An analytical approach to production logging in enhanced geothermal systems using distributed fiber optic thermal slug tracking

• DFOS detects thermal slugs caused by flow changes in geothermal wells. • Thermal slug velocity does not necessarily equal the bulk fluid velocity. • Heat conduction to the casing slows thermal slug velocity relative to fluid velocity. • Inflow temperature and reservoir conductivity have little effect on slug velocity. • Analytic model accurately estimates flow rates inferred from Utah FORGE field data. Short circuit pathways in an enhanced geothermal system (EGS) lead to early thermal breakthrough and subeconomic performance. Geothermal operators use production and injection logs to quantify the flow distribution across completion intervals to identify these pathways. One method for production logging in geothermal wells involves using distributed fiber optic sensing (DFOS) to correlate thermal slug velocities with bulk fluid velocities. A thermal slug is a thermal transient that moves along the wellbore via convection with the wellbore fluid. DFOS tracks the movement, or velocity, of thermal transients through the wellbore. In conventional practice, thermal slug velocities are often estimated arbitrarily by manually drawing lines along thermal signals in depth-time waterfall plots; this study establishes a more objective method to determine these velocities compared to subjective straight-line fitting by hand. Meanwhile, coupled wellbore-fracture-reservoir models can rigorously calculate bulk fluid velocities but are computationally demanding and analytically intractable. We hypothesize that flow distribution can be reasonably estimated based on convection and instantaneous conduction to highly conductive wellbore components. A sensitivity analysis was performed to investigate how key parameters affect thermal slug velocities. Findings showed that heat conduction to the surroundings resulted in slower such velocities; however, these velocities remained relatively unchanged even when the imposed inflow temperature was substantially altered or the thermal conductivity of relatively non-conductive surrounding rock doubled. The methods were further validated using data from a circulation test conducted on the Utah FORGE EGS, exhibiting strong consistency with field-inferred flow rates. This novel approach provides a reliable, efficient tool for improving flow diagnostics in EGS development.