Abstract
Abstract The formation and deposition of inorganic salts on industrial equipment surfaces pose significant financial and technological challenges for various industries, particularly the oil industry, due to the transportation of multiphase fluids such as water, oil, and gas under high temperature, pressure, and salinity. (Crabtree, M., Eslinger, D., Fletcher, P., Miller, M., Johnson, A., King, 1999; Kamal et al., 2018a). These conditions can bring significant challenges in scale control, especially for calcium carbonate scaling, which is a scale type that can be vulnerable to pressure and temperature variations (Blue et al., 2017; Cosmo, 2013a; Du & Amstad, 2019). To ensure optimal scale control and surveillance, smart completions have emerged as one of the most favorable approaches in the oil and gas industry. These completions offer real-time and selective zone control in oil and gas wells, minimizing unwanted water production and maximizing oil and gas production. They allow operators to isolate or produce specific zones, controlling or preventing mixing of incompatible water chemistries. Additionally, smart completions provide water shutoff capabilities, allowing operators to remotely control valves and downhole tools to shut off water-producing zones. This feature significantly reduces the undesirable production of water, commonly encountered during oil or gas production in mature reservoirs (Bouamra et al., 2020; H. F. L. L. Santos et al., 2017). However, the design, size, and geometry of the smart completion tool can impact the prevention of scaling deposition. As a result, there is a need to investigate operating conditions and equipment design that can promote the formation and deposition of precipitates within the oil production process (Kamal et al., 2018a; Sanni et al., 2022). To address this issue, a novel mathematical methodology has been developed to predict precipitation rates along the oil and gas workflow within these smart completions. A complete simulation of the particles, characterizing the kinetic, thermodynamic, and fluid-dynamic aspects of the CaCO3 produced within the fluids produced in the oil and gas industry, could be used as a virtual sensor for potential analysis, control and monitoring of incrustation problems, offering a more complete tool than the pure thermodynamic simulations that are usually used as prediction tools by the oil and gas industry (Bouamra et al., 2020; Lassin et al., 2018; T. Neubauer et al., 2022; Sanni et al., 2015). The proposed methodology involves the use of 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 particle kinetics, a multiphase thermodynamic model to simulate supersaturation conditions, and computational fluid dynamics to produce the pressure and fluid flow profiles along the equipment. The combined simulation of the three models produces kinetic and thermodynamic precipitation rates that are used to obtain a CaCO3 risk index. This work describes the model calculations to assess calcium carbonate formation in an open-hole completion assembled with a perforated liner composed of multiple tiny, drilled holes along the production tubing.
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