Observational analysis integrates geomechanical simulation with seismic modelling, revealing complex faults and implications for AI interpretation.
Fault complexity in seismic data can be more accurately represented by integrating geomechanical simulation and forward seismic modelling. A multi-layer stratigraphic model subjected to progressive deformation was constructed using the Discrete Element Method (DEM). Acoustic impedance fields derived from mechanical evolution provided the basis for calculating vertical reflection coefficients, which were then convolved with zero-phase Ricker wavelets using a 1D approach to produce synthetic seismic sections. Compared to conventional planar-fault representations, the resulting images display intricate reflector terminations, and amplitude dimming associated with distributed fault damage and rotated blocks. These results highlight that even a single fault, when modelled with physics-based deformation, produces richer and more varied seismic responses than matrix-deformation/warping approaches used to create labelled training datasets, providing a more geologically reliable basis for AI fault-segmentation and interpretation.
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Perez et al. (2026) studied this question.
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