Optimal design of focused experiments and surveys

Details Optimal design of focused experiments and surveys Optimal design of focused experiments and surveys

Oct 1999

adsabs.harvard.edu/cgi-bin/nph-data_query?bibcode=1999geoji.139..205c&link_type=abstract

Geophysical Journal International, Volume 139, Issue 1, pp. 205-215.

Astronomy and Astrophysics

Astronomy

17

Cross Borehole, Design, Focus Information, Optimal Experiment, Survey, Tomography

Scientific paper

Experiments and surveys are often performed to obtain data that constrain some previously underconstrained model. Often, constraints are most desired in a particular subspace of model space. Experiment design optimization requires that the quality of any particular design can be both quantified and then maximized. This study shows how the quality can be defined such that it depends on the amount of information that is focused in the particular subspace of interest. In addition, algorithms are presented which allow one particular focused quality measure (from the class of focused measures) to be evaluated efficiently. A subclass of focused quality measures is also related to the standard variance and resolution measures from linearized inverse theory. The theory presented here requires that the relationship between model parameters and data can be linearized around a reference model without significant loss of information. Physical and financial constraints define the space of possible experiment designs. Cross-well tomographic examples are presented, plus a strategy for survey design to maximize information about linear combinations of parameters such as bulk modulus, κ =λ+ 2μ/3.

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