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Record W1973477647 · doi:10.2118/151227-ms

Size Degradation of Granular Lost Circulation Materials

2012· article· en· W1973477647 on OpenAlexaff
Paul D. Scott, David Beardmore, Zack D. Wade, Eddie Evans, Krista D. Franks

Bibliographic record

VenueIADC/SPE Drilling Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsConocoPhillips (Canada)
FundersConocoPhillips
KeywordsLost circulationCirculation (fluid dynamics)Degradation (telecommunications)Particle sizeDrilling fluidEnvironmental scienceDrillingForensic engineeringProcess engineeringComputer scienceEngineeringMechanical engineeringAerospace engineeringTelecommunicationsChemical engineering

Abstract

fetched live from OpenAlex

Abstract Lost circulation is a major cause of drilling non-productive time with significant cost implications for many locations throughout the world. Increased attention on the performance of lost circulation materials and engineered solutions to lost circulation, such as wellbore strengthening and the recycling lost circulation materials, has brought about the need to use materials which do not size-degrade rapidly. Little mechanical property data or shear degradation information is available for most lost circulation materials as they are normally not highly engineered materials, and standard test methods have not been developed. In addition, lost circulation materials are often sourced locally to reduce cost, and logistics are such that they may not come from sources with consistent quality. Anecdotal information about which materials size-degrade most is common in the industry but little scientific information is available. Field data has conclusively shown that lost circulation materials degrade in size with time. A laboratory procedure has been developed and used to study the relative reduction in particle size of the most common granular products. Laboratory and field data are presented to demonstrate the relative size degradation rates for several common lost circulation materials. This data on the relative degradation in the particle size distribution of granular lost circulation materials will provide improved understanding of their performance for more efficient application of the materials. This will lead to improvements in wellbore strengthening and lost circulation material recycling applications.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.124
Threshold uncertainty score0.634

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 head0.016
GPT teacher head0.209
Teacher spread0.193 · 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 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

Citations31
Published2012
Admission routes1
Has abstractyes

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