Single Well Petrophysical Analysis: A Case Study of Belle Fourche Shaly-Sand, Hatton Gas Field, Southwest Saskatchewan
Bibliographic record
Abstract
This case study shows the petrophysical evaluation of the Belle Fourche Formation, Hatton Gas Field, Southwest Saskatchewan, using conventional well log interpretation techniques. The Belle Fourche reservoir analysed is indicated as shaly-sand formation, while petrophysical parameters calculated includes gross thickness, net thickness, volume of shale, porosity, and water saturation. Cross plots, in conjunction with previous core sedimentology study was used to identify lithology as shale dominated by mixed clay. The potassium content remains relatively constant as the clay content increases. In contrast, the thorium content increases with an increase in the clay content presenting thorium potassium ratio of 12, composed of montmorillonite and mixed-layer clay. Shale content increases as the thorium and uranium content increases. Results from the petrophysical evaluation revealed a gross reservoir thickness of 6.36 m, an average net shaly-sand thickness of 2.13 m, an average volume of clay of 13 %, the porosity of 15 %, and average water saturation of 43 %. Rock petrophysics cross plot of density versus P-wave (Vp) velocity was attempted to identify hydrocarbon saturation. The calculated velocities using the Greenberg and Castagna relation indicate slight increase in Vp and a decrease in density in shaly-sand data indicating hydrocarbon saturation in the reservoir interval. This paper has presented conceptually simple petrophysical method, structured in a manner that is easy to understand for a shaly-sand formation evaluation.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".