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

1. BIG DATA IN OIL AND GAS –
DATA TO DOLLARS
Suvradeep Rudra

2. Agenda
• Type of Data
• Various Applications
• Big Data
• Big Data Management
• Big Data Governance

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. 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. 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. 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. 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. THANK YOU

9. QUESTIONS?