Big Data Adds Real Value for the Oil and Gas Industry

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01 Data Adds Real Value“Big Data” is one of today’s more intriguing buzz words. More specifically, many define the rather broad term as referring to data that comes in extremely high volume, velocity and variety. The O & G industry is one of the most dynamic, rapidly changing game in town. It is also data rich and proper use of timely data can make a real impact in adding value to an energy company. Indeed, the promise of effective use of big data is not only identifying areas of increased productivity, more effective real-time use of assets, it can also help mitigate future risk.
Big data encompasses many technologies and systems but it is this very complexity that is not only generating vast amounts of data, but also demand that useful, actionable information be rapidly filtered out. What good is information if it’s not actionable?

Some examples of how big data based information can make a big difference. Take a company that trades energy options for hedging price volatility. The ability to analyze and make rapid decisions from factors exogenous to price data such as weather patterns, crude inventories and productions costs can help make those minute-by-minute trading decisions. Likewise, big data can help a company optimize pricing strategies by rapidly processing such variables as competitor pricing strategies and trends, market demographics, transportation costs, customer sentiment, etc. No one would argue that this type of correlated information wouldn’t be a nice thing to have. By its very existence, big data is a mandate once the competition has it.
In a white paper produced by Microsoft last year, a list of specific O & G areas where big data can add significant value was presented.

Exploration and development
When exploring for new resources, big data and the use of advanced analytics combine to perform “identity traces.” This combination is invaluable for identifying previously overlooked, yet potentially productive seismic trace signatures.

Other areas where the analytical tools associated with big data can benefit O&G exploration include:
• Enhancing searches. Combine enterprise data, including financials and back-office operational detail, with real-time production data to deliver new insights to operating groups.
• Assessing acreage and generating new prospects. Create competitive intelligence using sources such as geospatial data, news feeds, or other syndicated information sources.

Drilling and completions
Using big data to anticipate likely interruptions to drilling is of obvious interest to providers. Being able to use large data volumes to identify conditions or anomalies that would impact drilling can save millions in labor and equipment costs alone.

Related areas where analytics can enhance geoscience include:
Leveraging scientific models. Incorporate geologic measurement and scientific models into everyday processes, such as shale development.
Improving engineering studies. Engage sophisticated subsurface models and conduct detailed
engineering studies on wells to identify commercial prospects earlier and with less risk.
Optimizing subsurface understanding. Use big data tools to understand the earth’s subsurface better and to deliver more affordable energy, safely and sustainably

Production and operations
Big data is of great interest to production and operation work. Being able to predict future performance based on historical results, or to identify sub-par production zones, can be used to shift assets to more productive areas. Oil recovery rates can be improved, as well, by integrating and analyzing seismic, drilling, and production data to provide self-service business intelligence to reservoir engineers. Better predictive maintenance also becomes possible:
Preventing down time. Understand how maintenance intervals are affected by variables such as pressure, temperature, volume, shock, and vibration to prevent failure and associated downtime.
• Optimizing field scheduling. Use this insight to predict equipment failures and enable teams to more effectively schedule equipment maintenance in the field.
Improving shop floor maintenance planning. Integrate well and tool maintenance data with supply chain information to optimize scheduling of shop floor maintenance

Enterprise security
In recent years, O&G companies have spent enormous sums on security, deploying a wide range of technologies designed to protect their intellectual property.4 So using big data to better manage internal network threats is a natural fit. Correlating network events with metrics over time, identifying patterns, and predicting cyber-terror threats is critical, particularly in light of recent events at oil refineries in the Middle East. With enhanced security and operational monitoring as their goals, O&G companies are beginning to apply analytics to identify anomalous information patterns on networks and to perform more effective intrusion detection.

They are also anticipating IT security breaches by using predictive analytics and bolstering security with data from video monitoring. Meanwhile, there is growing interest in deploying complex event processing (CEP) technology to monitor security concerns in the O&G industry in real time by:
• Combining data from multiple sources to infer events or patterns that indicate a current or
imminent threat.
• Making faster decisions, supported by faster delivery of decision support information, to identify possible threats.

Integrating big data into enterprise strategy
Microsoft helps customers with big data initiatives as part of its Enterprise Strategy Program (ESP), which focuses on helping companies realize value from their IT investments.

• Enterprise architects. Dedicated to the customer and charged with accelerating customers toward their business goals.
Network. Subject-matter experts from across all areas of Microsoft, including O&G industry expertise, product groups, research and development, internal IT resources, and Microsoft Research.
Value realization framework (VRF). This framework and methodology is designed to deliver on the value proposition of ESP . Using the VRF, Microsoft has worked on a number of specific challenges that are common to many customers and, as a result, developed the Big Data VRF Accelerator.
IP library. A collection of exclusive intellectual property that includes comprehensive guidance, reference architectures, and implementation information, plus real examples from the field of Microsoft engagements.

In closing, the focus on big data has been shifting toward the rapid, reliable, validated information harvested by big data. In addition, the new focus has also included the presentation of the information that makes it easy to understand and make confident decisions.

 

Additional Reading

About Using Big Data: The Three Core Dependencies You Can’t Live Without

Combining Operations and IT – Mixing Oil and Water With Operational Excellence For Success

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