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Record W2923499434 · doi:10.2118/0419-0012-jpt

Comments: Shale’s Second Act

2019· article· en· W2923499434 on OpenAlexaboutno aff
John Donnelly

Bibliographic record

VenueJournal of Petroleum Technology · 2019
Typearticle
Languageen
FieldEnergy
TopicGlobal Energy and Sustainability Research
Canadian institutionsnot available
Fundersnot available
KeywordsOil shaleShale oilShale oil extractionTight oilPetroleum industryChinaFossil fuelAgricultural economicsBusinessEconomyEngineeringEconomicsGeographyWaste managementEnvironmental engineeringArchaeology

Abstract

fetched live from OpenAlex

Editor's column Another industry report issued last month touts the coming gains in US shale, predicting that the country will soon be the largest oil producer and possibly exporter in the world. The International Energy Agency’s (IEA) Oil 2019, a 5-year outlook on the global energy industry, touts the “second wave” of the shale sector, which will transform oil markets worldwide. The IEA says the US will lead the way in oil supply growth over the next 5 years because of continued growth in shale, primarily from the Permian Basin. By the end of that 5-year period, the US will surpass Russia and be close to Saudi Arabia in total oil exports. Although consumption from China will decline and the use of electric vehicles will grow, demand will be stronger for jet fuel and petrochemicals, leading to an annual global increase of 1.2 million B/D. US oil output will account for almost three-fourths of the supply increase over the period, growing a total of 4.4 million B/D, following a production increase of 2.2 million B/D in 2018. “The second wave of the US shale revolution is coming,” IEA Executive Director Fatih Birol said in releasing the report. US oil output, including natural gas liquids, will rise to 19.6 million B/D by 2024. Excluding liquids, oil production will increase from the current 11 million B/D to 13.7 million B/D. One transformation taking place in the US shale sector is the entry of majors. Independents have dominated the play so far, led by such companies as Pioneer and Apache. But the short-cycle production time and geopolitical safety is increasingly attracting interest from large firms such as ExxonMobil, Chevron, and ConocoPhillips. ExxonMobil and Chevron announced plans last month to increase spending even more in the Permian Basin over the next few years. Although the industry has consistently underestimated US shale growth, some producers and engineers have a more nuanced outlook for the sector. There are potential hurdles to overcome if shale is going to continue to be the star in the global supply picture. Steep decline curves, parent-child well interference (or frac hits), and perhaps even a lower inventory of high-quality drilling locations are concerns. The issue of frac hits dominated discussion at the recent SPE Hydraulic Fracturing Technology Conference. Parent-child well interactions may be lowering oil recovery factors from new child wells by 20–40% while also causing losses on older, yet less productive, parent wells, according to US and Canadian operators. That has led Mark Papa, one of the pioneers in US shale and chief executive officer of Centennial Development Resources, to become less optimistic about the future of US shale production. Frac hits and fewer high-quality drilling options may force a lower ceiling on shale, undermining these optimistic forecasts, which leads him to believe that the shale sector is already in its mature phase of producibility, he said during a panel discussion at the IHS Markit CERAWeek conference in Houston last month. But panelist Greg Powers, vice president of global innovation at Halliburton, cautioned that most of the learnings from shale to date have been experiential, not fundamental, and that a lot of the resource is still in the ground. In addition, he said, the chemistry of hydraulic fracturing is still a bit of a mystery. In other words, there is still much to figure out before concluding whether shale’s second act is its final one.

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 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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.900
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.007
GPT teacher head0.257
Teacher spread0.250 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2019
Admission routes1
Has abstractyes

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