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Record W2032238463 · doi:10.2118/74466-ms

Project Management and Technology Provide Enhanced Performance for Shallow Horizontal Wells

2002· article· en· W2032238463 on OpenAlexaff
M. Sander, Richard B. Norgaard, Kristen Kern, T. M. Warren

Bibliographic record

VenueAll Days · 2002
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsNexen (Canada)
Fundersnot available
KeywordsDrillingScheduleDrillDirectional drillingEngineeringHayPetroleum engineeringProject managementEnvironmental scienceComputer scienceMechanical engineeringOperating system

Abstract

fetched live from OpenAlex

Abstract Seven rigs were employed in the Hay Project to drill eighty-three laterals - 22 triple laterals, 4 dual laterals, and 9 single laterals for oil production, water injection and water source during the 2000/2001 winter drilling season. These laterals were typically longer than 3,300 ft, with laterals as long as 4,060 ft being drilled at a TVD of 1,065 ft. The overall drilling project was completed 21 days ahead of schedule and significantly under budget. Project organization, the application of technology, and agreeable weather conditions were the main factors contributing to this outstanding performance.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.769
Threshold uncertainty score0.526

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 head0.010
GPT teacher head0.188
Teacher spread0.178 · 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

Citations0
Published2002
Admission routes1
Has abstractyes

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