Model-based fluid factor for controlled source electromagnetic data

What is it about?

We investigate the possiblity to detect an subsurface anomaly in EM data, when there are large uncertainties in the overburden. We derive a methodology which is easy to implement, provide reliable results and have numerous possibilities for extension. We also show how this approach can be used to evaluate the value of an EM survey prior to collecting the data.

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Why is it important?

We make a highly complex problem computational feasible, by utilizing standard statistical techniques in classification and dimension reduction.

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