An improved mapping adaptation method from three-dimensional non-solid geological information models to numerical computational models

Abstract

Three-dimensional (3D) geological information models and numerical computational models differ substantially in their representation objectives, geometric organization, parameter systems, and spatial scales, which makes direct conversion between the two difficult. This study proposes a mapping-adaptation framework for transforming surface- or interface-based non-solid geological information models into geomechanical numerical computational models. Four principal mismatch types are identified, including geometric representation, structural discretization, parameter and solution-condition inheritance, and spatial extent. Correspondingly, geometric solidification, local structural adaptation, parameter and solution-condition mapping, and engineering-oriented computational-domain adaptation are integrated into a continuous mapping procedure linking the geological information model, geometric solid model, volumetric mesh model, and numerical computational model. In the case study, Delaunay triangulation was used to subdivide the original borehole distribution and introduce 50 virtual boreholes as supplementary geological constraints. The mean stratigraphic-sequence similarity increased from 0.483 to 0.553, while the mean depth-discretized stratigraphic consistency rate increased from 0.233 to 0.440 after virtual-borehole augmentation. The reconstructed stratigraphic surfaces were subsequently converted into closed geometric solids, discretized into volumetric meshes, and assigned corresponding material parameters, constitutive relationships, boundary conditions, and loading conditions. The resulting model was then used to complete the numerical calculation workflow. The case study demonstrates the continuity and numerical executability of the proposed geological-to-numerical mapping framework. In the present case, the computational-domain adaptation component is included as a framework capability rather than quantitatively evaluated through domain-size sensitivity analysis. The numerical results are used to verify workflow feasibility rather than the predictive accuracy of a specific engineering response.