This template can be used as a starter file for presenting training materials in a group setting.SectionsRight-click on a slide to add sections. Sections can help to organize your slides or facilitate collaboration between multiple authors.NotesUse the Notes section for delivery notes or to provide additional details for the audience. View these notes in Presentation View during your presentation. Keep in mind the font size (important for accessibility, visibility, videotaping, and online production)Coordinated colors Pay particular attention to the graphs, charts, and text boxes.Consider that attendees will print in black and white or grayscale. Run a test print to make sure your colors work when printed in pure black and white and grayscale.Graphics, tables, and graphsKeep it simple: If possible, use consistent, non-distracting styles and colors.Label all graphs and tables.
Give a brief overview of the presentation. Describe the major focus of the presentation and why it is important.Introduce each of the major topics.To provide a road map for the audience, you can repeat this Overview slide throughout the presentation, highlighting the particular topic you will discuss next.
Big data in Oil and Gas Industry
BIG DATA IN OIL AND GAS –
DATA TO DOLLARS
• Type of Data
• Various Applications
• Big Data
• Big Data Management
• Big Data Governance
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
– Petabyte seismic data sets
– High performance computing
– Real-time SCADA and process
– Control systems
– Down hole sensors
– Energy Trading
– Risk analysis and trade simulation
Equipment maintenance: using data collected from pumps
and wells to adjust repair schedules and prevent or anticipate
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.
– Wide seismic data acquisition
– Real-time streaming data from drill-heads and equipment
– Structured, unstructured, semi structured (processed) data
– Increased speed to first oil
– Increased production
– Reduced risk
– Reduced cost
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 :
• Big data infrastructure and architecture
• Lifecycle process for big data – determine
requirements, capture/store, process, integrate/organize and
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
• Data quality and profiling
• Data Policies
• Data Security and Privacy