Indirect electromagnetic (EM) geothermometer developed recently in (Spichak et al., 2007a,b) is applied to the temperature extrapolation in depth in the Hengill geothermal zone (Iceland). The approach used is based on the artificial neural network (ANN) analysis of the implicit conductivity-temperature relations rather than on the prior assumptions of the electrical conductivity mechanisms.
The samples for indirect EM geothermometer calibration consisted from the well temperature records and electrical conductivity values determined for the same depths from the magnetotelluric data measured in the vicinities of 8 boreholes. The testing of the estimates was carried out using the temperature records not involved in the calibration. The results indicate that the temperature extrapolation accuracy essentially depends on the ratio between the well length and the extrapolation depth. In particular, in extrapolation to a depth twice as large as the well depth the relative error is 5-6%, and in case of its threefold excess the error is around 20%.
This result makes it possible to increase significantly the deepness of indirect temperature estimations in the geothermal areas without additional drilling. The method developed could be especially useful when exploring supercritical geothermal resources located at depths 4-5 km or deeper, where the temperature estimates could be made using the EM geothermometer calibrated by the shallow parts of the available temperature logs.

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