M. Mohamad, M. Rahman, Benayad Nourreddine, M. H. Yakup, M. F. Sedaralit
{"title":"Advanced Reservoir Characterisation of Meandering Fluvial Environment, 3D Modelling Study Offshore Malaysia","authors":"M. Mohamad, M. Rahman, Benayad Nourreddine, M. H. Yakup, M. F. Sedaralit","doi":"10.2118/197664-ms","DOIUrl":null,"url":null,"abstract":"\n Thorough reservoir modeling studies have been performed for field ABC, however there are still challenges to be addressed in modelling of some specific sand reservoir depositional systems i.e. meandering fluvial reservoirs (point bars and crevasse splays). The current modelling approaches especially for fluvial reservoirs are mainly controlled by wells and have contributed to uncertainties in lateral variation based on geostatistic (variograms etc) between and away from well control. Moreover, the existing modelling approach is using sixth to fifth order (lower order) hierarchical architecture elements and this project further refines the model up to third order (higher order) which enables capturing lateral accretion of point bars.\n Advanced fluvial workflow (AFW) have been developed to improve the understanding of the reservoir architecture of fluvial reservoirs. It comprises of three main steps which are, first, details study on fluvial reservoir sedimentology characteristics derived from core analysis and literature. Second, qualitative geophysical study and interpretation derived from seismic dataset. Third, integration between the first and second steps into a three dimensional (3-D) reservoir model.\n As a result of AFW implementation in field ABC, this has led to better representation of the reservoir heterogeneities, more accurate STOIIP assessment, improved history matching quality index (HMQI) and enhanced subsurface risks and uncertainties understanding. This enable optimization of future field development plan such as infill well reactivation, water flood and chemical enhanced oil recovery (EOR). The AFW is a robust modelling method that can be used in any reservoir modelling platform (PETREL, CMG, RMS, TNAV) with multiple realizations capability using automated workflows.","PeriodicalId":11328,"journal":{"name":"Day 4 Thu, November 14, 2019","volume":"75 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-11-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 4 Thu, November 14, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2118/197664-ms","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
Thorough reservoir modeling studies have been performed for field ABC, however there are still challenges to be addressed in modelling of some specific sand reservoir depositional systems i.e. meandering fluvial reservoirs (point bars and crevasse splays). The current modelling approaches especially for fluvial reservoirs are mainly controlled by wells and have contributed to uncertainties in lateral variation based on geostatistic (variograms etc) between and away from well control. Moreover, the existing modelling approach is using sixth to fifth order (lower order) hierarchical architecture elements and this project further refines the model up to third order (higher order) which enables capturing lateral accretion of point bars.
Advanced fluvial workflow (AFW) have been developed to improve the understanding of the reservoir architecture of fluvial reservoirs. It comprises of three main steps which are, first, details study on fluvial reservoir sedimentology characteristics derived from core analysis and literature. Second, qualitative geophysical study and interpretation derived from seismic dataset. Third, integration between the first and second steps into a three dimensional (3-D) reservoir model.
As a result of AFW implementation in field ABC, this has led to better representation of the reservoir heterogeneities, more accurate STOIIP assessment, improved history matching quality index (HMQI) and enhanced subsurface risks and uncertainties understanding. This enable optimization of future field development plan such as infill well reactivation, water flood and chemical enhanced oil recovery (EOR). The AFW is a robust modelling method that can be used in any reservoir modelling platform (PETREL, CMG, RMS, TNAV) with multiple realizations capability using automated workflows.