Abstract

A large collection of data recorded during coiled tubing (CT) operations has been analyzed using proprietary pattern recognition algorithms to identify downhole events with a high degree of confidence. These events include the drilling of plugs and stuck pipe incidents. Key performance indicator (KPI) metrics derived from this analysis provide insight into industry trends over time and by region, and can provide useful performance benchmarks for service providers and operator companies.

Depth, weight and pressure data from multiple sources has been streamed and stored on a shared platform over a five year period, creating a record of over 39,000 data files. This data was processed to generate KPI-type statistics for over 500,000 detected plugs and 760 possible stuck pipe scenarios, based on analysis of depth and weight signatures. Using surface measurements to quantify downhole events has some limitations, but the method has proven sufficiently robust to allow useful trends to be observed and evaluated. While the analysis is confidential to the parties involved, a contributing company can compare their ‘performance’ statistics (as evaluated by the third party algorithms) against averages representative of the industry at large, arranged by year and geographic region, to identify areas of relative strength or weakness. An operator company can likewise compare metrics for different service providers (derived solely from jobs performed for their company) for those which elect to share data in this fashion.

This paper presents statistics for plug drilling operations and stuck pipe incidents in North America between 2016-2020, a period of significant change in the CT industry. Examples show how average plug drilling times have generally decreased, with less frequent use of short trips and fewer pipe cycles. The data shows that, for some companies, faster operations have come at the expense of more frequent or severe stuck pipe incidents, whereas other companies have experienced fewer such problems. This comparative analysis illustrates how downhole outcomes can be deduced from surface measurements, and resulting performance metrics can vary widely between companies, fields and geographic regions.

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