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The Chingshui geothermal field is the largest known productive geothermal area in Taiwan. The purpose of this paper is to delineate this geothermal structure by integrating geophysical data and borehole information. The existence of a magma chamber in the shallow crust and shallow intrusive igneous rock results in a high heat flow and geothermal gradient; furthermore, the NE deep fault system within the meta-sandstones provides meteoric recharge from a higher elevation to artesianally drive the geothermal system. There is evidence that geothermal fluid deeply circulated within the fracture zone and was heated by a deeply located body of hot rock. The geothermal reservoir of the Chingshui geothermal field might be related to the fracture zone of the Chingshuihsi fault. It is bounded by the C-fault in the north and Xiaonanao fault in the south. Based on information obtained from geophysical interpretations and well logs, a 3-D geothermal conceptual model is constructed in this study. Further, the geothermal reservoir is confined to an area that is 260 m in width, N21°W, 1.5 km in length, and has an 80°dip toward the NE. A high-temperature zone is found in the SE region of the reservoir, which is about 500 m in length; this zone is located near the intersection of the Chingshuihsi and Xiaonanao faults. An area on the NE side of the high-temperature zone has been recommended for the drilling of production wells for future geothermal development.

Direct current resistivity data acquired on rough terrain can be interpreted by using an appropriate inversion technique after a topographic correction. In order to avoid the influence of a possibly incomplete topographic correction, an improved two-dimensional resistivity inversion algorithm has been developed to estimate the subsurface resistivity distribution in the presence of topography.In this paper, fully discretized modeling is based on the finite-element method, and the iterative inversion scheme is derived from the second-order Marquardt damped least-squares method. The algorithm has been tested on both synthetic and field resistivity data with topography incorporated explicitly into the inversion model. Both theoretical and field studies indicate that the technique is computationally efficient and provides an improved geologic interpretation for complex subsurface structures. A four-electrode configuration is used in the algorithm so that the inversion can represent most field measurements.

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