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An approach for predicting geothermal reservoirs distribution using wavelet transform and self-organizing neural network: a case study of radon and CSAMT data from Northern Jinan, China

Crossref DOI link: https://doi.org/10.1007/s40948-022-00468-1

Published Online: 2022-09-14

Published Print: 2022-10

Update policy: https://doi.org/10.1007/springer_crossmark_policy

Authors

Zhang, Kai

Lin, Niantian https://orcid.org/0000-0002-5316-5445
Wan, Xiaolei

Yang, Jiuqiang

Wang, Xiaodong

Tian, Gaopeng
Funding

Funding for this research was provided by:

Natural Science Foundation of Shandong Province (ZR202103050722)

National Natural Science Foundation of China (41174098)
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Text and Data Mining valid from 2022-09-14

Version of Record valid from 2022-09-14
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Article History

Received: 13 March 2022

Accepted: 29 August 2022

First Online: 14 September 2022

Declarations

:

: 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.

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