Special Issues

Geomechanical Issures in the Development of Reservoirs and New Energy

Submission Deadline: 31 December 2025 (closed) View: 1110 Submit to Journal

Guest Editor(s)

Prof. Xian Shi

Email: xianshiupc@126.com

Affiliation: School of Petroleum Engineering, China University of Petroleum (East China), Qingdao, 266580, China

Homepage:

Research Interests: geomechanics, reservoir stimulation, petroleum engineering big data, wellbore stability

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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

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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

Published Papers


  • Open Access

    ARTICLE

    Formation Pore Pressure Detection Using a Hybrid Model of Convolutional Neural Network and Machine Learning under Physical Constraints

    Xinniu Xu, Jinde Li, Hong Huang, Guangfu Cao, Yuhe Shi, Biao Ruan, Daojin Ge, Hu Yang
    Energy Engineering, DOI:10.32604/ee.2026.077889
    (This article belongs to the Special Issue: Geomechanical Issures in the Development of Reservoirs and New Energy)
    Abstract Accurate detection of formation pore pressure is a critical technology for ensuring the safety of oil and gas drilling and reservoir evaluation. Due to the heterogeneity of geological structures and the nonlinearity of stress-strain relationships, traditional empirical formulas and numerical simulation methods often fail to meet the precision requirements when detecting formation pore pressure, constrained by the limited amount of logging data. The physically-constrained convolutional neural network-Transformer (Phys-CNN-Transformer) hybrid architecture proposed in this paper enhances the accuracy and generalization capability of formation pore pressure detection. The convolutional operations in CNN learn the mapping relationships of… More >

  • Open Access

    ARTICLE

    Statistical Modeling and Prediction of Hydraulic Fracture Propagation in Carbonate Reservoirs

    V. V. Poplygin, A. Dieng, Min Wang, Xian Shi
    Energy Engineering, DOI:10.32604/ee.2025.074170
    (This article belongs to the Special Issue: Geomechanical Issures in the Development of Reservoirs and New Energy)
    Abstract Hydraulic fracturing in carbonate reservoirs presents unique challenges due to their complex pore structures and heterogeneous mechanical properties. This paper explores the application of statistical methods to improve fracture prediction and optimization in carbonate formations. Hydraulic fracturing is actively carried out on these formations. In order to properly plan hydraulic fracturing, it is necessary to identify the main factors affecting oil production after hydraulic fracturing. This study introduces an integrated framework combining information amount theory (IAT) and Gray relational analysis (GRA) to identify and rank the dominant parameters controlling hydraulic fracturing performance in heterogeneous carbonate… More >

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