Case Study: Devon Energy achieves faster, safer oil exploration and scalable data pipelines with Databricks

Safer oil exploration with AI

Devon Energy, an oil and gas exploration company focused on unconventional reserves, faced fragmented data, a legacy on‑premises ETL/Hadoop stack, and costly DevOps that left teams unable to scale, collaborate, or extract timely insights from billions of records. Slow queries, frequent data “traffic jams,” and non‑reproducible ML workflows hindered operational efficiency and safety improvements.

By moving to Azure Databricks (Delta Lake, data engineering, MLflow) and adopting a cloud‑first, unified analytics platform with auto‑scaling and Power BI integration, Devon streamlined pipelines, reduced cluster management overhead, and enabled cross‑team collaboration. The result: scalable processing (1,000+ cores), full‑well processing in 1–2 hours, large queries cut from ~2 days to ~30 minutes, lower costs, and faster, more reliable ML‑driven decisions.

Devon

Paul Bruffett

Data and Analytics Architect