Bibliographic record
Abstract
President's column - 2012 SPE President Ganesh Thakur offers his “unconventional” views. The word “unconventional” has become quite common in today’s E&P (exploration and production) lexis. A quick search of SPE’s OnePetro.org library returns more than 1,750 documents using the word in the title. This is not surprising, since most energy analysts believe that world sources of unconventional hydrocarbons—such as gas hydrates, tight gas sandstones, and oil and gas shales—hold more fuel than undiscovered conventional hydrocarbon sources. According to the International Energy Agency’s World Energy Outlook 2011, the long-term global natural gas resource base is very roughly estimated at more than 800 Tcm, of which about 50% is unconventional gas. Total natural gas resources could sustain today’s production for more than 250 years, and all regions have resources approximately equal to at least 75 years of current consumption. The IEA also projects oil demand will hit 99 million B/D in 2035. A growing share of oil equivalent output will come from natural gas liquids and unconventional crude resources, such as extra heavy oil, oil sands in Canada, and tight oil in the US. Unconventional oil production will play an increasingly important role in the global energy economy. These unconventionals are the new conventional.
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 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) | 0.001 | 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 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".