Deep learning enhanced joint inversion for mineral exploration using airborne geophysics: Application in Decorah area-Reference-Cited by-同舟云学术

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Deep learning enhanced joint inversion for mineral exploration using airborne geophysics: Application in Decorah area

Published:2023-12-14 Issue: Volume: Page:
ISSN:
Container-title:Third International Meeting for Applied Geoscience & Energy Expanded Abstracts
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Author:

Hu Yanyan¹,Wei Xiaolong¹,Wu Xuqing¹,Sun Jiajia¹,Chen Jiefu¹,Huang Yueqin²

Affiliation:

1. University of Houston

2. Cyentech Consulting LLC

Publisher

Society of Exploration Geophysicists and American Association of Petroleum Geologists

Link

https://library.seg.org/doi/pdf/10.1190/image2023-3910948.1

Reference19 articles.

1. SimPEG: An open source framework for simulation and gradient based parameter estimation in geophysical applications

2. Colombo, D., W. Li, D. Rovetta, E. Sandoval-Curiel, and E. Turkoglu, 2020, Physics-driven deep learning joint inversion: 90th Annual International Meeting, SEG, Expanded Abstracts, 1775–1779, doi: 10.1190/segam2020-3424997.1.

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Innovative imaging of iron deposits using cross‐gradient joint inversion of potential field data with petrophysical correlation;Near Surface Geophysics;2024-08-08

2. Deep Learning Framework for Multi-Physics Joint Inversion and its Application in the Decorah Area;IGARSS 2024 - 2024 IEEE International Geoscience and Remote Sensing Symposium;2024-07-07

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