MétaCan
Menu
Back to cohort
Record W3120315558 · doi:10.3720/japt.83.103

Freeze application to replace damaged wellhead equipment

2018· article· en· W3120315558 on OpenAlexaboutno aff
Toshimitsu Itoh, Tazuru Nishiyama, Y.. Matsuno

Bibliographic record

VenueJournal of the Japanese Association for Petroleum Technology · 2018
Typearticle
Languageen
FieldEngineering
TopicGrouting, Rheology, and Soil Mechanics
Canadian institutionsnot available
Fundersnot available
KeywordsWellheadPetroleum engineeringInjectorWaste managementSlurryLeakage (economics)Spark plugEnvironmental scienceEngineeringEnvironmental engineeringMechanical engineering

Abstract

fetched live from OpenAlex

At a Steam Assisted Gravity Drainage (SAGD) project on Japan Canada Oil Sands Limited (JACOS), CANADA, steam leakage from a wellhead of a steam injector was discovered. The steam injection was ceased to eliminate the effects on the environment. Some damages on the wellhead were suspected as the cause of the leakage. In order to inspect an inside of the wellhead due to steam leakage, a “Freeze Application (Ice Plug)” without killing the steam injector was safely applied to remove the wellhead. The integrity of the ice plugs was confirmed by pressure tests, and then steam leakage points at the wellhead were safely remedied with minimal fluid loss to the formation. A typical “Freeze Application” process is shown as below. 1) An area is displaced with a “plug” of uncontaminated bentonite gel mixed to thick slurry. 2) The gel plug is frozen in place by use of dry ice (solid form of carbon dioxide) contained in a cribbing and tamped manually to keep in contact with the area to be frozen at all the times. 3) Pressure testing is always conducted to one and a half times the surface pressure of the well, or to the maximum wellhead pressure rating. In this paper, it consists of background of the steam leakage from the objective steam injector, investigation of remedial action, and then selection and introduction of “Freeze Application”.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.345
Threshold uncertainty score0.438

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0010.000
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 head0.222
Teacher spread0.217 · 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 designBench or experimental
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
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the Japanese Association for Petroleum TechnologySame topicGrouting, Rheology, and Soil MechanicsFrench-language works237,207