H. Ismail, C. L. Lew, Muhd Rapi Mohamad Som, M. Kadir, M. Tajuddin
{"title":"Advanced Meandering Fluvial Reservoir Characterisation for Static Model Improvement","authors":"H. Ismail, C. L. Lew, Muhd Rapi Mohamad Som, M. Kadir, M. Tajuddin","doi":"10.2523/IPTC-19352-MS","DOIUrl":null,"url":null,"abstract":"\n Modelling of meandering fluvial reservoirs with point bars and crevasse splays is very challenging. The conventional modelling approaches, especially for meandering fluvial reservoirs, are mainly controlled by wells, which have contributed to uncertainties in lateral variations between and away from well control. Integration of the improved sedimentology, geophysics and 3D reservoir geomodelling techniques of fluvial reservoir system are proposed in the study. In stratigraphic and structural framework building, the improved methodologies included 3D seismic geobody extraction, stratal slicing and high order architectural elements interpretation. 3D geobody extraction and stratal slicing technique enhanced interpreter ability to visualize fluvial features at specific time-equivalent stratigraphic surface. In lithofacies modelling, more refined high-order architectural elements were modelled using methodologies included 3D facies seismic probability, local varying azimuth and dip angle to capture lateral accretion of point bars inside the channels for better facies distributions following point bar architectures. In property modelling, porosity was populated using Gaussian Random Function Simulation constraint to lithofacies trend to control the distribution of porosity away from wells. This methodology resulted in the porosity distributions being well controlled following the lithofacies trend. The proposed workflows and methodologies enable geomodeller to produce a more geological realistic meandering fluvial reservoir model with internal lithofacies and property distribution honouring well data and input distribution.","PeriodicalId":11267,"journal":{"name":"Day 3 Thu, March 28, 2019","volume":"77 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2019-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Day 3 Thu, March 28, 2019","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.2523/IPTC-19352-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
Modelling of meandering fluvial reservoirs with point bars and crevasse splays is very challenging. The conventional modelling approaches, especially for meandering fluvial reservoirs, are mainly controlled by wells, which have contributed to uncertainties in lateral variations between and away from well control. Integration of the improved sedimentology, geophysics and 3D reservoir geomodelling techniques of fluvial reservoir system are proposed in the study. In stratigraphic and structural framework building, the improved methodologies included 3D seismic geobody extraction, stratal slicing and high order architectural elements interpretation. 3D geobody extraction and stratal slicing technique enhanced interpreter ability to visualize fluvial features at specific time-equivalent stratigraphic surface. In lithofacies modelling, more refined high-order architectural elements were modelled using methodologies included 3D facies seismic probability, local varying azimuth and dip angle to capture lateral accretion of point bars inside the channels for better facies distributions following point bar architectures. In property modelling, porosity was populated using Gaussian Random Function Simulation constraint to lithofacies trend to control the distribution of porosity away from wells. This methodology resulted in the porosity distributions being well controlled following the lithofacies trend. The proposed workflows and methodologies enable geomodeller to produce a more geological realistic meandering fluvial reservoir model with internal lithofacies and property distribution honouring well data and input distribution.