• DRE I Research article I 2026(1): 100232
  Numerical and experimental studies of the natural mixing behavior between an uncemented paste backfill and dumped waste rock in stopes from laboratory toward field conditions. Part I: Calibration and validation of a numerical model
  Yuyu Zhang, Li Li*, Serge Ouellet, Louis-Philippe Gélinas
  
  Cite: Zhang, Y.Y.; Li, L.; Ouellet, S.; Gélinas, L.-P., Numerical and experimental studies of the natural mixing behavior between an uncemented paste backfill and dumped waste rock in stopes from laboratory toward field conditions. Part I: Calibration and validation of a numerical model, Deep Resources Engineering 2026, 3 (1): 100232. https://doi.org/10.1016/j.deepre.2025.100232
• DRE I Research article I 2026(1): 100202
  Multidimensional thorough perception system for surrounding rock disasters in underground engineering and its application
  Haoyu Mao, Nuwen Xu*, Peiwei Xiao, Xiang Zhou, Xinchao Ding, Biao Li
  
  Cite: Mao, H.Y.; Xu, N.W.; Xiao, P.W.; Zhou, X.; Ding, X.C.; Li, B., Multidimensional thorough perception system for surrounding rock disasters in underground engineering and its application, Deep Resources Engineering 2026, 3 (1): 100202. https://doi.org/10.1016/j.deepre.2025.100202
• DRE I Research article I 2026(1): 100233
  An innovative approach for oil well bottomhole pressure forecasting using Kolmogorov-Arnold Neural Networks (KANs): A case study in an offshore oilfield
  Adeboye Adeyinka*, Opedamola Oriola, Olusegun Stanley Tomomewo*
  
  Cite: Adeyinka, A.; Oriola, O.; Tomomewo, O.S., An innovative approach for oil well bottomhole pressure forecasting using Kolmogorov-Arnold Neural Networks (KANs): A case study in an offshore oilfield, Deep Resources Engineering 2026, 3 (1): 100233. https://doi.org/10.1016/j.deepre.2025.100233
• DRE I Research article I 2026(1): 100207
  Infrared thermal image detection method of stressed sandstone fracture based on deep learning
  Hai Sun*, Xinyi Hou, Liqiang Ma, Wenshuang Gao, Kun Wang
  
  Cite: Sun, H.; Hou, X.Y.; Ma, L.Q.; Gao, W.S.; Wang, K., Infrared thermal image detection method of stressed sandstone fracture based on deep learning, Deep Resources Engineering 2026, 3 (1): 100207. https://doi.org/10.1016/j.deepre.2025.100207
• DRE I Research article I 2026(1): 100231
  Improving deconvolution reliability in well test analysis with an automated objective function
  Mina S. Khalaf*
  
  Cite: Khalaf, M.S., Improving deconvolution reliability in well test analysis with an automated objective function, Deep Resources Engineering 2026, 3 (1): 100231. https://doi.org/10.1016/j.deepre.2025.100231
• DRE I Review I 2026(1): 100200
  Casing damage in oil and water wells: Causes and prevention
  Jiang-Feng Liu, Xin-Yue Zhang*, Li-Yuan Yu*, Xiao-Liang Wang, Yun-Hu Lu, Zi-Hao Zhang, Zhi-Jie Jian
  
  Cite: Cite: Liu, J.F.; Zhang, X.Y.; Yu, L.Y.; Wang, X.L.; Lu, Y.H.; Zhang, Z.H.; Jian, Z.J., Casing damage in oil and water wells: Causes and prevention, Deep Resources Engineering 2026, 3 (1): 100200. https://doi.org/10.1016/j.deepre.2025.100200

• DRE I Research article I 2024(2): 100019
  Rockburst risk control and mitigation in deep mining
  Ming Cai*
  
  Cite: Cai, M., Rockburst risk control and mitigation in deep mining. Deep Resources Engineering 2024, 1 (2): 100019. https://doi.org/10.1016/j.deepre.2024.100019
• DRE I Research article I 2024(2): 100008
  Artificial intelligence technology in rock mechanics and rock engineering
  Xia-Ting Feng*, Cheng-Xiang Yang, Ben-Guo He, Zhi-Bin Yao, Lei Hu, Wei Zhang, Rui Kong, Jun Zhao, Zao-Bao Liu, Xin Bi
  
  Cite: Feng, X.-T.; Yang, C.-X.; He, B.-G.; Yao, Z.-B.; Hu, L.; Zhang, W.; Kong, R.; Zhao, J.; Liu, Z.-B.; Bi, X., Artificial intelligence technology in rock mechanics and rock engineering. Deep Resources Engineering 2024, 1 (2): 100008. https://doi.org/10.1016/j.deepre.2024.100008
• DRE I Research article I 2024(1): 100001
  Numerical analysis of thermo-hydromechanical process related to deep geological radioactive repository
  Jian-Fu Shao*, Zhan Yu, Zaobao Liu, Minh-Ngoc Vu, Gilles Armand
  
  Cite: Shao, J.-F.; Yu, Z.; Liu, Z.B.; Vu, M.-N.; Armand, G., Numerical analysis of thermo-hydromechanical process related to deep geological radioactive repository. Deep Resources Engineering 2024,1 (1): 100001. https://doi.org/10.1016/j.deepre.2024.100001
• DRE I Research article I 2024(2): 100023
  A three-dimensional numerical study on the stability of layered rock spillway tunnels in alpine canyon areas
  Peng-Zhi Pan* , Fuyuan Tan, Fengqiong Li, Fudong Chi, Xufeng Liu , Zhaofeng Wang
  
  Cite: Pan, P.-Z.; Tan, F.Y.; Li, F.Q.; Chi, F.D.; Liu, X.F.; Wang, Z.F., A three-dimensional numerical study on the stability of layered rock spillway tunnels in alpine canyon areas. Deep Resources Engineering 2024, 1 (2): 100023. https://doi.org/10.1016/j.deepre.2024.100023
• DRE I Research article I 2025(1): 100164
  Practice and validation of inversion of seismic source localisation based on genetic algorithm
  Quan Zhang, Junpeng Zou*, Yu-Yong Jiao, Jiapeng Gao
  
  Cite: Zhang, Q.; Zou, J.P.; Jiao, Y.-Y.; Gao, J.P., Practice and validation of inversion of seismic source localisation based on genetic algorithm. Deep Resources Engineering 2025, 2 (1): 100164. https://doi.org/10.1016/j.deepre.2025.100164
• DRE I Review I 2024(2): 100020
  Advances in dynamic test of deep rocks considering in-situ mechanical and hydraulic conditions
  Kaiwen Xia*, Minlei Wang, Yan Fu, Bangbiao Wu, Ying Xu, Wei Yao*
  
  Cite: Xia, K.W.; Wang, M.L.; Fu, Y.; Wu, B.B.; Xu, Y.; Yao, W., Advances in dynamic test of deep rocks considering in-situ mechanical and hydraulic conditions. Deep Resources Engineering 2024, 1 (2): 100020. https://doi.org/10.1016/j.deepre.2024.100020
• DRE I Review I 2024(3): 100113
  Advances in stability analysis and optimization design of large underground caverns under high geostress condition
  Long Li, Quan Jiang*, Qingfu Huang, Tianbing Xiang, Jian Liu
  
  Cite: Li, L.; Jiang, Q.; Huang, Q.F.; Xiang, T.B.; Liu, J., Advances in stability analysis and optimization design of large underground caverns under high geostress condition. Deep Resources Engineering 2024, 1 (3): 100113. https://doi.org/10.1016/j.deepre.2024.100113