Semantic Web Technologies for Smart Oil Field Applications

Abstract

Abstract In model based oil field operations, engineers rely on simulations (and hence simulation models) to make important operational decisions on a daily basis. Three problems that are commonly encountered in such operations are: on-demand access to information, integrated view of information and knowledge management. The first two problems of on-demand access and information integration arise because a large number of, and different kinds of simulation models, each modeling a different facet of the oil-field, are used. An engineer is generally an expert in one aspect of oil-field modeling and trained to use a few tools; therefore, accessing information captured in models that do not lie in an engineer's area of expertise is not easy. Moreover, since these models are created by different processes and people, the same information is represented differently across models. A unified view of the models and their simulations is desirable for decision making, and thus the necessity for information integration. In the third problem- knowledge management problem, we address the situation in which an engineer performs many analyses before making a decision. A systematic way to capture the rationale (knowledge) behind the various decisions is needed for audit tracking purposes as well as for future references. We examine the application of semantic web technologies to address these three problems, present a prototype implementation which addresses them and provide an evaluation of the technology.