Cluster-Based Flare-Gas Aggregation in the Niger Delta and Empirical Gas-to-Power Modelling for Enhanced Energy Security in Nigeria

Aims: This study aims to quantify the power-generation potential of optimally aggregated flare-gas clusters in the Niger Delta. This is achieved by integrating geospatial clustering, gas-conditioning process simulation, and empirical gas-to-power modelling. The objective of the study is to provide a practical basis for translating flare-gas recovery into enhanced energy security in Nigeria. Study Design: The study adopts a quantitative, model-based analytical design. It builds on an existing geospatial clustering framework and extends it through process simulation and data-driven power-generation modelling. Place and Duration of Study: The study focuses on twenty-four onshore oil and gas flowstations located in the Niger Delta, Nigeria. Power-plant operational data used for the empirical modelling cover the period from 1 January 2024 to 15 August 2024. Methodology: Previously optimized flare-gas clusters were adopted as fixed spatial units. Cluster-level gas compositions were determined using volume-weighted aggregation while gas-conditioning simulations, including dehydration and natural gas liquids recovery, were performed in Aspen UniSim Design to produce turbine-suitable lean gas. An empirical gas-to-power regression model was developed using operational data from the Afam VI combined-cycle gas-turbine plant. The regression was applied to deliver the simulated lean-gas outputs to estimate both cluster-level and total power-generation potential. Results: The conditioned lean-gas streams exhibited stable methane-rich compositions, with lower heating values ranging from 46.29 to 47.92 MJ/kg. Applying the empirical model yielded an estimated total recoverable capacity of approximately 578 MW. This corresponds to 13,872 MWh/day or 5.06 TWh/year. Over 70% of this capacity is concentrated in two clusters, demonstrating the effectiveness of spatial aggregation for prioritizing infrastructure investment. Conclusion: The results demonstrate that cluster-based flare-gas aggregation, combined with realistic gas conditioning and empirical power modelling, can deliver meaningful and achievable electricity generation. This approach provides a credible pathway for reducing gas flaring while strengthening Nigeria’s energy security.