Abstract
Abstract "A field" located in offshore Abu Dhabi has produced oil from the Upper Jurassic carbonate reservoirs for 25 years. The one of the main characteristic of this reservoir is an existence of bitumen (tar mat) zone intersecting sub-layers in the reservoir and porosity deterioration is observed in the bitumen zone and below bitumen zone. Since porosity deteriorates sharply from 20% to less than 5% at top of the bitumen, it is crucial to represent the bitumen surface in order to estimate hydrocarbon reserves and optimize future infill well locations In order to characterize the reservoir properties and identify the bitumen surface, an ocean bottom cable (OBC) 3D seismic data was acquired over A field in 2010. Seismic processing results was confirmed as a high quality data to proceed reservoir characterization studies by seismic to well tie, amplitude fidelity and low frequency level during structural interpretation work. However one of the main challenges to achieve the objective is seismic resolution because the porous interval above bitumen zone is thinning toward the flank area. Therefore seismic acoustic impedance (AI) inversion with a geostatistical approach was selected to overcome this challenge. This geostatistical AI inversion was performed by (1) log data editing and rock property analysis (2) well to seismic tie and wavelet extraction (3) low frequency model building (4) deterministic AI inversion (5) geological model framework building, and (6) stochastic AI inversion, with investigations of these uncertainties. For stochastic AI inversion stage, 50 number of multi-realizations of AI and porosity volumes were generated in order to define the top bitumen surface. Based on these realizations, several combinations of porosity and probability cut-off values were generated to identify the probabilistic top bitumen surface as well as high reservoir quality area. These results can be used as a guide to build a 3D geological model and define well planning.
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