Missing well logs prediction using deep learning integrated neural network with the self-attention mechanism

An integrated network with the self-attention is proposed to process logging data. The self-attention is introduced to improve network's attention to relevant features. The variation trend with depth and local correlation of well logs can be considered. The results confirmed that the proposed method is accurate and reliable. Well logs are employed for analyzing lithology, determining formation parameters, and evaluating oil and gas reservoirs.