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Efficiency in the Energy Sector: Pumping the Value out of Data

In the ever-so-cyclical oil and gas industry, long gone are the good ol’ days of $100/barrel and partying like it’s 2008. At the most recent industry peak in June of 2008, featuring oil prices north of $150/barrel, energy companies directed 100% of their efforts into drilling and pumping more black gold from beneath the earth’s surface. Efficiency and optimization be damned! Such principles took a back seat to simply drill baby drill; they couldn’t get the stuff out of the ground fast enough.

Following a sharp rebound after the recession of 2008/2009, an onslaught of market forces such as extensive U.S. shale production, excessive oil production by OPEC, and slowing energy demand in developing nations, resulted in a tremendous oversupply of oil in the marketplace. The law of supply and demand is never wrong and with this excess supply and slowing demand, what followed was a drastic nose dive in oil prices to below $30/barrel, before stabilizing in the $40-$50/barrel range, where they remain today.

From Boom to Bust and Bust to Boom

Generally speaking, energy companies got fat and happy in the boom days and as prices came crashing down, so did payrolls, leaving a dark and dreary outlook across the industry. The ramifications of this unpredictable pattern are numerous, as hiring and retaining highly skilled and experienced professionals in the energy industry becomes more challenging throughout each cycle.

The energy industry now needs to place more of a focus on optimization and squeezing every ounce of efficiency from the assets they possess. Oil and gas companies need to learn how to do more with less and to control their rates of expansion and collapse through each cycle.

When speaking of maximizing production from assets in the energy industry, oil and gas reserves naturally come to mind first. However, one additional asset that energy companies possess in abundance is data. A typical oil well produces 1 to 2 Terabytes of data on a daily basis. However, studies by consulting firm McKinsey & Company have shown that less than 1% of data gathered by sensors on oil wells is used efficiently.

Goodbye Data Silos

In the context of a typical oil and gas project, there are three distinct types of data collected during the distinct phases of an oil exploration and production project:

  1. Seismic data processed by geoscientists during the exploration phase
  2. Drilling data processed by engineers during the drilling phase
  3. Well production data processed by petroleum engineers during the production phase

A common data management challenge for energy companies is how best to integrate this data from multiple, relatively closed-off systems, which are virtually inaccessible throughout the rest of the organization. Decision makers need access to a singular, holistic, and integrated view of data across the entire enterprise in order to retrieve actionable insight. Without such insight, it becomes challenging for oil and gas professionals to make informed decisions based on a total and complete assessment of a company’s data and energy assets.

A data integration architecture built on Denodo’s data virtualization platform is the ideal solution to this significant data management challenge. Data virtualization enables real-time access to data that resides in disparate systems, making it easier to cross examine and analyze data across the distinct phases of the oil and gas lifecycle more efficiently.

Data Virtualization: The Key to Efficiency

The process of finding, drilling, and pumping this valuable black gold from the earth’s subsurface presents the opportunity for generating astronomical revenues. However, this revenue potential comes at an extremely high cost, with profit margins for the oil and gas majors typically being in the 8% to 9% range. In this new era of $50/barrel oil, in which energy companies must adjust to significantly smaller revenues, reducing costs associated with a typical project is vital for achieving maximum profitability. The underutilized data assets that energy companies gather in abundance is the key to gaining efficiency across the exploration and production lifecycle.

By being able to seamlessly analyze data across all phases of the oil and gas lifecycle and eliminate the silos of data that have historically plagued the industry, decision makers will be well-equipped with actionable insights to maximize profitability throughout each ebb and flow of this cyclical industry.

Data virtualization is a solution that enables integrated field decisions to be made in a cost effective and efficient manner, which can positively impact the profitability of these projects. To learn more about how data virtualization improves efficiency for the energy sector, watch the Drillinginfo case study video.

Chris Walters

Chris Walters

Chris Walters is a Senior Data Solutions Consultant with Denodo Technologies. He has over 20 years of experience in the architecture, design, implementation, and integration of a wide variety of enterprise systems.
Chris Walters

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