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Robert Gordon University

Predicting hydrates plugging risk in subsea gas pipeline: CFD, analytical and linear regression modelling.

Abstract

dc:description.abstract

This study addresses critical limitations in managing hydrate plugging risk for gas pipelines. The main challenges lie in accurately predicting hydrate deposition rates and associated pressure drops. To overcome these limitations, the study developed and validated a 3D computational model using computational fluid dynamics (CFD) and mathematical models. The model simulates a 10-meter long, 0.0204-meter diameter horizontal pipe section. The core of the model employs Eulerian-Eulerian multiphase modeling within ANSYS Fluent software. This approach successfully predicted hydrate deposition rates within a ±10% uncertainty range across various subcooling temperatures and gas velocities. At lower gas velocities (4.7 m/s), the model exhibited significant improvement over existing methods. Compared to a 925.7% deviation from experimental results, the model outperformed an analytical model which underpredicted by 27-33%. Similarly, at higher velocities (8.8 m/s) and varying subcooling temperatures, the CFD model demonstrated high accuracy, with deviations ranging from a slight underprediction (1%) to a moderate overprediction (14%). The study revealed a significant finding related to pipewall shear stress. The model predicted a sequential increase in average shear stress along the pipe at different gas velocities (2 m/s, 4 m/s, 6 m/s, and 8 m/s). These values exceeded 100 Pa, aligning well with established experimental observations. Beyond deposition rates, the CFD model accurately predicted the location, phase changes, and pressure drop profiles during hydrate formation, agglomeration and deposition. This aligns with findings from previous experimental studies. Furthermore, the model achieved a mean relative error of 4%, significantly outperforming models with higher errors. The model for predicting plugging flowtime also yielded valuable results. While it underpredicted plugging time by a mean relative error of 9%, this level of discrepancy is considered acceptable for proactive intervention strategies. The study acknowledges practical limitations and emphasizes the need for field validation of its propositions. Nonetheless, the findings provide valuable insights and pave the way for future research in this domain.

Degree

thesis:*
Grantor dc:publisher.institution
Robert Gordon University
Year dc:date.issued
2024

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Umuteme, Oghenethoja Monday
Advisor dc:contributor.advisor
  • S.Z. Islam, M. Hossain and A. Karnik

Subjects

dc:subject × 5

Rights

Language dc:language
en

Identifiers

dc:identifier.*
Identifier
oai:rgu-repository.worktribe.com:2571400
https://doi.org/10.48526/rgu-wt-2571400
Author Identifier
0000-0002-2536-325X
OAI identifier oai:identifier
oai:rgu-repository.worktribe.com:2571400

Chain of custody

source
Harvested from
Robert Gordon University
Base URL
rgu-repository.worktribe.com/oaiprovider
Last updated
2026-07-24
Source record
OAI-PMH GetRecord
citation

Umuteme, Oghenethoja Monday. Predicting hydrates plugging risk in subsea gas pipeline: CFD, analytical and linear regression modelling.. Robert Gordon University, 2024. https://rgu-repository.worktribe.com/2571400/1/UMUTEME%202024%20Predicting%20hydrates%20plugging%20risk