oa Application of statistical experiment design: Are our data sets "optimal"?

Reliable characterization of subsurface targets is the primary objective of every geophysical exploration technique. Regardless of the physical properties being mapped, or the variant of the geophysical method employed, quantifying the resolution of the Earth is a common theme of all field experiments. Inverse theory has proven essential for this task since, for a linear relationship between model parameters and data, it provides an exact mapping between data errors and model uncertainty. In this regard, the amount of information that can be extracted from measured data (i.e. the success or failure of a geophysical experiment) depends explicitly on data quality. Yet measurement accuracy and precision alone do not define data quality. Data independence and sufficiency are also important and illustrate the need for ensuring the collection of appropriate data through experimental design.