A new procedure for generating data covariance inflation factors for ensemble smoother with multiple data assimilation
Author:
Funder
Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Petrobras
Publisher
Elsevier BV
Subject
Computers in Earth Sciences,Information Systems
Reference29 articles.
1. Towards a robust parameterization for conditioning facies models using deep variational autoencoders and ensemble smoother;Canchumuni;Comput. Geosci.,2019
2. Ensemble-based closed-loop optimization applied to Brugge field;Chen;SPE Reserv. Eval. Eng.,2010
3. Ensemble randomized maximum likelihood method as an iterative ensemble smoother;Chen;Math. Geosci.,2012
4. Levenberg–Marquardt forms of the iterative ensemble smoother for efficient history matching and uncertainty quantification;Chen;Comput. Geosci.,2013
5. Coutinho, E.J., Emerick, A.A., Li, G., Reynolds, A.C., 2010. Conditioning multilayered geologic models to well-test and production-logging data using the ensemble Kalman filter. In: Paper Presented at the SPE Annual Technical Conference and Exhibition, Florence, Italy, 19–22 September, p. 134542.
Cited by 8 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. A latent space method with maximum entropy deep reinforcement learning for data assimilation;Geoenergy Science and Engineering;2024-12
2. Prediction and History Matching of Observed Production Rate and Bottomhole Pressure Data Sets from in Situ Cross-Linked Polymer Gel Conformance Treatments Using Machine Learning Methods;Day 3 Fri, June 28, 2024;2024-06-26
3. A new procedure for well productivity and injectivity calibration to improve short-term production forecast;Geoenergy Science and Engineering;2023-10
4. Analytical solutions of fractal and anomalous diffusion models for pressure and rate transient analysis;Geoenergy Science and Engineering;2023-10
5. A fusion-based data assimilation framework for runoff prediction considering multiple sources of precipitation;Hydrological Sciences Journal;2023-03-12
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