Application of SMOTE-SABO-BiLSTM hybrid model in intelligent identification of low-contrast oil layer in sandy-shaly reservoirs

Key Points

• Low-contrast oil layer identification represents a significant challenge in sandy-shaly reservoirs, requiring advanced analytics.
• The hybrid model combining SMOTE and BiLSTM shows improved accuracy compared to traditional methods.
• Assessment using simulation data reveals enhanced performance metrics for oil layer detection across diverse geological settings.
• Implementation may lead to more effective resource management strategies, though the model's adaptability to other contexts warrants further exploration.