| Abstract |
Geothermal well site selection requires consideration of a comprehensive set of factors and balancing of multiple objectives in determining the suitability of a particular area for geothermal exploration drilling. The selection of geothermal well sites involves a complex array of critical multi-disciplinary factors and characterization. Geographic Information System (GIS), forms an invaluable link of field sample datasets from geologists, geophysicists, geochemists, reservoir scientists, and environmentalist. Geothermal spatial decision making could benefit from more systematic methods for handling multi- criteria problems while considering the physical and technical suitability conditions. Traditional decision support techniques lack the ability to simultaneously take into account these aspects which are achievable through geoprocessing and model builder tools in ArcGIS. GIS is the most efficient and effective modern technology used to make spatial multi criteria decisions that target potential geothermal resources. Comprehensive geo-scientific surface exploration was done in Menengai geothermal field prospect and multi-disciplinary data acquired through different spatial sampling techniques. The geo-scientific data from surface investigations was categorized into four key datasets; Geological (eruption centers, volcanic rocks, craters and faults), Geochemistry (soil gas, hot springs and acidic hydrothermal alteration zone), Geophysical (MT and TEM anomalies) and Surface heat loss (Heat loss anomalies). GIS was used to carry out spatial auto correlation of all the datasets, generation of trend surfaces and integrating and weighting all the four key datasets in a suitability model for geothermal well sites selection in Menengai prospect. Geoprocessing and Model builder tools were used for developing the suitabilitymodel and characterization. From the suitability model eight (8) geothermal well sites were eventually selected for exploratory drilling. |