MétaCan
Menu
Back to cohort
Record W2009906421 · doi:10.2118/161998-ms

Problems and Solutions for Shallow Heavy Oil Production

2012· article· en· W2009906421 on OpenAlexaboutno aff
Р Р Ибатуллин, Н Г Ибрагимов, Р С Хисамов, А.Т. Zaripov

Bibliographic record

VenueSPE Russian Oil and Gas Exploration and Production Technical Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicOil and Gas Production Techniques
Canadian institutionsnot available
Fundersnot available
KeywordsPetroleum engineeringCasingOil productionOil fieldPetroleumSteam injectionEnvironmental scienceOil in placeEnhanced oil recoveryWork (physics)Production (economics)Vapor qualityGeologyEngineeringEnvironmental engineeringRefrigerantHeat exchangerMechanical engineering

Abstract

fetched live from OpenAlex

Abstract To-date, more than 450 heavy oil fields and deposits have been identified in the Republic of Tatarstan with oil-in-places ranging between 1.4 and 7.0 billion tons, according to different estimates. Thermal recovery has proved itself as a reliable method and seemed a logical solution however it did not work properly in vertical wells. Building on the experience of development of the Yaregskoye field (the Komi Republic, Russia) and oilsands in the Canadian province of Alberta, the focus was shifted on working out of recovery methods involving horizontal wells. Engineering solutions accounting for concrete geologic environment and the steam assisted gravity drainage method used for production of heavy oil aim at high-quality casing, leak control in the interstring space, sand control, etc. In shallow heavy oil reservoirs with variable oil saturation of utmost importance are production control practices to ensure profitable oil production, to maintain optimal steam-oil ratio and safe operating pressure to ensure cap rock integrity.

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)0.001
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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.927

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.002
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 head0.051
GPT teacher head0.250
Teacher spread0.200 · 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 designOther design
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

Citations4
Published2012
Admission routes1
Has abstractyes

Explore more

Same venueSPE Russian Oil and Gas Exploration and Production Technical Conference and ExhibitionSame topicOil and Gas Production TechniquesFrench-language works237,207