Guest Editors
Prof. Xian Shi
Email: xianshiupc@126.com
Affiliation: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, 266580, China
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Research Interests: geomechanics, reservoir stimulation, petroleum engineering big data, wellbore stability
Dr. Lei Han
Email: Xhan0414@126.com
Affiliation: School of Petroleum Engineering, Xi'an Shiyou University, Xi'an, 710065, China
Homepage:
Research Interests: geomechanics, oil and natural gas stimulation, machine learning prediction and analysis
Summary
The exploration and development of oil and gas resources are facing increasingly complex challenges, including deep/ultra deep reservoirs, unconventional oil and gas reservoirs (such as shale gas, tight oil), and improving oil recovery in old oil fields. In these processes, geomechanics plays an irreplaceable role as a key discipline that connects reservoir characteristics with development engineering. Traditional reservoir characterization often ignores geomechanical factors or only considers them as static parameters, resulting in deviations between development plans and actual geological conditions.
The special issue focuses on the integration of geomechanics with oil and gas, geological modeling, fine reservoir characterization, and advanced technologies such as artificial intelligence and digital twins, promoting the combination of theoretical breakthroughs and engineering practice.
Topics of interest include, but are not limited to:
1) Multi scale geomechanical modeling and reservoir characterization
2) Evolution of geostress field and dynamic response of reservoir
3) Geomechanics fluid coupling and productivity prediction
4) Application of intelligent algorithms in geomechanical parameter inversion
5) Geomechanics and fracturing optimization of unconventional reservoirs
6) Deep reservoir geomechanics and engineering risk control
7) Application of geomechanics in enhancing oil recovery efficiency
Keywords
oil and gas, geomechanical, big data analysis, optimization methods, geologic modelling, fine characterization of reservoirs, multi-scale, advanced technology
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