[Objective]In geothermal exploration,a clay cap is a typical hydrothermal geothermal system,and its depth and distribution range can provide crucial information for delineating the scope of geothermal resources and determining the location of geothermal drilling.Clay caps are usually composed of a clay layer formed through hy-drothermal reactions and are characterized by low resistance.The low-resistivity cap can be effectively imaged using the audio-frequency magnetotelluric method.To obtain uncertainty information about the distribution of clay cap layers and imaging results,this paper employs the 1D trans-dimensional Bayesian inversion method to investigate the detection capabilities of low-resistance cap layers in geothermal areas through audio electromagnetic data.[Methods]In this paper,a model test is first carried out to establish a geoelectric model of a typical geothermal system.Subsequently,a 1D trans-dimensional Bayesian algorithm is used to invert the synthetic data to obtain the uncertainty information of the subsurface electrical structure and interface position.Then,the method was applied to the processing of measured audio frequency magnetotelluric data in the Yanggao geothermal area of Shanxi Prov-ince.[Results]This method has relatively accurate identification ability for low-resistivity clay caps,and the ob-tained uncertainty analysis results of the upper and lower interfaces of low-resistivity caps are also relatively reliable according to numerical tests.It was found that this method has a good ability to identify shallow low-resistivity caps and can provide an uncertainty evaluation of the clay cap interface position via field data tests.The 2D inversion re-sults of this survey line verify the reliability of the 1D inversion.[Conclusion]This method has relatively accurate imaging capabilities and uncertainty analysis capabilities for shallow geothermal clay caprocks and has strong appli-cation prospects in geothermal detection.
维普
万方数据