{"title":"Functional Estimator For Reservoir Proxy Models Made Scalable Through A Big Data Platform","authors":"M. Piantanida, A. Amendola, G. Formato","doi":"10.3997/2214-4609.201803028","DOIUrl":null,"url":null,"abstract":"Summary The abstract documents how a Big Data Analytics platform allowed to implement a complex functional estimator of a reservoir proxy model, involving complex machine learning operations on dynamic reservoir models, so that it can scale up to the size of realistic reservoir models.","PeriodicalId":231338,"journal":{"name":"First EAGE/PESGB Workshop Machine Learning","volume":"37 4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-11-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"First EAGE/PESGB Workshop Machine Learning","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.3997/2214-4609.201803028","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
Summary The abstract documents how a Big Data Analytics platform allowed to implement a complex functional estimator of a reservoir proxy model, involving complex machine learning operations on dynamic reservoir models, so that it can scale up to the size of realistic reservoir models.