A hybrid PSO-SVM-based model for determination of oil recovery factor in the low-permeability reservoir-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

A hybrid PSO-SVM-based model for determination of oil recovery factor in the low-permeability reservoir

Published:2018-03 Issue:1 Volume:4 Page:43-49
ISSN:2405-6561
Container-title:Petroleum
language:en
Short-container-title:Petroleum

Author:

Han Bing,Bian Xiaoqiang

Funder

National Natural Science Foundation of China

State Key Laboratory of Oil and Gas Reservoir Geology and Exploitation

Innovation team project of Sichuan Provincial Department of Education

Publisher

Elsevier BV

Subject

Geochemistry and Petrology,Geology,Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology

Reference58 articles.

1. Forecasting methods of oil field development indexes;Ji;Pet. Geol. Oilf. Dev. Daqing,1994

2. Correction to Tong's standard formula and its application;Xu;J. Jianghan Pet. Inst.,2002

3. Creation of the fractional flow curve from purely production data;Macary,1999

4. Predicting natural gas production using artificial neural network;Al-Fattah,2001

5. Application of empirically derived oil recovery factor regression equations to water drive reservoirs in Niger delta;Okpere,2013

Cited by 52 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. The injection pattern investigation of hydrocarbon gas enhanced oil recovery in heterogeneous reservoirs;Petroleum Science and Technology;2024-08-05

2. Quality assessment of Compound Yuxingcao Mixture produced by different manufacturers using high performance liquid chromatography and near infrared spectroscopy combined with multivariate algorithms;Infrared Physics & Technology;2024-06

3. Prediction of flow stress in Mg-3Dy alloy based on constitutive equation and PSO-SVR model;Materials Research Express;2024-05-01

4. A novel framework for predicting non-stationary production time series of shale gas based on BiLSTM-RF-MPA deep fusion model;Petroleum Science;2024-05

5. Multiple linear regression and gene expression programming to predict fracture density from conventional well logs of basement metamorphic rocks;Journal of Petroleum Exploration and Production Technology;2024-04-20

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线，采集、加工和组织学术论文而形成的新型学术文献查询和分析系统，可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容，当前同舟云学术共收录了国内外主流学术期刊6万余种，收集的期刊论文及会议论文总量共计约1.5亿篇，并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询！咨询电话：010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号京ICP备18003416号-3