Estimating Properties of Unconsolidated Petroleum Reservoirs using Image Analysis
Bibliographic record
Abstract
Unconsolidated petroleum reservoirs are non-crystalline rock and include tight gas sands, heavy oil, and bitumen rich sands. These can be both near surface and at depth. This is a “methods” paper which discusses the use of thin section image analysis to obtain reservoir properties from unconsolidated sand reservoirs. A case study was carried out on samples from the Upper McMurray Member of the Athabasca Oil Sands in Canada. Using petrographic image analysis, porosity and permeability were obtained from thin sections from selected regions of interest (ROI). This was accomplished by generating 2D grain and void architecture models from binary images.Porosity and averaged particle size distribution for the coarse components or sand size components were derived directly from oil sand thin sections, whereas permeability was calculated. Values of porosity and permeability obtained using this method were found to be in typical value ranges of those obtained by conventional methods, including petrophysical and core analysis. The application of image analysis to sand reservoirs, such as oil sands, is a rapid and economical method of estimating reservoir properties, especially within regions of interest, and there is the added advantage of direct observation.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".