Resource assessment methodologies: Current status and future direction
Bibliographic record
Abstract
Abstract A symposium on resource assessment methodologies, organized by the Canadian Gas Potential Committee in Calgary, Alberta, Canada, last April 10–12, 2002 highlighted the need for ongoing research in resource assessment. Methodologies used by the U.S. Geological Survey and the Canadian Gas Potential Committee can produce significantly different results; for example, estimates for Canadian plays by the U.S. Geological Survey were only 20% of the volume estimated by the Canadian Gas Potential Committee. Key issues in assessment of exploration plays established by discoveries include determination of the underlying distribution of hydrocarbon pool or field sizes and use of economic cutoffs. For conceptual plays where no discoveries have been made, the most critical issue involves the correct appraisal of exploration risk to be applied. Future directions for assessment in established plays include the application of iterative history matching in discovery process models and Bayesian analyses. For conceptual plays, postmortem studies of both successful and unsuccessful exploration ventures are required to calibrate exploration-risk parameters. Non-conventional resources, specifically coalbed methane and gas hydrates, present special assessment issues of determining how much of the in-place resources will be actually be recoverable (Hughes and Osadetz, Geological Survey of Canada). Assessment of such plays primarily involves engineering evaluation of the volumes of hydrocarbons that can be economically recovered. A future meeting on assessment methodology is planned for 2004. The establishment of test sites where good-quality play data may be evaluated using a variety of assessment methodologies is planned.
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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 | 0.037 | 0.021 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.007 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.008 | 0.015 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.012 | 0.004 |
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".