Calcium Carbonate Risk Index Assessment for Smart Completion Systems Employing Thermodynamic and Kinetic Precipitation Rates
Authors: Neubauer T. M. , Poletto V. G. , Mazuroski M. E. , De Lai F. C. , Junqueira S. L. M. , Castro B. B. , Martins A. L. 
Published: September 2024

The formation and deposition of inorganic salts on industrial equipment surfaces pose significant financial and technological challenges for various industries, particularly the oil industry, because of the transportation of multiphase fluids, such as water, oil, and gas, under high temperature, pressure, and salinity conditions (Crabtree et al., 1999; Kamal et al., 2018). Calcium carbonate scaling presents a particular challenge for scale control, as it is sensitive to pressure and temperature variations (Blue et al., 2017; Cosmo, 2013a; Du & Amstad, 2019). Smart completions are a favored method for production control and scale surveillance, as they enable the reduction of water production or the mixing of incompatible water chemistries (Bouamra et al., 2020; Santos et al., 2017). However, the design, size, and geometry of smart completion tools can impact the prevention of scaling deposition. Thus, there is a need to investigate operating conditions and equipment designs that can influence the formation and deposition of precipitates within the oil production process (Lai et al., 2020; Olajire, 2015).
A mathematical methodology has been developed to predict precipitation rates along the oil and gas workflow within these smart completions. This involves a comprehensive simulation of the particles, characterizing the kinetic, thermodynamic, and fluid-dynamic aspects of CaCO3 produced within the fluids in the oil and gas industry. Such a simulation can serve as a virtual sensor for potential analysis, control, and monitoring of incrustation problems, offering a more complete tool than the purely thermodynamic simulations typically used for prediction by the oil and gas industry (Bouamra et al., 2020; Lassin et al., 2018; Neubauer et al., 2022; Sanni et al., 2015).
The proposed methodology integrates calcium carbonate thermodynamics, kinetics, and flow dynamics along the production flow to assess the risk of CaCO3 precipitation. The simulation workflow combines a polymorphic population model to define the CaCO3 risk index based on particle kinetics, a multiphase thermodynamic model to simulate supersaturation conditions, and computational fluid dynamics to produce pressure and fluid flow profiles along the equipment. By combining these three models, kinetic and thermodynamic precipitation rates are calculated to obtain a comprehensive CaCO3 risk index. This work introduces one of the first approaches to characterizing the calcium carbonate risk index along the oil production process by incorporating both fluid dynamics and population modeling. The presented methodology offers a robust alternative for evaluating the criticality of various equipment designs and operating conditions within the oil industry. In addition to the conventional thermodynamic approach, this work will explore different methods to calculate the index using integrated thermodynamic, kinetic, and flow information.