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Drilling Systems Modeling & Automation, Part 1: Introduction to digital twins

This is part of a series. Stay tuned for part 2, coming soon. 

Efforts are underway in the oil and gas industry to improve operations efficiency and cost through drilling systems automation.  Recently, there has been a convergence of several technologies such as modeling algorithms, artificial intelligence and Internet of Things. This has created an opportunity to use models for design and testing of equipment. Combining physics-based models with data driven modeling techniques enables quicker overall product development time of rig systems as well as flexibility in optimizing the design parameters. These are also key to the concept of 'digital twins.'

This video series explores drilling systems modeling, with a focus on surface equipment including the drawworks, top drive, and mud pumps. We will demonstrate the following elements:

1. Building a physics-based model and incorporating controls using pre-built blocks.
2. Calibrating the model to the field data to create the digital twin using automated parameter estimation.
3. Using the digital twin for optimizing system performance given operational constraints.
4. Implementing state-based supervisory logic on the digital twin for testing control logic.
5. Formal methods for verification, validation and testing of control logic against system requirements.
6. Generating PLC and C++ code directly from the model. This code can be used for rapid prototyping, embedded code deployment or Hardware-in-the-loop (HIL) testing.
7. Import existing PLC code for verification and testing.

Additional Resources: - MATLAB for the Oil and Gas Industry: - Simulator codes on File Exchange: - Simulator codes on GitHub:

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