MEMPREDIKSI LAJU PRODUKSI MINYAK, GAS, DAN AIR MENGGUNAKAN RECURRENT NEURAL NETWORKS : STUDI KOMPARATIF DENGAN LSTM, GRU, DAN VANILLA RNN

• Main Author: Putri Aurelia, Salsabila
• Format: Final Project
• Language: Indonesia
• Subjects: Pertambangan dan operasi berkaitan
• Online Access: https://digilib.itb.ac.id/gdl/view/73481
• Institution: Institut Teknologi Bandung

This research focuses on using machine learning techniques to predict well performance in the petroleum industry. Traditional methods like Decline Curve Analysis and reservoir simulation have limitations in accurately predicting production performance. Therefore, the study explores the use of machin...