Exploring the Significance of Digitalized Logs and Seismics through Structural Modelling and Petrophysical Analyses: Case study: Neogene-Paleogene reservoirs of the Rio Del Rey Basin, Gulf of Guinea. Cameroon

Abstract

The advent of geophysics into the world of hydrocarbon exploration has been proven to date very far back in time demonstrated by information from well logs and seismics. This study tries to characterize the reservoir using well logs and seismics originally digitized from analogue from the Rio Del Rey basin of Cameroon. Well logs and seismic maps were transformed from analogue to digital format using the Neuralog software 2018 package. Five well logs: Log L1, L2, L4, and L5, and five digital seismic maps were available for this study generated from LongiviNeuralog and Neuramap respectively. One very important reservoir was mapped for the five well scenarios. Plots were produced randomly in Interactive petrophysics software; Porosity plots, shale volume, and petroleum play maps. Reservoirs were delineated randomly in all the well scenarios with different thicknesses. Lithological plots of these formations indicated that reservoirs consist of sand, limestone, and dolomite and a Ypression mega sequence of deposition containing 4 – 6 sand units (S1.0, S1A2, S1A3, S1A4, SB). The presence of hydrocarbon in a complex paralic sand environment was inferred from the highly faulted area (7 listric faults). Finding saw reservoir compartmentalization from the structural, petrophysical, and stratigraphic anisotropy observed; 0.37–0.45 well L2, 0.08–029 well L4, 0.1624–0.30 well L1, and 0.10–0.35 well L5 for porosity, 4.099–133.4 mD, 2068.9 – above 10000 mD, 1.4228–227.3726 mD, 12.5237–454.8518 mD, For L1, L2, L4, L5 respectively. So, drilling for wells at the center of the study area is discouraged for those at the western and eastern edge of the study area. This study extends the understanding of the reservoir characterization of the Neogene-Paleogene formation proving efficient digitization using Neuralog, Petrel 2017, and an efficient reservoir study using Interactive petrophysics, Techlog, and Petrel.