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Record W2090098960 · doi:10.2118/134257-ms

The Recommended Practice for Surface Casing Vent Flow and Gas Migration Intervention

2010· article· en· W2090098960 on OpenAlexaff
H. J. Slater

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2010
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsPenn West Exploration (Canada)
Fundersnot available
KeywordsCasingPetroleum engineeringAnnulus (botany)Seal (emblem)Fossil fuelPetroleumIntervention (counseling)Process (computing)Environmental scienceEngineeringComputer scienceForensic engineeringWaste managementGeologyMaterials science

Abstract

fetched live from OpenAlex

Abstract The migration of gas to surface by means of the production casing/openhole and the production/surface casing annulus is a common occurrence in the petroleum industry. There are also situations wherein migrating gases will negotiate a route to surface outside the surface casing. The repair of these situations is a non-revenue generating exercise with the potential to reach significant expenditures. The recommended strategy will efficiently initiate and direct this process consequently minimizing the total cost of this intervention. The process commences with a logical technical approach to identify the gas source or sources that are responsible for the problem. The next step is to communicate with this gas source in a manner that enhances a remedial cementing activity. It concludes with the task of cement squeezing the source using a low rate cement squeeze technique to permanently seal the gas source thus preventing gas flow. This methodology has proven to be extremely successful and the subject paper describes in detail the recommended methods for identification, access to and sealing of the gas source responsible for these issues. Case histories will also be presented to illustrate strategies within the intervention.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.851
Threshold uncertainty score0.310

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 head0.012
GPT teacher head0.255
Teacher spread0.243 · 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

Citations12
Published2010
Admission routes1
Has abstractyes

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