Geostatistical reservoir modeling provides multiple equally probable realizations of structure, facies, and petrophysical properties. A large number of realizations should be processed to ensure that production decisions and strategies are not unduly affected by an unusually good or bad simulated realization. Flow simulation, however, often requires significant computational and professional time. Only a few geostatistical realizations can be subjected to detailed flow modeling. An integrated approach is developed for ranking geostatistical realizations. A small number of representative realizations can then be selected for flow processing. The ranking and selecting of realizations must be tailored to the flow process. Techniques that work for conventional oil and gas reservoirs are not necessarily suitable for in-situ and SAGD bitumen recovery methods. This paper describes static connectivity measures tailored to heavy oil recovery processes from the McMurray Formation. Flow simulation is performed on many geostatistical realizations to calibrate the ranking measures to production response. This permits reliable inference in reservoir areas where it is not possible to perform many flow simulations. Introduction The Athabasca Oil Sands or McMurray Formation is located northwest of Fort McMurray, Alberta, Canada. Surface mining and in-situ recovery methods are employed due to its shallow proximity and high viscosity. At average conditions, there is a 20m net pay interval 120m below the surface with a bitumen viscosity of 10,000,000cp (Komery, 1998). The formation spans 40,000 km2 and contains an estimated 174.4 billion barrels of bitumen reserves rivaling conventional oil reserves in the Middle East (Polikar, 2004). Approximately 10% of the reserves are located close enough to the surface to allow economical surface mining. The demand for innovative in-situ heavy oil sands extraction technology has been on the rise in the last 40 years. Steam assisted gravity drainage (SAGD) is a popular in-situ heavy oil recovery process. The technology was pioneered and developed by Dr. Roger Butler and his collogues at Imperial Oil in the late 1970's (Butler, 1998).SAGD was pilot tested at AOSTRA's Underground Test Facility (UTF) (Komery, 1995). Since the late 1990's, several SAGD projects have been approved. There are over 40 major Oil Sands projects under way or planned with an expected yield of 1.8 million barrels per day by 2010 (Moritis, 2004). There are also several foreign SAGD operations and plans such as within the Xinglongtai Formation in the Liaohe Oilfields of China (Shangqi, 1998) and within the Tia Juana field in the Orinoco Belt of Venezuela (Robles, 2001). The SAGD procedure is applied to multiple horizontal well pairs up to 1000m long. The upper injection well and lower production well are nominally parallel and separated by 5m of elevation. To initiate inter-well connectivity, steam is injected through both wells for the first 3 to 6 months. Steam circulation then continues to be injected through the upper injection well only forming a cone shaped steam chamber anchored at the production well. As new reservoir is heated, bitumen lowers in viscosity and flows downward along the outside of the steam chamber boundary via gravity into the production well (Butler, 2004). The primary production performance parameters are the rate oil is produced from the production well (OPRATE) and the amount of steam used relative to oil production or steam-oil-ratio (SOR). Reservoir geology and heterogeneity affect SAGD production performance (McLennan, 2004). Although there are many factors that affect SAGD production performance prediction, connectivity and the spatial distribution of facies, porosity, water saturation, and permeability are the most significant. Geological heterogeneity and connectivity is impossible to exactly predict between wells. The unique true distribution of reservoir properties will remain unknown. Geological uncertainty is an inherent characteristic of any geological model. Geostatistics can be used to quantify uncertainty in the geological model through the construction of multiple equally probable realizations of reservoir properties. The difference between geological realizations is a measure of geological uncertainty (Deutsch, 2002a).
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