4.6 Article

Subsurface temperature prediction by means of the coefficient correction method of the optimal temperature: A case study in the Xiong'an New Area, China

期刊

GEOPHYSICS
卷 87, 期 4, 页码 B269-B285

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SOC EXPLORATION GEOPHYSICISTS - SEG
DOI: 10.1190/geo2021-0339.1

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资金

  1. National Key Research and Development Program of China [2018YFC0604303, 2018YFC1503705]
  2. National Nature Science Foundation of China [41630317]

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Accurate estimation of the earth's interior temperature is crucial for geothermal research. Using resistivity as a temperature-dependent proxy parameter can overcome the limitations of existing temperature estimation methods. The electromagnetic geothermometer based on the coefficient correction method of the optimal temperature (CCMOT) demonstrates high accuracy in predicting subsurface temperature in the Xiong'an New Area, making it of significant importance.
Accurate estimation of the earth's interior temperature is extremely important for studying fundamental scientific and applied geothermal problems. Existing temperature estimation methods cannot provide reliable accuracy in the cross-borehole space and beyond the borehole's depth; however. resistivity could overcome this difficulty as a temperature-dependent proxy parameter. At present, this approach is based on the use of purely empirical formulas, whose validity is unjustifiably postulated to be invariant with respect to geologic settings. We develop an electromagnetic (EM) geothermometer based on the coefficient correction method of the optimal temperature (CCMOT). This geothermometer can accurately determine the relationship between the normalized resistivity and temperature in an underground space based on resistivity-temperature logging data and EM data; therefore, a visualized temperature distribution can he calculated. The CCMOT is applied to the subsurface temperature prediction in the Xiong'an New Area, with an accuracy of 86.69%-97.25%. Sensitivity analysis of the key variables of the CCMOT reveal that the CCMOT has relatively little dependence on the number of constraining boreholes and the optimization of the subdivision spacing of the logging data can significantly improve temperature prediction accuracy. The CCMOT can be used to determine the distribution of the heat structure of the reservoir and to interpret the geothermal field. In addition, the CCMOT is of great significance to the evaluation, scientific development, and sustainable use of geothermal resources.

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