Application of Machine Learning to predict future performances, and to do sensitivity analysis in reservoir simulations, which helps to solve petroleum engineering computational problems and taking decisions in a timely manner.
Jupyter NotebookGPL-3.0
Applications of Machine Learning in Petroleum Engineering
Application of Machine Learning in petroleum engineering for predicting future performance, to help minimize the time and computational cost, in order to achieve History-Matched numerical models.
Data Driven analysis helps find the optimum variables instead of matching model that is highly uncertain and takes time to give results.
accuracy in ML models is very high and more accurate than simulation models data, beacause of Upscaling and other procedures that lead to un-representative numerical models.
The project is in progress for 2022 year, If you are interested and want to contribute, please contact me on email: a.saoud2000@gmail.com