№85-9
Modeling of deposit accumulation processes and optimization of their removal systems in main pipelines
V. Rastsvietaiev1, https://orcid.org/0000-0003-3120-4623
Jamil Haddad2, https://orcid.org/0000-0003-3787-0010
O. Pashchenko1, https://orcid.org/0000-0003-3296-996X
A. Shporta1, https://orcid.org/0000-0002-1260-7358
S. Tymchenko1 https://orcid.org/0000-0002-6314-420X
1Dnipro University of Technology, Dnipro, Ukraine
2Al-Balqa Applied University, Amman, Jordan
Coll.res.pap.nat.min.univ. 2026, 85:114–126
Full text (PDF)
https://doi.org/10.33271/crpnmu/85.114
ABSTRACT
Purpose. To develop a mathematical model for predicting the spatiotemporal accumulation of paraffin, asphaltene, mineral, and corrosion deposits in trunk pipelines and an integrated system for their prevention, removal, and predictive control, reducing flow assurance risks, energy losses, and operating costs.
The methods. CFD modeling based on the Navier-Stokes equations was combined with thermodynamic and kinetic deposition models in ANSYS Fluent/OpenFOAM using laboratory and field data. Sensitivity and Monte Carlo analyses assessed key parameters, while control strategies included chemical inhibition, pigging, thermal flushing, and optimized predictive scheduling.
Findings. Simulations predict deposit thicknesses of 8–18 mm after 180–365 days, with maximum accumulation occurring 40–70 km downstream due to cooling below the wax appearance temperature (WAT). Initial deposition fluxes of 0.8–6 g/(m2·day) decrease over time because of deposit aging and shear stripping. Organic deposits contain 45–75 wt% paraffins and 10–30 wt% asphaltenes, while inorganic fractions reach 15–45 wt%. The optimized hybrid strategy reduces pigging frequency by 40–65%, pumping energy losses by 28–35%, remediation and downtime costs by 40–55%, and corrosion rates by up to 50%, while maintaining 92–98% of design throughput.
The originality. Dependences of deposit formation intensity on temperature, flow velocity, fluid composition, wall roughness, and inhibitor efficiency were established using coupled CFD and thermokinetic modeling. Deposition aging patterns and zones of maximum accumulation under cooling below WAT were identified, and an adaptive predictive control algorithm for cleaning processes was developed.
Practical implementation. The proposed system enables predictive, risk-based flow assurance management, reducing chemical use, maintenance interventions, energy losses, shutdowns, and environmental risks while improving pipeline integrity and sustainability.
Keywords: trunk pipelines, deposit formation, modeling, wax appearance temperature, asphaltene deposition, predictive flow assurance, hybrid cleaning optimization.
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date of first submission of the article to the publication – 04/10/2026
date of acceptance of the article for publication after review – 05/11/2026
date of publication – 06/30/2026