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September 11, 2012 Annual Meeting | Poster

Using Multiple-Point Statistics for Conditioning a Zama Pinnacle Reef Facies Model to Production History

Since October 2005, the Zama oil field in northwestern Alberta, Canada, has been the site of acid gas (approximately 70% carbon dioxide[CO2] and 30% hydrogen sulfide [H2S]) injection for the simultaneous purpose of enhanced oil recovery (EOR), H2S disposal, and CO2storage. Injection began in December 2006 and continues through the present at a depth of 4900 feet into the Zama F Pool, which is oneof over 800 pinnacle reef structures identified in the Zama Subbasin. To date, over 90,000 tons of acid gas has been injected, with anincremental production of over 50,000 barrels of oil. The primary purpose of this work is to verify and validate stored volumes of CO2, withthe ultimate goal of monetizing carbon credits.Pinnacle reefs have very complex geologic and facies relationships, and as a result, a thorough understanding of the geology is necessaryin order to properly monitor and predict fluid movement in the reservoir. Core-calibrated multimineral petrophysical analysis wasperformed on well logs, and borehole image logs were used to more accurately identify the dierent facies and determine each faciesproperties along the wellbores. Seismic attribute data interpretations were used to identify the reef versus nonreef facies to aid in thedistribution of the facies in the reservoir. These properties were then spatially distributed throughout the reservoir using a combination ofmultiple-point statistics and object modeling to produce equiprobable reef facies, structure, and volumetric realizations. Theseequiprobable static realizations were ranked to further use them in dynamic modeling.A few selected static and dynamic realizations were further conditioned to obtain a reasonable match between simulated results andhistorical data. A more realistic depiction of geological and reservoir features using the modeling approaches adopted in this study isexpected to provide more reliable dynamic models for simulating long-t

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Event/Meeting Information

PCOR Partnership 2012 Annual Meeting
9/11/2012
Milwaukee, WI