Bibliographic record
Abstract
Editor's column PTT Exploration and Production’s (PTTEP) agreement with Statoil to take a share of a Canadian oil sands development is just the latest in a string of deals by Asian oil companies made to gain access to unconventional resources in North America. Firms from China and India bought into projects throughout 2010 looking to gain access to new reserves as well as to gain technical knowhow. Thailand’s PTTEP acquired a 40% interest from Statoil Canada in the Kai Kos Dehseh Oil Sands Project in western Canada in late November for USD 2.3 billion for its debut in the oil sands market. Statoil will keep the remaining 60% of the project. Kai Kos Dehseh has estimated reserves of 4.3 billion bbl and, using steam-assisted gravity drainage (SAGD), is on target to reach early production of 10,000 b/d in the first quarter of this year. Peak output is projected to be 300,000 b/d, which would help PTTEP move toward its goal of more than tripling current production to reach 900,000 BOEPD by 2020. “This acquisition provides the company access to a highly attractive oil sands deposit in Canada and a strong platform for future growth into unconventional resources,” the company said in a statement. This follows deals by China firm Sinopec to buy ConocoPhillips’ stake in oil sands producer Syncrude Canada, China Petrochemical Corp.’s purchase of Calgary-based Addax Petroleum, and PetroChina’s buy-in of a stake in Athabasca Oil Sands’ MacKay and Dover oil sands projects. China first began buying small stakes in oil sands projects in 2005. Asian state oil companies are investing billions of dollars in oil sands projects in Canada and shale plays in the US. The goal is to secure new resources to fuel their booming economies and to learn the techniques and technologies that will help them develop unconventional resources in their own backyards. With oil prices steady above USD 70/bbl, SAGD oil sands projects remain economic and, with gas prices still depressed, independent producers are welcoming the infusion of Asian cash. Shale developments in North America have attracted a string of deals over the past 2 years, the latest being Chinese National Offshore Oil Corp.’s purchase of a one-third stake in Chesapeake Energy’s Eagle Ford shale acreage in south Texas in November. Although reserves estimates for Asia’s unconventionals potential are sketchy, the International Energy Agency puts China’s unconventional gas reserves at 144 trillion cm. Some analysts believe that figure is much higher. Last August, China inaugurated a shale gas research center and set goals of locating 1 trillion cm of recoverable shale gas reserves, building 15 billion cm to 30 billion cm of production capacity, and producing 8% to 12% of China’s natural gas needs from shale by 2020. The US government is also encouraging China’s development of shale in hopes that it will help the country cut carbon emissions.
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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 | 0.004 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.002 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.018 | 0.012 |
| Insufficient payload (model declined to judge) | 0.272 | 0.133 |
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".