Hydrate Risk Assessment and Restart-Procedure Optimization of an Offshore Well Using a Transient Hydrate Prediction Model
A produced-hydrocarbon stream from a wellhead encounters formation of solid gas-hydrate deposits, which plug flowlines and which are one of the most challenging problems in deep subsea facilities. This paper describes a gas-hydrate model for oil-dominated systems, which can be used for the design and optimization of facilities focusing on the prevention, management, and remediation of hydrates in flowlines. Using a typical geometry and fluid properties of an offshore well from the Caratinga field located in the Campos basin in Brazil, the gas-hydrate model is applied to study the hydrate-plugging risk at three different periods of the well life. Additionally, the gas-hydrate model is applied to study the performance of the injection of ethanol as a thermodynamic hydrate inhibitor in steady-state flow and transient shut-in/restart operations. The application of the transient gas-hydrate model proved to be useful in determining the optimal ethanol concentration that minimized the hydrate-plugging risk.
Offshore explorations in deeper and colder waters impose more-challenging scenarios to the flow assurance of the produced streams. High pressures and low temperatures of operation of production facilities with longer subsea tiebacks will promote the formation of natural-gas hydrates: crystalline compounds formed be hydrogen-bonded water molecules in a lattice structure that is stabilized by encapsulating a small guest molecule (e.g., methane and ethane) (Sloan and Koh 2008). Gas hydrates form in the presence of appropriate quantities of gas and water, and are considered one of the most challenging problems in subsea facilities because of their rapid formation compared with other solid deposits (Sloane 2005).
Addressing the Gaps in Subsea Produced Water Treatment
Operators are looking for ways to better handle water coming from subsea wells, which is typically treated at topside facilities. Subsea separation systems are not equipped to discharge water back into the reservoir, so how do companies close the gaps?
Neural Networks Plus CFD Speed Up Simulation of Fluid Flow
High-fidelity 3D engineering simulations are valuable in making decisions, but they can be cost-prohibitive and require significant amounts of time to execute. The integration of deep-learning neural networks with computational fluid dynamics may help accelerate the simulation process.
Greedy Pursuit: Algorithms Show Promise in Measuring Multiphase Flow
“Greedy pursuit” in the realm of algorithms is a good thing. Saudi Aramco studied such algorithms to produce images simulating the flow inside a pipe’s cross section, possibly reducing the need for separator-based multiphase flowmeters.
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