Topic: Myths and Misconceptions

Formal Risk Assessment—Is it helping me?

Ever consider that true risk management sometimes occurs only at the lower levels of some pipeline organizations?  That is, personnel performing field activities are in effect setting risk levels for the company.  Their choices of day-to-day activities are essentially driving risk management and thereby establishing corporate risk levels.  This is not just theoretical—real choices are […]

Myth Busting—I don’t have enough data (Part 2)

In the first part of this discussion, we hopefully dispelled some myths about low data availability.  We discussed how reasoning is used to generate data and how many useful pieces of risk insight emerge from even simple pieces of knowledge. We also contrasted a statistical approach to risk assessment with a physics based approach.  The […]

Pipeline Risk Assessment—Myth Busting Part 1

In the first installment of this column, we introduced the concept of pipeline risk assessment Essential Elements.  This is a list of ingredients that arguably must be included in any pipeline risk assessment.  In this installment, let’s examine “I can’t do good RA because I don’t have enough data.” There are at least two aspects […]

I want to keep using our relative points scoring system. I don’t see why we should change.

Perhaps first question is this: ‘is your scoring system really giving you new knowledge and useful insights into actual risks?’ If not, then that alone should be a compelling reason to change—especially when modern risk assessment is both more efficient and less expensive. See more extensive discussion here.

It sounds like you have methods that very accurately predict failure potential. Is this true?

Unfortunately, no. While the new modelling approaches are powerful and the best we’ve ever had, there is still huge uncertainty. We are unable to accurately predict failures on specific pipe segments except in extreme cases. With good underlying data, we can do a decent job of predicting the behaviour of numerous pipe segments over longer […]

What about the concern that a more robust methodology suffers more from lack of any data?

That is a myth. In the absence of recorded information, a robust RA methodology forces SMEs to make careful and informed estimates based on their experience and judgement. From direct estimates of real-world phenomena, reasonable risk estimates emerge, pending the acquisition of better data. Therefore, I would respond that lack of information should drive you […]

But if an estimate as to how often a pipeline segment will fail from a certain threat is needed, aren’t numbers needed to ascertain how often similar pipelines have failed in the past from that threat?

No, it’s not essential. It’s helpful to have such numbers, but not necessary and sometimes even counter-productive. Note that the historical numbers are often not very relevant to the future – how often do conditions and reactions to previous incidents remain so static that history can accurately predict the future? Sometimes, perhaps, but caution is […]

If the new risk assessment methods produce results similar to QRA, why not just use classic QRA?

Several reasons, classic QRA is expensive and awkward to apply to a long, linear asset in a constantly changing natural environment – can you imagine developing and maintaining event trees/fault trees along every foot of every pipeline? The classical QRA was created by statisticians and relies heavily on historical failure frequencies. Ask a statistician how […]

How can the new risk assessment methods be both easy and more informative?

More informative, since they produce the same output as the classic QRA but are more accurate. Easy, because they directly capture our understanding of pipelines and what can cause them to fail. The word ‘directly’ is key here – previous methods relied on inferential data and/or scoring schemes that tended to interfere with our understanding.