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Beyond Incidents Counts: A Multi-Dimensional Statistical Analysis of Consequence Intensity and Recovery Dynamics in Oil and Gas Pipelines
Subject area: Science,Engineering and Technology · Area of research: Machine Learning
DOI: 10.64388/IREV10I4-1724185
Abstract
Pipeline incident surveillance often uses event counts or one consequence measure to set priorities, obscuring differences between total burden, consequence concentration, and service disruption. This study analyses 1,681 audited incidents across five categories: Bunkering (BK), Hot Tapping (HT), Ruptured Line Leak (RLL), Sabotage Explosive (SE), and Valve Insertion (VI), and a separate series of 120 monthly aggregates from January 2015 to December 2024. The weighted Composite Risk Score (CRS) combined category mean recorded volume, mean downtime, mean repair cost, and the 95th percentile of recorded volume. Consequence intensity was calculated as the mean incident-level outcome per reported affected kilometre. The SE ranked highest on the CRS (100.00), while VI had the highest recorded-volume and repair-cost intensity and RLL had the highest downtime intensity. Welch ANOVA and Kruskal–Wallis tests did not detect category differences for recorded volume, downtime, repair cost, or affected length (all p > 0.05); this is not evidence of equivalence. Recorded volume was not significantly associated with downtime (Pearson r = 0.0229, p = 0.348; Spearman ρ = 0.0255, p = 0.296), and simple regression explained 0.052% of downtime variation. In the separate monthly series, all four aggregate measures peaked in 2019 and were lower in 2024; additive decomposition showed May elevations in volume, downtime, and affected length, while repair cost peaked seasonally in October. HAC-adjusted linear trends were not significant. The findings support outcome-specific reporting rather than treating counts or a composite score as a complete risk measure.
Keywords
affected-length intensity; composite risk score; consequence analysis; downtime; pipeline incidents
How to cite this paper
@article{1724185,
author = {Ojeyemi Festus Oluwaseun, Amusa Kamoli Akinwale, Owoeye Samuel Oluyemi, Adejumobi Isaiah Adediji},
title = {Beyond Incidents Counts: A Multi-Dimensional Statistical Analysis of Consequence Intensity and Recovery Dynamics in Oil and Gas Pipelines},
journal = {Iconic Research And Engineering Journals},
year = {2026},
volume = {10},
number = {4},
pages = {3271-3283},
issn = {2456-8880},
url = {https://www.irejournals.com/formatedpaper/1724185.pdf},
abstract = {Pipeline incident surveillance often uses event counts or one consequence measure to set priorities, obscuring differences between total burden, consequence concentration, and service disruption. This study analyses 1,681 audited incidents across five categories: Bunkering (BK), Hot Tapping (HT), Ruptured Line Leak (RLL), Sabotage Explosive (SE), and Valve Insertion (VI), and a separate series of 120 monthly aggregates from January 2015 to December 2024. The weighted Composite Risk Score (CRS) combined category mean recorded volume, mean downtime, mean repair cost, and the 95th percentile of recorded volume. Consequence intensity was calculated as the mean incident-level outcome per reported affected kilometre. The SE ranked highest on the CRS (100.00), while VI had the highest recorded-volume and repair-cost intensity and RLL had the highest downtime intensity. Welch ANOVA and Kruskal–Wallis tests did not detect category differences for recorded volume, downtime, repair cost, or affected length (all p > 0.05); this is not evidence of equivalence. Recorded volume was not significantly associated with downtime (Pearson r = 0.0229, p = 0.348; Spearman ρ = 0.0255, p = 0.296), and simple regression explained 0.052% of downtime variation. In the separate monthly series, all four aggregate measures peaked in 2019 and were lower in 2024; additive decomposition showed May elevations in volume, downtime, and affected length, while repair cost peaked seasonally in October. HAC-adjusted linear trends were not significant. The findings support outcome-specific reporting rather than treating counts or a composite score as a complete risk measure.},
keywords = {affected-length intensity; composite risk score; consequence analysis; downtime; pipeline incidents},
month = {October},
doi = {https://doi.org/10.64388/IREV10I4-1724185}
}