Hydrocarbon Reservoir Evaluation in Triassic-Jurrasic Strata in the Western Sverdrup Basin, Canadian Arctic Islands
Bibliographic record
Abstract
The western Sverdrup basin is a petroliferous basin in the Canadian high Arctic, in which 17 oil and gas fields were discovered from 1969 to 1986 (Embry, 2011; Chen et al., 2000). Almost all discovered oil and gas fields of the basin (Fig.1) occur in Triassic-Jurassic strata and are sourced by primarily by oilprone, bituminous shale of Middle and Late Triassic age (Embry, 2011), and a deeper source rock has been suggested for the gas accumulations found in Drake and Hecla gas fields (Dewing and Obermajer, 2011). The main reservoirs consist primarily of shallow marine sandstones in the Upper Triassic-Lower Jurassic Heiberg Group, Mid-Upper Jurassic Awingak Formation and the sandstones in the Schei Point Group of Mid-Upper Triassic succession, as well as the sandstones of the Bjorne Formation of Lower Triassic succession (Fig.2). In this study, the reservoir characteristics of TriassicJurassic sandstones are studied using core measurements (Hu & Dewing, 2010) and through petrophysical analyses of well logs. Cross sections are constructed by a combination of well logs, estimated petrophysical parameters, core analysis and well test results, illustrating the reservoir properties in tested hydrocarbon zones and identified potential intervals. Data analysis suggests that the Triassic-Jurassic strata contain large volumes of sandstone reservoirs that display a variety of porosity and permeability characteristics. This study will provide key petrophysical parameters for further hydrocarbon resources assessment.
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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 | 0.003 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".