The Application of Near-Surface Geophysics at Proposed Pipeline River Crossings: A Comparative Overview of Various Techniques and Their Associated Capabilities and Limitations
Bibliographic record
Abstract
The cost, design, and in some instances, feasibility of directional drilling large diameter or lengthy pipeline river crossings is primarily dependent on ground conditions encountered during construction. Geotechnical investigations are commonly used to explore and assess subsurface conditions at proposed crossings. Ground conditions are determined using borehole drilling and near surface geophysics. Borehole drilling provides subsurface sediment stratigraphy and depth to bedrock information. Geophysics is used to provide information between borehole locations or where borehole drilling is determined to be too difficult or too costly. When used to augment borehole results, geophysical surveys provide more complete geologic cross-section models throughout the length of a proposed directional drill path. This paper presents an overview of the more common geophysical methodologies used to profile subsurface conditions at proposed pipeline crossings. The methods discussed include ground penetrating radar (GPR), seismic refraction profiling and electrical resistivity tomography (ERT). The appropriateness and feasibility of each method is discussed in terms relating to investigation objectives of geotechnical and pipeline design engineers. All three methods were applied to two survey lines at a typical river crossing site on the Bow River, downstream from Calgary, Alberta. Results from the overlapping surveys are presented and the capabilities and limitations for each method compared. Borehole information obtained within the survey area is used to corroborate the interpreted geophysical results.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".