Abstract

Gonghe Basin is the most critical distribution area of hot dry rock (HDR) geothermal resources in China. Geophysical results (resistivity, velocity, density, etc.) provide an indirect way to image the spatial distribution to understand its genesis, which has a multisolution problem. However, heat flow and thermal conductivity are the most direct and reliable evidence to reveal the distribution of geothermal resources. The conventional thermal conductivity and heat flow obtained based on geologic surveys and rock samples are highly accurate, but it is challenging to characterize the regional distribution characteristics. In this paper, we develop the heat transfer adaptive finite-element equation parameter inversion workflow to invert the thermal parameters and analyze the geothermal formation mechanisms in the Gonghe Basin. First, the synthetic model test verifies that our inversion process has reliable accuracy and strong antinoise ability. For the Gonghe Basin HDR geothermal example, we use high-precision aeromagnetic data to estimate the Curie depth using the improved Parker-Oldenburg method. Then, the regional conductivity thermal and temperature field can be established according to the empirical formula as the initial input model for the inversion procedure. In addition, we collect the temperature data of six HDR geothermal wells across the Gonghe-Guide Basin as a priori constraint information. Combined with the inverted thermal parameters (thermal conductivity, geothermal gradient, and heat flow), geologic structure, and geophysical result, we infer that the high thermal conductivity layer at a depth of 5–10 km provides the main deep heat source channel and the shallow low thermal conductivity fine sandstone layer of Neogene provides good caprock protection for forming a high-temperature geothermal reservoir.

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