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Record W1969766379 · doi:10.2118/2004-305

Should NI 51-101 and SEC Definitions Yield Different Proved Reserve Estimates?

2004· article· en· W1969766379 on OpenAlexaboutno aff
Darius M. Adams

Bibliographic record

VenueCanadian International Petroleum Conference · 2004
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicFinancial Reporting and Valuation Research
Canadian institutionsnot available
Fundersnot available
KeywordsYield (engineering)Computer sciencePhysicsThermodynamics

Abstract

fetched live from OpenAlex

Abstract The 2003 year end reserves reporting of Canadian oil and gas companies over the first quarter of 2004 seems to have been dominated by the significant influence of the newly implemented Canadian Securities Administrators (CSA) regulations as prescribed by the recently introduced National Instrument (NI) 51–101. Many of the large Canadian senior issuers have obtained exemptions from certain aspects of NI 51–101 to report under the U.S. Securities and Exchange Commission (SEC) regulations nevertheless we still hear of references to NI 51–101 apparently negatively influencing reported results. Even though the Canadian Oil and Gas Evaluation Handbook (COGEH - the reference source for the definition of proved reserves under NI 51–101) states that differences with SEC for proved reserve estimates (based on constant prices) should not be material, at least one large independent referred to a more conservative methodology now being used by outside advisors which apparently had a negative impact on their reserve estimates. Almost no reserve estimates in Western Canada are prepared using probabilistic methods and so references to certain probability levels in COGEH, particularly by those not closely involved with evaluating reserves, suggest a lack of understanding of both the written regulations and their application. This paper therefore revisits the SEC and NI 51–101 reserve definitions and discusses the level of uncertainty inherent in reserve estimates in the context of current industry practice. The aggregation effect is discussed using a typical Western Canada portfolio example. Guidelines are discussed for classifying proved reserves under both definitions and a practical approach is recommended for estimating proved reserves at the entity level which satisfies both SEC and NI 51–101 regulations. Undoubtedly industry practices in estimating reserves are changing under the influence of an increasingly vigilant regulatory environment in both the U.S. and Canada. It is therefore essential for practicing reserve evaluators to be fully involved in shaping practical approaches to satisfying legal reserve disclosure requirements. Introduction The world of reserves reporting has changed significantly in the last year or so as corporate governance has come under increasing regulatory vigilance. The passing of the Sarbanes- Oxley Act in the U.S. in July 2002 following the Enron meltdown and the implementation of NI 51–101 in Canada in September 2003, following several well publicized reserve write-downs and bankruptcies, have resulted in unprecedented scrutiny regarding the evaluation and disclosure of reserves. There have been several large write-downs reported on both sides of the border as well as by Shell in Europe in the first quarter of 2004. Is this because the regulations have materially changed or is it because there is now a perception that the guidelines are now being more strongly enforced? This paper attempts to assess the former in the context of large Canadian independents. For U.S. public companies reserve disclosures have to comply with the SEC regulations, which have not changed since 1987 (Reference 1). For Canadian public companies engaged in oil and gas activities reserve disclosures have to now follow the NI 51–101 regulations that were finalized in September 2003 (Reference 2).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.663
Threshold uncertainty score0.901

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.133
GPT teacher head0.302
Teacher spread0.169 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations1
Published2004
Admission routes1
Has abstractyes

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