Thermally induced release and generation of CO2 and C1–C4 hydrocarbons in Opalinus Clay from Mont Terri (Switzerland)

Claystone formations are candidate host rocks for high-level heat-emitting nuclear waste (HLW). Temperatures from 90 to 150 °C at the canister surface are discussed internationally as potential emplacement and storage conditions. The thermal energy emitted from waste containers will be transported into the host rock formation, accelerating chemical reactions including the release of sorbed and dissolved gases and the generation of new gases. This study investigated gas release and generation in Opalinus Clay from Mont Terri (Switzerland) at elevated temperature and pressure conditions relevant for HLW storage and beyond. Hydrous pyrolysis experiments were conducted in Dickson-type flexible gold-titanium reaction cells and gold capsules in the temperature range of 80–345 °C and at 20 MPa. CO_2(g) was the predominant product, followed by C₁–C₄ hydrocarbons, which decrease in abundance with increasing carbon atom number. Neither CO nor H₂S was detected. H₂ was generated only in high temperature experiments at 315 °C and 345 °C, respectively. A combination of CO_2(g) quantification, stable carbon isotopic composition data, thermodynamic calculations and aqueous fluid composition (dissolved ions, pH) demonstrated that ≥80 % of the measured CO_2(g) originated from carbonate mineral dissolution. The model calculations also suggest that the fraction of CO_2(aq) in DIC increases from ∼50 % at 80 °C to nearly 100 % at higher temperatures. Thermal transformation of organic matter represented an additional source for CO_2(g) and was the predominant process yielding the C₁–C₄ hydrocarbons. Our findings stress the importance of quantitative geochemical data for the safety assessment of potential host rocks for HLW storage. We demonstrated that two sources are involved in gas release and generation at temperatures relevant for HLW storage, e.g., in the Opalinus Clay – organic matter and carbonate minerals. Our data will contribute to numerical modelling studies and the refinement of feature, events, and processes (FEP) catalogues.