Driving Industrial-Scale Energy Analytics Through Push Compute
Modernizing the analytical architecture of the digital oil field
Navigating market volatility and operational complexity in today’s energy sector requires a fundamental shift in data processing architecture. Traditional workflows rely on extracting high-volume datasets—such as SCADA streams, LAS well logs, and seismic attributes—from central databases into local environments for analysis. This legacy approach creates severe performance bottlenecks, increases security risks, and limits cross-domain collaboration.
Spotfire Push Compute addresses this challenge by shifting calculations directly to where the data resides. By pairing the Spotfire energy-specific visual workspace with the distributed processing power of the Snowflake AI Data Cloud, organizations can run heavy, data-intensive calculations directly within their secure database environment.
This white paper explores how executing analytics at the data layer eliminates latency, reduces data movement, and scales advanced workflows across the entire oil and gas value chain.
What you’ll learn:
Architectural benefits of push compute: How executing advanced transformations and ML models within Snowflake clusters maintains data security, lowers egress costs, and preserves fluid, in-memory visual manipulation in Spotfire.
Technical application workflows: How to scale complex computations—including basin-wide Decline Curve Analysis (DCA), bulk petrophysical calculations, grid-scale volumetrics, and automated SCADA anomaly detection.
Domain-specific use cases: Practical applications across asset valuation, field development optimization, production monitoring, and operational risk mitigation.
