THREE-DIMENSIONAL MODELLING OF STACKED TURBIDITE CHANNELS IN WEST AFRICA: IMPACT ON DYNAMIC RESERVOIR SIMULATIONS

Abstract

The examination of production history from hydrocarbon fields composed of turbidite deposits indicates that fluid flow behaviour is often more complex than expected. The cause is commonly linked to the presence of fine-scale sedimentary heterogeneities, which complicate the reservoir. This is especially true in the case of turbiditic submarine channel complexes with final channel-filling, stages composed of lateral migration deposits. These fine-scale heterogeneities are usually below seismic resolution and are rarely represented in initial reservoir models designed for such fields. Thus, it is difficult to match the production history or identify methods to improve production and reduce associated risks. The various depositional patterns recognized in channel migration and aggradation packages from the Oligocene Malembo Formation of the Congo Basin, offshore Angola, exhibit different dynamic responses when modelled in a reservoir simulator. These dynamic differences are related to the different preservation rates of bank collapse sediments within isolated channel bodies, hereafter referred to as 'elementary channels'. According to these preservation differences, the vertical stacking pattern of channels results in better connectivity than the true lateral migration. This effect has been incorporated into a full-field simulation model by applying petrophysical upscaling methods. The recognition and modelling of detailed sedimentological heterogeneities, and their distribution along full-field models produces a better history match when the inherent uncertainties have been taken into account. Incorporating all available data and concepts to define reservoir architecture is essential in understanding the impact that fine-scale heterogeneities have on reservoir management. As the lateral extent and areal distribution of heterogeneities is still unknown, our modelling workflow incorporates uncertainty in the form of multiple realizations to identify and measure all uncertainties that might impact dynamic response. © 2006 EAGE/Geological Society of London.