Pioneer

Pioneer Natural Resources Company is an independent oil and gas exploration and production company. The Company engages in onshore oil and gas drilling, exploration, and production in the United States. Its 11,000-plus gross producing wells mine about 85 million barrels of oil each year.

Challenge

Pioneer faced a complex challenge: transitioning from disparate legacy BI tools to a unified cloud-based data ecosystem. The shift aimed to improve agility, scalability, and innovation across the organisation. Technical hurdles included schema drift, metadata automation, and ingestion pipeline modularity.

The Azure-powered solution enabled significant business outcomes:

• Improved efficiency: Modular ingestion architecture reduced development time and facilitated easier maintenance.
• Higher data trust: Through built-in reconciliation and core data validation mechanisms, the system ensured data integrity.
• Faster onboarding: Use of accelerators like Stage Object and Stored Proc generators allowed rapid scaling and inclusion of new data sources.

Solution

Pioneer Natural Resources partnered with Elixirr Digital to migrate their enterprise data and reporting platform from a legacy on-premises environment to a robust, scalable Azure-based cloud solution. This initiative centered on transforming operational and analytical data pipelines for departments such as Finance, HR, Supply Chain, and Production Operations.

The project made extensive use of Microsoft technologies, including Azure Data Factory, Azure Synapse Analytics, Azure SQL Database, and Azure Data Lake Storage. The solution also leveraged Microsoft Event Grid and APIM services for orchestration and integration, delivering a modern, cloud-native platform that enhances data ingestion, transformation, and reporting capabilities.

Benefits

The new Hadoop platform enabled Pioneer to integrate all its structured, unstructured & semi-structured data in one place (data lake). By bringing IOT sensor data in-house, Pioneer was able to run critical models to predict equipment failures, improve well operations resulting in significant cost saving. Users were able to seamlessly query both real-time and batch data using various tools and get data in consistent format.