Bibliographic record
Abstract
Abstract The E&P industry is taking steps to educate, test and certify qualified petroleum geologists and engineers in the specialty practice of evaluating and estimating petroleum reserves. The primary benefit of the elective certification program would be to heighten understanding and upgrade competencies through a rigorous curriculum designed by experts in the field. A secondary benefit would be to help restore a loss of investor confidence in publicly reported reserves estimates. This loss occurred after several major reserves writedowns during the first quarter of 2004. Also, the self-administered program may head off current initiatives to make third-party reserves audits mandatory, creating an opportunity for industry to take the lead before government does. For justification, one should look no further than the value of world proved reserves and lesser, yet very significant value of reserves reported to the U.S. Securities and Exchange Commission. At $35/bbl and $5/thousand cubic feet (Mcf), for example, which is significantly lower than fourth quarter 2004 prices, reserves owned by U.S. companies reported to the SEC and investors represent a total value of more than $2 trillion (U.S.). This is a mere 3 percent of worldwide reserves, which are reported in a variety of ways. Inarguably, these staggering values should be estimated in accordance with internationally accepted practices by highly competent evaluators. Evaluator certification is a step in that direction. Engineers or geologists certified as specialists would be recognized by the administering organization as having advanced skill levels as well as substantial experience in accepted methods. Requirements for accreditation would include prescribed levels of education and special training, experience and job history, knowledge and scoring on certification exams.
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 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 | 0.048 | 0.122 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.008 | 0.006 |
| Scholarly communication | 0.028 | 0.020 |
| Open science | 0.005 | 0.011 |
| Research integrity | 0.018 | 0.019 |
| Insufficient payload (model declined to judge) | 0.060 | 0.036 |
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".