Optimized Gun Barrel Based on Numerical Simulation to Produced Oil With Low BSW Content

Abstract

This work presents the methodology and results of the optimization of the internals (Inlet distributor, oil and water collectors) of a 20,000 BPD (0.037 m3/s) gun-barrel tank starting from an existing design. Computational fluid dynamics (CFD) was applied to simulate and evaluate the performance of various internal configurations. These simulations were performed to determine the best configuration to ensure efficient separation of the oil-water mixture and oil with a low BSW content < 2% at the outlet. The simulations were carried out using the commercial software ANSYS Fluent under the two-phase flow VOF model and k-ε realizable turbulence model. Further CFD simulations were performed to evaluate the behavior of the gun barrel tank under different operating conditions (Different inlet flow rate) and to determine the maximum operation flow which allows obtaining the crude-oil with a maximum BSW content of 0.5%. From the simulation results, an operating curve (operating flow vs retention time) was constructed. This information allows, in practice, to identify the inlet flow rate based on the desired content of BSW in the separated oil.

Evaluation of the Influence of Water Content in Oil on the Metrological Performance of Oil Flow Measurement Systems

“…API MPMS [16] defines requirements for the application of liquid flow measurement systems. According to this standard, the volumetric flow of oil in the standard measurement condition, that is, at a temperature of 20 • C and a static pressure of 101.325 kPa, is given by Equation (2).…”

“…The mathematical model that describes the relationship between the control factors From Tables 13 and 14 and Figure 11, the influence of fluid temperature (x 1 ) and flow rate (x 2 ) on the response variable is statistically significant. Additionally, the quadratic portion of the fluid temperature (x 2 2 ) and the interaction between the fluid temperature and the flow rate (x 1 × x 2 ) influence the second-order model estimated for the response variable.…”

“…Globally, the oil and gas industry presents several challenges, especially in multiphase flow, where measurement uncertainties are due to different flow rates and BSW [1]; on the other hand, different operating conditions (flow and temperature) can be correlated with a maximum BSW content to ensure reliable measurements [2]. Furthermore, in offshore oil production, fluctuations in flow rates and BSW content can destabilize the process, resulting in operational losses and environmental fines [3].…”