Translating tomographic ambiguity into the probabilistic inference of hydrologic and engineering target parameters

摘要: ABSTRACTGeophysical tomography allows for spatially continuous imaging of physical parameters. In many hydrological or engineering exploration tasks, other parameters than those imaged by geophysical are higher interest, but they cannot be measured continuously in space. We have developed a methodology linking multiple tomograms different with sparsely target parameter striving to achieve probabilistic, predictions the distribution. Building on fully nonlinear tomographic model reconstruction searching solution space globally, we translate ambiguity into prediction parameter. doing so, structurally integrate physically achieved individual inversion transforming them fuzzy sets. postinversion analysis, systems linear equations then set up and solved sets sparse information about t...