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Record W2044642256 · doi:10.2118/77681-ms

Exceptional Proppant Flowback Control for the Most Extreme Well Environments: The Shape of Things to Come

2002· article· en· W2044642256 on OpenAlexaff
Christopher Stephenson, Brian Ward, David Milton Taylor, Harold Brannon, Allan Rickards

Bibliographic record

VenueSPE Annual Technical Conference and Exhibition · 2002
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsOptech (Canada)
Fundersnot available
KeywordsPetroleum engineeringFracturing fluidCompletion (oil and gas wells)Fracture (geology)WellboreEnhanced oil recoveryPressure dropGeologyEnvironmental scienceMaterials scienceGeotechnical engineeringMechanics

Abstract

fetched live from OpenAlex

Abstract Proppant flowback within deep hot wells and/or highly productive wells is a major problem in the oil and gas industry. Under these extreme conditions, many of the current products and processes to control flowback often fail. As such, improved or alternative technology and procedures are constantly being sought. One such technology is the development of deformable proppants. Material and structural improvement to a deformable proppant has allowed laboratory test conditions to be extended to higher temperature, closure stress and flowrate. As a result of this fine tuning, exceptional proppant flowback control has been obtained. Testing of this new deformable proppant, blended with typical fracturing proppant, has shown 50 fold increases in flowrate and 100 fold increases in pressure drop are attainable without pack failure, while still maintaining fracture conductivity. Furthermore, this deformable proppant has been applied in wells where current technology would either fail or have serious drawbacks. In two primarily gas producing reservoirs, the addition of this deformable proppant to proppant packs placed during fracturing treatments, has been observed to very effectively control proppant flowback under conditions of high bottom hole temperature, high fracture closure stress and high production regimes. In order to facilitate field application, new addition and monitoring procedures were developed to accomplish these successful fracturing operations. The developmental testing, successful application and well performance all indicates significant improvement in proppant pack integrity.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score0.309

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 head0.024
GPT teacher head0.224
Teacher spread0.201 · 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 designNot applicable
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

Citations6
Published2002
Admission routes1
Has abstractyes

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