Principal component analysis (PCA) based hybrid models for the accurate estimation of reservoir water saturation-Reference-Cited by-同舟云学术

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Principal component analysis (PCA) based hybrid models for the accurate estimation of reservoir water saturation

Published:2020-12 Issue: Volume:145 Page:104555
ISSN:0098-3004
Container-title:Computers & Geosciences
language:en
Short-container-title:Computers & Geosciences

Author:

Asante-Okyere Solomon,Shen Chuanbo,Ziggah Yao Yevenyo,Rulegeya Mercy Moses,Zhu Xiangfeng

Funder

Major National Science and Technology Programs in the “Thirteenth Five-Year”

Natural Science Foundation of Hubei Province

Program of Introducing Talents of Discipline to Universities

Wuhan Science and Technology

Publisher

Elsevier BV

Subject

Computers in Earth Sciences,Information Systems

Reference37 articles.

1. Development of artificial neural network models for predicting water saturation and fluid distribution;Al-Bulushi;J. Petrol. Sci. Eng.,2009

2. Improving water saturation estimation in a tight shaly sandstone reservoir using artificial neural network optimized by imperialist competitive algorithm- A Case study;Amiri;J. Petrol. Sci. Eng.,2015

3. The electrical resistivity log as an aid in determining some reservoir characteristics;Archie;Transactions of AIME,1941

4. Investigating the predictive performance of Gaussian process regression in evaluating reservoir porosity and permeability;Asante-Okyere;Energies,2018

5. Prediction of water saturation in a tight gas sandstone reservoir by using four intelligent methods: a comparative study;Baziar;Neural Comput. Appl.,2016

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