Reducing uncertainty in fractured carbonate reservoir models throughmultiscale discrete fracture network integration and dynamic calibration
Abstract
Fractured carbonate reservoirs are highly heterogeneous, and their multiscale fracture systems make it difficult to reliably characterize fracture geometry and hydraulic properties. This study presents an integrated discrete fracture network (DFN) approach for a Carboniferous fractured carbonate reservoir in the Kappa Field. Seismic interpretation and curvature attributes were used to identify fracture-related structural features and constrain their spatial distribution at the field scale. These results were integrated with fracture orientations and occurrences identified from borehole image logs and core observations to constrain fracture geometry at the well scale. Dynamic well-test data were then incorporated through transmissivity (KH) calibration to constrain fracture aperture and permeability and to evaluate the hydraulic behavior of the modeled network. The integration of these datasets provides complementary constraints on fracture geometry and hydraulic properties across different observation scales. The resulting DFN model shows improved consistency with the observed reservoir pressure response and provides a more reliable representation of fracture connectivity and hydraulic communication. This study demonstrates that integrating seismic interpretation, curvature attributes, borehole image logs, core observations, and dynamic well-test data provides a robust basis for reducing uncertainty in DFN construction and developing fracture models for reservoir simulation and field development planning.
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BibTeX
@article{hassan2026reducing,
title = {{Reducing uncertainty in fractured carbonate reservoir models throughmultiscale discrete fracture network integration and dynamic calibration}},
author = {Mohamed A. Hassan and Ahmed Abu El-Ata and Hazem Badreldin and Abdel Moktader A. El Sayed},
journal = {Scientific Reports},
year = {2026},
month = nov,
doi = {10.1038/s41598-026-73696-0},
url = {https://www.nature.com/articles/s41598-026-73696-0},
note = {CC BY 4.0},
}
RIS
TY - JOUR
TI - Reducing uncertainty in fractured carbonate reservoir models throughmultiscale discrete fracture network integration and dynamic calibration
AU - Mohamed A. Hassan
AU - Ahmed Abu El-Ata
AU - Hazem Badreldin
AU - Abdel Moktader A. El Sayed
PY - 2026
DA - 2026/11/02
JO - Scientific Reports
DO - 10.1038/s41598-026-73696-0
UR - https://www.nature.com/articles/s41598-026-73696-0
AB - Fractured carbonate reservoirs are highly heterogeneous, and their multiscale fracture systems make it difficult to reliably characterize fracture geometry and hydraulic properties. This study presents an integrated discrete fracture network (DFN) approach for a Carboniferous fractured carbonate reservoir in the Kappa Field. Seismic interpretation and curvature attributes were used to identify fracture-related structural features and constrain their spatial distribution at the field scale. These results were integrated with fracture orientations and occurrences identified from borehole image logs and core observations to constrain fracture geometry at the well scale. Dynamic well-test data were then incorporated through transmissivity (KH) calibration to constrain fracture aperture and permeability and to evaluate the hydraulic behavior of the modeled network. The integration of these datasets provides complementary constraints on fracture geometry and hydraulic properties across different observation scales. The resulting DFN model shows improved consistency with the observed reservoir pressure response and provides a more reliable representation of fracture connectivity and hydraulic communication. This study demonstrates that integrating seismic interpretation, curvature attributes, borehole image logs, core observations, and dynamic well-test data provides a robust basis for reducing uncertainty in DFN construction and developing fracture models for reservoir simulation and field development planning.
SN - 2045-2322
ER -