Permeation Damage of Polymer Liner in Oil and Gas Pipelines: A Review

材料科学 渗透 聚合物 傅里叶变换红外光谱 复合材料 极限抗拉强度 差示扫描量热法 扫描电子显微镜 化学工程 化学 生物化学 热力学 物理 工程类
作者
Hafiz Usman Khalid,Mokhtar Che Ismail,Norlin Nosbi
出处
期刊:Polymers [Multidisciplinary Digital Publishing Institute]
卷期号:12 (10): 2307-2307 被引量:75
标识
DOI:10.3390/polym12102307
摘要

Non-metallic pipe (NMP) materials are used as an internal lining and standalone pipes in the oil and gas industry, constituting an emerging corrosion strategy. The NMP materials are inherently susceptible to gradual damage due to creep, fatigue, permeation, processing defects, and installation blunder. In the presence of acid gases (CO2, H2S), and hydrocarbons under high pressure and temperature, the main damage is due to permeation. The monitoring of possible damage due to permeation is not well defined, which leads to uncertainty in asset integrity management. Assessment of permeation damage is currently performed through mechanical, thermal, chemical, and structural properties, employing Tensile Test, Differential Scanning Calorimetry (DSC), Fourier-transform Infrared Spectroscopy (FTIR), and Scanning Electron Microscopy (SEM)/Transmission Electron Microscopy (TEM), to evaluate the change in tensile strength, elongation, weight loss or gain, crystallinity, chemical properties, and molecular structure. Coupons are commonly used to analyze the degradation of polymers. They are point sensors and did not give real-time information. Polymers are dielectric materials, and this dielectric property can be studied using Impedance Analyzer and Dielectric Spectroscopy. This review presents a brief status report on the failure of polymer liners in pipelines due to the exposure of acid gases, hydrocarbons, and other contaminants. Permeation, liner failures, the importance of monitoring, and new exclusive (dielectric) property are briefly discussed. An inclusive perspective is provided, showing the challenges associated with the monitoring of the polymer liner material in the pipeline as it relates to the life-time prediction requirement.
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