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Big data in Oil and Gas Industry


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How Big Data can play a BIG role in Oil and Gas industry

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Big data in Oil and Gas Industry

  2. 2. Agenda • Type of Data • Various Applications • Big Data • Big Data Management • Big Data Governance
  3. 3. Type of Data • The data is large, complex, and fast moving that it’s difficult to handle using everyday data management tools. – Huge volume of Structured data – Exploration – Petabyte seismic data sets – High performance computing – Real-time SCADA and process – Control systems – Down hole sensors – Energy Trading – Risk analysis and trade simulation
  4. 4. Various Applications  Equipment maintenance: using data collected from pumps and wells to adjust repair schedules and prevent or anticipate failure.  Production optimization: using powerful modeling capabilities to anticipate costs and production volumes.  Price optimization: using scalable compute technologies to determine optimum commodity pricing.  Safety and compliance: using weather or workforce scheduling data to avoid creating dangerous conditions for workers and mitigating environmental risks.
  5. 5. Big Data • Volume – Wide seismic data acquisition • Velocity – Real-time streaming data from drill-heads and equipment sensors • Variety – Structured, unstructured, semi structured (processed) data • Value – Increased speed to first oil – Increased production – Reduced risk – Reduced cost
  6. 6. Big Data Management With proper Big data management, it can gain insight from real- time data and content and make organizations more agile and responsive to market and customer needs. Key considerations are : • Technology • Big data infrastructure and architecture • Lifecycle process for big data – determine requirements, capture/store, process, integrate/organize and consume
  7. 7. Big Data Governance IT helps organization capture its critical big data by starting in the right path with a big data governance strategy to resolve potential challenges in business processes. • Business stakeholders • Business requirements • Various Data sources • Metadata management • Technology • Data quality and profiling • Data Policies • Data Security and Privacy
  8. 8. THANK YOU
  9. 9. QUESTIONS?