Laboratory and Numerical Simulations of Pipeline Leakage Behaviour: Volatile Organic Compound (VOC) Migration Through Porous Media and Subsequent Atmospheric Dispersion
Bibliographic record
Abstract
The transport of diluent (i.e. condensate blend) and/or diluted bitumen (i.e. dilbit) using buried pipelines is common practice. Aerial surveys are conducted on a regular basis as a part of the leak detection strategy at Enbridge Pipelines. During these surveys, the pilot flies over the right-of-way to visually inspect the pipeline for leakage along the pipeline corridor. Beyond visual inspection, the detection of proximal indicators of leakage by using remote sensors mounted on the aircraft is proposed in order to further enhance visual aerial leak detection methods. These sensors are designed to detect volatile organic compounds (VOCs) which are expected to evolve, even from small liquid leaks within the shallow subsurface and subsequently reach the atmosphere. If these VOCs can be detected in the local atmosphere in the vicinity of a leak during aerial surveys, then small liquid leaks may be more easily identified, characterized and remediated. This study is aimed to characterize and model VOC movement through soil to quantify the amount of VOC concentration expected to diffuse into the atmosphere within the vicinity of leakage. The experimental study consisted of the characterization of three organic fluids, and one type of soil material representative of that used in pipeline construction. Two types of dilbit with different viscosities, as well as a typical diluent (i.e. condensate), were used because these types of organic fluids are commonly transported using pipelines. Batch laboratory tests were conducted using glass screw top vessels in order to determine the concentration and organic species evolving from these fluids. Headspace VOC and other gas species were characterized after 24 hours following the addition of the fluid to the sealed vessel. Custom designed laboratory-based columns were constructed, based upon scaled down field dimensions, and were used to simulate fluid leakage. Fluid was injected at the base of each column, over which porous media was suspended. Each test characterized the migration of VOCs through the porous medium, VOC breakthrough at the surface and data allowed the calculation of VOC flux into the overlying headspace. Columns were operated under closed and flow through modes. Data obtained from the laboratory experiments defined bounding parameters for numerical simulations comprising of decoupled subsurface and atmospheric models. Subsurface modelling of the experimentally simulated leakage event was refined and validated using experimental data and a larger scale field leak scenario was modeled. Data from the laboratory testing and subsurface numerical simulations was used to construct atmospheric dispersion models of a potential field leak simulation. All atmospheric dispersion modelling used a Gaussian Dispersion Model within the Polair Software package (Odotech Inc.).
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".