Panel: Oil And Gas Reserve Estimates
Bibliographic record
Abstract
Preface This manuscript is intended to set the stage for a panel discussion on "Oil and Gas Reserves Estimates" scheduled for May 5, 2005 at the conference. The manuscript is based on the "white-paper" input from participants of this panel discussion. The participants include:Ron Harrell, (Keynote Speaker), CEO, Ryder Scott Company, LP.Ron Gajdica, Atlantis Development Manager, BHP Billiton.Dave Elliott, Senior Petroleum Evaluation Geologist, Alberta Securities Commission.Thomas S. Ahlbrandt*, World Energy Project Chief, U.S. Geological Survey. (*Vice Chairman, United Nations Ad Hoc Group of Experts on the supply of Fossil Fuels).Sandeep Khurana (Moderator), Senior Specialist, JP Kenny, Inc. Abstract This manuscript provides a comprehensive overview of issues faced in oil and gas reserve estimates. It addresses how these issues are further complicated with the expanding importance of the worldwide deepwater arena and how this deepwater reserves can be analyzed, interpreted and conveyed in a consistent, reliable way to investors and other stakeholders. The continually-improving technologies such as 3D and 4D seismic and wireline formation evaluation procedures, can lead to improved estimates of production and reserves but are not necessarily presently recognized by regulatory authorities as an indicator of "reasonable certainty", a term used since 1964 to describe proved reserves in several venues. Additionally discussed is the rapidly changing stance taken by several regulatory authorities in reporting reserves in the midst of ever increasing global nature of the industry. The manuscript examines certain solutions debated in the industry to arrive at a reporting mechanism that generates consistency and at the same time leads to useful parameters in assessing a company's value without compromising confidentiality. Areas covered are:Technical uncertainty inherent to reserves;Political and economic uncertainty related to reliability of reserves estimates;Addressing this uncertainty through reserves categories and classifications;SEC reserves and reporting regulations, technical definitions such as those adopted by the SPE and WPC, unified energy definitions under study by the United Nations; and emerging regulations in other countries or groups of countries;Deepwater arena- where new technology can arguably be used to reliably estimate reserves and for evaluating fields but cannot be used to estimate reserves publicly reported under certain regulations creating a potentially large gap in real value versus reported reserves, particularly for some producers;Lack of understanding of regulatory guidance in dealing with international Production Sharing Contracts (PSC) and unique contract issues on reporting reserves faced while dealing with National Oil Companies (NOCs);Internal booking practices;A brief assessment of Canada's NI (National Instrument) 51-101 regulations regarding the reporting of proved, probable and possible reserves beginning with year-end 2003, andWay forward for the industry. Introduction The manuscript begins with current issues on reserve estimation in the industry. A basic background on reserve definitions, inherent technical uncertainties, and reporting regulations is provided. The document then continues to discuss challenges faced in resolving these issues given the wide range of worldwide business practices and expectations.
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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 | 0.000 | 0.001 |
| 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 | 0.001 |
| 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".