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Profiling

A risk profile is a view–graphical or tabulated–of changing risk along the length of the pipeline. The profile is an essential element of managing risk since it reveals aspects of risk such as the presence of systemic issues versus ‘hot spots’.

Underlying a profile is the data that indicating the changes in conditions or characteristics along the pipeline. Therefore, this discussion involves the following associated concepts:

Profiling Capability is an Essential Element

Elsewhere on this site, we introduced the concept of pipeline risk assessment Essential Elements (EE). That guideline is a list of ingredients that must be included in any pipeline risk assessment before that assessment can be considered complete. Following these guidelines helps to ensure a technically sound risk assessment that should satisfy all stakeholders, including regulators, and provide useful decision-making support to owner/operators. The EE risk assessment is a Quantitative Risk Assessment (QRA).

Numerical estimates of risk – a measure of some consequence over time and space, like ‘losses per mile-year’ – are the most meaningful measures of risk we can create. Anything less is a compromise. Compromises lead to inaccuracies; inaccuracies lead to diminished decision-making; leading to misallocation of resources; leading to more risk than necessary. Good risk estimates are highly valued. If you can get the most meaningful numbers at the same cost as compromise measures, why would you settle for less?

However, a pipeline QRA risk assessment differs in important ways from a QRA typically seen in the nuclear, chemical, and aerospace industries. In this installment, let’s note some key differences and examine the essential element dealing with one of those differences—the need for a risk profile.

Profiles in QRA

The idea of a risk profile—changes in risk over ‘space’—is what sets pipeline risk assessment apart from many other QRA applications. Traditional QRA is normally applied to facilities that do not occupy a constantly changing ‘space’. Even air- and spacecraft QRA’s make only limited use of changing environmental conditions—they tend to focus on the extreme conditions that govern design requirements.  On the other hand, long, linear assets like pipelines, highways, power lines, and others, must recognize changing surroundings as a key aspect of risk, which often changes constantly along a route.  It would not be productive to focus solely on a few locations that harbor the worst set of conditions.

There are similarities in QRA approaches, but some key differences emerge when comparing older QRA’s with the approach advocated here. Modern QRA’s are best performed using reductionism and are unique from others in several key respects:

  1. Efficient and independent examination of three distinct PoF ingredients: exposure, mitigation, resistance
  2. Substantially reduced reliance on historical incident rates.
  3. In the case of pipelines, we can add a third:  Methodology that efficiently accommodates long, linear assets with constantly changing environmental and loading conditions

#3 above reflects the need for a risk profile–a plot of changing risk (or any risk-related variable) along a route–as a key differentiating aspect from single-location assets. A profile acknowledges the unique aspects of long, linear assets, recognizing that there are many ‘individual’ pipe segments among the ‘population’ of segments that make up a pipeline. As with any treatment of populations vs individuals, behavior is much more accurately predicted for populations compared to individuals.

Profiles Preventing Missteps

Traditional QRA relies heavily on historical incident rates.  When applied to pipelines, this means that a pipeline—a population of pipe segments in varying environments—is modeled to behave as point estimates of populations of other, supposedly comparable pipelines—also collections of individual segments.  As the foundation for a risk assessment, this is potentially very inaccurate.  The use of a profile helps to avoid some common missteps in the use of historical data.

Let’s examine some of the implied assumptions embedded in the use of historical incident rates:

  1. When benchmarking against an overall average, the comparison population (collections of pipe segments from similar pipelines) can be accurately represented by a single value—ignoring extremes is appropriate; ie, the fact that some segments of pipelines may carry much less or much more risk, is not germane. This can be a serious misstep.
  2. Subject pipeline, considered as a whole, is fairly represented by the comparison population. Another potential misstep.
  3. All parts of subject pipeline behave similarly—the sum of the parts equals a value represented by the comparison. Again, potential for significant errors.

Obviously, such assumptions will very often be very incorrect.  It is a classic error of using the behavior of a population to estimate the behavior of an individual.  Population behavior is much more predictable than individual behavior. We are trying to understand the individual—ie, what are the risk issues for this particular segment of pipeline?  Risk management occurs on the segment level.

These potential missteps become apparent from the production of a profile since it forces the consideration of changing factors along the route—pipe properties (wall thickness, age, coatings, etc); operational parameters (pressure, temperature, etc); and the many environmental changes (soil types, population density, nearby structures, etc).  Some of these factors will change every few feet along the pipeline. 

When we use a profile to see variability along a pipeline route, we are less inclined to treat the pipeline as a single unit and more inclined to take the correct view of the pipeline as a collection of components, where differences in risk among components might be significant. So, a key first step is to divide the pipeline into segments appropriate for risk analysis.

Segmentation Drives the Profile

A profile is essentially a plot of segments’ value(s). So, segmentation drives the profile. Many, shorter segments results in a profile different from fewer, longer segments. Recall that segment density (segment count per mile) can be an indication of data quality.

This image has an empty alt attribute; its file name is profile.png

Profiles Support Risk Management

The end game in risk assessment is of course risk management.  In risk management practice as with risk assessment, a potentially high segment count emerging from full risk assessment should not be worrisome.  The count will not be burdensome to processes that rely on the assessment results since profiles can be readily summarized.  Proper aggregation allows a ‘summary’ risk value for any stretch of pipe, regardless of the number of changes in risk properties along that stretch. 

Summary values for a pipeline section–a collection of segments–can include averages, medians, ranges, maximums, standard deviations, and many others. Generating summary values via proper aggregation is critical since any improper approach can lead to masking of real issues.  This is fully discussed in segmentation and length-effects.

Prior to any summarization, however, the profile itself reveals some risk management challenges.  Note the sample figure above.  The two pipelines have different lengths and widely different risk profiles.  Even if the risk estimates underlying these profiles is perfect, risk management solutions are not immediately obvious—which pipeline warrants more immediate attention?  Longer lengths of ‘medium risk’ pipeline may be just as troubling as ‘risk spikes’. 

Basic plotting mathematics tells that the ‘area under the curve’ can be a very useful summary value when comparing multiple plots (profiles).  But it is often incomplete as a summary value. Imagine that, in the previous plot, the two profiles have exactly the same ‘area under the curve’. Given that summary number alone, one might believe the risks were identical. Viewing the profiles reveals that, even though the final risk values may be identical, the causes and hence the solutions to the risk are very different.

Once a pipe section—again, a collection of segments—becomes a candidate for risk management based on some summary value, we go back to the profile. The drill-down (via profiles) quickly reveals the cause(s) of all risk issues.  Risk mitigation plans are then made accordingly. 

Proper risk management cannot even begin until the risk profile is understood.  That is why the profile is an essential element of pipeline risk assessment.

Published inPMMRisk Management