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The structural approach to joint inversion, entailing common boundaries or gradients, offers a flexible way to invert diverse types of surface-based and/or crosshole geophysical data. The cross-gradients function has been introduced as a means to construct models in which spatial changes in two models are parallel or anti-parallel. Inversion methods that use such structural constraints also provide estimates of non-linear and non-unique field-scale relationships between model parameters. Here, we invert jointly crosshole radar and seismic traveltimes for structurally similar models using an iterative non-linear traveltime tomography algorithm. Application of the inversion scheme to synthetic data demonstrates that it better resolves lithological boundaries than the individual inversions. Tests of the scheme on observed radar and seismic data acquired within a shallow aquifer illustrate that the resultant models have improved correlations with flowmeter data than with models based on individual inversions. The highest correlation with the flowmeter data is obtained when the joint inversion is combined with a stochastic regularization operator, where the vertical integral scale is estimated from the flowmeter data. Point-spread functions shows that the most significant resolution improvements of the joint inversion is in the horizontal direction

Joint inversion of crosshole radar and seismic traveltimes acquired at the South Oyster Bacterial Transport Site