conference paper · SPE Nigeria Annual International Conference and Exhibition
Abstract As a part of the preliminary phase of an initiative, SMARTGAIN, the geophysical assessment of deep geothermal energy potential of Niger Delta region, Nigeria, was carried out using aeromagnetic data, to provide preliminary insights that could aid the exploration and production of hidden or blind deep geothermal energy resources for electricity generation and environmental decarbonization in the region as it evolves into a smart region. Aeromagnetic data covering the sedimentary basin of the Niger Delta region, acquired from the Nigerian Geological Survey Agency, underwent standard processing and interpretation for geothermal exploration, including centre for exploratory targeting grid analysis technology and visual tracing, softsign function filter, tilt angle, 3D Euler deconvolution, source parameter imaging, spectral analysis, 2D conceptual and numerical modelling, and volumetric static method of potential estimation. The mapped geotectonic structures dominantly trend ENE–WSW and WNW–ESE with a maximum lineament density of 0.48 km/km² and magnetic depths from 0.1 km to 52.4 km. Estimated Curie Point Depth ranges from 12.4 km to 52.4 km, geothermal gradient (GG) ranges from 11.1ºC/km to 45.2ºC/km, and heat-flow ranges from 27.8 mW/m² to 113.2 mW/m². Based on cut-off GG of 30°C/km, seventeen geothermal prospect areas were identified, with an average cut-off depth of 6.2 ± 1.0 km. Their estimated deep geothermal power potential ranges from 340 MWe to 117,334 MWe and totals 234,320 MWe, assuming a 10% recovery factor, 10% conversion efficiency, and 100% load factor over 100 years. The findings will guide further exploration for economically-drillable deep geothermal energy production and support policymakers, stakeholders, and smart city developers working to harness deep geothermal resources for electricity generation in the Niger Delta region and environmental decarbonization of the Niger Delta region, thereby reinforcing its sustainable digital transformation into a smart region.
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DOI: 10.2118/228737-ms
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