Bibliographic record
Abstract
Technology Focus Natural gas had a bullish year in 2016 as the average Henry Hub spot price jumped from USD 2.28/million Btu in January to USD 3.59/million Btu in December (+58%), “the largest percentage increase in price among energy commodities,” according to the Energy Information Administration (EIA). According to the same source, the US market consumed 75.07 Bcf/D of gas in 2016, 0.6% more than 2015, while US consumer-grade natural-gas production was down 2.4% from 74.14 to 72.36 Bcf/D compared with 2015. Coupled with the electric-power (+4.2%) and industrial (+1.9%) sectors, this contributed to a noticeable rise in gas prices. Although the US is a net gas importer, 2016 officially marked the US as an exporter of liquefied natural gas (LNG) (by Cheniere Energy from zero in 2015 to 0.5 Bcf/D in 2016). While gas transportation primarily by pipeline over land and LNG over water remain the most economically attractive means to transport large quantities of gas over long distances, cost-effectively monetizing stranded gas is still a challenge, especially in offshore environments. A recent absorption-system development by ExxonMobil claims to improve the efficiency of removing water vapor from natural gas, in both on- and offshore environments, by shrinking the surface footprint by 70%, reducing the overall weight by half, and, ultimately, lowering the total cost. This technology should enable the development of some otherwise uneconomical fields. To learn more, attend the SPE workshop Floating LNG—Weathering the Challenges, in Kuala Lumpur on 20–21 March, and the SPE Annual Technical Conference and Exhibition, on 9–11 October in San Antonio, Texas, USA. Recommended additional reading at OnePetro: www.onepetro.org. SPE 181610 Planning for Uncertainties in Gas Composition: Reduce Project Risks by Early Adoption of a Robust Gas-Processing Concept by Pavan Chilukuri, Shell, et al. SPE 183510 Flared-Gas Monetization With Modular Gas-to-Liquid Units: Oilfield Conversion of Associated Gas Into Petrol at Small Scales by Zhong He, Primus Green Energy, et al. SPE 183403 New Economical Process To Monetize High-CO2 Natural Gas by Conrad Ayasse, Canada Chemical Corporation, et al.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".