Development and evaluation of combined methods for cleaning paraffin wax deposits in pipelines oil and gas industry

Purpose. To develop and assess the efficacy of combined mechanical, chemical, and thermal methods for removing paraffin wax deposits from extended pipelines with circular cross-sections and drilling systems, addressing operational challenges in the oil and gas industry. Methodology. A multidisciplinary approach was employed, integrating laboratory experiments, numerical modeling, and field trial validation. Laboratory tests used steel pipeline models and production tubing to simulate paraffin deposition under varying temperature (20–60 °C) and pressure (10–50 MPa) conditions. Deposit composition was analyzed via gas chromatography and mass spectrometry, while cleaning methods – mechanical pigging, chemical solvents, and thermal heating – were evaluated for removal efficiency. Computational fluid dynamics (CFD) simulations using ANSYS Fluent modeled deposition and cleaning dynamics, focusing on flow velocity, turbulence, and pipeline geometry. Field trials, where feasible, validated laboratory results on operational pipelines and drilling rigs. Findings. Combined methods achieved up to 90 % removal efficiency, with hybrid approaches (chemical solvents and mechanical pigging) outperforming single methods in high-paraffin oils and drilling tubing. Deposit thickness (2–5 mm) correlated with temperature gradients, with critical deposition zones identified in pipeline bends and drilling inlets. Mechanical methods were cost-effective (50–100 USD/m) but less efficient in smaller-diameter tubing, while thermal methods were energy-intensive (20–50 MJ/m). Recommendations include hybrid cleaning protocols and IoT-based monitoring for proactive maintenance. Originality. This study introduces a novel framework integrating mechanical, chemical, and thermal methods tailored to circular pipelines and drilling systems, with CFD models quantifying deposition dynamics. New insights into the interplay of pipeline geometry and drilling conditions enhance cleaning optimization. Practical value. The proposed methods reduce downtime by 20 % and maintenance costs by 15–25 %, with IoT integration enabling predictive maintenance. These solutions are applicable to diverse oil compositions and drilling environments, improving operational efficiency and environmental sustainability.