Physics – Geophysics
Scientific paper
Oct 2011
adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=2011geoji.187..214p&link_type=abstract
Geophysical Journal International, Volume 187, Issue 1, pp. 214-224.
Physics
Geophysics
Image Processing, Inverse Theory, Ground Penetrating Radar, Hydrogeophysics
Scientific paper
Difference geophysical tomography (e.g. radar, resistivity and seismic) is used increasingly for imaging fluid flow and mass transport associated with natural and engineered hydrologic phenomena, including tracer experiments, in situ remediation and aquifer storage and recovery. Tomographic data are collected over time, inverted and differenced against a background image to produce 'snapshots' revealing changes to the system; these snapshots readily provide qualitative information on the location and morphology of plumes of injected tracer, remedial amendment or stored water. In principle, geometric moments (i.e. total mass, centres of mass, spread, etc.) calculated from difference tomograms can provide further quantitative insight into the rates of advection, dispersion and mass transfer; however, recent work has shown that moments calculated from tomograms are commonly biased, as they are strongly affected by the subjective choice of regularization criteria. Conventional approaches to regularization (Tikhonov) and parametrization (image pixels) result in tomograms which are subject to artefacts such as smearing or pixel estimates taking on the sign opposite to that expected for the plume under study. Here, we demonstrate a novel parametrization for imaging plumes associated with hydrologic phenomena. Capitalizing on the mathematical analogy between moment-based descriptors of plumes and the moment-based parameters of probability distributions, we design an inverse problem that (1) is overdetermined and computationally efficient because the image is described by only a few parameters, (2) produces tomograms consistent with expected plume behaviour (e.g. changes of one sign relative to the background image), (3) yields parameter estimates that are readily interpreted for plume morphology and offer direct insight into hydrologic processes and (4) requires comparatively few data to achieve reasonable model estimates. We demonstrate the approach in a series of numerical examples based on straight-ray difference-attenuation radar monitoring of the transport of an ionic tracer, and show that the methodology outlined here is particularly effective when limited data are available.
Day-Lewis Frederick D.
Pidlisecky Adam
Singha Kamini
No associations
LandOfFree
A distribution-based parametrization for improved tomographic imaging of solute plumes does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.
If you have personal experience with A distribution-based parametrization for improved tomographic imaging of solute plumes, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and A distribution-based parametrization for improved tomographic imaging of solute plumes will most certainly appreciate the feedback.
Profile ID: LFWR-SCP-O-1489769