S.L. Nimmagadda (Kuwait) and H. Dreher (Australia)
Petroleum exploration, heterogeneous data, schemas, data integration, warehouse modeling, data mining and knowledge mapping
Success of information flow depends on intelligent data storage and its management in a multi-disciplinary environment. Multi-dimensional data entities, data types and ambiguous semantics, often pose uncertainty and inconsistency in data retrieval from volumes of petroleum data sources. In our approach, conceptual schemas and sub-schemas have been described based on various operational functions of the petroleum industry. These schemas are integrated, to ensure their consistency and validity, so that the information retrieved from an integrated metadata (in the form of a data warehouse) structure derives its authenticity from its implementation. The data integration process validating the petroleum metadata has been demonstrated for one of the Gulf offshore basins for an effective knowledge mapping and interpreting it successfully for the derivation of useful geological knowledge. Warehoused data are used for mining data patterns, trends and correlations among knowledge-base data attributes that led to interpretation of interesting geological features. These technologies appear to be more amenable for exploration of more petroleum resources in the mature gulf basins.
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