Cloud and Ontology Based Knowledge Collaboration - a Digital Oil Field Initiative

Continuous increase in oil pricing is not only causing difficulties to consumer but the imbalance in demand and supply is impacting the producer and refineries also. Consumer may adjust the demand dynamically as per the price fluctuation but oil major cannot change the production so dynamically. The recommended solution is the latest technology which could optimize the production, meeting the increasing but fluctuating demand at reasonable production price. Continuous increasing in oil prices and demand for crude, the hydrocarbon industry is serious in reaching to its full potential for value creation unless it is not developing the technological innovation. The emerging solution is Cloud based intelligent energy solution. Cloud based smart oil filed engineering is one of the initiative where the oil fields are mathematically modelled as a process industry with unpredictable feed (production). Real time engineering visualization and geospatial scientific computing integration on mobile system is major challenge. Cloud technology has opened an unrestricted universe for Hydrocarbon industry. Cloud Computing led Digital Oil Field is business-centric engineering solutions which has empowered the oil majors to optimize the resources, decreased infrastructure cost, ubiquitous access to business-centric integrated solution, easy engineering visualization and flexible business modelling, ultimately resulting reduction in the production cost of oil & gas. The cloud based solution is hired on demand service provides robust security, business, modelling, engineering solution, real time visualization, market analytics and management controls on smart mobile device. This paper talks about the case study of a cloud based application (name EICEbox) helping oil companies solving the complex engineering problem and providing the knowledge collaboration platform to oil and gas companies. Keywords— Cloud Computing, Cloud Ontology, Digital Oil field, Engineering Knowledge Management ---------------------------------------------------------------------***--------------------------------------------------------------------