A Deep Learning Object Detection Method for Fracture Identification Using Conventional Well Logs-Reference-Cited by-同舟云学术

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A Deep Learning Object Detection Method for Fracture Identification Using Conventional Well Logs

Published:2024 Issue: Volume:62 Page:1-16
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Dong Shaoqun¹^ORCID,Hao Jingru¹^ORCID,Zeng Lianbo²,Yang Xu¹^ORCID,Wang Leting¹^ORCID,Ji Chunqiu²^ORCID,Zhong Zhaohui¹^ORCID,Chen Shutong¹^ORCID,Fu Kaifeng¹^ORCID

Affiliation:

1. State Key Laboratory of Petroleum Resources and Prospecting and the College of Science, China University of Petroleum, Beijing, China

2. State Key Laboratory of Petroleum Resources and Prospecting and the College of Geoscience, China University of Petroleum, Beijing, China

Funder

National Natural Science Foundation of China

China Post-Doctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Link

http://xplorestaging.ieee.org/ielx8/36/10354519/10596318.pdf?arnumber=10596318

Reference68 articles.

1. Fracture identification by semi-supervised learning using conventional logs in tight sandstones of Ordos Basin, China

2. Integrating deep learning and logging data analytics for lithofacies classification and 3D modeling of tight sandstone reservoirs

3. Natural fractures and their influence on shale gas enrichment in Sichuan Basin, China

4. An Improved Scheme of Azimuthally Anisotropic Seismic Inversion for Fracture Prediction in Volcanic Gas Reservoirs

5. Deep classified autoencoder for lithofacies identification

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