Bibliographic record
Abstract
Overview This article is written in support of the Society of Petroleum Engineers’ Annual Technical Conference and Exhibition. As of the time of this writing, the event is scheduled to take place in Houston, Texas, during the week of October 3, 2022. The ATCE is the SPE's flagship international event. The host facility will provide over 90,000 square feet of exhibition space along with numerous presentation rooms. It is an honor to be a part of this program. The author has been tasked with preparing an article that discusses the role that patents have played in the development of the oil and gas industry. As someone who has written hundreds of patent applications in various energy generation fields over the last 22 years, and as a degreed petroleum engineer himself, the author believes that he is uniquely suited for the task. A number of years ago, the author wrote an article for the Society of Petroleum Engineers entitled Intellectual Property for the Oilfield The article was written in connection with a presentation at an International Association of Drilling Contractors (IADC) Drilling Conference held in Dallas, Texas. A reciprocal article was published by a patent attorney in Canada the same year. See R.B. Caldwell, Patent Monopoly-Protecting Your Ideas (in Canada). The two articles focused much more on the patent process itself than the development of oil and gas technology and the role that the patent process has played. The author is unaware of any attempts that have been made, scholarly or otherwise since 2002 to discuss the role that patents play in the oil and gas industry. This paper is a humble attempt to fill that void.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.011 | 0.013 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".