Fast transdimensional Bayesian transient electromagnetic imaging for urban underground space detection

Abstract The transient electromagnetic method (TEM) is one of the most effective geophysical methods for detecting urban underground space. The underground resistivity distribution obtained by this imaging technique is important for engineers in urban construction and planning. The conventional transdimensional Bayesian (Trans-Bayes) imaging method gives the credible interval of the data model and quantifies the uncertainty in the imaging results. However, due to the large number of calculations needed and the slow speed of TEM forward modelling, the engineering practicality of Trans-Bayes method is poor. To solve this problem, we propose a fast Trans-Bayes imaging approach based on the Bayesian information criterion (BIC) and the adaptive Metropolis (AM) algorithm. Our simulation and field experiments show that this BIC-AM approach can greatly improve Trans-Bayes imaging efficiency while ensuring imaging accuracy. This method may provide fast uncertainty estimates for urban TEM data.