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Optimizing Subsurface Predictions With Limited Capital Investment


In both highly developed and exploratory hydrocarbon producing regions the predictability of reservoir properties is limited by the quality and amount of available data. During the latest industry down turn, we have been challenged with ‘do more with less capital’ and subsequently less subsurface information, while maintaining and in some cases improving probability of success. However, if a systematic approach to interpretation of the available data is employed, a maximization of return on investment and confident decision making is obtained. Here we present an example of the Highvale Oil pool located in Central Alberta, Canada, which produces light oil from dolomitzed carbonates of the Mississippian Banff Formation and we employ a systematic approach to the integration of outcrop data, a pre-existing 3D seismic survey and petrophsyical log data in order to gain a clear definition of the subsurface. This approach includes outcrop analysis, the creation of internal stratigraphic correlation within the erosional remnants of the Banff Formation, the identification of fluid contacts, estimation of saturations and porosity, mineral identification and the integration of recently developed 5D interpolation of seismic data to regularize, fill in data gaps, to increase the fold and create the common depth point gathers more suited to pre-stack time migration (PSTM). With nominal costs and time associated with data quality improvements and interpretations of the existing data, the resultant work provides a clear image of the Highvale Oil Pool Mississippian surface. This approach to subsurface prediction and planning leads to savings including, necessary data integration, interpretation time, confidence in the subsurface model and ultimately optimizing drilling locations.