Abstract
Temperature logs have important applications in the geothermal industry such as the estimation of the static formation temperature (SFT) and the characterization of fluid loss from a borehole. However, the temperature distribution of the wellbore relies on various factors such as wellbore flow conditions, fluid losses, well layout, heat transfer mechanics within the fluid as well as between the wellbore and the surrounding rock formation, etc. In this context, the numerical approach presented in this paper is applied to investigate the influencing parameters/uncertainties in the interpretation of borehole logging data. To this end, synthetic temperature logs representing different well operation conditions were numerically generated using our newly developed wellbore simulator. Our models account for several complex operation scenarios resulting from the requirements of high-enthalpy wells where different flow conditions, such as mud injection with- and without fluid loss and shut-in, occur in the drill string and the annulus. The simulation results reveal that free convective heat transfer plays an important role in the earlier evolution of the shut-in-time temperature; high accuracy SFT estimation is only possible when long-term shut-in measurements are used. Two other simulation scenarios for a well under injection conditions show that applying simple temperature correction methods on the non-shut-in temperature data could lead to large errors for SFT estimation even at very low injection flow rates. Furthermore, the magnitude of the temperature gradient increase depends on the flow rate, the percentage of fluid loss and the lateral heat transfer between the fluid and the rock formation. As indicated by this study, under low fluid losses (< 30%) or relatively higher flow rates (> 20 L/s), the impact of flow rate and the lateral heat transfer on the temperature gradient increase can be ignored. These results provide insights on the key factors influencing the well temperature distribution, which are important for the choice of the drilling data to estimate SFT and the design of the inverse modeling scheme in future studies to determine an accurate SFT profile for the high-enthalpy geothermal environment.
Highlights
Geothermal explorations depend strongly on reservoir conditions which are evaluated by increasingly sophisticated reservoir simulators (Cacace et al 2010; O’Sullivan and O’Sullivan 2016; Konrad et al 2019)
The underestimation errors range from − 61.9 to − 31.3 °C depending on the rate of heat transfer rate assumed in the model
The static formation temperature (SFT) tends to be overestimated under low heat transfer rates (h = hc, 2hc) and underestimated under higher heat transfer rates (h = 10hc, ∞)
Summary
Geothermal explorations depend strongly on reservoir conditions which are evaluated by increasingly sophisticated reservoir simulators (Cacace et al 2010; O’Sullivan and O’Sullivan 2016; Konrad et al 2019). Various temperature correction methods based on different simplified physical models have been developed, e.g., the Horner-plot method [or constant line source method (Bullard 1947; Dowdle and Cobb 1975)]; the spherical and radial heat flow method (Ascencio et al 1994, 2006); the Hasan-Kabir method (or conductive-convective cylindrical heat source model (Hasan and Kabir 1994) and the Kutasov–Eppelbaum method [or generalized Horner method (Kutasov and Eppelbaum 2005)] These methods are based on linear or non-linear regression models that describe the relationship between measured BHT and time functions (Verma et al 2006a, Verma et al 2006b; Wong-Loya et al 2012) accounting for the transient effects of thermal recovery during the shut-in phase of the borehole. The simplicities in these methods make them very prevalent engineering tools for estimating SFT
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