Digital Solutions
(Source: Teradata)
Realizing the value of data in oil and gas
With integrated analytics operationalized and simplified at scale, energy companies can adopt a true data-driven approach.
Niall O’Doherty, Teradata

echnology often drives industry disruption and is a foundational element to support and react to any changes in the business. But for industries experiencing the ripple effects of disruption brought on by the COVID-19 pandemic this year, adopting advanced technologies and a digital-first strategy have become critical for many companies to merely survive.

While energy organizations were among the first to adopt digitization, Deloitte emphasized in a recent report that many are now taking the necessary next steps to embrace the power of analytics, collect and integrate troves of HSE and security (HSSE), operations, supply chain and finance data, as they recognize the opportunity to make their “$3.4 trillion asset base smarter and more efficient.”

To understand how data and analytics can best be delivered at scale for organizations as large as E&P operators, this article will note three key pillars that play crucial roles in helping oil and gas organizations realize the full value of data and turn insights into action—data integration, speed and simplification.

Implementing the right technology within an organization to provide a real-time, holistic view of their data helps companies make more fact-based decisions that ultimately impact the bottom line to reduce costs, increase workforce productivity and safety, and improve output.

However, barriers such as siloed and unstructured data and an evolving regulatory climate have slowed how companies move forward on leveraging data to guide business operations, meaning it can take months or even years to act on insights. But addressing these issues does not require a complete overhaul of the technology already in place.

Companies can integrate the collective data from sources including field assets, rigs, wells, plants, sensors and more, for increased visibility to ensure it is being used more effectively and helping to avoid silo-induced blind spots. Businesses can improve productivity, resiliency and agility through the whole supply chain as well by leveraging data analytics to combine operational data, inventory data and logistic information.

Sharing data analytics across the organization also goes beyond pure optimization to empower all employees, including those in the field, to make data-informed decisions. For example, someone stationed on an oil rig can determine if the equipment is working correctly, and employees downstream can ensure gasoline is blended correctly—all in a matter of hours rather than months.

Decentralized decision-making gives employees—from supply chain operators to the finance department—the necessary information to see changes or deviations in near-real time and address them immediately, compared to waiting for communications from the top down. By integrating data at a detailed level, it becomes available to whoever needs it, when they need it, to turn insights into action faster.

Energy companies don’t have months to spare translating data insights, running the risk that information becomes stale and useless before it can be acted upon. With the right data platform, however, companies can collect and integrate various types of data into one holistic view, for example, analyzing HSSE data faster and applying automated rules for proactive identification of possible issues. A scalable platform capable of bringing together, analyzing and sharing data in a reliable way builds credibility in the data and delivers high-value outcomes. It allows companies to better predict potential issues, make more informed decisions and move toward automation.

Safety and health have long been a priority within the energy industry. Companies that have progressed in their digital evolution are using safety analytics and machine learning to identify high-risk environments quickly and offer insights into both human and machine behaviors that may result in an accident. Capturing various data types—Internet of Things (IoT) sensor, voice, text and multichannel data—from end-to-end processes allows the creation of dynamic safety intelligence.

Speeding up data insights gives all employees the on-the-ground tools and insights they need to do their jobs in a more timely and effective manner. This allows them to be more successful in creating a safer and more productive work environment and removing themselves from potentially hazardous situations.

However, creating this type of environment requires the ability to access, share and analyze extensive and complex datasets achievable with a scalable, integrated and simplified analytics platform.

Making data intelligence pervasive within an organization is necessary to equip it with the tools and insights to compete amid the unprecedented situation caused by COVID-19 and the accelerating need for digital innovation to drive business value. Enabling highly complex processes with a simplified data and analytics approach, to minimize complications, provides decision-makers with the right data at the right time with the right governance.

Cross-industry initiatives, like the Open Subsurface Data Universe, are helping to further simplify data implementation by creating a standardized data platform to reduce silos and centralize data within organizations. Companies that break down previously siloed datasets and pivot to integrate data pervasively throughout the organization can realize new synergies, visibility and business value. Two other examples of data simplification include optimizing the entire supply chain with rich, cross-functional cost forensics or moving from a spreadsheet-driven culture to a simplified, multi-source data-driven integrated dashboard for running a refinery.

Having a strong data foundation in place will ensure organizations have the data they need to make an informed transition.
With integrated analytics operationalized and simplified at scale, energy companies can adopt a true data-driven approach to their business to achieve new levels of efficiency, safety and asset optimization as well as remain competitive in a continuously changing landscape.
Rethinking data
By combining integration, speed and simplification, oil and gas companies can create a truly data-first approach to make more informed decisions faster and enable improvements across the end-to-end process—from drilling and production to finance and supply chain. Even as the energy industry turns its eyes toward future initiatives, such as the EU goal to become carbon-neutral by 2050 or American oil companies adapting to lower oil prices, having a strong data foundation in place will ensure organizations have the data they need to make an informed transition.

Many energy companies have already begun to embrace the power of analytics to realize the value of their data; therefore, they don’t require revolutionary changes to how they’re using it. Evolutionary changes, however, can simplify their analytics to prudently advance toward immediate and enhanced efficiency, sustainability, safety and productivity—delivering all of the above at speed to lay a strong foundation for recovery and growth.