Wettability of the Montney Tight Gas Formation
Bibliographic record
Abstract
Abstract The abundant hydrocarbon resources in low-permeability formations are now technically accessible due to advances in drilling and completion of multi-lateral/multi-fractured horizontal wells. However, measurement and modeling of petrophysical properties, required for reserve estimation and reservoir-engineering calculations are the remaining challenges for the development of tight formations. In particular, characterizing wettability (wetting affinity) of tight rocks is challenging due to their complex pore structure, which can be either in hydrophobic organic materials or in hydrophilic inorganic materials. We conduct comparative and systematic imbibition experiments on ten binary core plugs from the Montney tight gas formation, which is an enormous tight gas fairway in the Western Canadian Sedimentary Basin. Both contact angle and imbibition data indicate that the formation has a stronger affinity to oil than to water. However, the ratio between oil and water uptake of these samples is usually higher than what capillary-driven imbibition models predict. This discrepancy can be explained by the strong adsorption of oil on the surface of a well-connected organic pore-network that is partly composed of degraded bitumen. We also define a wettability index based on the equilibrium oil and water uptake of the binary samples. Oil wettability index is positively correlated with Total Organic Carbon (TOC) and clay content of the rocks which increase with depth from the Upper Montney to the Lower Montney.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".