In this study, scales of all sections of geothermal facilities were taken. The database consists of scale samples from 13 geothermal pumps, 6,000 m production pipe (sample interval 10 - 12 m), 11 heat exchanger revisions, 2 injection pipes, and numerous filter elements. The samples were analyzed by SEM-EDX, XRD, Raman spectroscopy, and acid digestion to assess their chemical and mineralogical composition. From direct gauge measurements at six facilities during pump changes, scale rates were determined along the production pipes. From indirect measurements (multifinger caliper measurements) scale rates are derived for the region below the pump. Hydrochemical analyses from the wellhead were taken from 13 sites to feed the hydrogeochemical models. The calcite scale rates in the production pipes increase from the pump to the wellhead, where they reach 1.5 - 4.1 µmol/m² s. Scale rates below the pump reach up to 1.5 µmol/m² s. Given the slight change of hydrochemistry on the rise through the production pipe, where < 4 % of dissolved calcium ions precipitate as scale, scale rates cannot be derived from water samples at the wellhead, but require direct gauge measurements. The small amount of precipitation, together with fully turbulent conditions suggests that all measured rates are controlled by the surface-reaction of calcite crystallization following the nomenclature of Appelo and Postma (2004). Two approaches are used for the modeling of the scale rates. The first approach is based on hydrogeochemical modeling with PHREEQC. Scale rates calculated by this method are one order of magnitude higher than the measured ones. The second approach is based on correlations between the measured scale rates at the wellhead at six facilities and identified thermodynamic scale drivers \Delta log(pCO2), \Delta total pressure, \Delta pH, and SIcalcite. The correlations allow linear regressions which are used for the prediction of the scale rate at the wellhead, along the whole production pipe, and below. The modeling results show that scale prediction based on the new regressions that rely on thermodynamic scale drivers works better than existing hydrogeochemical models, already without implementation of kinetic parameters (CO2-stripping and magnesium inhibition).
Full article at https://geothermal-energy-journal.springeropen.com/articles/10.1186/s40517-020-00180-x