Quantifying Reservoir Uncertainty in Highly-Compacted Depositional Environments Using Reflectivity Models from Monte Carlo Simulations

Fuqua, D. Alan¹ (1) Chevron Nigeria Limited, Lagos, Nigeria

The use of the seismic amplitude method for recognizing Direct Hydrocarbon Indicators (DHIs) is generally restricted to Class 3 and Class 2n AVA reflectivity. When the reservoirs of interest are more compacted and indurated the seismic signature is generally Class 1 or Class 2p AVA. In this scenario our ability to recognize fluid effects is severely diminished, and in many cases our ability to recognize reservoir is significantly subdued as a result of the large geological ambiguity in the system, i.e., determining shale-shale reflectivity from shale-reservoir reflectivity is extremely difficult. As we explore and develop in deeper water environments our need for the capability to seismically identify reservoir and fluid in the presence of geological ambiguity becomes more prevalent. This paper introduces a workflow to quantify our ability to recognize reservoir and/or DHIs in the presence of Class 1 and Class 2p AVA reflectivity and the large geological ambiguity that arises from these classes of reflectivity. Half space models are constructed from Monte Carlo realizations of various shale-shale, shale-brine, and shale-oil interfaces. From the half space models several tens of seismic and inversion-related attributes are generated for quantification in various cluster analysis techniques. The results indicate an astonishing capability to discern reservoir and even DHIs in the presence of extremely large geological ambiguity, given sufficient seismic data quality. This has significant implications in the context of better quantifying uncertainty related to exploration, appraisal, and development economic scenarios.