Statistical Modelling for the Source Rock Parameters of the Montney Formation, NE British Columbia, Canada
Bibliographic record
Abstract
Hydrocarbons in self-sourced reservoirs are determined by the concentration and maturation of organic matter in sediments. As a result, lowering risk in unconventional resource research and development requires knowledge of hydrocarbon potentiality factors. The geochemical data for the Montney Formation samples studied suggest that it is a fair to good source rock with type IV kerogen that can generate gas in general. The statistical modelling of the analyzed data reveals a valuable technique for identifying characteristics, clusters, and linkages that affect source rock assessment. The Spearman’s correlation coefficient showed a good positive correlation between the total organic carbon (TOC) and free hydrocarbons (S1), generating potential (S2), and potential yield (GP). There was a weak correlation with the maturity index (Tmax) and hydrogen index (HI) and a highly negative correlation between the TOC and oxygen index (OI). On the other hand, the principal component analysis (PCA) showed the presence of three factors affecting the source rock evaluation. Factor 1 included TOC, S1, and S2, which are related to organic richness and hydrocarbon potentiality; factor 2 contained the production index (PI), and the generated CO2 (S3) was related to the organic matter source. Factor 3 included the Tmax and HI related to the type of organic matter and thermal maturity. In addition, the TwoStep cluster analysis separated the source rock in the study area into two major groups. Cluster 1 is characterized relatively by high HI, TOC, S1, S2, and PI, with Tmax < 455 °C indicating good source rock in the mature level with the capability to generate little oil and condensate gas. Cluster 2 is characterized by relatively low HI, TOC, S1, S2, and PI, with Tmax > 455 °C, indicating an over-mature source rock in the dry gas window.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.004 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".