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← Dr. Aous Abdo

Founder background

Work from Dr. Abdo's time at HP. He did this as an employee of HP, so it is part of his background, not Analytica past performance.

Four decades of pipeline incidents, and the gap between reporting and resolution

Alberta had four decades of oil-spill records and no clear picture of what they showed. The analysis covered roughly 62,000 incidents and found the delays were in resolution, not reporting.

Client
Government of Alberta
Sector
Energy · Environment · Public sector
Role
Dr. Abdo, as an employee of HP
Period
38 years of records, 1975–2013
Result
~62,000 incidents analyzed
incidents over 38 years
~62,000incidents over 38 years
reported same day
94%reported same day
resolved same day
20%resolved same day

The problem

Alberta holds four decades of oil and pipeline incident records, and wanted to know what they showed: what caused the incidents, whether response was improving, and whether reactive maintenance was still defensible.

What was done

The team assembled roughly 62,000 incident records spanning 1975 to 2013 and joined them against public environmental and geological data from NASA, NOAA and the USGS, plus contemporary news reporting for context the official record didn't carry.

Then geospatial mapping of incident locations, time-series decomposition at yearly and monthly resolution, categorization by incident type, and distribution analysis of notification lag against time-to-completion.

Reporting vs. resolution

Reporting worked: 94% of incidents were reported the same day, and 100% within three days. The regulatory machinery around notification was doing its job.

Resolution lagged far behind. Only 20% of incidents were closed out the same day. Half took ten days or more. Some ran for months or years. Putting the notification and completion distributions side by side measured how long incidents stayed open after they were known.

~62,000 incidents · 1975–2013

Reporting lag against time to resolution, and the March 1997 outlierTwo distributions over the same buckets. Reporting lag is concentrated almost entirely in the first bucket: 94 percent of incidents were reported the same day and all of them within three days. Time to resolution is spread across every bucket — only 20 percent were closed the same day, and the distribution runs out through weeks and months. The distance between the two shapes is the exposure the engagement quantified. Below, a yearly incident count rising with extraction activity, with one month that doesn't fit the trend: March 1997, coinciding with a magnitude 4.0 earthquake 350 miles away — a temporal association the analysis surfaced, not a demonstrated cause.REPORTEDNearly every incident was reported within three days.94%RESOLVEDResolution time had never been measured before this work.20%SAME DAY1–3 DAYS4–10 DAYS11–30 DAYS1–3 MONTHSLONGERONE MONTH THAT DID NOT FITMarch 1997 — coincides with a magnitude 4.0 earthquake 350 miles away19752013
Reporting was fast and consistent; resolution was slow and spread out, and this work measured the gap between them. The two distributions share the same buckets and the same scale because the finding is the distance between them. The stated figures come from the engagement record; the shape of the tail is drawn from its description of the data, and the 1997 spike marks a temporal coincidence, not an established cause.

The spike

The time series showed a steady rise in incidents over the period, consistent with rising extraction activity. It also showed one anomalous spike, in March 1997, that did not fit the trend.

The spike coincided with a magnitude-4.0 earthquake approximately 350 miles away, on 31 March 1997. The analysis identified the temporal association; it did not establish causation.

Capability

Large-scale record analysis, geospatial and time-series modeling

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