How the energy industry is using the cloud

From financial services organizations building more reliable and resilient services and healthcare organizations accelerating projects in areas like population health, personalized medicine and clinical research to retail customers scaling how they use their data, our customers are doing extraordinary things in the cloud. And this includes the energy industry as well.

Energy companies—like oil and gas, utilities, and renewable energy—have a long history of generating and gathering data, but many use only a small fraction of what they acquire. The volume and variety of data are wide, ranging from subsurface seismic information imaging the earth to millions of sensors collecting billions of updates each day. But as that data grows, so does their need for tools to help them find the right insights in all that information.

As a result, cloud technologies have become increasingly important to energy companies that want to grow and evolve. The cloud can help them get on-demand access to more data than ever before, and make huge leaps in computational power to produce actionable insights that can have a real impact. The technologies of cloud mean that energy companies can make better, faster and safer decisions. With high-quality data analytics, these companies can do more precise work that’s mindful of environmental needs and worker safety.

One example of a business doing exactly that is U.S.-based oil and gas company Anadarko, one of the largest in its market. Today, Anadarko announced through its Advanced Analytics and Emerging Technologies Team (AAET) that it is migrating its exploration and production models, applications and platforms to GCP as part of its broad digital strategy.

Anadarko developers are using GCP to build apps that monitor drilling and completions operations in real time, allowing them to be more precise with their efforts and making it faster for them to learn what’s happening with ongoing operations. Since early 2018 they’ve been streaming all rig and completion crews data into a GCP tenant. They’re now deploying process analytics models and allowing real-time data analysis from onshore and offshore facilities, which lets them predict—and ideally avoid—unplanned shutdowns.

The technology of energy
There are a number of cloud technology tools that we’re seeing energy companies use to collect and get more out of their data. Anadarko is using a number of cloud technologies as part of their efforts. For example, they’re applying deep learning methods to build high-density seismic interpretations for subsurface characterization. They’re using Google Kubernetes Engine (GKE) and BigQuery to get near-limitless scalability for their application performing log correction. On the back end, Cloud TPUs and Nvidia GPUs are powering their model training workflows. And the combination of Cloud Pub/Sub, Cloud Dataflow and AutoML is allowing them to deploy predictive maintenance systems faster, and at a lower cost than traditional IT operations.

In many ways, Anadarko is a lot like many other businesses in the energy industry using the cloud to evolve their business processes and find meaningful insights from their data.

The Finnish energy company Neste uses Google Cloud to help them create clean fuel solutions with renewable raw materials. “Being the world’s largest producer of renewable diesel refined from waste and residues, as well as being a technologically advanced refiner of high-quality oil products, requires us to take advantage of leading-edge technological possibilities,” says Tommi Touvila, Chief Innovation Officer. “We have worked together with Google Cloud to accelerate our journey into the digital future. We share the same vision to leave a healthier planet for our children. Running services on an efficient and sustainably operated cloud is important for us.” 

To help geologists, geophysicists, reservoir and geo-information engineers explore and assess oil and gas fields faster and with minimal environmental impact, we’re jointly developing AI technology with French energy company Total. Through this collaboration, we hope to make it possible to interpret subsurface images (notably from seismic studies using Cloud Vision) and automate technical document analysis using Cloud Natural Language.

At Next ‘18, a geophysicist from Chevron described how the company uses AutoML Vision and AutoML Natural Language APIs to make their vast troves of geographic data available so that business decision-making is quicker and much more efficient. And energy services company Schlumberger is using TensorFlow on GCP to do complex petrotechnical interpretation of seismic and wellbore data (that’s detailed information about drilled holes), as well as to automate their log quality control and 3D seismic interpretation applications.

Along with ML and AI tools, energy companies also require highly scalable databases. For example, Aker BP, one of the world’s leading oil exploration companies, collects their data into Cloud Bigtable, GCP’s open time-series database, in order to capture data from hundreds of sources and 500,000 sensors. The company uses that insight to improve worker safety and to discover data-driven optimizations.

Advanced cloud technologies can benefit energy companies in so many ways—from increased operational efficiency and improved decision-making to reduced environmental impact. As AI, ML and big data technology continue to mature, these energy companies can delve deeper into their data to make important leaps forward.

Find out more about how energy companies are using Google Cloud on our solutions page.