Prediction of drilling rate of penetration (ROP) using hybrid support vector regression: A case study on the Shennongjia area, Central China-Reference-Cited by-同舟云学术

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Prediction of drilling rate of penetration (ROP) using hybrid support vector regression: A case study on the Shennongjia area, Central China

Published:2019-10 Issue: Volume:181 Page:106200
ISSN:0920-4105
Container-title:Journal of Petroleum Science and Engineering
language:en
Short-container-title:Journal of Petroleum Science and Engineering

Author:

Gan Chao,Cao Wei-Hua,Wu Min,Chen Xin,Hu Yu-Le,Liu Kang-Zhi,Wang Fa-Wen,Zhang Suo-Bang

Funder

Hubei Provincial Technical Innovation Major Project

National Natural Science Foundation of China

National Key R&D Program of China

Fundamental Research Funds for the China Academy of Geological Sciences

111 project

Fundamental Research Funds for the Central Universities

China Scholarship Council

Publisher

Elsevier BV

Subject

Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference66 articles.

1. A review on the wear of oil drill bits (conventional and the state of the art approaches for wear reduction and quantification);Abbas;Eng. Fail. Anal.,2018

2. Bayesian prediction of TBM penetration rate in rock mass;Adoko;Eng. Geol.,2017

3. Computational intelligence based prediction of drilling rate of penetration: a comparative study;Ahmed;J. Petrol. Sci. Eng.,2019

4. A hybrid particle swarm optimization and support vector regression model for modelling permeability prediction of hydrocarbon reservoir;Akande;J. Petrol. Sci. Eng.,2017

5. Drilling rate of penetration prediction through committee support vector regression based on imperialist competitive algorithm;Ansari;Carbonates Evaporites,2017

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