Limited knowledge about the spatial distribution of aquifer properties typically constrains our ability to predict subsurface flow and transport. Here we investigate the value of using high resolution full‐waveform inversion of cross‐borehole ground penetrating radar (GPR) data for aquifer characterization. By stitching together GPR tomograms from multiple adjacent crosshole planes, we are able to image, with a decimeter scale resolution, the dielectric permittivity and electrical conductivity of an alluvial aquifer along cross sections of 50 m length and 10 m depth. A logistic regression model is employed to predict the spatial distribution of lithological facies on the basis of the GPR results. Vertical profiles of porosity and hydraulic conductivity from direct‐push, flowmeter and grain size data suggest that the GPR predicted facies classification is meaningful with regard to porosity and hydraulic conductivity, even though the distributions of individual facies show some overlap and the absolute hydraulic conductivities from the different methods (direct‐push, flowmeter, grain size) differ up to approximately one order of magnitude. Comparison of the GPR predicted facies architecture with tracer test data suggests that the plume splitting observed in a tracer experiment was caused by a hydraulically low‐conductive sand layer with a thickness of only a few decimeters. Because this sand layer is identified by GPR full‐waveform inversion but not by conventional GPR ray‐based inversion we conclude that the improvement in spatial resolution due to full‐waveform inversion is crucial to detect small‐scale aquifer structures that are highly relevant for solute transport.

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Suitable training images (TI) for multiple-point statistics (MPS) are difficult to identify in real-case three-dimensional applications, posing challenges for modelers trying to develop realistic subsurface models. This study demonstrates that two-dimensional geophysical images, when employed as training and conditioning data, can provide sufficient information for threedimensional MPS simulations. The advantage of such data-driven approach is that it does not rely on any external (possibly inappropriate) TI. The disadvantage is that three-dimensional MPS simulations must be carried out based N. Gueting Agrosphere (IBG-3),

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Due to the recent system developments for the electromagnetic characterization of the subsurface, fast and easy acquisition is made feasible due to the fast measurement speed, easy coupling with GPS systems, and the availability of multi-channel electromagnetic induction (EMI) and ground penetrating radar (GPR) systems. Moreover, the increasing computer power enables the use of accurate forward modeling programs in advanced inversion algorithms where no approximations are used and the full information content of the measured data can be exploited. Here, recent developments of large-scale quantitative EMI inversion and full-waveform GPR inversion are discussed that yield higher resolution of quantitative medium properties compared to conventional approaches. In both cases a detailed forward model is used in the inversion procedure that is based on Maxwell's equations. The multi-channel EMI data that have different sensing depths for the different source-receiver offset are calibrated using a short electrical resistivity tomography (ERT) calibration line which makes it possible to invert for electrical conductivity changes with depth over large areas. The crosshole GPR full-waveform inversion yields significant higher resolution of the permittivity and conductivity images compared to ray-based inversion results. KEY WORDS: ground penetrating radar, electromagnetic induction, full-waveform inversion. INTRODUCTIONThe electromagnetic tools, EMI and GPR, can be used for a wide range of applications to non-invasively image the subsurface. Due to the fast data acquisition, where the measured data can be directly linked with high resolution GPS systems, it is becoming more and more feasible to map GPR and EMI over large areas. The use of multi-channel EMI and GPR makes it possible to acquire simultaneously EMI and GPR data for different source-receiver offsets that enable an improved subsurface characterization. Ray-based or approximate techniques are often used where only part of the data is exploited. Improved subsurface characterization can be obtained by including advanced modeling tools that are able to calculate the electromagnetic wave propagation with high accuracy using Maxwell's equations. In the following, we will describe recent advancements in the high-resolution imaging of EMI and GPR data.