Predicting rate of penetration (ROP) based on a deep learning approach: A case study of an enhanced geothermal system in Pohang, South Korea
Author:
Funder
National Research Foundation of Korea
Publisher
Springer Science and Business Media LLC
Subject
General Earth and Planetary Sciences
Link
https://link.springer.com/content/pdf/10.1007/s12145-023-01149-7.pdf
Reference38 articles.
1. Abdel Azim R (2020) Application of artificial neural network in optimizing the drilling rate of penetration of western desert Egyptian wells. SN Appl Sci 2:1177. https://doi.org/10.1007/s42452-020-2993-8
2. Ahmed A, Ali A, Elkatatny S, Abdulraheem A (2019) New artificial neural networks model for predicting rate of penetration in deep shale formation. Sustainability 11:6527. https://doi.org/10.3390/su11226527
3. Al-Abduljabbar A, Gamal H, Elkatatny S (2020) Application of artificial neural network to predict the rate of penetration for S-shape well profile. Arab J Geosci 13:784. https://doi.org/10.1007/s12517-020-05821-w
4. Al-AbdulJabbar A, Elkatatny S, Mahmoud M, Abdulraheem A (2018) Predicting rate of penetration using artificial intelligence techniques. In: SPE Kingdom of Saudi Arabia Annual Technical Symposium and Exhibition. SPE
5. Alali AM, Abughaban MF, Aman BM, Ravela S (2021) Hybrid data driven drilling and rate of penetration optimization. J Pet Sci Eng 200:108075. https://doi.org/10.1016/j.petrol.2020.108075
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