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Record W2138668769 · doi:10.2118/77679-ms

Coiled-Tubing Fracturing Increases Deliverability, Recoverable Reserves, and NPV of Infill Development Wells in a Mature Shallow Gas Field

2002· article· en· W2138668769 on OpenAlexaboutno aff
Stanley F. Wolny, Glen Schiffner, Eric Schmelzl, Merrill Jamieson, Marty Stromquist

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2002
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsInfillCoiled tubingHydraulic fracturingPetroleum engineeringNatural gas fieldWell stimulationGeologyNatural gasReservoir engineeringEngineeringCivil engineeringPetroleumWaste management

Abstract

fetched live from OpenAlex

Abstract A comparative study was undertaken to review the production results, reserve recovery, and economics between conventional hydraulic stage fracturing and coiled-tubing (CT) fracturing on infill development wells in a mature shallow gas field near Medicine Hat in southeastern Alberta, Canada. Selective stimulation through coiled tubing was developed for this area as a response to demands operators placed on service companies to improve the completion efficiency of a shallow gas well with multizone potential. The main benefit of CT fracturing is that each prospective productive interval is selectively stimulated. This translates to improved deliverability, reserve recovery, and project economics. The process also improves logistics, decreases workforce requirements, and minimizes environmental impact. This paper provides in detail how these benefits can be accomplished with coiled-tubing fracturing.

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)0.000
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.056
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
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 science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.014
GPT teacher head0.217
Teacher spread0.203 · 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 designObservational
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

Citations8
Published2002
Admission routes1
Has abstractyes

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