Rig performance benchmarking is an important focus for drilling operations to effectively maximize asset utilization and minimize drilling costs. Effective key performance indicators (KPIs) play a critical role in optimizing drilling processes. By advanced data examination, new technology enables analyzing data from the rig-site to generate rig and drilling KPI statistics and the results can be used for extended understanding of the rig operations and advanced reporting.
With the ultimate purpose of improving rig and drilling performance, continuous improvement efforts are made to find ways to enhance the value of acquired data in terms of analysis and visualization. Such value cannot be accomplished without an effective information system that provides meaningful and informative metrics, asset overviews, dashboards and rig KPI reporting.
A real-time analytical application was developed to collect, visualize and track the performance of multiple drilling and rig-related activities, providing tailored rig KPIs. The solution combines improved data quality, enhanced ease of use and quantitative benchmarking with drilling performance analysis, crew performance overviews, comparison with offset wells and enhanced visualization. Performance Opportunity Time (POT) is important information for management and operations across drilling organizations. Continuous monitoring can be achieved with extended reporting that focuses on drilling performance and is typically conducted from real-time operations centers.
The paper will outline the value added and functionality of the new business intelligence solution where rig metrics, KPIs and dashboards are monitored and visualized in real time for an immediate performance overview of specific assets, leveraging of best practices and technical review. The background of the data that encompasses the foundation of the system is described so the end user better understands the data presented. The paper also presents how the system is used in daily operations and the outline for planned development in the form of big data analytics for management reporting.