Schlumberger Strengthens DELFI Environment with TIBCO Spotfire Analytics
Disruptive data science and analytics and reduced deployment time
In answer to declining oilfields, Schlumberger wanted to equip its customers with faster and better insights to support growth and production efficiencies. In keeping with its leadership position, it wanted to do so in an innovative, industry-disrupting way.
To meet and exceed customer expectations, Schlumberger partnered with TIBCO; Spotfire software is a key part of its DELFI environment, providing customers with analytics at massive scale and radically faster time to insight.
Schlumberger provides oil production and exploration services including measurement, well drilling, and software for extracting oil from the subsurface. TIBCO Spotfire software provides the scalable digital foundation for enhancing the services, capabilities, and value of its DELFI environment.
"Designing a scalable ecosystem is absolutely critical," said Trygve Randen, president of Schlumberger Software Integrated Solutions. "We can take full advantage of TIBCO technology to enhance the capabilities we provide to customers."
Innovative, Disruptive Data Science and Analytics Enablement
Schlumberger saw an opportunity to disrupt the oil & gas market with DELFI, its new analytics offering, but needed a proven partner to help realize this vision. With Spotfire analytics, Schlumberger addresses "data overwhelm" and improves data management and quality.
"TIBCO is the best partner to analyze vast amounts of data," said Randen. "Our data science and analytics workflows are vastly improved by incorporating TIBCO technology into our stack."
Reduced Deployment Time
With the Spotfire implementation, Schlumberger is using the right data analysis tools to vastly accelerate development in DELFI. The Spotfire+DELFI combination is a key driver, enabler, and value-add for customers. One example, Woodside, an extremely innovative Australian oil and gas company, "achieved some amazing results,” said Randen. "The goal was to take the subsurface modeling workflow down from 18 months to 18 days, and they actually delivered an eight-day result."