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Record W1734226026 · doi:10.3968/7263

The Application of Magnetic Guidance Drilling Technology in Shengli Oilfield

2015· article· en· W1734226026 on OpenAlexvenueno aff
Xiangfeng Cao, Qinglong Liu

Bibliographic record

VenueAdvances in petroleum exploration and development · 2015
Typearticle
Languageen
FieldEngineering
TopicDrilling and Well Engineering
Canadian institutionsnot available
Fundersnot available
KeywordsMeasurement while drillingDrillingPetroleum engineeringDirectional drillingEngineeringDrilling engineeringWell drillingDrilling fluidOil fieldMagnetic fieldMechanical engineering

Abstract

fetched live from OpenAlex

The magnetic guidance drilling technology could use the magnetic guidance instrument to measure the distance between the signal source and the instrument, which is used to control the well trajectory. It is an essential supplement of the existing steering drilling technology. At present, the magnetic guidance drilling technology is mainly applied to dual horizontal wellslls for heavy oil reservoir, CBM horizontal connected wells, wells to mine underground soluble minerals, and relief wells. This paper mainly introduces the working process of magnetic guidance drilling technology and connected wells. In order to test the overall performance of this technology, an experimental study is conducted on it, and the field test was carried on Shengli oil field.

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: none
Teacher disagreement score0.958
Threshold uncertainty score0.270

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 head0.221
Teacher spread0.211 · 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
Published2015
Admission routes1
Has abstractyes

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