Stratigraphic rule-based reservoir modeling

Abstract

Research Article| December 01, 2015 Stratigraphic rule-based reservoir modeling Michael J. Pyrcz; Michael J. Pyrcz Chevron Energy Technology Company, 1500 Louisiana Street, Houston, TX 77002, USA Search for other works by this author on: GSW Google Scholar Richard P. Sech; Richard P. Sech Chevron Energy Technology Company, 1500 Louisiana Street, Houston, TX 77002, USA Search for other works by this author on: GSW Google Scholar Jacob A. Covault; Jacob A. Covault Bureau of Economic Geology, University of Texas at Austin, PO Box X, Austin, TX 78713, USA Search for other works by this author on: GSW Google Scholar Brian J. Willis; Brian J. Willis Chevron Energy Technology Company, 1500 Louisiana Street, Houston, TX 77002, USA Search for other works by this author on: GSW Google Scholar Zoltan Sylvester; Zoltan Sylvester Chevron Energy Technology Company, 1500 Louisiana Street, Houston, TX 77002, USA Search for other works by this author on: GSW Google Scholar Tao Sun Tao Sun Chevron Energy Technology Company, 1500 Louisiana Street, Houston, TX 77002, USA Search for other works by this author on: GSW Google Scholar Bulletin of Canadian Petroleum Geology (2015) 63 (4): 287–303. https://doi.org/10.2113/gscpgbull.63.4.287 Article history received: 29 Nov 2014 accepted: 04 Nov 2015 first online: 13 Jul 2017 Cite View This Citation Add to Citation Manager Share Icon Share Facebook Twitter LinkedIn MailTo Tools Icon Tools Get Permissions Search Site Citation Michael J. Pyrcz, Richard P. Sech, Jacob A. Covault, Brian J. Willis, Zoltan Sylvester, Tao Sun; Stratigraphic rule-based reservoir modeling. Bulletin of Canadian Petroleum Geology 2015;; 63 (4): 287–303. doi: https://doi.org/10.2113/gscpgbull.63.4.287 Download citation file: Ris (Zotero) Refmanager EasyBib Bookends Mendeley Papers EndNote RefWorks BibTex toolbar search Search Dropdown Menu toolbar search search input Search input auto suggest filter your search All ContentBy SocietyBulletin of Canadian Petroleum Geology Search Advanced Search Abstract Stratigraphic rule-based modeling methods approximate sedimentary dynamics to generate numerical descriptions of reservoir architecture and the spatial distribution of petrophysical properties. A few intuitive rules included in a reservoir model construction workflow are shown to render realistic reservoir heterogeneity, continuity, and spatial organization to petrophysical property distributions that are difficult to obtain using conventional reservoir modeling methods. These rules may be inferred from mature reservoirs, surface and subsurface datasets, and process-based models. Examples include confinement, meander, compensation, and healing rules. By incorporating stratigraphic rules that relate to the underlying geological processes in temporal sequence, rule-based modeling methods offer more realistic representation of inferred reservoir heterogeneity beyond conventional geostatistical reservoir modeling approaches. These include variogram-based, multiple point-based and object-based approaches that rely on a limited set of spatial statistics to describe the products of geological processes. Moreover, since these methods operate within a geostatistical framework, uncertainty can be explored by varying geologically meaningful parameters over multiple scenarios and realizations whilst maintaining consistency with input data constraints and applied to reservoir modeling studies within standard workflows.Rule-based modeling methods enable a variety of applications, including use: directly as reservoir models, as a source of reservoir model input statistics such as variograms and training images, and as a numerical analog laboratory to explore relationships between data, model choices and forecasts. Challenges remain, such as reliability of emergent features, alignment to grid framework, and feasibility for broad application. Despite challenges, rule-based methods can offer uplift when the natural facies continuity patterns and their corresponding petrophysical properties are critical to support decisions in reservoir modeling projects. You do not have access to this content, please speak to your institutional administrator if you feel you should have access.