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Record W2218602087 · doi:10.3968/7917

Changyuan Periphery Oilfield Economic Evaluation Method of Waterflood Potential Exploitation Measures

2015· article· en· W2218602087 on OpenAlexvenueno aff
Jiawei Ren, Xisheng Zhou, Dong Zhang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2015
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsWater cutProduction (economics)Petroleum engineeringOil productionEconomic evaluationIndex (typography)Payback periodEconomic feasibilityFossil fuelProduction costEnvironmental economicsNatural resource economicsEnvironmental scienceBusinessEngineeringComputer scienceEconomicsWaste managementMicroeconomics

Abstract

fetched live from OpenAlex

Changyuan periphery oilfield stable form of 5.2 million production requires fine waterflood to reduce the amplitude of production decline and relieve pressure. However, the effiency of Potential Exploitation Measures were uneven, affecting oil production and economic benefits. So there need to economic evaluation for measures and make measures adjustment. Assessed two different blocks’ economic through evaluated single oil and water well measures and the combined effect of blocks measures. Single well economic evaluation of oil and water wells measures include: measures validity, income, the incremental input-output ratio, payback period and efficiency 5 indicators. The combined effect of blocks measures evaluate by index P. In Changyuan periphery five demonstration area as an example, analysised of the best and worst economic effect of each blocks, and obtain a comprehensive evaluation results of the demonstration area. The evaluation results were consistent with actual situation, it should be widely applied.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.781
Threshold uncertainty score0.499

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 communication0.0000.001
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 head0.051
GPT teacher head0.315
Teacher spread0.264 · 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
GenreMethods

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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