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Record W2081078225 · doi:10.2523/iptc-10684-abstract

Deploying New Technology To Improve Canada's Underbalanced Operations

2005· article· en· W2081078225 on OpenAlexaboutno aff
D.A. Pavel, T.M. Mitchell

Bibliographic record

VenueInternational Petroleum Technology Conference · 2005
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsUnderbalanced drillingCasingDrill stringIsolation (microbiology)Software deploymentComputer scienceDrillEngineeringPetroleum engineeringDrillingDrilling fluidMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

This reference is for an abstract only. A full paper was not submitted for this conference. Abstract As global trendsetters in underbalanced operations, Canadian operators are taking a bold new approach to the drilling phase. Recently as a result of increased QHSE concerns around snubbing operations, operators are considering alternative methods to trip under live well conditions. This presents the opportunity to explore new alternatives in pressure control during underbalanced operations, as opposed to conventional methods such as snubbing and killing the well with an overbalanced fluid column. These methods createglaring problems such as rig non-productive time, environmental and safety hazards, and wellbore damage. One such alternative is the downhole isolation valve. The downhole isolation valve is a casing deployed valve system that is set at a predetermined depth and used to shut-in the well to allow for deployment of the drill string and completion assemblies. This paper will discuss the needs of operators and how they were met with the downhole isolation valve, the benefits realized by deploying this technology, and the results from wells where these tools were run.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.648
Threshold uncertainty score0.911

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 integrity0.0000.000
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 head0.005
GPT teacher head0.214
Teacher spread0.209 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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
Published2005
Admission routes1
Has abstractyes

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