Webinar: An approach to autonomous drilling: on the importance of balancing performance with risk management and data availability and quality
In this talk, Mihai will present an approach to balance drilling performance with risk management and data availability and quality. The implementation of this approach is an integrated part in the demonstration of proof of concept for autonomous drilling in OpenLab, NORCE’s own lab facility that includes an advanced drilling simulator.
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The future direction for drilling automation is towards autonomous drilling operations. This is supported by the current increase in well complexity, the need for increased efficiency and the desire to decrease environmental impact by reducing CO2 emissions.
An important aspect when it comes to achieving autonomous drilling is the close connection to reliable and accurate estimation of the current state of the system. In other words, the better the estimation, the greater success factor for achieving good performance by the autonomous system. Given the non-holonomic nature of the drilling process, the estimation of current status of the system is a complex problem. In order to estimate current state of the system one should consider all previous states and all actions that occurred before reaching current state. Even so, assumptions need to be made in this process, resulting in a probabilistic approach of the problem. Thus, the uncertainties evaluation is of major importance when trying to balance performance with risk management in drilling.
The entire process is also conditioned by data. Both data quality and availability are of high relevance and complement each other. For instance, very accurate data which is available only after a drilling operation is completed, is of little, or no relevance for the online decision making in an autonomous system. At the same time, real time available data with low accuracy contributes to increased uncertainty in the probabilistic analysis mentioned before, thus having a direct impact on the risk management and consequently, on drilling performance.
About Rodica Mihai
Rodica Mihai is a senior researcher in the Drilling and Well Modelling research group in NORCE Energy. She holds a PhD from University of Bergen, Department of Informatics.
Rodica has been working for the past 10 years within drilling automation, both as a researcher and in project management.
She is currently Technical Leader for Autonomous Drilling – research, development, testing and demonstration in an ongoing Demo200 project funding by Norwegian Research Council and industry partners.