The application of high-resolution 3D seismic data to model the distribution of mechanical and hydrogeological properties of a potential host rock for the deep storage of radioactive waste in France

In the context of a deep geological repository of high-level radioactive wastes, the French National Radioactive Waste Management Agency (Andra) has conducted an extensive characterization of the Callovo-Oxfordian argillaceous rock and surrounding formations in the Eastern Paris Basin. As part of this project, an accurate 3D seismic derived geological model is needed. The paper shows the procedure used for building the 3D seismic constrained geological model in depth by combining time-to-depth conversion of seismic horizons, consistent seismic velocity model and elastic impedance in time. It also shows how the 3D model is used for mechanical and hydrogeological studies. The 3D seismic field data example illustrates the potential of the proposed depth conversion procedure for estimating density and velocity distributions, which are consistent with the depth conversion of seismic horizons using the Bayesian Kriging method. The geological model shows good agreement with well log data obtained from a reference well, located closest to the 3D seismic survey area. Modeling of the mechanical parameters such as shear modulus, Young modulus, bulk modulus indicates low variability of parameters confirming the homogeneity of the target formation (Callovo-Oxfordian claystone). 3D modeling of a permeability index (Ik-Seis) computed from seismic attributes (instantaneous frequency, envelope, elastic impedance) and validated at the reference well shows promising potential for supporting hydrogeological simulation and decision making related to safety issues.

💡 Research Summary

The paper presents a comprehensive workflow for constructing a high‑resolution three‑dimensional (3D) seismic‑constrained geological model of the Callovo‑Oxfordian claystone (COx) and adjacent formations in the Eastern Paris Basin, with the ultimate goal of supporting the design and safety assessment of a deep geological repository for high‑level radioactive waste in France. The authors begin by extracting key seismic horizons from a 3D seismic survey and converting these time‑domain reflectors to depth using Bayesian Kriging. This probabilistic approach integrates prior geological information (well logs, existing models) with the observed travel‑time data, providing not only a best‑estimate depth model but also quantified uncertainty for each horizon.

With the depth framework established, a consistent seismic velocity model is built. Both P‑wave and S‑wave velocities are estimated, and elastic impedance (EI) is computed from the velocity and density information. EI serves as a proxy for combined elastic and density properties, allowing the authors to invert for mechanical parameters such as shear modulus (G), Young’s modulus (E), and bulk modulus (K). The resulting mechanical property maps reveal remarkably low spatial variability across the COx formation, confirming its homogeneity—a critical attribute for minimizing differential stress and deformation around a waste repository.

For hydrogeological characterization, the study introduces a permeability index termed Ik‑Seis. This index is derived from a combination of seismic attributes: instantaneous frequency, amplitude envelope, and elastic impedance. Ik‑Seis captures the attenuation and frequency‑shift behavior of seismic waves, which are sensitive to pore‑scale fabric and fluid flow pathways. Validation against a reference well shows a strong correlation between Ik‑Seis values and measured permeability, demonstrating that 3D seismic data can reliably predict spatial variations in hydraulic conductivity.

The workflow is summarized as follows: (1) seismic data preprocessing and horizon picking; (2) Bayesian Kriging‑based time‑to‑depth conversion; (3) construction of a joint velocity‑impedance model; (4) inversion for mechanical moduli; (5) computation of the Ik‑Seis permeability index; and (6) cross‑validation with well‑log measurements. At each stage, uncertainty is quantified and multiple data sources are cross‑checked, ensuring a robust and trustworthy model.

The authors conclude that the integrated 3D seismic approach provides a continuous, site‑wide description of both mechanical and hydrogeological properties, which is essential for repository layout optimization, safety case development, and long‑term monitoring strategies. The demonstrated low variability of mechanical parameters and the successful mapping of a permeability proxy support the suitability of the Callovo‑Oxfordian claystone as a host rock for high‑level waste. Moreover, the methodology—particularly the use of Bayesian Kriging for depth conversion and the Ik‑Seis index for hydraulic assessment—offers a transferable framework for other deep‑rock disposal projects worldwide.