As competitive and financial pressures rise, the energy industry has come to the realization that big data and new analytics tools and techniques can help cut down costs across operations. The industry is filled with data that stream in from an array of sources including exploration, production, transportation and distribution.
Energy companies are struggling to organize this critical data, and they are desperately searching for data science professionals who can analyze information and glean insights from volatile fuel prices, carbon tax implications, greater competition, supply chain risk and growing regulatory requirements.
According to a 2013 study from Tata Consultancy Services companies in the utilities and energy/resources industries have the highest expectations for generating returns on their big data investments. Analyzed correctly, big data has the potential to help the industry discover new energy sources, save money on drilling and exploration, increase efficiency and productivity and gauge consumption patterns.
APPLICATIONS OF DATA IN ENERGY
The Digital Oil Field
Big data can also help energy companies predict and stop accidents before they happen. The advent of the “digital oil field” helps produce cost-effective energy while addressing safety and environmental concerns. Why are digital oil fields so effective? Every single piece of equipment is relaying a constant stream of data back to headquarters. Smart rigs inform operators so they can maintain production flows. Sensors alert workers about wells in need of repairs. Compressors warn staff when they are in danger of overloading.
These sensors provide huge volumes of data that support and inform operational decision-making. By combining sensor information such as pressure, temperature, volume, shock and vibration data with real–time data analytics and high-speed international communications, companies can monitor every step of the production process and prevent costly problems before they occur. This cannot be done successfully, however, without the analytical wherewithal of trained data scientists who can process information quickly and effectively.
The use of 2D, 3D and 4D seismic monitoring equipment has always been very useful in the exploration and discovery of new oil and gas deposits. Once the discovery has been made, companies need to assess the likelihood that it will be profitable. Multiple parallel processing platforms are now used to process the host of data variables that can affect the viability of drilling operations, including soil quality, geologic anomalies, production costs, weather-related factors and transport considerations.
By being able to quickly decipher seismic data sets, companies can reduce their cost and risk and move faster into new markets. A recent Accenture report titled, “The Looming Global Analytics Talent Mismatch in Oil and Gas” states that for oil companies moving into unconventional plays like shale gas, analytics can be used to model essential geophysical features and production data of each well.
DATA SCIENTISTS IN DEMAND
This same report also suggests that oil and gas companies will struggle to find the thousands more analytics scientists, experts and specialists they will need to manage their projects and operations effectively. As energy companies focus more sharply on efficiency, reliability and competitive positioning, they will need legions of analytics talent – people with the ability to use statistics, quantitative analysis and information – modeling techniques to make business decisions.
Based on the current and foreseeable future state of the energy sector, data scientists will continue to be in high demand. By obtaining a degree in data science, you will possess skill sets that are critical in an industry where companies are facing unique talent challenges in different markets and where talent supplies will not keep pace with new job growth. Click here to learn more about data science degree offerings that will set you on the path to employment in the energy field.