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Record W1984003475 · doi:10.2118/81708-ms

Re-Completion Techniques on Shallow Gas Wells Using Coiled Tubing Conveyed Fracturing

2003· article· en· W1984003475 on OpenAlexaboutno aff
Darren Thatcher, Stephen Glanville, Dennis Zander, Harlan Jirges, Jon Weishoff

Bibliographic record

VenueSPE/ICoTA Coiled Tubing Conference and Exhibition · 2003
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsCasingWellborePetroleum engineeringCompletion (oil and gas wells)GeologyCoiled tubingHydraulic fracturingDrillingNatural gas fieldWell stimulationPetroleumReservoir engineeringEngineeringNatural gasPaleontologyMechanical engineering

Abstract

fetched live from OpenAlex

Abstract Hundreds of depleted shallow gas wells in the Saco, Montana area of the Northwestern United States have been found to have bypassed pay that until recently was believed uneconomical to recover. Wells in the area were traditionally completed with one production zone and were fractured by conventional means down the casing. The pay zones were then efficiently depleted through the use of siphon strings and flow line compression. Upon review of the well logs, it was determined there may be enough bypassed pay within the existing wellbore to continue producing the well as a multi-zone completion. This paper outlines the logistics, execution, and evaluation of coiled tubing conveyed fracturing for depleted gas wells. Formations that were stimulated in this study appear to have similar characteristics to the thin producing lenses typically treated in Southeastern Alberta, Canada. The majority of the wells treated received up to six fractures and averaged 100,000 lbs of sand placed into each wellbore. The challenges and results from an initial pilot project are reviewed along with the subsequent multi-well project that followed.

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 categoriesMeta-epidemiology (narrow)
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 score0.343
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.223
Teacher spread0.202 · 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.

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

Citations4
Published2003
Admission routes1
Has abstractyes

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