Big dollars for big oil with big data Analytics saves billions in upstream exploration and production
Deloitte reported in a recent study that increased data capture and analysis can likely save billions of dollars for the energy industry. Reuters also found that Oil and Gas companies are "envisioning billions of dollars in savings" through the use of analytics and the IoT.
Oil and gas companies are inundated with data but starving for insights and smart actions on business operations. As the quest for hydrocarbons and alternative energy sources extends into deeper and harsher environments, operators, service companies, and asset owners need to rely on Spotfire® Data Science, Spotfire® Visual Analytics, and the Internet of Things (IoT) to ensure their employees are safer, their fields are more productive, and their capital assets are operating at peak efficiency."
3 ways to improve your oil and gas operations
Let's break down this opportunity into the three major ways you can improve your oil and gas operations with analytics:
- Visual analytics:
Figure 2: Sensors on submersible pumps are monitored real-time in distant control centers
The collection of IoT and sensor data and using data science to analyze it — including machine learning and geoanalytics — enables optimized operations. The data from IoT sensors is run through software representations of physical assets, processes, and systems (e.g., “digital twins”). These digital twins are used to predict outcomes so intervention becomes possible.
Use cases in energy companies: IoT, sensor data, and machine learning can be used for production surveillance, condition-based maintenance, environmental health and safety, and drilling optimization. These implementations enhance production by keeping systems running smoothly and prevent failures to extend equipment life; directly impacting revenue and top-line growth while attending to safety and environmental concerns.
- Real-time data:
Figure 3: Above, the process for applying Data Science model into Streaming is shown. Below, a machine learning model for drill bit wear is injected in to Streaming DataOps workflow.
In today’s challenging market, real-time data streaming platforms provide efficient, real-time, customized tools that allow you to reduce the amount of time it takes to drill the well – without compromising the wellbore quality or well safety.
Use Case: A real-time data streaming platform creates a dynamic, real-time picture of the wellbore and key drilling variables while the drilling is in motion so operators can direct the drill towards a more profitable outcome, leading to less wasted time, fewer broken wellbores, and a safer drilling environment.
Taking action when and where it matters most is incredibly important for the energy industry. That means reducing data bottlenecks and implementing machine learning models across your organization, including sensors, processes, and equipment. With Spotfire® Visual Analytics, Spotfire® Data Science, and Spotfire® Streaming, you can analyze all of your IoT data to address process and equipment surveillance challenges.
That goes for every company today, not just those in the oil and gas industry. The digital innovation possibilities we’re seeing for oil and gas can be applied to every industry. And it’s no longer an option to ignore the need to transform. From healthcare to manufacturing to aerospace and more, digital leaders must capture data to fuel their business and make faster, smarter decisions based on that data.
We’ll help you become a digital leader at TAF 2019
At the 18th annual TAF, you’ll learn how to spot and act on the operational data coming into your business every day.
At the forum, you’ll learn many ways to get ahead of the competition using analytics and the IoT from customer success stories, hands-on training, access to experts, and detailed demos with real-life applications.