Real-time operations have long provided a crucial decision support and collaboration capability that enhances decision making during the well construction process. Operators, drilling contractors, and service companies use real-time capabilities to improve operations service quality, create efficiencies, understand formation geology, and enhance overall reservoir knowledge.
Historical applications have provided domain experts with real-time information to support less-experienced wellsite personnel, provide advice and guidance, and conduct remotely performed operations. However, the information was typically centered on a single well and often with a discrete job-focused execution mindset, even when the same provider delivered multiple services.
The industry focus on "digital transformation" creates new opportunities for the real-time environment. The promise of real-time analytics and machine learning increases the potential value of having access to all petrotechnical data. To be successful, these systems should simultaneously integrate data across two dimensions: all services provided throughout a single asset's life cycle and all wells across an entire basin. While engineers use historical real-time data for offset analysis during their next well design, data typically remain filed away, relatively inaccessible for large-scale analytics.
This paper presents a case history on the development and implementation of an enterprise real-time data environment in support of the digital transformation. Key objectives for the environment are to ensure data accessibility for analytics modeling while maintaining the digital coherence necessary during the data collection and distribution processes across multiple services and wells.
Functional capabilities include a multi-well, real-time historian, automated data distribution to a big data environment for full-scale analytics, the capability to run analytics models at the edge, and interconnectivity with other field systems for more context-enriched datasets. Key design principles for success are the use of an open architecture to accelerate innovation and a cloud-first, microservices design to maximize implementation flexibility. Key development learnings are also discussed.
Similar to digital companies, data in the oil and gas industry is being increasingly recognized as a key asset. Operators collect data during appraisal, planning, design, and wellsite execution. However, it has been relatively inaccessible for consumption much beyond its immediate, primary purpose. New opportunities exist to leverage data for innovations that can deliver better, more-productive assets and create greater operational efficiencies. New data systems are necessary that can combine data in new ways and expose insights in real time not historically possible because of limited computational resources.
