Spatial reasoning and integration techniques for geophysical and geological exploration dat

An integrated approach is one of the most distinguishing characteristics of exploration for non-renewable resources. The integrated exploration using multiple spatial data sets is mathematically represented and modeled in this thesis. Fuzzy set theory provides an adequate tool to represent imprecise and incomplete geophysical and geological information and to integrate the information for a specific exploration target. Dempster-Shafer evidential belief function provides a more natural basis for representation of geophysical and geological information than the traditional probability approach. Integrated results using belief function consequently provide a more realistic description about a proposition towards the exploration target. The fuzzy set approach and the Dempster-Shafer approach can be used both in areas where there are actual known exploration target occurrences and also in areas where there are as yet no reported target occurrences. An object-oriented knowledge representation structure and corresponding inference mechanisms based on belief function theory are developed for a knowledge-based approach of integrating geophysical and geological data. An object-oriented and map-based prototype expert system is implemented to test this object-oriented knowledge representation structure and its corresponding inference mechanisms for base metal exploration application. The resulting system appears very effective in handling complex integrated exploration problems. The information representation and integration techniques using fuzzy set and belief function approaches, and the prototype expert system are tested with real mineral exploration data for the Farley Lake and Snow Lake areas, Manitoba, Canada. The test results demonstrate considerably improved accuracy and effectiveness in information representation techniques using the fuzzy set and belief function approaches relative to the conventional intuitive approach. The knowledge representation structure and inference mechanisms implemented in the expert system also performed well and provide a robust theoretical basis for developing a comprehensive expert system for non-renewable resource exploration.