MMXXIVIIIXI/SPE-Africa-Region-Datathon-2025

. Organized by SPE DSEATS Africa Region, the challenge aims to leverage historical production data to accurately classify a group of 20 wells based on their observed performance trends. The Society of Petroleum Engineer (SPE) Data Science and Engineering Analytics Technical Section (DSEATS) Africa Datathon Challenge presents an exciting opportunity for participants to harness the power of machine learning to address real-world challenges in the oil and gas industry. Organized by SPE DSEATS Africa Region, this challenge aims to leverage historical production data to accurately classify a group of 20 wells based on their observed performance trends. 1.2 Challenge Objective Participants are expected to work in teams of 3 to 5 persons (max) from at least 2 different organizations and/or schools to develop a machine learning (ML) model that accurately categorizes the 20 wells provided in the dataset by analysing their daily production data trends. The teams should explore innovative approaches to accurately categorize or classify the wells.