A method for evaluating resource potential and oil mobility in liquid-rich shale plays—An example from upper Devonian Duvernay formation of the Western Canada Sedimentary Basin
Bibliographic record
Abstract
This paper discusses methods of assessing oil and gas resources and evaluating their mobility in shale reservoirs using programed pyrolysis data in conjunction with reservoir engineering parameters derived from production data. The hydrocarbon resource is calculated from the measured free hydrocarbon by programed pyrolysis with correction of evaporative loss that occurred during coring, storage and sample preparation. The correction takes account of the loss of light hydrocarbon fluids as a result of phase change during core retrieval to the surface and evaporative loss related to storage and sample preparation. Based on their response to ramping temperature during sample pyrolysis and thermal equilibrium behavior of distinct petroleum products at different thermal maturities, the estimated oil and gas resources are divided into three categories: non-movable, restricted, and movable to characterize the mobility of the petroleum fluids. The mobility classification is compared with oil compositional grouping based on evaporative kinetics of petroleum products in rock samples to examine their affinity. Pyrolysis analysis results from naturally matured samples and production data from different fluid zones in the Duvernay Shale resource play in Western Canada Sedimentary Basin (WCSB) were used to demonstrate the application of the proposed method. While the mobility of petroleum fluids increases with thermal maturation in general, the total movable resource reaches its maximum at the end of oil generation window, then declines as a result of massive loss due to hydrocarbon expulsion towards to gas window where liquids are thermally cracked to gaseous hydrocarbons. Compositional grouping based on evaporative kinetics does not show a complete accordance with mobility grouping, suggesting composition is only one of many factors affecting hydrocarbon fluid flow in shale reservoir. More studies are required to better understand the fundamentals of oil mobility in shale reservoir.
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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 | 0.004 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 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".