Constrained inversion of seismic refraction data using the controlled random search

When designing models for 2-D seismic refraction inversion, it is desirable to frame the models as polygonal units with well-defined geophysical chara cteristics. 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 suite d 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 const raints may be used. The CRS samples large model spaces, resists local minim a, and can find multiple global minima. A new program has been developed fo r inversion of 2-D seismic refraction data which incorporates geologic comp atibility constraints for polygon-based models. A theoretical example and p ractical applications of this technique to environmental investigations ill ustrate its characteristics.