Authors: Howells Frank Amalagha Brown, Ikechi Igwe, Kingdom. K. Dune
Abstract: Accurate reservoir simulation initialization plays a vital role in predicting hydrocarbon recovery and assessing the economic potential of oil and gas projects. However, many traditional models assume uniform fluid composition and often ignore compositional grading (CG) effects such as gravity, temperature gradient, and thermal diffusion. This limitation can lead to unrealistic production forecasts and poor economic evaluations. Therefore, this study evaluated the economic viability of initializing reservoir simulation models with CG models that better capture real reservoir behavior. Using secondary data from the literature, cumulative oil and gas production data were analyzed for five models such as constant composition, isothermal, zero thermal diffusion, Haase’s, and Kempers’ CG models, respectively. Deterministic discounted cash flow (DCF) analysis was performed using Microsoft Excel at a 12% discount rate to compute Net Present Value (NPV) and Profitability Index (PI) for each model. The findings revealed that all models produced positive NPVs, ranging from $1.85 × 10⁸ to $3.67 × 10⁸ and PIs greater than 1, indicating strong profitability. The constant composition model achieved the highest PI of 3.675, mainly due to its overestimation of oil production of about 41.7 million barrels. However, the nonisothermal CG models recorded slightly lower oil output but showed improved financial performance through additional gas revenues exceeding $25 million, which compensated for their higher modeling costs. The study concludes that incorporating CG effects in reservoir models not only enhances simulation accuracy but also improves economic viability, making it a practical approach for sustainable reservoir development.
