Abstract

An important challenge usually faced by exploration teams is the need to establish and validate the economic potential of multiple deepwater prospects using seismic amplitudes while understanding the impact of these potential DHIs on prospect risking and volume resource estimations. Effective DHI evaluation requires explicit identification and evaluation of potential failures or false positives. Low gas saturation in reservoir sands is considered by the industry as a recurrent false positive and is usually associated with tertiary hydrocarbon migration, where a small fraction of residual gas in a reservoir generates a seismic response comparable to high saturation. Seismic anomalies probably associated with tertiary migration are explained using a saturation scale model (uniform vs. patchy) consistent with expected trap failure mechanisms. Top seal failure, where the buoyancy force is sufficient to force hydrocarbons into and through the caprock or overpressure that is high enough to fracture the top or lateral seal will generate relatively slow gas flow rates and the remaining residual gas saturation remains uniform. In this case, the elastic properties of the residually saturated reservoir are very similar to that of a fully saturated one – hence, therefore, the quantification of gas saturation using seismic analysis is not possible. In contrast, trap failure associated with tectonic tilting involves that hydrocarbons spill out of the original trap through a carrier bed. Flow rates are much higher due to the higher porosity and permeability of the tilted reservoir as compared to when a compromised shale layer is proving the fluid escape route. Residual gas saturation is in this case patchy – this means that impedance and seismic reflectivity decreases linearly with increasing gas saturation, making it possible to separate false positive responses (e.g. low saturation) from DHIs representing success cases. This novel rock physics-based characterization of tertiary hydrocarbon migration was successfully applied for multiple prospect risking and volume resource estimations in a major deepwater basin which we will demonstrate here. The same approach could be easily deployed to basins where prospect derisking is amplitude supported and a reliable predictive framework is established.

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