Disclosures of Resources Other Than Reserves Under Canadian Guidelines
Bibliographic record
Abstract
Abstract The importance of improved guidance for the estimation and classification of "Resources other than Reserves" (abbreviated herein as ROTR) has recently been driven by the evolution of the petroleum industry away from maturing conventional accumulations towards unconventional accumulations such as petroleum in ultra-low permeability reservoirs (including shales) and heavy oil/bitumen resources. Commonly these unconventional opportunities involve newer, capital intensive technologies to exploit areally extensive deposits; accordingly, early-stage estimates of in-place petroleum quantities and potentially recoverable volumes may be very large, creating new and critical challenges to communicating clear and consistent information, including the associated uncertainties, relating to resource opportunities. To date, evaluators involved in estimation and reporting of ROTR have had to rely on only limited guidance. Under Canadian Securities Administrators National Instrument (NI) 51–101 Standards of Disclosure for Oil and Gas Activities, companies are obligated to disclose Proved and Probable Reserves but have the option to additionally disclose Possible Reserves, Contingent Resources and Prospective Resources. NI 51–101 references technical guidelines contained in the Canadian Oil and Gas Evaluation Handbook (COGEH) maintained by the Canadian Chapter of the Society of Petroleum Evaluation Engineers (SPEE). Disclosure of ROTR estimates in Canada has increased substantially in recent years and based on reviews of many filings, is often unclear, inconsistent or potentially misleading. A SPEE Calgary committee has recently proposed additional guidance to promote and improve consistency in the estimation of ROTR for business operations and public disclosure. It is intended to augment other guidelines in COGEH Volumes 1 to 3. Issues addressed with respect to estimation, classification and reporting of ROTR include the following: Clarification of definitions and principles pertaining to petroleum accumulations, particularly in relation to continuous deposits, Clarification of definitions and principles pertaining to recovery projects and technologies, Exploration and technical and commercial risks, Aggregation of resource estimates. Guidance on reporting the results of ROTR evaluations Reporting of the results of a resource evaluation under the recommended revised guidelines should provide information for both internal management and external investors sufficient to make informed investment decisions. The revised definitions and classification guidance may be equally applicable in future updates of the Petroleum Resources Management System (PRMS).
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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".