Stepwise hydrogeological characterisation utilising a geosynthesis methodology; A Case study from the Mizunami Underground Research Laboratory project

Saegusa, Hiromitsu; Osawa, Hideaki  ; Onoe, Hironori ; Oyama, Takuya ; Takeuchi, Ryuji  ; Takeuchi, Shinji

The Mizunami Underground Research Laboratory (MIU) is now under construction in the Cretaceous Toki granite in the Tono area of central Japan. One of the main goals of the MIU project, which is a broad scientific study of the deep geological environment as a basis of research and development for geological disposal of nuclear wastes, is to establish comprehensive techniques for the investigation, analysis and assessment of the deep geological environment in fractured crystalline rock. For this purpose, a geosynthesis methodology has been developed and will be tested in a dry run to determine if it produces the data required for repository design and associated integrated safety assessment modeling. Surface-based hydrogeological characterization, intended to develop conceptual models of the deep geological environment based on an understanding of the undisturbed conditions before excavation of this URL, was carried out in a stepwise manner. This allows field investigations, construction of geological and hydrogeological models and interpretation of resultant groundwater flow simulations to develop in an iterative manner. Investigations have the goal of obtaining information on factors relevant to repository design, associated construction, operational and post-closure safety assessment, evaluation of the practicality of implementation and environmental impact assessment. Data obtained from field investigations is utilized for the construction of hydrogeological models and groundwater flow simulations, which can be used to identify and prioritize key issues for further investigations. Results show that such an approach, focusing hydrogeological characterizations by a structured geosynthesis methodology, leads to an improved understanding of the deep hydrogeological environment and allows repository-relevant datasets to be produced in an efficient and traceable manner.