Fractured Reservoir Characterization and Modeling: Challenges, Methods and Applications
A special issue of Geosciences (ISSN 2076-3263).
Deadline for manuscript submissions: closed (15 August 2022) | Viewed by 217
Special Issue Editor
Interests: reservoir characterization/stimulation; THMC modeling; geophysical inversion; uncertainty quantification; enhanced geothermal systems; deep learning
Special Issue Information
Dear Colleagues,
The purpose of this Special Issue is to collect original research articles on the characterization and modeling of fractured reservoirs with various applications in energy recovery, CO2 sequestration, waste storage, etc.
The exploitation of subsurface reservoirs is an essential component of the global effort to combat worldwide environment pollution and energy shortage issues. Major challenges in the development of subsurface reservoirs include the characterization of complex fracture networks and the modelling of multi-physics coupled thermal-hydro-mechanical-chemical (THMC) processes in fracture–rock systems. The characterization of fracture networks is often accomplished through the inversion of indirect hydraulic or geophysical data. Due to the generally spatially sparse data and complex fracture geometry/properties, such an inversion problem is highly ill-posed and requires advanced machine learning methods and inversion strategies to: 1) reduce model dimensionality to mitigate the ill-posedness issue; 2) develop efficient surrogate models to accelerate inversion processes; 3) quantify uncertainties through probability inversion methods. The rapid development of deep learning algorithms in recent years has led to new opportunities to further improve fracture network characterization.
The modelling of coupled THMC processes in fracture–rock systems is a long-standing challenge in subsurface reservoir development. High-density fractures make it extremely difficult to appropriately represent the effect of fractures and cause many issues in the numerical simulation of the underlying coupled THMC processes. Various methods have been proposed to tackle these difficulties and issues, such as the embedded discrete fracture model, extended finite element method, phase field, and so on.
Therefore, we would like to invite you to submit your recent research with respect to fractured reservoir characterization and modelling to this Special Issue. The topics include (but are not limited to):
- Fracture network characterization;
- Permeability/aperture inversion;
- THMC experiments and modelling in fractured reservoirs;
- Innovative machine learning algorithms for reservoir characterization;
- Advanced inversion/data assimilation methods for reservoir characterization.
Dr. Hui Wu
Guest Editor
Manuscript Submission Information
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Keywords
- fractured reservoir
- reservoir characterization
- coupled THMC modeling
- machine learning
- deep learning
- inversion
- data assimilation
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