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Record W2014008234 · doi:10.2118/115527-ms

Case History: Expanding the Boundaries of a Hydraulic Workover Unit into New Economic Levels

2008· article· en· W2014008234 on OpenAlexaff
David Attong, David Robertson, Michael Wyatt, S. Perai, S. Persad, K. Joseph, J. F. García, C. Fleary

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2008
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsCarbon Engineering (Canada)
Fundersnot available
KeywordsWorkoverUnit (ring theory)Barrel (horology)Petroleum engineeringCasingEngineeringWork (physics)Marine engineeringSubmarine pipelineFossil fuelEnvironmental scienceOperations managementComputer scienceMechanical engineeringWaste managementMathematicsGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract A 600K Hydraulic Workover (HWO) Unit has proven that it has the capability to safely access and deliver offshore gas reserves. This paper identifies the business environment, challenges, learnings, results and the key success factors of a three (3) well project that delivered a total of 250 million standard cubic feet per day (mmsfcd) using a 600K HWO unit. The primary result of the project demonstrated the capability of the HWO unit in handling challenges previously thought better suited for conventional larger rigs. HWO units have proven to be particularly effective in bpTT's offshore operations, however their application had been limited to tubing changeouts, workovers, oil recompletions and short oil sidetracks. This project expanded the capability of the 600K HWO unit to perform high rate uphole gas recompletions. The project consisted of three uphole gas recompletions in 9-5/8 inch casing. Each recompletion was executed at approximately $0.50/barrel of oil equivalent (boe) which made the project extremely attractive and made gas reserves economically viable. Completing the same work with a larger Jackup unit would have cost $3 -4/boe clearly showcasing the economic advantage of the HWO unit. Another major advantage was the ability to move the HWO unit in unfavourable weather conditions when compared to a Jack Up rig. Weather conditions can result in significant and costly delays during the December – April period for jack up units.

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.323
Threshold uncertainty score0.411

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 head0.048
GPT teacher head0.256
Teacher spread0.208 · 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 designNot applicable
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
Published2008
Admission routes1
Has abstractyes

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