Success Story

Identifying Failure Before it Happens

14 days' lead time to predict equipment failure

When a critical rig component is about to fail, rig personnel may have only hours to act before drilling comes to a halt. Unfortunately, the warning signs of failure are often fragmented and buried in sensor data without an easy way to foresee imminent issues.

Imagine knowing which changeable components are at high risk of failure with 14 days of lead time to make decisions about mitigation. End-of-well maintenance is no longer a mystery: it becomes targeted, efficient, and proactive. Having this predictive capability isn’t science fiction—it's proven problem-solving made possible by Max™.

Max is NOV's industrial data platform and associated services that enable the large-scale collection, aggregation, accessibility, and analytics of real-time equipment data. Max handles all data from a variety of sources including land rigs, offshore rigs, service equipment, and manufacturing facilities.

A graphic demonstrating the likelihood of blowouts

Rig uptime is valuable, and it takes the right information to run operations with confidence. Through modern predictive analytics powered by an integrated data platform, we can maintain awareness of component health and provide the tools needed to detect degradation of components before it causes downtime.

Because NOV builds your tools and services your equipment, we understand the value in what the data are saying. Max allows us to analyze the sensor data and answer complex questions about equipment health and performance.

An NOV worker smiles while standing near BOP equipment
A screenshot showing software used to predict blowouts
An NOV employee points something out on a computer to another employee
An inside view of a rig

NOV's latest innovative breakthrough is the development of an end-to-end predictive solution to foresee operational failures in critical components of subsea blowout preventers (BOPs), with a prediction horizon of 14 days. This solution is the result of a team of engineers, data scientists, and subsea experts analyzing more than 14 years of historical data and maintenance logs paired with 60 years of design and manufacturing experience.

BOPs are just the beginning. Early identification of failure modes will be made available to customers as part of RIGSENTRY™, NOV's family of condition monitoring systems and services, to enable condition-based predictive maintenance of all rig equipment.

A venn diagram displaying the overlap of people, tech platform, and industry presence

NOV's investments in technology and expertise are part of an overall objective to develop smarter products and give our customers greater visibility into the health and performance of their equipment. Through these resources we can begin to identify anomalies and failure patterns across all product lines, providing you with the right information at the right time.

Authors

Carl Fehres
Vice President of Engineering Technology
NOV Employee Carl Fehres

Carl Fehres has worked at NOV for 20 years, first as a product engineer and project manager, and now as vice president of corporate engineering. Carl holds bachelor’s and master’s degrees in mechanical engineering and completed the Executive General Management program at Harvard Business School. In recent years, big data is his life. He is passionate about developing and implementing big data solutions into NOV products and services.