Geomechanical model calibration in the absence of in-situ stress magnitude data

Geomechanical modeling aims to predict the 3D in-situ stress state of the Earth’s crust and to assess the stability of subsurface rock volumes for applications such as radioactive waste disposal, energy storage, or CO₂ geo-sequestration. However, model calibration typically relies on sparse in-situ stress magnitude data which are expensive to acquire, limited in spatial coverage, and may not represent stress conditions over larger rock volumes, away from the measurement sites. Here we present a probabilistic forward-calibration framework that uses the borehole failure interpreted from routinely acquired borehole-image logs as indirect stress data and formation integrity tests (FIT) to calibrate 3D geomechanical models.

Our approach integrates four types of indirect stress observations: the occurrence of borehole breakouts (BO), drilling-induced tensile fractures (DITF), formation integrity tests (FIT), and the documented absence of both BO and DITF at micro-hydraulic fracturing (MHF) stations. Although these indirect data provide only upper and lower limits on the stress state, they offer the critical advantage of scanning the entire borehole trajectory with high resolution, yielding far more extensive spatial coverage than point measurements. The absence of borehole failure provides simultaneous upper and lower bounds on horizontal stress magnitudes, addressing a key limitation in previous approaches that struggled to constrain the maximum horizontal stress magnitude. We developed a forward uncertainty quantification framework that explores hundreds of thousands of model scenarios at each observation point using linear elastic principles and compares the agreement between predicted and observed stress indicators through a probabilistic assessment.

In the Zürich Nordost siting region for a potential deep geological repository for radioactive waste in northern Switzerland, we leverage an exceptional stress magnitude dataset from two deep boreholes. This dataset comprises 30 high-quality microhydraulic fracturing tests and 15 dry sleeve reopening tests, accompanied by comprehensive borehole image logs and detailed laboratory measurements of Young's modulus and rock strength. Using the stress magnitude data alone to calibrate the geomechanical model yields accurate stress predictions with well-constrained uncertainties, providing a rigorous benchmark against which to evaluate models calibrated solely with indirect stress indicators.

Our results demonstrate that stress predictions based solely on indirect observations achieve comparable accuracy to those calibrated with an exceptionally large and robust dataset of in-situ stress magnitude data. For the magnitude of the minimum horizontal stress S_hmin, high-agreement scenarios reproduce the reference stress predictions throughout most of the stratigraphic section, with uncertainties dominated by natural rock property variability rather than stress magnitude uncertainty. For the magnitude of the maximum horizontal stress S_Hmax, the approach successfully delivers constrains within physically realistic ranges, though systematic overestimation of 2–3 MPa in some formations suggests remaining model limitations. This work demonstrates that indirect stress data, readily available during routine drilling operations, can provide reliable, uncertainty-quantified stress predictions without requiring expensive in-situ stress measurement campaigns, opening new possibilities for stress field characterization in subsurface projects worldwide.