Drilling is one of the most expensive activities in any oil and gas operation. Monitoring drilling and completion fluid and maintaining these at desired levels of viscosity and density is essential for optimum drilling fluid performance, efficient hole cleaning, and Equivalent Circulating Density (ECD) management, as well as preventing failures of surface and downhole equipment during drilling. Automated RT determination of rheological parameters of drilling and production fluids has so far proved challenging, due partly to the instrumentation used. There is an unmet need in the market for a fully automated system to determine and adjust rheological properties of drilling fluids.
Researchers at The University of Texas at Austin have come up with a sophisticated control and data analysis software that integrates with their pipe rheometeric device to provide complete real-time analysis of the fluid characteristics. Some of the key features include:
- Fully automated measurement and data acquisition process.
- Fully automated data analysis: the program determines mud rheological parameters, transitional Reynolds number, and turbulent friction factor. It uses several non-Newtonian rheological models (Bingham plastic, power law, yield power law etc) to obtain the best fit.
- Accurate prediction of ECD and annular pressure profile
- Simulates pump start-up and real-time hydraulics for MPD operations
- Allows real-time decision making during drilling and cementing operations
The software package may be used for real-time advanced hydraulic modeling as well. Parameters obtained from the pipe rheometer can be used to predict the annular pressure profile, bottomhole pressure, ECD, pump pressure, etc. Techniques such as Managed Pressure Drilling, which rely on accurate prediction of ECD, can significantly be improved by using this software package
This software package offers a very user-friendly interface and makes fully automated “one-click” mud check possible. Robust data analysis process makes the output very reliable. The software provides more accurate predictions than the current state of the art.