Search
Filters
Close

96051 QUANTITATIVE CORROSION RISK ASSESSMENT BASED ON PIG DATA

Product Number: 51300-96051-SG
ISBN: 96051 1996 CP
Author: Steven W. Rust, Patrick H. Vieth, Elden R. Johnson, Michael L. Cox
$0.00
$20.00
$20.00
In-line inspection of underground pipelines for corrosion damage using “smart” pigs is now quite common. With the advent of high-resolution pigs that can identifi large numbers of potential anomalies, more sophisticated methodologies are required for interpreting the results of an in-line inspection. Of particular interest is the probability that the depth of corrosion in a particular location exceeds a critical depth defined by the local pipe characteristics and maximum operating pressure. In this paper, a Bayesian statistical methodology for determining the probability that corrosion exceeds critical magnitude is presented. The estimated probabilities (from the posterior distribution) are based on an assumed pit depth distribution (the prior distribution), the pig call data produced by the in-line inspection (the data), and the detection and depth accuracy performance characteristics of the pig utilized (the data model). The resulting exceedance probabilities can be used with or without corrosion consequences to make inspection/maintenance policy decisions. Keywords: pipeline corrosion, in-line inspection, pig performance, Bayesian statistics, risk assessment
In-line inspection of underground pipelines for corrosion damage using “smart” pigs is now quite common. With the advent of high-resolution pigs that can identifi large numbers of potential anomalies, more sophisticated methodologies are required for interpreting the results of an in-line inspection. Of particular interest is the probability that the depth of corrosion in a particular location exceeds a critical depth defined by the local pipe characteristics and maximum operating pressure. In this paper, a Bayesian statistical methodology for determining the probability that corrosion exceeds critical magnitude is presented. The estimated probabilities (from the posterior distribution) are based on an assumed pit depth distribution (the prior distribution), the pig call data produced by the in-line inspection (the data), and the detection and depth accuracy performance characteristics of the pig utilized (the data model). The resulting exceedance probabilities can be used with or without corrosion consequences to make inspection/maintenance policy decisions. Keywords: pipeline corrosion, in-line inspection, pig performance, Bayesian statistics, risk assessment
PRICE BREAKS - The more you buy, the more you save
Quantity
1+
5+
Price
$20.00
$20.00
Product tags
Also Purchased
Picture for 07174 Risk Based Assessment of Underground Pipelines and Storage Tanks
Available for download

07174 Risk Based Assessment of Underground Pipelines and Storage Tanks

Product Number: 51300-07174-SG
ISBN: 07174 2007 CP
Author: J. F.M. Van Roij, A. Blaauw, W. E. Liek, S. A. Lewandowski, D. Dobie, L. Harris, A. M. Etheridge
Publication Date: 2007
$20.00
Picture for 99009 CORROSION RISK ASSESSMENT AND RISK
Available for download

99009 CORROSION RISK ASSESSMENT AND RISK BASED INSPECTION FOR SWEET OIL AND GAS CORROSION - PRACTICAL EXPERIENCE

Product Number: 51300-99009-SG
ISBN: 99009 1999 CP
Author: M. J. Pursell, C. Selman and M. F. Nielsen
$20.00
Picture for 96050 CORROSION PIG PERFORMANCE EVALUATION
Available for download

96050 CORROSION PIG PERFORMANCE EVALUATION

Product Number: 51300-96050-SG
ISBN: 96050 1996 CP
Author: Patrick H. Vieth, Steven W. Rust, Elden R. Johnson, Michael L. Cox
$20.00