Michael Chavez and Brandon Dyck
Platinum Control
For decades, VRUs have been deployed as compliance equipment and treated as commodity hardware – sized on rough estimates, lightly engineered, and minimally monitored. The results have been predictable: inconsistent runtime, chronic loading instability, ever-increasing maintenance costs, and a long-standing belief that VRUs simply “don’t work.” This paper examines why that legacy persists and outlines a modern engineering and measurement framework that significantly changes VRU performance, economics, and reliability.
The approach centers on precise sizing, real-time operational data, and flexible deployment strategies designed to match dynamic vapor loads. A comprehensive operational dataset – including pressures, temperatures, load signatures, runtime behavior, oil level, and measured vapor flow – enables predictive maintenance, drift detection, and stable runtime across a wider range of operating conditions. Rather than relying on a single indicator, this data ecosystem provides the analytical foundation for a proactive VRU program. The same infrastructure also supports accurate emissions accounting, turning VRUs into valuable compliance assets as regulators move toward measurement-based methane reporting and as operators work to reduce the significant financial exposure tied to modern methane enforcement.
Field deployments in the Permian Basin show significant improvements in uptime, maintenance cost, and equipment longevity, with operators experiencing fewer cycling events, reduced downtime, and lower LOE. These results indicate that a measurement-driven VRU program can prevent both oversized and vapor-constrained installations, significantly reducing risk while improving economic return.
This paper will present the engineering principles, measurement insights, and early field learnings behind this next-generation approach – and why solving the long-standing VRU problem ultimately turns vapor recovery from a perceived liability into a measurable, high-value asset.