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Record W1994612313 · doi:10.2118/2005-006

Advances In Production Automation

2005· article· en· W1994612313 on OpenAlex
B.Y.P. Fung, K.T. O apos Brien

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

VenueCanadian International Petroleum Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicFlexible and Reconfigurable Manufacturing Systems
Canadian institutionsnot available
Fundersnot available
KeywordsAutomationProduction (economics)Computer scienceSystems engineeringManufacturing engineeringEngineeringMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Process Control & Automation Technology (PCAT) has been well understood and utilized by the downstream petroleum industry for years. The upstream is a somewhat different story. Rig-site or wellsite automation, for instance, had been and still is perceived by many as impractical or an overkill. Undeniably, results of past experimentation with production automation had been far from conclusive. The primary reasons for such a checkered past are mostly technical and partially human. However, substantial technological advances in recent years are changing the picture. If the current trends hold, in a matter of say 5 to 10 years, the majority of wellsites in Canada will be automated. Operating wells and fields with automated control systems will become the norm, and PCAT will eventually evolve into yet another standard tool for the upstream oilpatch. As a result, production personnel - engineers, technicians, field operators, and even administration and supporting staffs must learn to adapt to survive. Production automation is a tedious, and at times, confusing subject because it combines a wide range of engineering disciplines from production to process design, to instrumentation, control, and electronics, with the constantly evolving computer technologies. This paper will attempt to shed some light on this PCAT subject from a user's and non-specialist's perspective, and explore some of the recent developments that will likely have a significant impact on the petroleum industry. Introduction Instrumentation and process control are standard technologies for any fluid flow operation in the oilpatch, from the reservoirs all the way to the consumers, passing through wellbores, wellheads, wellsites, pipelines and various levels of treating and handling facilities. Prior to the 1940s, all process control devices were mechanical (pneumatic or hydraulic) or electromechanical in nature. The invention of transistor in 1947 ushered in the electronic age, whereby sophisticated electronic sensors and control devices were quick to follow, and would eventually become indispensable in the industrial world. The petroleum industry has always been a leader in nurturing new technologies, and PCAT was no exception. By 1959, an oil refinery in Texas would turn out to be the first commercial deployment of a full-fledged computer-based control system in human history. With the heavy development of integrated circuit and mainframe computer during the 1960s and 1970s, and with the introduction of programmable logic controller (PLC) in 1969, automation quickly spread to all segments of the downstream business. All sorts of processing plants, oil refineries, petrochemical plants, pipeline and truck-based transportation networks, right down to the point-of-sale systems in our friendly neighbourhood gas stations would be automated in time. Nowadays, it would be a real oddity to find any such downstream facilities not operated by some forms of automation, and it is hard to imagine how such facilities could have been operated on what was largely a manual basis back then. On the upstream side though, progress had been very slow, and at times, nonexistent.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.631
Threshold uncertainty score0.790

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)0.0000.000

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 head0.009
GPT teacher head0.212
Teacher spread0.203 · 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