THE STOCHASTIC INVERSION OF MAGNETICS AND RESISTIVITY DATA USING THE SIMULATED ANNEALING ALGORITHM

Simulated annealing is a stochastic combinatorial optimization technique, based on ideas from statistical mechanics, thermodynamics and multivariable probability theory. This paper presents the use of simulated annealing as a means of inversion for both linear magnetics and non-linear resistivity problems. The subsurface is viewed as being constructed of smaller elemental blocks which possess either uniform internal magnetization or conductivity, enabling larger structures to be modelled. Simulated annealing is employed to calculate the distribution of the particular physical property which causes a measured anomalous field curve. A general description of simulated annealing and its application is given, followed by specific descriptions of its application to the magnetics and resistivity cases. For the magnetics case the subsurface consists of 2D prismatic elements as the basis for the forward model. Synthetic model data is used to test the algorithm and an example of actual field data; a survey across an igneous dike is used to demonstrate the use of the method with real data. In the resistivity case, the finite-element method is used to generate the forward models. Synthetic vertical profiling data is used to test the application of the simulated annealing method to the resistivity case. Actual data from an archaeological survey is used to show again the use of the method with real data. Simulated annealing is shown to be capable of inverting both the linear and non-linear methods of magnetic surveying and resistivity surveying respectively.