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Record W2046034613 · doi:10.2118/162043-ms

Potential to Increase Oil Reserves Due to Non-used "Lost" Deposits Located at Presently Operated Fields of OAO "Samaraneftegas"

2012· article· en· W2046034613 on OpenAlexaff
V. S. Arkhipov, Yu. A. Zubova, Yu. D. Krainiy, A.E. Manasyan, A. S. Ustinov

Bibliographic record

VenueSPE Russian Oil and Gas Exploration and Production Technical Conference and Exhibition · 2012
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsOntario Association of Optometrists
Fundersnot available
KeywordsOil reservesOil fieldEnvironmental scienceOil productionWork (physics)Fossil fuelPetroleum engineeringProduction (economics)Resource (disambiguation)Production ratePetroleumNatural resource economicsEngineeringWaste managementGeologyComputer scienceProcess engineeringEconomics

Abstract

fetched live from OpenAlex

Abstract Presently the objective to expand the resource basis of the now-operated hydro-carbon reserves remains rather acute. The experience in building-up the oil reserves is given on the basis of revealing previously non-operated reservoirs at the field that are presently operated. The practical efficiency of considered approach is proved. The search and start-up of these now not-operated reservoirs allows to build-up the amount of active reserves and to produce oil using the low-cost measures. The paper presents the basic results of a system work with the same subject for the last two years. In 2010 they have opened and commissioned 6 new reservoirs at 5 fields that contain 1,364 million of tons of recoverable oil; the growth in oil production rate has made 843 t/d. In 2011 they have opened 14 new reservoirs at 13 fields, of which 11 pools were included into state balance. The build-up in recoverable reserves by industrial category C1 has made 1,681 million tons, the oil production rate growth - 801 t/d.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.265
Threshold uncertainty score0.649

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 communication0.0000.001
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 head0.026
GPT teacher head0.262
Teacher spread0.236 · 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 designBench or experimental
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
Published2012
Admission routes1
Has abstractyes

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