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Record W2010149263 · doi:10.2118/113695-ms

Coiled-Tubing-Conveyed Proppant Treatment Yields Increase in Production Efficiency and Return on Investment

2008· article· en· W2010149263 on OpenAlexaff
Zeke T. Peak, Matthew Montes, David Natenberg, Marc Durkee

Bibliographic record

VenueSPE/ICoTA Coiled Tubing and Well Intervention Conference and Exhibition · 2008
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsProduction (economics)Investment (military)Well stimulationCoiled tubingReturn on investmentEnvironmental sciencePetroleum engineeringProduction efficiencyNatural resource economicsBusinessOperations managementEngineeringGeologyEconomicsReservoir engineeringMechanical engineeringMicroeconomics

Abstract

fetched live from OpenAlex

Abstract Formation sand production and stimulation proppant flowback are large and costly production problems in maturing assets. Recently, a new coiled-tubing-conveyed proppant treatment (CTCPT) was applied for the operator in the Carr-Lundell field in Webb County, Texas. This technology effectively eliminated the production of formation solids and stimulation proppant. The result yielded increased efficiency in associated production time and decline rates, which have optimized return on investment. The new treatment has also reduced residual operational expenditures by eliminating costly workovers, equipment repair, and lost production caused by this escalating industry problem.

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)0.000
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 score0.004
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

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)0.0040.001

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 head0.018
GPT teacher head0.226
Teacher spread0.209 · 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

Citations0
Published2008
Admission routes1
Has abstractyes

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