TY - JOUR
T1 - Analytical detection methods for measuring residual corrosion inhibitors in oil and gas and other industrial facilities
AU - Bakdash, Rashed S.
AU - Younis, Muhammad Naeem
AU - Chanbasha, Basheer
AU - Oladepo, Sulayman A.
AU - Abdulhadi, Abdullatif
AU - Rasheedi, Nayif A.
AU - Alanazi, Nayef M.
AU - Ayodele O, Okunola
AU - Raji, Mukhtar
AU - Ahmad, Muhammad S.
AU - Al-Betar, Abdulrahman
N1 - Publisher Copyright:
© 2025 The Author(s).
PY - 2026/3
Y1 - 2026/3
N2 - Corrosion remains one of the most pervasive and costly challenges across industrial systems, particularly in oil, gas, and steam generation facilities. Corrosion inhibitors (CIs) are widely employed to mitigate metal degradation; however, monitoring their residual concentrations—termed residual corrosion inhibitors (RCIs) is essential to ensure adequate protection and regulatory compliance. This review presents a comprehensive and critical evaluation of analytical techniques currently used for the detection and monitoring of RCIs in industrial environments. Conventional methods such as colorimetric and spectrophotometric analyses, chromatography, mass spectrometry, and electrochemical approaches are systematically discussed, with emphasis on their principles, detection limits, operational advantages, and inherent limitations. Emerging technologies, including vibrational spectroscopies, surface-enhanced Raman spectroscopy, and electrochemical sensors, are also examined for their potential to provide more sensitive, rapid, and field-deployable RCI measurements. Despite significant progress, no universal standard method exists for RCI detection, mainly due to the diversity of inhibitor formulations and complex sample matrices. The review highlights the urgent need for collaborative industrial efforts to develop portable, cost-effective, and automated on-site detection systems capable of continuous and interference-free monitoring. Future directions are proposed to adopt green corrosion inhibitors and adapt analytical methods suitable for environmentally sustainable corrosion management.
AB - Corrosion remains one of the most pervasive and costly challenges across industrial systems, particularly in oil, gas, and steam generation facilities. Corrosion inhibitors (CIs) are widely employed to mitigate metal degradation; however, monitoring their residual concentrations—termed residual corrosion inhibitors (RCIs) is essential to ensure adequate protection and regulatory compliance. This review presents a comprehensive and critical evaluation of analytical techniques currently used for the detection and monitoring of RCIs in industrial environments. Conventional methods such as colorimetric and spectrophotometric analyses, chromatography, mass spectrometry, and electrochemical approaches are systematically discussed, with emphasis on their principles, detection limits, operational advantages, and inherent limitations. Emerging technologies, including vibrational spectroscopies, surface-enhanced Raman spectroscopy, and electrochemical sensors, are also examined for their potential to provide more sensitive, rapid, and field-deployable RCI measurements. Despite significant progress, no universal standard method exists for RCI detection, mainly due to the diversity of inhibitor formulations and complex sample matrices. The review highlights the urgent need for collaborative industrial efforts to develop portable, cost-effective, and automated on-site detection systems capable of continuous and interference-free monitoring. Future directions are proposed to adopt green corrosion inhibitors and adapt analytical methods suitable for environmentally sustainable corrosion management.
KW - Analytical detection methods
KW - Corrosion inhibitor
KW - Detection of residual corrosion inhibitor
KW - Oilfield waters
KW - Residual corrosion inhibitor
KW - Treated water supply wells
UR - https://www.scopus.com/pages/publications/105024855584
U2 - 10.1016/j.rineng.2025.108547
DO - 10.1016/j.rineng.2025.108547
M3 - Review article
AN - SCOPUS:105024855584
SN - 2590-1230
VL - 29
JO - Results in Engineering
JF - Results in Engineering
M1 - 108547
ER -