Reducing Well Downtime With Machine Learning Systems

The Problem

Improving efficiency of operations and reducing downtime for critical equipment has become vital for oil and gas companies to avoid losses. Unplanned failures in critical assets can cost oil and gas companies millions of dollars in a single day. Can predictive approaches be developed for maintenance to reduce well downtimes?

Solution

Machine learning models deployed on Kranium can analyse large volumes of real-time data from multiple sources to predict well collapses before they occur. Such systems can help alert managers about impending failures before they happen so that they can take appropriate steps to resolve the issue, thereby reducing unexpected downtimes and drastically reducing losses to oil and gas companies.