While global inflation is stabilizing, the residual effects of the rapid price increases in 2022 and 2023 are still felt across industries. For oil and gas companies, rising operational costs—spanning equipment, materials, and labor—exacerbate financial pressures. Reducing non-productive time (NPT) has become crucial in maintaining profitability in this competitive market.
NPT refers to periods when drilling operations are halted or delayed, often due to equipment failure, weather conditions, or logistical issues. This downtime not only impacts overall efficiency but also significantly affects the bottom line. In the oil and gas industry, NPT can lead to substantial financial losses due to the high costs associated with idle rigs and delayed projects. It’s estimated that just 27 days of NPT over the course of a year can lead to a $38 million loss for larger oil and gas companies.
Reduce NPT in the Oil and Gas Industry: A Guide for Drilling Engineers and Maintenance Supervisors
For the purposes of this blog post, we will examine drilling downtime data collected from a medium-sized company. The company wanted to reduce the amount of NPT they experienced in their drilling operations.
They gathered data from 39 significant NPT events from the past month. On average, these events lasted 3.32 hours. The team wanted to understand what was causing these lengthy instances, so they used Minitab Statistical Software to produce a Pareto chart to better understand the percentage of occurrences that could be attributed to mechanical failure, electrical issues, or operator errors. This is because Pareto charts are ideal for identifying the most frequent contributors to a problem. By visualizing the distribution of downtime causes, the team could focus their improvement efforts on the areas with the biggest impact:
Slightly over 50% of all instances were caused by mechanical failure, with electrical issues causing roughly 38%. Operator errors accounted for about 10% of all instances of NPT. While all three areas could be improved, addressing the mechanical failures first makes the most sense since this type of failure leads to the most downtime.
To granularize the data further, the team wanted to understand exactly which mechanical elements were failing. Again, they went to a Pareto chart to see what the mechanical failures could be attributed to. Since they already knew mechanical failures were the biggest culprit, using another Pareto chart here allowed them to drill down even further and pinpoint the specific equipment causing the most NPT:
There was a clear distribution with this data as well, with drill bit failures causing 56% of NPT instances related to mechanical failures, with 32% attributed to the pump and 9% caused by issues with the top drive.
While the team’s goal was to reduce the overall number of instances of NPT, they also realized that these events would inevitably continue to happen occasionally. They wanted to reduce the overall number of hours for each of these instances, ideally to no more than 4 hours per instance. They also wanted to reduce the mean amount of NPT per incident by more than 40%.
Interventions for Improvement
The team devised a straightforward action plan to reduce downtime lengths. This plan focused on the drill bits and pumps since these accounted for nearly 88% of all equipment failures. Their plan was as follows:
Drill Bits:
- Conduct Pareto analysis to prioritize failure modes contributing to NPT lengths.
- Implement enhanced preventative maintenance schedules based on failure patterns.
- Introduce rigorous quality checks during installation and routine inspections.
Pumps:
- Analyze downtime data to identify critical factors contributing to NPT lengths.
- Develop preventive maintenance protocols for vulnerable pump components.
- Train operators on optimal pump operation and troubleshooting techniques.
Results after Improvement Implementation
The team implemented the above interventions and monitored data on an ongoing basis. After three months, they had roughly the same number of NPT incidents as the previous month, indicating a substantial improvement. They used Minitab Assistant in Minitab Statistical Software to conduct a before/after capability comparison between the set of data collected before interventions were implemented and afterwards:
The presentation-ready results that Minitab’s Assistant feature produced demonstrate a clear improvement from the data before interventions to after interventions, and the mean NPT length was reduced from 3.32 hours to 1.6 hours–an over 50% improvement. It’s also significant to note that the company was able to achieve a Ppk improvement from 0.23 to 1.11, indicating that the interventions did indeed work and the current results are well within control and reliable.
This analysis also produced IM-R charts and ran normality tests:
These data further demonstrate that the new conditions made possible by the interventions implemented by the company enable stable processes leading to a notably less amount of NPT.
Data-Driven Results that Improve Your Bottom Line
This use case demonstrates that a data-driven approach can significantly reduce NPT in oil and gas drilling operations. By leveraging Pareto charts and capability analyses, drilling engineers and maintenance supervisors can pinpoint root causes of downtime and implement targeted interventions. The results showcased here offer valuable insights for oil and gas companies seeking to improve operational efficiency and profitability in a competitive market.
In instances like these, companies can save millions of dollars annually through targeted data collection, strategic planning, and ongoing preventative maintenance. And with Minitab’s support team on call and ready to provide personalized training, you will have the support and assistance to save valuable time, resources, and money.
Be the first to comment