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A Statistical Analysis of the Gamma Exponent Model; a New Methodology for Corrosion Assessment of Localized Metal Loss Flaws and Stress Corrosion Cracking in Oil and Gas Pipelines

Picture for A Statistical Analysis of the Gamma Exponent Model; a New Methodology for Corrosion Assessment of Localized Metal Loss Flaws and Stress Corrosion Cracking in Oil and Gas Pipelines
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Product Number: 51321-16368-SG
Author: Colin Scott, PhD
Publication Date: 2021
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The Gamma Exponent Model (“GEM”) is a recently developed methodology for failure pressure prediction of flaws in oil and gas pipelines. The model has already shown varied applicability for different flaw types. The focus of this work is axial metal loss flaws and axial stress corrosion cracking (SCC). The basic model is applicable to axial metal loss. The model is then modified to address issues associated with SCC. Specifically, this work demonstrates that a stress intensity factor relevant to periodic crack arrays, as observed in SCC colonies, can be used to account for crack-shielding. This results in more accurate failure predictions. The model is validated against available laboratory, hydrotest and in-service failure data. Statistical analyses are performed to demonstrate the mathematical form of the new model are valid. Failure pressure predictions are shown to be comparable or better than current industry models.

Keywords: fracture, corrosion management, stress corrosion cracking, risk

The Gamma Exponent Model (“GEM”) is a recently developed methodology for failure pressure prediction of flaws in oil and gas pipelines. The model has already shown varied applicability for different flaw types. The focus of this work is axial metal loss flaws and axial stress corrosion cracking (SCC). The basic model is applicable to axial metal loss. The model is then modified to address issues associated with SCC. Specifically, this work demonstrates that a stress intensity factor relevant to periodic crack arrays, as observed in SCC colonies, can be used to account for crack-shielding. This results in more accurate failure predictions. The model is validated against available laboratory, hydrotest and in-service failure data. Statistical analyses are performed to demonstrate the mathematical form of the new model are valid. Failure pressure predictions are shown to be comparable or better than current industry models.

Keywords: fracture, corrosion management, stress corrosion cracking, risk

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