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Record W4319040143 · doi:10.1039/9781839168987

Petroleum Engineering Explained: Basic Concepts for Novices

2020· book· en· W4319040143 on OpenAlexaboutno aff
David Shallcross

Bibliographic record

Venuenot available
Typebook
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsGlossaryPetroleumField (mathematics)EngineeringPetroleum industryPetroleum engineeringOperations researchGeologyMathematicsEnvironmental engineeringPaleontology

Abstract

fetched live from OpenAlex

Assuming no mathematical or chemistry knowledge, this book introduces complete beginners to the field of petroleum engineering. Written in a straightforward style, the author takes a practical approach to the subject avoiding complex mathematics to achieve a text that is robust without being intimidating. Covering traditional petroleum engineering topics, readers of this book will learn about the formation and characteristics of petroleum reservoirs, the chemical properties of petroleum, the processes involved in the exploitation of reservoirs, post-extraction processing, industrial safety, and the long-term outlook for the oil and gas production. The descriptions and discussions are informed by considering the production histories of several fields including the Ekofisk field in the North Sea, the Wyburn Field in Canada, the Manifa Field in Saudi Arabia and the Wilmington Field off the Californian Coast. The factors leading up to the well blowouts on board the Deepwater Horizon in the Gulf of Mexico and in the Mantara Field in the Timor Sea are also examined. With a glossary to explain key words and concepts, this book is a perfect introduction for newcomers to a petroleum engineering course, as well as non-specialists in industry. Professor David Shallcross is one of the foremost practitioners in chemical engineering education worldwide. Readers of this book will find his previous book, Chemical Engineering Explained, a useful companion.

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 categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.575
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
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)0.0000.000

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 head0.020
GPT teacher head0.266
Teacher spread0.245 · 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 designSimulation or modeling
Domainnot available
GenreOther

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

Citations1
Published2020
Admission routes1
Has abstractyes

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