Predicting the Temperature Field of Hot Dry Rocks by the Seismic Inversion Method

Hongjie Peng, Jingtao Zhao () and Rui Cui
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Hongjie Peng: State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China
Jingtao Zhao: State Key Laboratory of Coal Resources and Safe Mining, China University of Mining and Technology, Beijing 100083, China
Rui Cui: Schlumberger Technology Service Ltd., Beijing 100016, China

Energies, 2023, vol. 16, issue 4, 1-23

Abstract: Hot dry rocks, as clean and abundant sources of new energy, are crucial in the restructuring of energy. Predicting the temperature field of hot dry rocks is of great significance for trapping the target areas of hot dry rocks. How to use limited logging data to predict the temperature field within a work area is a difficulty faced in hot dry rock exploration. We propose a method to predict the hot dry rock temperature field (using seismic inversion results). The relationship between porosity and transverse wave velocity was established with petrophysical modeling. The difference in porosity calculated from the density and transverse wave velocity was incorporated in the seismic inversion results to find the thermal expansion and predict the temperature field. We applied the method to predict the temperature of hot dry rocks in the Gonghe Basin. The results showed that the temperature in the northeast work area was higher than in the southwest area at the same depth, and a depth of 150 °C of the hot dry rock reservoir was shallower. The thermal storage cover was analyzed from the geological stratigraphic data of the Gonghe Basin. The thermal storage cover in the northeastern part was thicker than in the southwestern part and had better thermal insulation, which is consistent with the prediction of the temperature field.

Keywords: hot dry rock; petrophysical modeling; pre-stack simultaneous inversion; temperature field prediction (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2023
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