Development of a non-invasive method for monitoring variations in salt concentrations of seawater using nuclear technique and Monte Carlo simulation. (August 2021) - Barbosa, Caroline M.; Kenup-Hernandes, Hericka O.; Raitz, Cesar; Dam, Roos Sophia de F.; Salgado, William L.; Lima, Inayá C.B.; Braz, Delson; Salgado, César M.
Abstract: In the oil production industry, water is used as a fluid injected into the well to raise the oil when the well is depressurized. Water thus produced presents variations in the concentrations of dissolved salts, as there is a mixture of different types of water, related to its origin (such as connate water, sea water). Because it is reused in oil production, water needs to be monitored to maintain the standard suitable for its use as it can be hypersaline, contributing to the encrustation of pipes and contamination of underground water reservoirs. In this study, a noninvasive method was developed to determine the salt concentration in seawater. The method uses a detection system that contains a NaI(Tl) detector, a 241 Am source, and a sample holder to measure the mass attenuation coefficient of saltwater samples. For validation, the same setup was also simulated using the MCNPX code. Saltwater samples with different concentrations of NaCl and KBr were used as a proxy for seawater. The mass attenuation coefficients for the simulation exhibited the smallest relative errors (up to 6.2%), and the experimental ones exhibited the highest relative errors (up to 25%) when compared with theoretical values. Highlights: Using a low energy radioactive source, a noninvasive method was designed to measure the salt concentrations (salinity) in seawater. To validate the method, five saline samples were prepared and titrated to yield precise densities. The mass attenuation coefficients of the samples were measured in experiments. The experiments were also simulated using the Monte Carlo method, and the results were compared to the XCOM reference values. The experimental results closely follow the linear behavior predicted by the Monte Carlo simulations.