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51316-7091-Improvement to Cathodic Protection Performance using DCVG Prioritization

Picture for Improvement to Cathodic Protection Performance using DCVG Prioritization
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This paper will show improvements in interpretation of direct current voltage gradient % IR and how accurate selection of pipeline coating rehabilitation location based on this concept would lead to improvements in cathodic protection performance. Case studies from previous external corrosion direct assessment digs will be presented.

Product Number: 51316-7091-SG
ISBN: 7091 2016 CP
Author: Chukwuma Onuoha
Publication Date: 2016
Industries: Pipelines, Tanks, and Underground Systems , Corrosion Monitoring and Control
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$20.00
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Due to the serious consequences of corrosion and leaks in underground pipelines external corrosion direct assessment (ECDA) as described in ANSI/NACE SP0502 was developed in an attempt to proactively prevent external corrosion and ensure the integrity of oil and gas pipelines that are difficult to pig. This standard requires a minimum of two indirect inspections to confirm the most susceptible locations on a pipeline for external corrosion to occur.Cathodic protection close interval survey (CP CIPS) and direct current voltage gradient (DCVG) are usually complimentary indirect inspection techniques used for assessing the effectiveness of the cathodic protection and coating performance. DCVG detects coating anomalies due to voltage gradient created as a result of direct current flow to coating anomaly. Coating severity index or DCVG % IR is used to prioritize coating anomalies for repair with the intent of improving the cathodic protection performance.Coating anomalies with large DCVG %IR are thought to have greater risk for external corrosion during ECDA; possibly due to large exposed metal to corrosive environment. However considering that a large coating anomaly would consume more CP current the tendency for corrosion is expected to be minimal.This paper will show improvements in interpretation of DCVG % IR and how accurate selection of pipeline coating rehabilitation location based on this concept would lead to improvements in cathodic protection performance. Case studies from previous ECDA digs will be presented.

Key words: downloadable, External Corrosion Direct Assessment, DC voltage gradient, close interval survey, cathodic protection, coating anomaly, data interpretation, severity classification

Due to the serious consequences of corrosion and leaks in underground pipelines external corrosion direct assessment (ECDA) as described in ANSI/NACE SP0502 was developed in an attempt to proactively prevent external corrosion and ensure the integrity of oil and gas pipelines that are difficult to pig. This standard requires a minimum of two indirect inspections to confirm the most susceptible locations on a pipeline for external corrosion to occur.Cathodic protection close interval survey (CP CIPS) and direct current voltage gradient (DCVG) are usually complimentary indirect inspection techniques used for assessing the effectiveness of the cathodic protection and coating performance. DCVG detects coating anomalies due to voltage gradient created as a result of direct current flow to coating anomaly. Coating severity index or DCVG % IR is used to prioritize coating anomalies for repair with the intent of improving the cathodic protection performance.Coating anomalies with large DCVG %IR are thought to have greater risk for external corrosion during ECDA; possibly due to large exposed metal to corrosive environment. However considering that a large coating anomaly would consume more CP current the tendency for corrosion is expected to be minimal.This paper will show improvements in interpretation of DCVG % IR and how accurate selection of pipeline coating rehabilitation location based on this concept would lead to improvements in cathodic protection performance. Case studies from previous ECDA digs will be presented.

Key words: downloadable, External Corrosion Direct Assessment, DC voltage gradient, close interval survey, cathodic protection, coating anomaly, data interpretation, severity classification

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