Siliciclastic reservoir characterisation and geometric trend modelling for hydrocarbon quantification and uncertainty analysis: a case study of Doma field, Niger Delta basin, Nigeria | ||
| NRIAG Journal of Astronomy and Geophysics | ||
| Volume 14, Issue 1, December 2025, Pages 1-17 PDF (31.08 M) | ||
| DOI: 10.1080/20909977.2025.2460326 | ||
| Authors | ||
| Hammed Ajibola Oyesomi; Sunday Oladele; Kehinde Festus Oyedele; Adeogun Oluwakemi Yemisi; Gabriel Efomeh Omolaiye | ||
| Abstract | ||
| Reservoir architecture delineation and understanding of heterogeneity in geological reservoir models are crucial for accurately estimating hydrocarbon reserves, production forecast, and recovery in an effective economic scenario. This work demonstrates the combination of statistical tools and geometric trend models for hydrocarbon quantification and uncertainty analysis in the Doma Field development. 3D seismic cube and five (5) well data were integrated to build structure, facies, and petrophysical models (total and effective porosity, water saturation, net-to-gross, and permeability). Eleven (11) hydrocarbon-bearing reservoirs were identified and modelled out of twenty-two (22) reservoirs (sand 1–1B2–5-IB1) delineated and correlated from the logs. The saturation height function (SHF) was generated to populate the water saturation model to mitigate capillary pressure build-up. The structural model shows that fault-dependent three-way closure dominated the field. The results of petrophysical analysis and modelling biased to the litho-facies models indicated an average effective porosity value between 20 and 37% and water saturation ranging from 0.1 to 0.5. The permeability model showed that the permeability value was greater than 100 mD. Based on uncertainty analysis, the low case, base case, and high case cumulative volumetric for oil is 43.63MMSTB, 56.72MMSTB, and 71.34MMSTB and for gas is 73.65BSCF, 96.3BSCF, and 120.59BSCF, respectively. The coefficient of variation computed from log-derived porosity varies from 0.14 in reservoir 1-IB1 to 0.44 in reservoir 14-IB2. Also, the coefficient of variation computed from the 3D model porosity varies from 0.21 in reservoir 2-IB1 to 0.45 in reservoir 14-IB2. Thus, the research study has created a bridge between statistical tools in quantifying reservoir model heterogeneity and established a reference model for siliciclastic reservoir heterogeneity classification and prediction in the area and development of reservoir parameters in the adjacent areas of the Niger Delta basin. | ||
| Keywords | ||
| modeling; structural interpretation; Reservoir characterisation; seismic image; Niger Delta basin | ||
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