TY  - JOUR
AU  - Wu, Hao
AU  - Lyu, Xinrui
AU  - Shang, Xiaofei
AU  - Huang, Xiaokai
AU  - Chang, Yanhai
PY  - 2026
DA  - 2026/08/08
TI  - A Sensitivity-Driven Inversion Framework for Efficient Calibration of 3D Geomechanical Models: Application to a Shale Reservoir
JO  - Reservoir Science
T2  - Reservoir Science
JF  - Reservoir Science
VL  - 2
IS  - 4
SP  - 305
EP  - 323
DO  - 10.62762/RS.2026.836628
UR  - https://www.icck.org/article/abs/RS.2026.836628
KW  - shale reservoir
KW  - geomechanical modeling
KW  - in-situ stress
KW  - sensitivity analysis
KW  - parameter inversion
KW  - cross-block transfer
AB  - Accurate in-situ stress characterization is essential for hydraulic fracturing design in shale reservoirs, yet 3D geomechanical model calibration still relies on iterative trial-and-error procedures that are computationally intensive and physically opaque. Sensitivity analysis, though widely used to evaluate the influence of elastic parameters, is typically treated as descriptive rather than predictive. This work proposes a sensitivity-driven inversion framework for efficient calibration of horizontal stresses in 3D geomechanical models. Controlled perturbation simulations on a baseline model quantify the responses of maximum and minimum horizontal stresses ($S_H$ and $S_h$) to variations in Young's modulus and Poisson's ratio across stratigraphic units. These responses form a sensitivity matrix establishing a first-order relationship between parameter perturbations and stress variations. A dual-objective inversion scheme then simultaneously constrains $S_H$ and $S_h$, enabling direct single-step parameter estimation and reducing reliance on iterative calibration. Application to a shale reservoir shows good agreement with reference stress profiles, with interval-averaged deviations reduced below 1%. Moreover, sensitivity relationships from a reference block serve as a first-order approximation for calibrating geologically similar neighboring blocks, demonstrating cross-block transfer potential. The framework offers an efficient, physically interpretable stress calibration approach and provides a practical alternative to conventional empirical methods.
SN  - 3070-2356
PB  - Institute of Central Computation and Knowledge
LA  - English
ER  - 

@article{Wu2026A,
  author = {Hao Wu and Xinrui Lyu and Xiaofei Shang and Xiaokai Huang and Yanhai Chang},
  title = {A Sensitivity-Driven Inversion Framework for Efficient Calibration of 3D Geomechanical Models: Application to a Shale Reservoir},
  journal = {Reservoir Science},
  year = {2026},
  volume = {2},
  number = {4},
  pages = {305-323},
  doi = {10.62762/RS.2026.836628},
  url = {https://www.icck.org/article/abs/RS.2026.836628},
  abstract = {Accurate in-situ stress characterization is essential for hydraulic fracturing design in shale reservoirs, yet 3D geomechanical model calibration still relies on iterative trial-and-error procedures that are computationally intensive and physically opaque. Sensitivity analysis, though widely used to evaluate the influence of elastic parameters, is typically treated as descriptive rather than predictive. This work proposes a sensitivity-driven inversion framework for efficient calibration of horizontal stresses in 3D geomechanical models. Controlled perturbation simulations on a baseline model quantify the responses of maximum and minimum horizontal stresses (\$S\_H\$ and \$S\_h\$) to variations in Young's modulus and Poisson's ratio across stratigraphic units. These responses form a sensitivity matrix establishing a first-order relationship between parameter perturbations and stress variations. A dual-objective inversion scheme then simultaneously constrains \$S\_H\$ and \$S\_h\$, enabling direct single-step parameter estimation and reducing reliance on iterative calibration. Application to a shale reservoir shows good agreement with reference stress profiles, with interval-averaged deviations reduced below 1\%. Moreover, sensitivity relationships from a reference block serve as a first-order approximation for calibrating geologically similar neighboring blocks, demonstrating cross-block transfer potential. The framework offers an efficient, physically interpretable stress calibration approach and provides a practical alternative to conventional empirical methods.},
  keywords = {shale reservoir, geomechanical modeling, in-situ stress, sensitivity analysis, parameter inversion, cross-block transfer},
  issn = {3070-2356},
  publisher = {Institute of Central Computation and Knowledge}
}