Remote Sensing Application in Geothermal Exploration: Case Study of Barrier Volcanic Complex, Kenya

Authors: Mutua, Joseph; Mibei, Geoffrey
Keywords: Shortwave and thermal infrared; multi-spectral; spectral resolution; geothermal; Kenya; Africa
Conference: Geothermal Resources Council Transactions Session: Exploration; Remote sensing; Mapping
Year: 2011 Language: English
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Abstract: Kenya’s vast geothermal energy resources have the potential of becoming a highly significant source of safe, secure, competitively- priced, emission free, renewable base load power supply for centuries to come. This potential combined with the evidence of risks posed by climate change is stimulating growth in development of geothermal energy. Recent significant improvements in the wavelength coverage, spectral resolution and quality of remote sensing imagery have lead to the extensive application of these data sets in geothermal exploration and site characterization. The traditional techniques in spectral and spatial analysis of imagery, coupled with new, high signal to noise data, allow their direct application to problems in geothermal energy exploration and development. High resolution thermal infrared remote sensing data can be used as a cost-effective tool to explore large areas for geothermal potential and pinpoint smaller target areas for further exploration using ground-based survey techniques. This work seeks to demonstrate and outline how airborne and spaceborne imagery can be used to map geothermal anomalous sites, mineralogy, geological features, thermal anomalies and hot spots over broad and inaccessible geothermal prospects regions within the Barrier volcanic complex in the Northern Kenya Rift. With clearly associated indicators, mineralogy, volcanic framework, geological formation, present and past geothermal activity, mapping can be conducted from different multi spectral and multi spatial satellite imagery. Remote sensing data can also be useful in identifying fault extensions not previously mapped by field Geologists. Future work will test these methods on new sites not yet producing power to confirm their predictive capabilities for new resources.
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