The algorithm of high-accuracy temperature prediction at large depths from seismic sounding data is suggested. The accuracy of its prediction is validated using neural network modeling. To this end the seismic sounding data along the latitudinal profile of the Northern Tien Shan and 2-D temperature model built earlier up to the depth of 27 km are used. The assessment of the prediction accuracy indicated that it practically does not depend on the ratio between the depths of the target and borehole, the data from which are used for neural network training. Therewith the average relative accuracy of the temperature prediction from longitudinal and transverse wave velocity up to the depth of 20 km was 92–93 % and 95–96 %, accordingly. The algorithm suggested could be used for high-accuracy temperature prediction at depth many times exceeding the borehole depth. This enables to increase the effectiveness of the geothermal exploration (in particular, of unconventional resources) and search for the hydrocarbons of organic nature.

Viacheslav V. Spichak
Doctor of Physical and Mathematical Sciences
Head of the Lab methodology of the EM data interpretation
Geoelectromagnetic Research Centre
of the Institute of the Physics of the Earth RAS
POB 30, GEMRC, Troitsk, Moscow Region, 108840, Russia
e-mail: v.spichak@mail.ru
ORCID ID: 0000-0001-6121-190X
SPIN-code: 7363-0529
AuthorID: 61066

Olga K. Zakharova
Candidate of Physical and Mathematical Sciences
Leading Researcher of the Lab methodology
of the EM data interpretation IPE RAS
Geoelectromagnetic Research Centre
of the Institute of the Physics of the Earth RAS
POB 30, GEMRC, Troitsk, Moscow Region, 108840, Russia
e-mail: okzakharova@mail.ru
AuthorID: 61066

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