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Record W3201183658 · doi:10.2118/205964-ms

Reassessment of Petroleum Engineering Education: Is It the End of an Era or a New Start?

2021· article· en· W3201183658 on OpenAlexaff
Tayfun Babadagli

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2021
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsRestructuringCurriculumEngineering educationRecessionPopularityPetroleum industryEngineeringEngineering managementEngineering ethicsPolitical scienceBusinessEconomicsEconomic growthFinance

Abstract

fetched live from OpenAlex

Abstract Since emerging more than a century ago, petroleum engineering (PE) education has increasingly kept its popularity despite significant downturns in the industry. During these downturn periods, observed at least four times since the 1973 oil crisis, structural changes in university programs have been considered. On the other hand, during the "heyday" periods, institutions have had to tackle enormous demand from industry, severely increased enrollments, and reestablish resources to provide a proper service. In light of these observations and while experiencing the fifth downturn period over the last five decades, it is time again to ask the same question: "Shall we continue with the same PE education model or radically shift to a new model?" In this paper, after reviewing more than fifty articles published over the last 85 years reporting the attempts made towards reshaping PE education, an option of restructuring PE programs is discussed. This option is less oil industry (and oil prices) dependent and more of a "general" engineering education program with an emphasis on the "geoscience" or "subsurface" engineering aspects of the PE discipline. Detailed discussions focus on curriculum updates to address the industry practice of "subsurface" related engineering applications. Viability of this option was discussed from industry, academia, and students’ perspective. This restructuring option requires substantial changes to curricula, skill development, and teaching and learning styles. Fundamentals are essential to include in PE education similar to other general (or major) engineering disciplines such as mechanical, civil, chemical, and electrical engineering. The essential elements of engineering skills such as creative design, decision making, problem description and solving, management under high degree of uncertainty, and data collection and processing for optimization are to be included in the new model. Finally, the model proposed is critically discussed and analyzed from different perspectives (industry, academia, and students) considering current and prospected subsurface engineering applications.

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)0.006
metaresearch head score (Gemma)0.019
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Commentary · Consensus signal: none
Teacher disagreement score0.007
Threshold uncertainty score0.034

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0010.003
Scholarly communication0.0070.008
Open science0.0010.002
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0030.001

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 head0.021
GPT teacher head0.277
Teacher spread0.256 · 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 designNot applicable
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

Citations4
Published2021
Admission routes1
Has abstractyes

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