Project
OptiDrill
Optimisation of Geothermal Drilling with Machine Learning
Optimisation of Geothermal Drilling Operation with Machine Learning
Completed
Oliveris role
WP4 Contributor — Real-Time Sensing, Data Acquisition & Lithology Intelligence
Horizon 2020 · Grant 101006964 · Coordinator: Fraunhofer IEG
Challenge
The challenge
The challenge
Geothermal drilling is expensive and uncertain. Operators need better real-time information about drilling conditions, formation changes and emerging problems while the drilling process is underway.
Approach
How the project works
How the project works
OptiDrill combined drilling measurements, advanced sensors, data analytics and machine-learning models to support rate-of-penetration prediction, lithology assessment, drilling-problem analysis and process optimisation.
Outcomes
What it delivers
- Real-time drilling intelligence
- Improved lithology assessment
- Sensor-informed machine learning
- Better operational decision support
Oliveris
Our contribution
Oliveris contributed to the sensing and data-analysis work used to understand drilling conditions in real time. The work included developing and testing drilling sensors, capturing vibration and motion data during drilling, analysing the signals to understand system behaviour, and evaluating machine-learning methods for lithology classification. The aim was to turn raw drilling measurements into useful information about the formation and support better operational decisions.
Capabilities
Technologies in this project
Technology Areas
Sectors this supports
Consortium
Organisations in this project
Funded by the European Union
This project has received funding from the European Union's Horizon 2020 research and innovation programme under Grant Agreement No. 101006964.
The content of this page reflects the author's view only, and neither the European Union nor CINEA is responsible for any use that may be made of the information contained herein.
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Discuss related work
If this project is relevant to your technical challenge, talk to Oliveris about the underlying capability, integration approach or a new collaborative application.
