Overview

Gravity and magnetic anomaly data are commonly expressed in standard formats for electronic analysis and archiving in digital data bases. A voluminous literature full of application-specialized jargon describes numerous analytical procedures for processing and interpreting anomaly data. However, when considered from the electronic computing perspective, these procedures simplify into the core problem of manipulating a digital forward model of the data to achieve the data analysis objectives. The forward model consists of a set of coefficients specified by the investigator and a set of unknown coefficients that must be determined by inversion from the input data set and the specified forward model coefficients. The inversion typically establishes a least-squares solution, as well as errors on the estimated coefficients and predictions of the solution in terms of the data and specified model coefficients. The inversion solution is never unique because of the errors in the data and specified model coefficients, the truncated calculation errors, and the source ambiguity of potential fields. Thus, a sensitivity analysis is commonly required to establish an “optimal” set or range of solutions that conforms to the error constraints. Sensitivity analysis assesses solution performance in achieving data analysis objectives including the determination of the range of geologically reasonable parameters that satisfy the observed data.