Identification of Carbonate Cave Reservoirs Based on Variational Bayesian Principal Component Analysis-Reference-Cited by-同舟云学术

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Identification of Carbonate Cave Reservoirs Based on Variational Bayesian Principal Component Analysis

Published:2023 Issue: Volume:61 Page:1-10
ISSN:0196-2892
Container-title:IEEE Transactions on Geoscience and Remote Sensing
language:
Short-container-title:IEEE Trans. Geosci. Remote Sensing

Author:

Chen Li¹^ORCID,Liu Xingye¹^ORCID,Zhou Huailai¹,Zhang Hao²,Lyu Fen¹,Mo Qianwen³

Affiliation:

1. Key Laboratory of Earth Exploration and Information Technology of the Ministry of Education, College of Geophysics, Chengdu University of Technology, Chengdu, China

2. Petrochina Hangzhou Research Institute of Geology, Hangzhou, China

3. Exploration Division, PetroChina Southwest Oil and Gasfield Company, Chengdu, China

Funder

Formation mechanism and “sweet spot” prediction of high-quality reservoirs in the Xu2 of the Western Sichuan Depression

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Earth and Planetary Sciences,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/36/10006360/10321703.pdf?arnumber=10321703

Reference60 articles.

1. Principal component analysis

2. Three-dimensional seismic exploration method for ultra-deep fault-related dissolution reservoirs in the Shunbei desert area;li;Geophysical prospecting for petroleum,2020

3. Palaeokarst of Cambro–Ordovician and oil-gas distribution in Tarim Basin;kang;Xinjiang Petroleum Geology,2005

4. Reservoir characteristics and influencing factors in the inner Yingshan formation in Guchengxu uplift, Tarim Basin;tang;Litholog Reservoirs,2013

5. Principal Component Analysis

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