No industry has received more scrutiny than oil and gas for its track record in safety. Now, changing attitudes in this sector may serve as an example for engineers in all fields.
The oil and gas drilling industry has typically placed less emphasis on machine reliability than other industries such as power generation, refining, and chemicals, but efforts to improve predictive maintenance practices are intensifying. That was the consensus of drilling-industry experts gathered at the recent SKF Asset Management 2011 conference.
The experts cited several reasons for the industry's traditional mindset, including a risk-taking culture that prioritizes immediate results over trending reliability data and properly maintaining equipment. Decision-making is usually in the hands of rig operators, who have long viewed condition-based monitoring as an unnecessary expense or even a luxury.
Another factor is location. Drilling operations often take place in extreme environments and isolated locations. Access is difficult, requiring the use of helicopters or barges to transport replacement parts and critical spares. Data transmission can also be limited, with priority given to production information rather than reliability data. This hampers the acquisition and analysis of machine data by experts located in remote diagnostic centers.
Addressing the challenges
The industry, however, is beginning to address these challenges. There is widespread recognition that the cost of machine failures, including the environmental impact, can be steep. Some oil and gas companies are developing a new operational culture of risk management, safety, and reliability. Decision-making and control are being shifted from rig operators to management. These companies are establishing new business structures and standard maintenance and reliability practices across their organizations without overburdening individual drilling sites.
What's clear is that as companies ramp up reliability initiatives, they can benefit from predictive maintenance systems and diagnostic centers that help collect and interpret reliability data, diagnose machine problems, and propose effective action.
Drilling-industry experts at the conference stressed the importance of identifying critical machine assets and developing sound data collection and analysis procedures. One crucial application, for example, is the widely used top drive, an electrically powered drilling device that provides rotational force — more than 100,000 ft-lb of torque — and can shut drilling operations down when they fail. Drilling rigs also have numerous compressors, generators, and pumps critical to production, and in some cases life support, which require monitoring to prevent unexpected failures.
Also discussed was an ongoing multi-year analysis of reliability data from drilling operations. To date, the study has pinpointed a number of operational and maintenance conditions that commonly lead to machine failures and production shutdowns. The study's goal is to identify the specific types of operational data that have the most predictive benefit.
Pilot program on an offshore oilrig
Recently, a drilling contractor conducted a reliability pilot program on an oil-drilling platform containing more than 500 machine assets. The company clarified employee roles and responsibilities and implemented numerous improvements. Key performance indicators were trended over time, including machine utilization, availability, and mean time between repairs.
The pilot proved successful and is now being replicated on other installations; machine data collection and lubricant analysis have been standardized across all platforms. The existing online monitoring systems, which were previously underutilized, are being upgraded. Finally, a formal failure analysis program has been put in place to determine the underlying causes of machine failures.
Dave Staples is business development manager, SKF Reliability Systems, a business unit of SKF USA Inc. He can be contacted at Dave.T.Staples@skf.com or (267) 436-6000.