Quantification of scalings in dynamic environments using a combination of Quartz Crystal Microbalance and Raman Microscopy

Abstract

In Bavaria, the exploration of geothermal energy from the carbonates in the Upper Jurassic reservoir is a promising and growing field, but the efficiency is seriously affected by scaling, i.e., the precipitation of CaCO3. Predictive maintenance tools aim to reduce service intervals and unexpected downtimes based on measurements and a prediction of the state of the installations. With regard to scaling, this requires forward modeling of carbonate precipitation. However, standard models overpredict the amount of precipitates, and data required for localized process parametrization under dynamic flow conditions is scarce. For hybrid multiphase models, this data has to include local hydrogeochemistry, shear forces, and interaction forces of the precipitates with the matrix. Our new experimental approach combines the quantitative measurement of the amount of precipitates using a highly sensitive quartz crystal microbalance (QCM) measurement with the qualitative analysis of the individual crystals with Raman microspectroscopy. The setup consists of a microfluidic flow channel in which NaOH solution and Munich tap water (carbonate-rich) were injected and allowed to mix under varying flow conditions. The increase in the pH value caused nucleation and precipitation, which was monitored in real-time. The experiments showed many newly formed carbonate particles, but only some of the particles were actually deposited on the QCM crystal. The remaining particles were not able to settle at the given flow velocities and flushed out of the microfluidic channel. The stability of the signal degraded in long-term experiments. Therefore, quantitative measurements are limited to shorter times (up to 1 day in our case) with semi-quantitative data beyond that time. For those short time frames, the combination of Raman microscopy and QCM allows to quantify the process of scaling formation under very controlled dynamic conditions.