A Random Forests-based sensitivity analysis framework for assisted history matching-Reference-Cited by-同舟云学术

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A Random Forests-based sensitivity analysis framework for assisted history matching

Published:2019-10 Issue: Volume:181 Page:106237
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Aulia Akmal,Jeong Daein,Saaid Ismail Mohd,Kania Dina,Shuker Muhannad Taleb,El-Khatib Noaman A.

Funder

Universiti Teknologi PETRONAS

Schlumberger

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference57 articles.

1. Sensitivity analysis of an accident prediction model by the fractional factorial method;Akgüngör;Accid. Anal. Prev.,2007

2. Empirical characterization of random forest variable importance measures;Archer;Comput. Stat. Data Anal.,2008

3. A new history matching sensitivity analysis framework with random forests and plackett-burman design;Aulia,2017

4. Plackett-Burman technique for sensitivity analysis of many-parametered models;Beres;Ecol. Model.,2001

5. Applications of machine learning for facies and fracture prediction using Bayesian Network Theory and Random Forest: case studies from the Appalachian basin, USA;Bhattacharya;J. Pet. Sci. Eng.,2018

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