Procedure for estimating salinity distribution based on resistivity data for a rock mass

Site characterization work will be conducted to understand the geological environment around any site of possible interest for geological disposal of HLW. An approach to reduce uncertainty in the understanding of a geological environment is to increase the investigation density. However, it can be costly and time consuming. Therefore, any increase in investigation density should be done as effectively as possible. Hydrochemical properties, essential characteristics of any geological environment, are developed using hydrochemical data. The data are generally obtained by chemical analyses of groundwater samples from boreholes. However, hydrochemical samples, though taken selectively are not continuous and thus hydrochemical data are point data. On the other hand, the resistivity data, determined using continuous borehole geophysical logging, can be used to estimate the hydrochemical (salinity) distribution. Therefore, if salinity distributions can be estimated from resistivity data, investigation density would be effectively higher. This study has aimed to develop the methodology for estimation of salinity distribution by resistivity data of the boreholes drilled around the Horonobe URL in Hokkaido, northern Japan. JAEA has established the URL as a part of the national R&D program for geological disposal of HLW. In addition, the technical knowledge and know-how learnt through this study are summarized as a "case-base (data base of investigation examples)" to incorporate into the Information Synthesis and Interpretation System (ISIS) that has been developed by JAEA for the Ministry of Economy, Trade and Industry, as a part of its supporting program in 2007. The procedure for estimation of salinity is as follows; (1) Confirmation the applicability of the data of resistivity logging, (2) Conversion of resistivity data to salinity, (3) Comparison of the results of chemical analyses and the calculated results in (2). This study shows that calculated salinity agree well with chemical analyses of groundwater. This suggests that resistivity data are applicable to estimates of salinity. The technical knowledge and know-how accumulated during this study for using resistivity data are as follows; -The induction sonde for resistivity logging has a transmitter and three receivers, which are "short", "medium", and "long", related to the distance between transmitter and receivers. The long induction data should be used to estimate salinity because salinity in immediate vicinity of borehole was changed by drilling fluid and/or drilling mud. -The resistivity data obtained is a combination of the resistivity of rocks and of groundwater. In this case, influence of rock resistivity is negligible because resistivity of dried rock cores is different in three classes from groundwater and is almost constant with depth. -Moisture content will be main factor for controlling the resistivity of rocks. Therefore, porosity data should be prepared to decrease uncertainty with calculated salinity. In conclusion, systematic investigation procedure to estimate salinity distribution based on resistivity data has been identified. Furthermore, technical knowledge and know-how obtained through the application procedure have been summarized. These indicate that this study would be a good case example for the estimation of salinity distribution using resistivity data.