MétaCan
Menu
Back to cohort
Record W2132402392 · doi:10.2118/59751-ms

Use of Silicate Mud to Control Borehole Stability and Overpressured Gas Formations in Northeastern British Columbia

2000· article· en· W2132402392 on OpenAlexaboutno aff
Michael R. Stewart, Bill Kosich, Brent Warren, John C. Urquhart, Michael McDonald

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsBoreholeDrilling fluidDrillingSilicateGeologyLost circulationMud loggingOil shaleScientific drillingSodium silicatePetroleum engineeringMineralogyGeotechnical engineeringMaterials scienceComposite materialChemistry

Abstract

fetched live from OpenAlex

Abstract A freshwater silicate based drilling fluid, containing 20-30% sodium silicate by volume, was successfully used to drill a gas well in northeastern British Columbia. Major drilling issues in the area include borehole instability in 500 plus meters of highly dispersible Ft. Simpson shale, high pressure gas zones and potential moderate-severe lost circulation. Despite problems of severe lost circulation and high mud weights, the caliper log on the silicate well showed <1% hole enlargement over the Ft. Simpson shale and 12% enlargement over the entire intermediate section. Typical offset calipers with other water-based muds average 48% and 31% enlargement over the Ft. Simpson and entire well section, respectively. Rates of penetration with silicate mud were generally better than offset wells. Uphole formations drilled to 1060 meters with a low solids, lower density silicate fluid (1195 kg/m3 mud density) drilled at an average of 19.2 m/hr. Offsets drilled with gel-chemical or gel-PHPA systems over the same interval normally averaged 12.6 m/hr. This paper describes the planning and drilling of the first well with a drilling fluid containing silicates up to 30% concentration. Topics discussed include borehole stability, rates-of-penetration, motor performance, drilling fluid stability and properties, and environmental aspects of silicate disposal.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.993

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 head0.008
GPT teacher head0.171
Teacher spread0.163 · 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 designSimulation or modeling
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
Published2000
Admission routes1
Has abstractyes

Explore more

Same topicDrilling and Well EngineeringFrench-language works237,207