Understanding and characterizing subsurface structures is challenging, especially when the objective is to investigate sites for nuclear waste disposal. This paper presents a multi‐geophysical approach for subsurface experimental investigations in which seismic data are used to improve electrical resistivity tomography quality. Different synthetic models ranging from simple to complex were created to quantitatively demonstrate the improvements enabled by the use of this strategy. Moreover, the scheme was tested at Beishan, a candidate site for the disposal of high‐level radioactive waste in northwestern China. The results show that the combination of geophysical data sources improves the interpretation of the subsurface over a single source. The root‐mean‐square level and runtime were found to rapidly decrease when using the proposed scheme.

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SUMMARYThis study consists of detailed analysis of 17 high-definition microresistivity images from a tight gas reservoir in western China. Most of the images are acquired in OBM with very adverse conditions for the imager tool resulting in limited image quality. Through extensive comparison between core and images and between OBM images and WBM images, we have improved and evaluated the accuracy of natural fracture interpretation from OBM images. In particular, one well is drilled and logged in OBM and then logged again in WBM over the same interval to compare the fracture interpretation results. The comparison shows that even in very harsh logging conditions, most of the fractures interpreted from WBM images can also be identified on OBM images. Interestingly, open fractures on OBM images have a conductive colour likely because of the magnetite used as weighting material in the mud. Thus, zones of effective fractures can be identified. This possibility is validated by mud loss data.