Data Science

The project Biomass Prediction and Design of an Optimum Demand-Supply Chain was a part of the Shell.ai hackathon for sustainable and affordable energy organized in 2023 presented a challenge to predict biomass production for the future years and design an efficient demand supply chain for the same by leveraging the provided data of the Gujarat State in India. An intelligent model was trained followed by an efficient demand supply chain with an accuracy rate of 76.765%, which was successfully deployed and ranked among the Top 10 teams worldwide.

Spot the Trend – A PetroAI hackathon presented a challenge to predict the bottom-hole pressure with the help of provided time series data. As a problem statement and its solutions, a bottom-hole pressure was to be predicted with an AI/ML model trained to decide whether a well is flowing or not. An AI model was then developed and optimized with 70.1% accuracy in predicting the BHP and well-flowingness.

The Shell.ai Hackathon organized in 2023 with a theme of sustainable and affordable energy presented a challenge to predict biomass production for the future years and design an efficient demand supply chain for the same by leveraging the provided data of the Gujarat State in India. An intelligent model was trained followed by an efficient demand supply chain with an accuracy rate of 76.765%, which was successfully deployed and ranked among the Top 10 teams worldwide.