Abstract

The spatial prediction of geothermal sites along the Gulf of Suez coastal area, is an essential goal as an attempt for the development of renewable energy sources in Egypt. Remote sensing, geophysical methods and Geographic Information System (GIS) were integrated to appraise the promising geothermal zones. Hot-springs and wells data were collected initially in database for modeling the potential zones through the Bayesian statistical approach. Multi-source datasets were selected to derive factor layers indicating the distribution of geothermal energy such as topographic and geologic maps, Bouguer gravity anomaly and aeromagnetic reduced-to-the-pole maps, seismic data, satellite images, earthquake activities, and Bottom Hole Temperature (BHT) from oil and gas wells. Eight evidence layers were derived, analyzed, and integrated in a GIS platform to develop a Geothermal Potential Model (GPM). The representative ranks and weights were estimated to the spatial evidence layers and their classes respectively based on information value (IV) and weights-of-evidence (WoE) analyses. The eight evidence layers include proximity to major fault, lineaments density, land surface temperature, density of seismic activities, heat flow, temperature gradient at different depths, Curie point depth, and Bouguer anomaly. A geothermal potential map was created and classified the study area into five relatively zones, varied from very poor to very good potential. The very good potential sites are distributed mainly in the highly deep-structured and permeable lithologies. The new promising sites are expected to be in Ras Matarma, Ras Badran, Abu Rudies, Belayim, Abu Durba, El-Tur and some sites in southwestern shoreline of Gulf of Suez. The geothermal potential map was correlated and tested against the distribution of thermal wells and hot-springs. The holistic integrated approach suggests an innovative technique to design management plan and development actions along Gulf of Suez coastal area.

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