See more from this Division: General Discipline Sessions
See more from this Session: Sediments, Carbonates / Clastic
Abstract:
By contrast, methods used to interrogate a reservoir directly are predominantly geophysical in nature, and are usually based on quantitative data. Geophysical data alone is never, however, able to constrain a reservoir model uniquely, and the injection of additional information is always necessary. An improved workflow that creates a direct interface between geologists' qualitative, process-based knowledge, and geophysicists' quantitative information would therefore be of considerable utility.
This talk will introduce novel methods in Bayesian uncertainty analysis applied to oilfield geological models, and in the field of elicitation theory (which incorporate statistics, cognitive psychology and computer science) to motivate new workflows that quantify geological knowledge explicitly and probabilistically. These enable geological information to be used quantitatively by integrating such information within a joint geological-geophysical workflow so as to reduce uncertainty in 2D/3D/4D geophysical models directly. The result is a more robust geological and geophysical interpretation of reservoir models, and ultimately more accurate prediction of reservoir behaviour during production.
See more from this Division: General Discipline Sessions
See more from this Session: Sediments, Carbonates / Clastic