Reservoir characterization and volumetric evaluation are central to defining the hydrocarbon potential and recovery strategy of producing fields. Although many Niger Delta studies have applied seismic attributes and petrophysical evaluation independently, fewer works have integrated deterministic reservoir characterization with probabilistic volumetrics to assess bypassed hydrocarbons. This study applies an integrated workflow combining three-dimensional (3D) seismic analysis, well log evaluation, and Monte Carlo simulation of Stock Tank Oil Initially in Place (STOIIP) to characterize the reservoir system and quantify bypassed hydrocarbon volumes in the Uden Field, Niger Delta, Nigeria. Three wells (UDEN-1, UDEN-2, and UDEN-3) along with a post-stack 3D seismic dataset were analyzed using Petrel 2014, Interactive Petrophysics, and Python-based stochastic modeling tools. Reservoir correlation delineated two sandstone units within the Agbada Formation, with average porosity of 0.25 – 0.29, permeability of 0.8 – 1.2 Darcy, and water saturation of 0.12 – 0.36. Seismic attribute analysis using RMS amplitude, maximum amplitude, and variance effectively delineated structural discontinuities and potential hydrocarbon accumulations. Deterministic mid-case STOIIP values for SAM-1 and SAM-2 were ~142 MMbbl, while Monte Carlo probabilistic simulation yielded P10, P50, and P90 estimates of 112, 142, and 177 MMbbl, respectively. Recovery factor estimates of 27 – 30% indicate remaining bypassed oil potential of up to ~121 MMbbl, supporting further infill drilling and recompletion opportunities. This integrated approach strengthens reservoir understanding and supports optimized recovery strategies in structurally complex Niger Delta settings.
Ekong et al. (2025) studied this question.