Abstract
Abstract As a primary issue of its integrity and corrosion control program, Pan American Energy implemented on 2003 a corrosion monitoring program for both external and internal corrosion, for oil production and water injection systems, based on electrochemical techniques 1. For this purpose, 200 electrochemical sensors were installed in the most critical sectors of Cerro Dragón oilfield, with capability for both DC and AC electrochemical measurements, including Polarization Resistance (PR), Electrochemical Impedance Spectroscopy (EIS), ON-OFF potential depolarization curves and cathodic protection current. This work is entirely based on field measurements and describes observations and results obtained in the last year, regarding early detection of critical corrosion cases, corrosion mechanisms identification and assessment of corrosion mitigation systems efficiency (external and internal). As a result of the new monitoring program, the following relevant results were so far obtained: Three oil treatment plants were identified as high-risk systems from the corrosion standpoint.Cathodic protection inadequacies were detected in more than 50 % of the instrumented systems.Inefficiency in chemical treatment dosage for internal corrosion control was established in at least 17 % of the instrumented systems. These outcomes are based primarily on PR and EIS measurements, being the latest one of the first field applications in oil and gas industry. They also allow to conclude that the application of advance electrochemical techniques to corrosion monitoring of oilfields facilities, provides a powerful tool for instantaneous detection of changes in corrosion behavior and trends, due to variations in operating conditions, fluid aggressiveness and corrosion mitigation parameters. The use of this methodology applies to corrosion monitoring of pipelines, tanks and surface facilities, and provides a direct contribution to technical knowledge in corrosion mechanisms identification, corrosion mitigation efficiency assessment, corrosion trend prediction and actual correlation between corrosion and operating variables.
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