Devon Energy and Whitson Collaborate to Save Time and Increase Production by Automatically Calculating Bottomhole Pressure

By architecting its Data Hub on Snowflake, Devon Energy democratizes access to data for more secure, efficient data sharing with SaaS vendors and better decisions around oil well production.



Wells with automatic bottomhole pressure calculated daily


Of application data now available to employees for better decision-making

contractor at a factory holding a tablet while smiling
Oil and gas
Oklahoma City, OK

Fueling the world’s energy needs

Devon Energy is focused on being North America’s premier independent oil and natural gas company. Each day, the company produces approximately 315,000 barrels of oil, 150,000 barrels of natural gas liquids and 1 billion cubic feet of natural gas — all while balancing the need for innovation, operational efficiency and environmental stewardship.

Profitably finding and producing oil and natural gas is a complex endeavor that requires industry expertise, advanced engineering and lots of data. As a long-time Snowflake customer, Devon Energy leverages Snowflake’s Manufacturing Data Cloud to democratize employee access to data, collaborate with vendors and drive business outcomes.

Devon Energy got serious about treating data like an asset more than 10 years ago. Snowflake has been a step change in how people use and access data, becoming a one-stop shop for anyone who wants insights.”

Clark Thomas
Lead Systems Analyst, Devon Energy
Story Highlights
  • Faster data access, richer insights: By bringing together data from 30+ sources in Snowflake’s data warehouse and data lake, employees have direct access to 95% of the organization’s data for better decision-making.

  • Easier two-way data sharing: With Snowflake Secure Data Sharing, Devon Energy shares time series and wellbore configuration data with software partner Whitson; in return, Whitson shares back calculations — which saves time and reduces complexity by eliminating the need to integrate data via APIs.

  • Cost-effective calculations for oil wells: Devon Energy’s reservoir and production engineering teams rely on accurate, automated bottomhole pressure data — without the need for manual labor or costly hardware — to power business goals.

Maximizing oil well production with data

Oil wells tend to produce less hydrocarbons as they age, which is why oil and gas companies must simultaneously optimize existing well performance and plan for future expansion. “It’s always a race against time and your drilling schedule,” says Jonathan White, technology manager at Devon Energy.

As a result, timely, reliable data is vital to making decisions that impact well production and capital investments. After three attempts with other solutions, Devon Energy turned to the elastic scale, concurrency and performance of Snowflake’s Data Cloud, which serves as the company’s enterprise data warehouse and data lake. 

Consolidating data from more than 30 sources — including Devon Energy’s SAP ERP systems — democratized employee access to 95% of the organization’s data. With broader access to analytics, teams now make faster, more informed decisions around everything from rig efficiency to future site selection. Snowflake Secure Data Sharing offered a convenient way to access data from vendors, including S&P Global Commodity Insights and Peloton. 

Today, Devon Energy leverages its Data Hub, powered by Snowflake, to support more than 1,000 users and around 9 million queries per month. “The growth in Snowflake usage is really taking off, and analytics is the driver of that,” says Clark Thomas, lead systems analyst at Devon Energy.

Calculating bottomhole pressure: “Like air to humans”

Democratizing data and analytics was an important first step, but it’s not where the story ends. Devon Energy also leverages its Data Hub to streamline critical processes like calculating bottomhole pressure — a metric that’s vital for numerous engineering exercises. 

“Bottomhole pressure in the oil and gas space is like air to humans. You can’t do anything without it,” says Mathias Carlsen, PE consultant and GM of Americas for Whitson. 

Before achieving an automated solution with Whitson and Snowflake, Devon Energy spent years looking for a feasible way to calculate and analyze bottomhole pressure. Manually deriving bottomhole pressure for more than 5,000 of Devon Energy’s wells was unscalable, but installing the $50,000 physical sensor in each well was uneconomical for the upfront well design and unrealistic once wells were already producing. By automating this critical process with Snowflake and Whitson, Devon Energy avoids significant installation, hardware and disruption costs while paving the way for sustained growth. 

Building collaboration with two-way data sharing

Devon Energy chose whitson+ as the best software for calculating bottomhole pressure, but Whitson’s collaborative approach was equally important to the project’s success. “We tell vendors that we’re not interested in their SaaS products unless we can share data via Snowflake Secure Data Sharing,” says White. “We found a vendor that was doing really cool scientific work and was willing to integrate with us in a different way. Rather than building APIs, which would have required much more work, they shared data back and forth via Snowflake.”

Snowflake Secure Data Sharing enables live access to large amounts of Devon Energy’s time series and wellbore configuration data that Whitson feeds into its physics-based engine and uses for digital twin capabilities. Calculations are made available in whitson+ and also shared back to Devon Energy via Snowflake Secure Data Sharing. 

Devon Energy’s first two-way data sharing use case accelerated collaboration with Whitson, resulting in a reliable bottomhole pressure calculation that runs daily for each well. White says, “What’s crazy is how hard we tried with other vendors — and how quickly this happened. It’s a testament to Whitson and Snowflake.”

Empowering engineering teams with insights and new SaaS features

Surfacing bottomhole pressure calculations in whitson+ and Devon Energy’s supervisory control and data acquisition (SCADA) systems helps production engineers identify underperforming wells and enhance performance. Reservoir engineers rely on timely bottomhole pressure data to understand reservoir health, determine the locations of new wells and plan for future expansion. Shared access to bottomhole pressure data helps both groups collaborate more effectively and unify around common goals.

For Whitson, the opportunity to work with Devon Energy’s production engineers — not just reservoir engineers — led to a new feature set in whitson+. “Now we have a whole suite of functionality in the tool for this audience,” says Carlsen. “We essentially could do that thanks to this collaboration with Devon Energy, which was made possible by sharing data through Snowflake.”

Beyond its engagement with Devon Energy, Whitson has used Snowflake Secure Data Sharing to collaborate with about a dozen other clients — and more opportunities are on the horizon. For Carlsen, connectivity with Snowflake is becoming a “license to operate” with some oil and gas companies. “It’s almost like a product offering, which helps us differentiate ourselves versus competitors,” says Carlsen.

Advancing innovation through AI/ML and data sharing

Moving forward, Devon Energy plans to support a growing number of AI/ML use cases with unified data stored in Snowflake. For example, the team is currently working on ingesting log data for a geosciences AI/ML project. According to White, “The first step for data science is getting data into Snowflake if it’s not already there.”

Devon Energy is also pushing more SaaS companies to collaborate via Snowflake Secure Data Sharing. “We want more vendors to be like Whitson,” says White. “We’re hoping to encourage more of them to use Snowflake and think creatively about sharing data back and forth.”

Start your 30-DayFree Trial

Try Snowflake free for 30 days and experience the Data Cloud that helps eliminate the complexity, cost and constraints inherent with other solutions.