Application of unsupervised learning and deep learning for rock type prediction and petrophysical characterization using multi-scale data-Reference-Cited by-同舟云学术

登录注册会员服务联系我们

Application of unsupervised learning and deep learning for rock type prediction and petrophysical characterization using multi-scale data

Published:2023-11 Issue: Volume:230 Page:212241
ISSN:2949-8910
Container-title:Geoenergy Science and Engineering
language:en
Short-container-title:Geoenergy Science and Engineering

Author:

Iraji Shohreh^ORCID,Soltanmohammadi Ramin^ORCID,Matheus Gabriela Fernandes^ORCID,Basso Mateus,Vidal Alexandre Campane

Funder

Equinor ASA

Publisher

Elsevier BV

Reference75 articles.

1. Three-dimensional P-wave tomography in the central alborz, Iran;Afra;Phys. Earth Planet. In.,2021

2. Brazil's presalt play;Beasley;Oilfield Rev.,2010

3. Pore typing using nuclear magnetic resonance, an example with samples from cretaceous pre-salt lacustrine carbonates in the Santos Basin, Brazil;Belila;J. Petrol. Sci. Eng.,2020

4. Committee neural networks for porosity and permeability prediction from well logs;Bhatt;Geophys. Prospect.,2002

Cited by 29 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. Machine learning based reservoir characterization and numerical modeling from integrated well log and core data;Geoenergy Science and Engineering;2024-12

2. RDA-Net: A multi-cascade network for DAS background noise attenuation;Geoenergy Science and Engineering;2024-11

3. Bridging the gap: Integrating static and dynamic data for improved permeability modeling and super k zone detection in vuggy reservoirs;Geoenergy Science and Engineering;2024-10

4. Extensive data analysis and modelling of carbon dioxide solubility in ionic liquids using chemical structure-based ensemble learning approaches;Fluid Phase Equilibria;2024-10

5. ESP vibration prediction based on pump operating conditions in laboratory using machine learning;Geoenergy Science and Engineering;2024-09

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