina Xinjiang, Tarim, Southwest and Changqing Oilfield Company for their assistance in providing data and for their technical input to this work.

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