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Record W2023141305 · doi:10.2118/1107-0078-jpt

Overview: Drilling and Completion Fluids (November 2007)

2007· article· en· W2023141305 on OpenAlexaff
Paul D. Scott

Bibliographic record

VenueJournal of Petroleum Technology · 2007
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsConocoPhillips (Canada)
Fundersnot available
KeywordsLuckDrillingDrilling fluidRate of penetrationCompletion (oil and gas wells)Operations researchComputer scienceEngineeringPetroleum engineeringMechanical engineering

Abstract

fetched live from OpenAlex

Drilling and completion fluids are the lifeblood of each well drilled. The effective use of fluids technology and an under-standing of fluid behavior can mean the difference between success and failure. Fluids have a significant influence on rate of penetration; amount of trouble time; cementing success; health, safety, and environment issues; time to drill and complete; and the ultimate reservoir performance for many wells. There you have it—know what you are doing with regard to drilling and completion fluids, and you will easily outperform your peers. For those of you who do not take the time to sort fact from fiction and insist on rigorous engineering evaluation of the fluids you use, good luck. Take a look at the industry statistics, and crunch the numbers. The value lost to fluids-related problems is an enormous economic drain on the industry and a huge opportunity lost. Last year, I wrote about today's increased understanding in fluid behavior and the increased number of fluid options we have today; that trend continues—but pick your tools carefully. If you could have read between the lines last year, you would have noticed that I indicate that there are fewer classic papers these days, too little rigorous science applied to drilling and completions fluids, and too much commercial publishing. Those trends also continue. The Editorial Committee members who write these overviews also pick the technical papers summarized and highlighted in each issue. To those whose papers were selected, congratulations. To those who did not make the short list, thank you for the contribution. For those of you who are business associates and friends, please understand that I raise the bar for those closest to me. Take time to read the summaries, and note the suggested additional reading; all seven papers are keepers. Drilling and Completion Fluids additional reading available at the SPE eLibrary: www.spe.org SPE 103336 "Drilling Fluids in an HP/HT Reservoir: Experiences With Three Different Systems on the Kristin Field Development" by S.A. Hansen, SPE, Statoil, et al. SPE 103934 "Successful Drilling of Oil and Gas Wells by Optimal Drilling-Fluid Solids Control—A Practical and Theoretical Evaluation" by B. Dahl, Statoil, et al. SPE 103731 "HP/HT Drilling-Fluids Challenges" by Ron Bland, SPE, Baker Hughes Drilling Fluids, et al. SPE 103088 "Apparatus for Measuring the Dynamic Solids-Settling Rates in Drilling Fluids" by R. Murphy, SPE, Halliburton, et al.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.129
Threshold uncertainty score0.432

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.003
Science and technology studies0.0010.001
Scholarly communication0.0060.005
Open science0.0020.002
Research integrity0.0050.003
Insufficient payload (model declined to judge)0.1290.167

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 head0.273
Teacher spread0.259 · 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 designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2007
Admission routes1
Has abstractyes

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