Constrained inversion of seismic refraction data using the controlled random search

Abstract

When designing models for 2-D seismic refraction inversion, it is desirable to frame the models as polygonal units with well‐defined geophysical characteristics. Such inversion is strongly nonlinear. Random search methods for nonlinear inversion, such as the genetic algorithm and simulated annealing, have received much attention in recent years. Such methods are well suited when the model space is large and contains multiple global minima to the misfit function. Constraints are necessary in the automatic construction of polygonal models. Controlled random search (CRS) is a member of this class of methods that has not been widely exploited. CRS is an iterative process based on the polytope algorithm, which offers a means by which linear constraints may be used. The CRS samples large model spaces, resists local minima, and can find multiple global minima. A new program has been developed for inversion of 2-D seismic refraction data which incorporates geologic compatibility constraints for polygon‐based models. A theoretical example and practical applications of this technique to environmental investigations illustrate its characteristics.