--> Abstract: Rule-Based Static Modeling of Carbonate Shoals Environments and Related Reservoirs, by Claude-Alain Hasler, Erwin W. Adams, and Brigitte Vlaswinkel; #90124 (2011)

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AAPG ANNUAL CONFERENCE AND EXHIBITION
Making the Next Giant Leap in Geosciences
April 10-13, 2011, Houston, Texas, USA

Rule-Based Static Modeling of Carbonate Shoals Environments and Related Reservoirs

Claude-Alain Hasler1; Erwin W. Adams2; Brigitte Vlaswinkel3

(1) Department of Geology and Paleontology, University of Geneva, Geneva, Switzerland.

(2) Sarawak Shell Berhad, Lutong, Malaysia.

(3) Shell International Exploration and Production B.V., Rijswijk, Netherlands.

Within various carbonate reservoirs, it has been demonstrated that individual carbonate sand bodies are correlatable over large distances (more than 10 km) and can have uniform stratigraphic thicknesses. Although being predictive in a stratigraphic and environment of deposition sense, internal sedimentologic and diagenetic partitioning of texture, fabric and pore types are intricate within such carbonate shoal layers. This later scale commonly is modeled geostatistically in reservoir models whereas a rule-base approach is far more applicable. We designed a cellular automata forward model aiming to reproduce these characteristics of shoal environments. Both sedimentary and early diagenetic processes are captured as cellular automata since these processes feedback and interlink through time during the development of the initial porosity and permeability architecture. Cellular automata are efficient in simplifying the interaction of complex processes and the model grid of the approach can be defined at the scale of the relevant heterogeneities within a subsurface reservoir. In order to reproduce interwell conditions, digital outcrop modeling of the Khuff in Oman has been used to quantitatively validate internal petrographic textures produced by cellular automata models. Emergent geometries have been calibrated against modern-day analogues. The forward model realizes typical shoal geometries and captures realistically internal partitioning. At a regional scale, models produced by the cellular automaton have been used as training images in a multipoint statistic approach, reproducing small sand waves, sand ridges, as well as large scale active shoal geometries observed in modern-day Bahamas carbonate banks. The ultimate goal is to enhance our ability to reduce uncertainty in subsurface static and dynamic models.