Calibration and filtering strategies for frequency domain electromagnetic data

echniques for processing frequency-domain electromagnetic (FDEM) data that address systematic instrument errors and random noise are presented, improving the ability to invert these data for meaningful earth models that can be quantitatively interpreted. A least-squares calibration method, originally developed for airborne electromagnetic datasets, is implemented for a ground-based survey in order to address systematic instrument errors, and new insights are provided into the importance of calibration for preserving spectral relationships within the data that lead to more reliable inversions. An alternative filtering strategy based on principal component analysis, which takes advantage of the strong correlation observed in FDEM data, is introduced to help address random noise in the data without imposing somewhat arbitrary spatial smoothing.


Read More: http://library.seg.org/doi/abs/10.4133/1.3445431