Gas-Bearing Prediction Using a Hybrid Method Based on a Combination of PCA-FastICA and CNN With the Attention Mechanism-Reference-Cited by-同舟云学术

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Gas-Bearing Prediction Using a Hybrid Method Based on a Combination of PCA-FastICA and CNN With the Attention Mechanism

Published:2023 Issue: Volume:61 Page:1-18
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Yang Jiuqiang¹^ORCID,Lin Niantian²^ORCID,Zhang Kai¹^ORCID,Fu Chao³,Tian Gaoping⁴

Affiliation:

1. College of Earth Sciences and Engineering and the College of Geodesy and Geomatics, Shandong University of Science and Technology, Qingdao, China

2. College of Earth Sciences and Engineering, Shandong University of Science and Technology, Qingdao, China

3. Transportation Institute, Inner Mongolia University, Hohhot, China

4. Nuclear Industry Huzhou Engineering Survey Institute Company, Ltd., Huzhou, China

Funder

Natural Science Foundation of Shandong Province

China Postdoctoral Science Foundation

National Natural Science Foundation of China

Young Talents Foundation of Inner Mongolia University

Qingdao Postdoctoral Science Foundation

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10305558.pdf?arnumber=10305558

Reference69 articles.

1. Shear wave velocity prediction using seismic attributes and well log data

2. Source-Free P-SV Converted-Wave Reverse-Time Migration Using First-Order Velocity-Dilatation-Rotation Equations

3. Sensitivity analysis of seismic attributes parametrization to reduce misinterpretations: Applications to deepwater channel complexes

4. Marmousi2: An elastic upgrade for Marmousi;martin;Lead Edge,2006

5. Extension of PCA to Higher Order Data Structures: An Introduction to Tensors, Tensor Decompositions, and Tensor PCA

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