| Summary: | The success of petroleum exploration business depends on appropriate design and implementation of seismic exploration programs. Volume of seismic data instances (deduced for structural interpretation) is used for modeling multidimensional data structures in a warehouse environment.Several business rules (constraints) are applied to the design and development of a data warehouse. Seismic-time horizons, welldata, reservoir properties and petroleum production as data dimensions or classes and their associated attributes, have been used for integrating and modeling their data instances with numerous hierarchies. Ontology addresses issues of semantics and contexts (naming conventions) involved during design of business rules and building relationships among severalhierarchies. Business rules inform the data integration and data mining process, especially when heterogeneous data structures are denormalized for fine-grained data structuring and facilitatethe association rule mining process. Several data views have been presented for analyzing the effectiveness and deliverability of warehouse-modeled information. Design of business rulescombined with fine-grained ontology structuring appears to have a definitive impact on data mining of seismic data instances, enhancing seismic data knowledge and improving geological interpretation. Petroleum ontology proves to be an effective knowledge mapping tool, which can revolutionize thepetroleum exploration industries.
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