Pore Pressure Modelling and Stress-Faulting-Regime Determination of the Montney Shale in the Western Canada Sedimentary Basin
Bibliographic record
Abstract
Summary This work establishes an effective approach to predict pore pressure in theoverpressured Montney shale and overburden from sonic logs by implementingnormal-trend and explicit methods. The cause of the overpressure condition inthe Montney is also addressed. These two methods were selected on the basis ofthe study carried out by Contreras et al. (2012) that worked successfully forpore pressure prediction under subpressured conditions in parts of the westernCanada sedimentary basin (WCSB). As a second objective, the stress-faultingregime was determined in the study area by use of stress polygons and data fromdiagnostic fracture-injection-test analysis as a quantification of the minimumhorizontal stress. This is of paramount importance because there is not ageneric theory explaining the stress-faulting regime for most of the westernregion of the WCSB. The Eaton method from sonic logs (Eaton 1975) and theBowers method (Bowers 1995) were implemented in two vertical wells drilledthrough the Montney shale. The first part of the analysis considered two normalcompaction trends, but unreasonable pressure profiles were obtained andrequired a revision on the depositional environment. It was found that for thestudy area, three normal compaction trends have to be considered. The Bowersmethod was initially implemented using both loading and unloading conditions inorder to establish a safe range of pore pressure to allow successful wellplans. It is concluded that undercompaction could be masked as the onlyoverpressure mechanism in the Montney shale in the study area. The formationexperiences an inverse faulting regime that will lead to the creation ofhorizontal hydraulic fractures. The Eaton method using three normal compactiontrends and an exponent equal to 0.9 works successfully in the study area. TheBowers method uses the loading and the unloading conditions, and the specificcorrelation parameters were found to be suitable for the study area and can beextrapolated to adjacent future production and exploratory wells.
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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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 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".