Sulfate minerals (barite, anhydrite and celestite) can be of technological hindrance as a result of scale formation especially at those productions where sea water injection involves. Situation could become even more challenging when producing from high-pressure/high-temperature (HP/HT) wells since it demands the highest-performance equipment's and accurate understanding of brine chemistries. Because of the lack of relevant experimental data, prediction of mineral scaling risk is generally being made assuming that there is no additional kinetic effect of the pressure even at ultra-high pressure level. Therefore, this study seeks to investigate whether there is additional risk involved due to the kinetic effect of the pressure. Just as there is a kinetic activation energy, E, we have measured a corresponding activation volume, V. Specifically, it aims to experimentally determine the magnitude of the effect of the pressure on sulfate mineral scaling kinetics at deep-water production environment.

To accomplish the goal, a flow-through apparatus has been developed to perform precipitation reaction of barite, anhydrite and celestite at range of pressures (15- 15,000 psia), temperature (up to 2000C), and at various TDS levels. Mineral nucleation (precipitation) kinetics as a function of the pressure was investigated under similar thermodynamic driving force (supersaturation level). Based on the experimental data, a robust semi-empirical barite nucleation model that correlates the precipitation kinetics (induction time) to T, P, SI was developed. The nucleation model is used to estimate the barite precipitation kinetics using simulated field conditions with and without including the kinetic effect of the pressure. Our results indicate that these sulfate mineral nucleation kinetic is a strong function of applied pressure. In fact, the actual mineral nucleation time at elevated pressure (e.g. 15,000 psia) could be more than two orders of magnitude faster than expected when kinetic effect of the pressure is neglected. We believe that our findings could potentially provide some insights to discrepancies between our prediction and field observations.

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