MétaCan
Menu
Back to cohort
Record W4200046814 · doi:10.2118/1121-0032-jpt

The Changing Role of Education in the New Era of Energy

2021· article· en· W4200046814 on OpenAlexaboutno aff
Judy Feder

Bibliographic record

VenueJournal of Petroleum Technology · 2021
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsMidstreamStraddleEngineeringWorkforceWork (physics)Upstream (networking)PetroleumPetroleum industryPublic relationsPolitical scienceBusinessMarketingLaw

Abstract

fetched live from OpenAlex

To say that the next generation of workers and leaders in our industry will be confronted by challenges unlike any we have known before is likely an understatement. For the foreseeable future, the list below provides a glimpse of what lies ahead. - An industry whose engineering and scientific foundation are still valid and necessary after 100 years but whose aversion to change has left it struggling to catch up in some areas, most notably in digital transformation (although significant progress has taken place in the past 18 months because of the pandemic) - The paradox of a world that will use fossil fuels to meet a large proportion of its energy demand for the foreseeable future while addressing the negative public and political perception of an industry tied to global climate change - Oil and gas companies morphing into “energy” companies, and petroleum engineers and geoscientists increasingly becoming known as “petrotechnical professionals” (PTPs) - The reality that petroleum engineering roles have expanded to straddle upstream, midstream, and downstream, whereas petroleum engineering programs are mostly geared to upstream and, more particularly, reservoir engineering - The replacement of Baby Boomers with Gen Zers who have an approach to work styles, life, and values generally different from the workforce they will need to lead This labyrinth of challenges, which is raising anxiety and questions about the future of petroleum engineering (PE) education, generated much interest and numerous ideas in the “Future Leaders’ Challenges and Educational Road Map” technical session at the 2021 SPE Annual Technical Conference and Exhibition (ATCE) in September. The papers in the session focused on what academia (and industry) can do to nurture the leaders of the future. A common thread was the need to enable students to not only sur-vive but also thrive as they transition into an evolving industry. The authors discussed issues they believe academia can control and govern—i.e., upgrading education and restructuring academic units—and issues such as demand changes, oil prices, and world politics that are beyond academia’s control. They also expressed agreement that certain elements within teaching and learning practices need periodic modifications—and sometimes serious paradigm shifts or even radical changes. Trends: What’s New (or Not) Paper SPE 205964 asked a rhetorical question, “Is it the end of an era or a new start?” Tayfun Babadagli, professor of petroleum engineering at the University of Alberta, pointed out that beginning with the first publication of an article on PE education in 1937, periodic reviews and evaluations—generally corresponding to industry downturns and drops in enrollment—have questioned whether PE programs should be removed from universities or restructured, depending on local conditions and industry needs. Following the 2014 crisis and a sharp decline in PE enrollments, several SPE papers suggested modernization options and changes in education that included options for local needs in certain geographic areas, field-based education, use of visual tools, and information technologies for smart wells and fields at a graduate (MSc) level. Inclusion of training in geothermal engineering was suggested in 2015. In the past couple of years, digital information sciences and new applications of PE sciences and subsurface storage and groundwater hydrology have been suggested.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.010
metaresearch head score (Gemma)0.009
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.038
Threshold uncertainty score0.127

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.009
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0070.011
Scholarly communication0.0160.024
Open science0.0010.010
Research integrity0.0070.012
Insufficient payload (model declined to judge)0.0380.005

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 head0.005
GPT teacher head0.248
Teacher spread0.243 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreCommentary

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

Citations2
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Petroleum TechnologySame topicReservoir Engineering and Simulation MethodsFrench-language works237,207