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ABSTRACT

Impressed current cathodic protection (CP) is one of the most effective means of corrosion control for well casings. In addition, computational modeling in this field has reached quite a mature stage, capable of offering cost-effective solutions during both the preliminary design stage and the subsequent monitoring stages in the productive lifespan.

During the design stage, computational modeling can be used to anticipate problems of interference and to identify configurations with optimal design according to the local environmental conditions.

While in principle performance monitoring of well casing CP systems is similar to pipelines, the fact that well casings are deployed in vertical direction makes the monitoring much more difficult. It is not generally possible from a practical point of view to have access to the soil-tocasing potentials. Hence, two different approaches are commonly used: E-Log I tests and voltage gradient measurements (CPET) along the casing. Then, proper interpretation from specialized technicians or engineers allows determining the level of performance of the complete corrosion control system. This approach requires experience and particularly in the case of CPET is an expensive procedure and on its own does not always provide detailed information of potential and normal current density profiles along the casing.

The aim of this paper is to demonstrate a number of applications in which computational modeling can benefit both the design stage and performance monitoring of CP systems for well casings. The basic mathematical background for 3D modeling with boundary elements is outlined. Case studies are presented demonstrating the use of modeling in the design phase of the system and in the performance monitoring of a well field and associated flow lines. Results are compared with field data to validate the model predictions and to highlight potential interference and other critical areas.

Keywords: CP, Cathodic Protection, Modeling, Multi-Layer soil, Well Casing, Boundary Element Method, design and monitoring

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