📑 arXiv 3d ago
Assessing the Potential of Masked Autoencoder Foundation Models in Predicting Downhole Metrics from Surface Drilling Data
Systematic review of 13 papers finds no existing work applies Masked Autoencoder Foundation Models to predict downhole oil/gas drilling metrics from surface sensor time-series, despite MAEFMs' proven effectiveness in time-series modeling. Current approaches rely on ANNs and LSTMs but struggle with scarce labeled downhole measurements.