Projects
Project AMOLL
Liquid loading of gas wells causes production difficulty and reduces ultimate recovery from gas wells. The accuracy of any predictive model would depend on the assumptions made for the droplet shape factor. Project AMOLL received funding in June 2017 to review existing models and develop a more accurate model for predicting liquid loading in gas wells. The new model outperformed existing models with as much as 43% increased accuracy and potential savings of $100,000s. Project AMOLL was concluded in January 2019.
Project MaGPRS
Project MaGPRS is aimed at integrating Machine Learning Models and Gas Production Reliability Studies. The project was delivered by a combined team of academia and industry experts consisting of teams from China, the UK, and Nigeria. With potential savings of $1,000,000s, Project MaGPRS identified key factors that could be used to predict the initial production rate of a reservoir using an artificial neural network.
The Ikuku-Ndu Ventilator Challenge was set up to fabricate low-cost simple, easy-to-use, and easy-to-build ventilators that can serve COVID-19 patients, within an emergency timeframe using local materials. Submissions were received from 11 teams across Nigeria. The top four teams were invited to an online interview session held on 17th May 2020. After the online interaction, the members of the advisory panel ranked the team’s performance based on cost, team competence, quality of work, and time to build. After which 2 teams were funded to build prototypes.
Project Output
A report prepared at the end of the project is found at: https://drive.google.com/file/d/1iNQvVPb_JQKMarangKhEQRDaU1h9m6xn/view?usp=share_link
