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Drilling in high temperature volcanic geothermal systems is technically challenging due to the mechanical heterogeneity of volcanic successions, where rapid transitions between lava flows, breccias and intrusions generate highly variable drillability. Understanding how drilling parameters reflect this variability is essential for optimizing drilling performance and improving subsurface characterization. This study evaluates the association between electrofacies porosity state variations on drilling response by integrating drilling parameters, rate of penetration (ROP) and weight on bit (WOB), with unsupervised machine learning derived electrofacies generated from neutron, resistivity, and gamma ray logs in four geothermal wells from the Theistareykir field, NE Iceland. Operational aspects that may affect on-bottom drilling performance were removed by pre-processing drilling data, enabling ROP and WOB to be interpreted as parameters that primarily reflect bit-rock interaction. The results show consistent drilling trends at electrofacies boundaries in which the low porosity facies exhibit low ROP whereas the high porosity facies exhibit higher ROP records at constant WOB. These trends reflect porosity related mechanical contrasts consistent with previously published laboratory measurements on volcanic rocks. By conducting the comparisons in drilling performance variation response to electrofacies-derived porosity and composition, we develop a conceptual geo-mechanical model that captures the effect of lava flows stacking and intrusion emplacement into host rocks on ROP and WOB trends. This integrated approach improves the interpretation of volcanic heterogeneity at the scale of the drill bit and identifying prognosed drilling performance in volcanic environments.
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Hammoud et al. (2026) studied this question.
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