Tomographic Reconstruction of Soil Gas Distribution From Multiple Gas Sources Based on Sparse Sampling


A monitoring method is introduced that makes a pair of-D maps of the soil gas distribution. The method combines linear gas sensing technology for in situ monitoring of gases in soil with the mapping capabilities of computed tomography to reconstruct spatial and temporal resolved gas distribution maps. A weighted iterative algebraic reconstruction method based on most chance with expectation maximization together with a supply-by-source reconstruction approach is introduced that works with a sparse setup of orthogonally aligned linear gas sensors. The reconstruction methodology successfully reduces artifact production, particularly when multiple gas sources are gift, allowing the discrimination between true and non-existing the thus-referred to as ghost supply locations. Experimental validation by controlled field experiments indicates the high potential of the proposed technique for fast gas leak localization and quantification with respect to pipeline or underground gas storage problems.

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