Application of spectral decomposition and neural networks to characterise deep turbidite systems in the outer fold and thrust belt of the Niger Delta

Abstract

We have applied a wavelet‐based spectral decomposition scheme and a multi‐layered feed‐forward neural network to interpret turbidite depositional systems from three‐dimensional reflection seismic data and well logs for a prospective hydrocarbon zone in the outer fold and thrust belt of the Niger Delta. The goal was to overcome difficulties in interpreting depositional systems from deep sections of the Field, occasioned by loss of seismic resolution with depth and the sparse distribution of wells. The decomposition scheme allowed us to delineate multiple depositional systems not apparent on the conventional seismic amplitude display. These systems include linear channel systems with terminal splay lobes, a sinuous channel system and its abandoned meander loops, and sediment wave features in overbank areas. Delineated channel morphologies and transport directions varied both laterally and vertically and were possibly dependent upon the disposition of the pre‐thrusting paleo‐seafloor. Terminal splay lobes are fragmented and coincident with the locations of topographic lows, which are possibly related to the initial configurations of the oceanic basement below. Predicted porosity and resistivity distributions have morphologies that correlate well with the mapping provided by the spectral decomposition scheme. The property distributions indicate that reservoir prone systems in the Field and possibly within the outer fold and thrust belt are composed primarily of channel systems, both linear and sinuous, and their associated splay lobes. The channel systems appear vertically stacked, and this situation possibly increases the potential success rate for exploration wells in the region. Beyond channel limits, redistributive bottom currents varying rapidly in speed and direction apparently encouraged the dispersal of sand‐rich sediments to form sediment waves. Despite the limited well control, the methodology significantly aided our interpretation. It proved effective at revealing the distribution of reservoir prone facies within the Field and provided insight into the dominant factors that controlled deposition within the Field.