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Record W2535025497 · doi:10.1115/ipc2000-100

The Evolution of Risk Management at Enbridge Pipelines

2000· article· en· W2535025497 on OpenAlexaboutno aff
Terris Chorney, Denise Hamsher

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicOffshore Engineering and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsPaceMultitudeDocumentationConsistency (knowledge bases)Risk analysis (engineering)Pipeline transportComputer scienceRisk managementNew product developmentProduct (mathematics)Operations researchEngineeringProcess managementBusinessMarketingEconomicsPolitical scienceManagementGeographyLaw

Abstract

fetched live from OpenAlex

1999 marks an important anniversary for Enbridge Pipelines Inc. of Canada and its U.S.-based affiliate, the Lakehead Pipe Line Company Ltd.: for 50 years we have been the primary link between the large oil production areas of western Canada and major market hubs in the U.S. midwest and eastern Canada. In retrospect, this strong history of success is chiefly due to thorough and logical planning and choice selection in all aspects of company endeavors. At Enbridge, as in countless other firms in a wide-range of industries, decision making was often the product of expert consensus and years of solid experience in dealing with similar situations. This approach has worked well for Enbridge and our stakeholders for five decades, as evidenced by the reliability, efficiency, and safety record of our pipeline system. However, as the millenium nears, we are increasingly finding formalized processes that integrate quantitative models and qualitative analysis helpful in planning and execution for both the short- and long-term. Several broad trends at the root of this movement include the heightened pace of change; the increasingly complex web of relevant factors; the growing magnitude of the consequences associated with sub-optimal decisions; the need for thorough documentation; and the apparent benefits of a framework that enables objectivity and consistency. In short, an approach that completely and systematically evaluates the multitude of dynamic factors that affect the ultimate outcome of the matter at issue is necessary. Although the term “risk management” is now often used to describe this process, Enbridge — along with many other responsible firms in the pipeline operating and other industries — has always practiced the underlying principles. This paper addresses the background of “risk management” in both the Canadian and U.S. pipeline industry, as well as accepted theory. It also encompasses the progression of risk management at Enbridge Pipelines, up to and including current initiatives. The usefulness of risk analysis, risk assessment, and risk management tools will be discussed, along with the overriding necessity of a well thought-out process, firm corporate commitment, and qualified expertise. Much of the focus will address the ongoing evolution and maturity of a comprehensive and well-integrated risk management program within the Enbridge North American business units. The criticality of maintaining focus on the core business function — in this case, pipeline operations — will also be addressed. In addition, past learning’s as well as future opportunities and challenges will be reviewed.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.647
Threshold uncertainty score0.165

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.003
GPT teacher head0.164
Teacher spread0.161 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2000
Admission routes1
Has abstractyes

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