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Record W2039167611 · doi:10.2118/0711-0037-jpt

Shale Gas: Promising Prospects Worldwide

2011· article· en· W2039167611 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueJournal of Petroleum Technology · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicAtmospheric and Environmental Gas Dynamics
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleGeological surveyChinaShale gasPetroleumMiddle EastGeologyUnconventional oilMining engineeringGeographyArchaeologyPaleontology

Abstract

fetched live from OpenAlex

Shale gas is everywhere. China's estimated technically recoverable shale gas resources, at 1,275 Tcf, are almost 50% greater than those touted in the US. Argentina, with 774 Tcf, contains 150 Tcf more than all of Europe. These numbers were spelled out in “World Shale Gas Resources: An Initial Assessment,” a study released April 2011 under the auspices of the US Energy Information Administration (EIA), which commissioned the study from Advanced Resources International (ARl). China, in fact, ranks first in shale gas resources, followed by the US, Argentina, Europe, Mexico, South Africa, Australia, and Canada. Although the study is preliminary and excludes areas like Russia and the Middle East, there is no doubt shale gas resources exist in abundance worldwide. The numbers ARl arrived at are rough. With more extensive data and more time to assess it, ARl stated, the amounts would be higher. However, Donald L. Gautier, chief of the US Geological Survey (USGS) World Petroleum Project, introduced a note of caution regarding the EIA study's figures. The USGS is in the midst of its own assessment of global continuous accumulations, including technically recoverable gas from source rock systems such as gas shales. Initial results from the first basins assessed will be released within the next few months. According to Gautier, the USGS approach, which is geologically based, probabilistic, and emphasizes application of well performance data from analog shale plays in North America, is quite different from that of ARI. “I wouldn’t be at all surprised if the results are as different as the methodology,” he said. Shale Gas Economic Requisites While shale yields approximately 20% (4.8 Tcf in 2010, according to the EIA) of US natural gas consumption, this resource has yet to contribute more than negligibly in regions elsewhere. Yet many countries, buoyed by and in some cases participating in US shale gas exploitation, appear poised to initiate shale gas development within their borders. However, with a lack of shale drilling and completion services, as well as gas production and transportation infrastructure, promising shale gas reservoirs need at least five to 10 years before production would be economic.

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.

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.175
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.008
GPT teacher head0.191
Teacher spread0.183 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it