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Muography is an imaging tool based on the attenuation of cosmic muons toobserve the density distribution of large objects, such as underground caves orfractured zones. Tomography based on muography measurements -- that is, threedimensional reconstruction of density distribution from two dimensional muonflux maps -- brings up special challenges. The detector field of view coveringmust be as balanced as possible, considering the muon flux drop at higherzenith angles and the detector placement possibilities. The inversion fromdirectional muon fluxes to 3D density map is usually underdetermined (morevoxels than measurements) which can be unstable due to partial coverage. Thiscan be solved by geologically relevant Bayesian constraints. The Bayesianprinciple results in parameter bias and artifacts. In this work, the linearized(density-length based) inversion is applied, the methodology is explained,formulating the constraints associated with inversion to ensure the stabilityof parameter fitting. After testing the procedure on synthetic examples, anactual high quality muography measurement data set from 7 positions is used asinput for the inversion. The result demonstrates the tomographic imaging of acomplex karstic crack zone and provides details on the complicated internalstructures. The existence of low density zones in the imaged space was verifiedby samples from core drills, which consist altered dolomite powder within theintact high density dolomite.

3D Muographic Inversion in the Exploration of Cavities and Low-density Fractured Zones