Deep geothermal well site selection method based on multi-scale geophysical data fusion

By integrating multi-scale geophysical data and establishing a quantitative evaluation system, the problems of multiple solutions and experience dependence in the site selection of deep geothermal wells have been solved, enabling detailed characterization and scientific site selection of deep geothermal reservoir systems, and improving exploration success rate and economic benefits.

CN122347360APending Publication Date: 2026-07-07JIANGSU GEOLOGICAL SURVEY INST
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Patent Information

Authority / Receiving Office
CN Β· China
Patent Type
Applications(China)
Current Assignee / Owner
JIANGSU GEOLOGICAL SURVEY INST
Filing Date
2026-04-09
Publication Date
2026-07-07

AI Technical Summary

Technical Problem

Existing technologies for deep geothermal well site selection suffer from multiple solutions due to the reliance on a single geophysical method, a lack of effective coordination and integration mechanisms, and poor scientific rigor and repeatability due to dependence on expert experience, which increases the risk and cost of drilling failure.

Method used

A multi-scale geophysical data fusion method is adopted. By collecting multiple geophysical data and registering and fusing them in the same coordinate system, a quantitative evaluation system is constructed. Combined with geological interpretation and known borehole information, a three-dimensional geological structure model is established, and hot well locations are selected through comprehensive evaluation indicators.

Benefits of technology

It enables detailed characterization of deep geothermal reservoir systems, improves exploration success rate and economic benefits, reduces exploration risks and costs, and enhances the scientific nature and repeatability of site selection.

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Abstract

The application discloses a deep geothermal well site selection method based on multi-scale geophysical data fusion, and belongs to the technical field of the intersection of geophysical exploration and geothermal resource evaluation. The method comprises the following steps: S1, multi-scale geophysical data acquisition and processing; S2, multi-physical field data fusion processing and geological interpretation; and S3, constructing a quantitative evaluation system and optimizing a geothermal well, wherein the quantitative evaluation system comprises six key indexes, i.e., a structure intersection index, a geothermal anomaly index, a geophysical anomaly coincidence index, a geothermal reservoir development index, a cap rock integrity index and an existing engineering index. Compared with the prior art, the application can effectively integrate multi-scale and multi-type geophysical information, and guide well site optimization through the construction of an objective and quantitative evaluation model, so that the transformation from 'experience driving' to 'data and model driving' is realized, and the success rate and economic benefits of deep geothermal exploration are improved.
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