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Record W1970331139 · doi:10.2118/163904-ms

First Field Application of 2-7/8" Scale Removal Tool for Offshore Well Abandonment

2013· article· en· W1970331139 on OpenAlexaboutno aff
Navneet Birk

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsWirelineScale (ratio)Submarine pipelineMarine engineeringPetroleum engineeringEngineeringGeologyComputer scienceGeotechnical engineeringTelecommunicationsPhysics

Abstract

fetched live from OpenAlex

Abstract In June 2010, as part of an operation in a producing well, offshore eastern Canada, a junk basket on wireline tagged its depth and became stuck. The bottomhole assembly (BHA) was disconnected and left in the well. When the wireline was back at surface, scale was determined to be the reason for getting stuck. This became more evident after an attempt was made to bait the fish, which was unsuccessful because loose scale had settled on top of the disconnected tool. A run was made with a lead impression block (LIB) to understand better the fish neck, but it returned with no impression. Previously, in 2005, naturally occurring radioactive material (NORM) was detected in this well, having been observed on logging tools returned back to surface. Similarly, a few years later, NORM scale concerns appeared in another producing well on the platform. Due to the inability to handle large amounts of NORM (mostly loose scale) on surface, no intervention work to date had been performed on this platform. The proposed solution was to perform a scale removal operation using coiled tubing (CT). Initially, a pilot hole was drilled with a motor and mill, but the main focus was the use of a 2 7/8-in. scale-removal tool that employed jetted beads. For optimal pump rates and suspension capabilities, a specific gelled fluid system was recommended. A shaker system was sourced to remove and contain solid cuttings on surface and to recycle the gelled fluid on surface by using two large fluid containment tanks. The operation was completed successfully and without any issues or concerns. Client was able to recover the slot for future sidetrack drilling, which is a priority on a fixed platform.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.003
GPT teacher head0.173
Teacher spread0.169 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2013
Admission routes1
Has abstractyes

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