Emissions data management in the oil and gas sector is becoming increasingly complex. We're generating unprecedented volumes of data with advanced methane monitoring technologies—on-site sensors, aerial surveys, and satellite observations. But are we effectively leveraging this data to reduce emissions?
A critical challenge is the lack of correlation between emissions measurements and operational data. Without integrating these datasets, accurate root-cause analysis becomes nearly impossible, hindering our ability to mitigate emissions effectively.
Moreover, inherent uncertainties in emissions measurement systems—sensor downtime, calibration errors, and environmental factors affecting aerial and satellite data—further complicate the situation.
Our latest article explores how automating data integration and workflows can bridge this gap. By unifying emissions data with operational metrics, we can enhance real-time insights, improve root-cause analysis, and take swift, informed actions to reduce emissions.
For those navigating the intricacies of emissions management and aiming to harness the full potential of their data, this article offers invaluable insights. It's a resource that will make your time reading it well-spent.
Read the full article here: https://hubs.ly/Q02TzLHC0
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