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Record W2072015005 · doi:10.2118/163402-ms

Delivering Consistent Top Quartile Drilling Performance Without Compromise

2013· article· en· W2072015005 on OpenAlexaff
Mark Cockram, Arne Wyller Christensen, Bruce Thistle, Willem Boon von Ochssee, Jean Claude Sinet, Frode Hevrøy, Svein Bjarne Barke

Bibliographic record

VenueAll Days · 2013
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsNexen (Canada)Suncor Energy (Canada)
Fundersnot available
KeywordsOperator (biology)EngineeringLeverage (statistics)Operations managementComputer scienceEngineering management

Abstract

fetched live from OpenAlex

Abstract When the operator embarked on an intermittent 5 well exploration, appraisal and development campaign offshore Norway between 2009 and 2012 using the West Alpha there were many challenges. The rig contract was part of a multi company consortium, the well program was varied, a 3rd generation semi submersible rig was being used and all inclusive operating rates were high at around $1,000,000 per day. Following and expanding upon the management principles previously employed 1, the lead operator identified an opportunity to leverage the consortium program and develop a strong relationship with the service companies, in particular the rig contractor. Health, Safety, Security and Environment (HSSE) was a key driver and over 1000 rig days were delivered without a Lost Time Incident (LTI). The lead operator was able to harmonise and standardise procedures used on every well, regardless of who operated the rig. This enabled a much clearer and more consistent message to be delivered to the work environment. This paper will outline the management process taken by the operator and contractor that enabled the following performance to be delivered: 1000 days LTI free rig operations. Record setting drilling performance with improvements up to 40%. No damage to the environment. This paper will also describe how the principles have been transferred to other parts of the operators & contractors organisations.

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: Empirical
Teacher disagreement score0.020
Threshold uncertainty score0.756

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)0.0000.001

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 head0.009
GPT teacher head0.177
Teacher spread0.167 · 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

Citations1
Published2013
Admission routes1
Has abstractyes

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