There is a fast-growing inventory of studies on borehole image logs acquired in geothermal reservoirs as more operators elect to deploy this technology. Our contribution to this inventory is to illustrate how judicious use of these data may reveal the geologic controls on permeability. We also provide an open source Python library that enables others to replicate the methods described herein. Our study includes a discussion of geometric sample bias, as well as those data integrity and geological factors that influence fracture frequency. We also demonstrate slip tendency modelling as an approach to identifying fractures that may be relevant beyond the borehole wall, which is key for geothermal wells where thermal stresses have enhanced both the number and apparent aperture of fractures at the borehole wall. We illustrate these methods using seven well case studies from a wide range of lithologies, four reservoirs, and two tectonic settings—one dominated by a volcano-tectonic rift and the other a mega-shear zone. The reservoirs are Muara Laboh and Rantau Dedap in Indonesia and Ngatamariki and Wairakei in New Zealand.