Prediction of Pressure Drop in Subsea Pipeline Using Pipesim Software

Abstract

The number of offshore developments for which long-distance tie-back is usually implemented has increased recently, leading to increasing pressure loss concerns from such systems. In the literature, it revealed that pressure drop in multi-phase transport is quite complex to compute manually. Hence the need for multi-phase flow simulation software. PIPESIM is a leading industry software currently used in the oil and gas industry for multiphase flow simulation. In this study, a 64km subsea pipeline system comprising two sections; 23km, 22.064in ID and 41km, 24inch ID, coated with 3mm (0.003m) polyethene insulation and transporting multiphase hydrocarbon fluid in an ultra-deep-water field was modelled in PIPESIM. Network simulation for the base case was carried out at 114barg (114MPa) inlet pressure and 18.7MMSCfd gas flowrate. The observed system pressure drop was dependent on pipeline inlet pressure, flowrates, and internal pipe diameter. 13.8barg (13.8MPa) was lost from the system for the base case simulation. Sensitivity analysis carried out using Gas volumetric flowrates of 3, 12 and 18.7 MMSCFd. The inlet pressures of 57, 114 and 171barg combined with six different pipe diameters generated a unique combination of 81 data points that were used in the development of a pressure drop correlation using the LINEST regression analysis tool in Microsoft Excel. At high flowrate and high inlet pressure, the pressure-drop observed was minimal and vice versa. Also, at constant flowrates and inlet pressures, the pressure drop was observed to increase with increasing pipe sizes. An R² value of 0.9226 was obtained from the analysis. The plot of Predicted Pressure-drop against Calculated pressure-drop similarly gave an R² value of 0.8025. Both results showed usefully, and hence the developed correlation can be used as an estimate in the absence of PIPESIM software for pressure drop prediction purposes.

Keywords: Pressure drop prediction, Multi-flow Simulation, PIPESIM, Pipe sizing, Regression Analysis

DOI: 10.7176/IEL/10-2-06

Publication date:March 31^st 2020