An Holistic Approach to Improving Drilling Performance in Realtime: Integrating Measured, Analysed, Modelled and Reported Drilling Data

Richard Kucs, Gerhard Thonhauser, Matt Regan, J. M. Hanson, Jonny Haugen, Odd Erik Gundersen

2015 · 10 citations · 10 references

Concepts

Abstract

Abstract The concept of enterprise level and standardised realtime data management solutions supporting drilling operations is rapidly gaining considerable recognition with dynamic and technology-comfortable Operators. Whether delivered physically in an Operations Centre or virtually via web browser, the business drivers are clear – when presented in an ergonomic fashion, the full suite of realtime drilling and geology data enables timely, informed and collaborative decision-making, leading to performance improvement and reduction in operational, and therefore financial, risk. However, there remains a common disconnect between: (i) primary measured and processed real-time data, (ii) unstructured data in the form of analytical results, and (iii) tertiary metadata from reports. Typically these three tiers of data, and the companies providing them, are isolated from each other. Once operations commence, dataflow may occur in one direction with realtime data feeding into analytics and reporting tools, accompanied by substantial subjective human input. This paper discusses how a major European independent Operator, with a diverse range of global assets and associated challenges, has worked with its various data solution providers to develop and implement a fully bidirectional ‘data highway’ in which realtime, analysed and reported data are seamlessly and efficiently exchanged. This holistic approach to data-driven operations support delivers a combined value far greater than the sum of the individual applications, as the various proprietary systems enhance and complement each other. Non-productive time (NPT), as well as Invisible Lost Time (ILT) analysis, is fed back into realtime monitoring, reported comments are tied to realtime curves, planned and modeled drilling optimisation recommendations are displayed and correlated alongside live drilling data. Carefully mapped dataflows drive workflows which in turn drive sophisticated deliverables that improve standard operating practices, and hence best practice. The result is improved drilling key performance indicators (KPIs) leading to performance improvement, risk mitigation and cost efficiency: All at an enterprise level and all in realtime.

References

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