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Record W2047240766 · doi:10.2118/145599-ms

Deployment of the Reelwell Drilling Method in a Shale Gas Field in Canada

2011· article· en· W2047240766 on OpenAlexaffabout
Miguel Belarde, O. M. Vestavik

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsShell (Canada)
Fundersnot available
KeywordsDrill stringDrillingPetroleum engineeringUnderbalanced drillingWirelineDrillConcentricMeasurement while drillingDrilling fluidDirectional drillingDrill pipeCompletion (oil and gas wells)EngineeringDrill bitMechanical engineeringGeologyTelecommunications

Abstract

fetched live from OpenAlex

Abstract The Reelwell Drilling Method (RDM) is a multi-purpose system incorporating a unique flow arrangement. It employs conventional drillpipe into which is fitted an inner string to form a concentric drill string. This arrangement allows the return fluid containing drill cuttings from the bottom of the well to be transported back through the inside of the drill string. The technique enables improved hole cleaning and improved downhole pressure control, and has unique features for application to managed pressure and extended reach drilling operations. Development of the RDM started in 2004 and has since then been through several full scale tests. In the fall of 2010 it was deployed in a shale gas well in Canada. The main goal was to demonstrate the system in a live gas well and to gain field experience of the technology. The system was used in both the vertical and horizontal sections of the well. The concentric drill string was used for drilling the whole well in several bit runs, with circulation in both conventional and concentric circulation modes. The well was drilled to 4250 m MD in 8¾" hole size. The operation validated the concept and demonstrated a practical implementation on conventional drilling rigs. The operation is an important step in the evolution of a technology, which has a significant potential to improve operational efficiency and thereby the recovery of petroleum resources.

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 score0.180
Threshold uncertainty score0.282

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 head0.011
GPT teacher head0.173
Teacher spread0.162 · 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

Citations11
Published2011
Admission routes2
Has abstractyes

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