History Matching Grosmont C Carbonate Thermal Production Performance
Bibliographic record
Abstract
Abstract The Devonian Grosmont Formation is a bitumen saturated carbonate unit located in northern Alberta. It is considered to be Canada's second largest unconventional oil resource after the McMurray Formation oil sands. Production from the Grosmont Formation has been tested by a consortium of Unocal, Canadian Superior, AOSTRA, Chevron and other companies between 1970's to 1980's with some success and significant learning. Since 2010, Laricina Energy Ltd. and Osum Oil Sands Corp. have started a new wave of testing thermal recovery processes for the Grosmont Formation using horizontal wells. The Grosmont C carbonate reservoir contains vugs and fractures at multiple scales, and thus has a different porosity and permeability network than the clastic oil sands. This paper describes a numerical simulation approach to history matching the performance of one of the pilot wells in order to better characterize reservoir properties such as fractures and vugs at multiple scales and their interactions with the rock matrix. CMG's STARS dual porosity dual permeability module was used to simulate this complex system. The results of the simulation suggest that small-scale vugs should be combined with the matrix in order to obtain a better history match of the reservoir and production performance. Parameters describing fracture properties have become critical not only in matching the well behavior, but also in matching reservoir thermal responses. Advantages, limitations, and recommendations for using a dual porosity and dual permeability model for understanding a multiple-scale porous and permeability system are also discussed.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 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) | 0.002 | 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".