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Record W2736460209

Estimation Method of Natural Water Bodies in the Fracture Cavity Carbonate Reservoir of the Sea

2017· article· en· W2736460209 on OpenAlexvenueno aff
Zhanhua Zhang, Xue Liu, Junbo Yao, Huiyun Wen, Guanhong Yang

Bibliographic record

VenueAdvances in petroleum exploration and development · 2017
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsnot available
Fundersnot available
KeywordsGeologyPetroleum engineeringCarbonateReservoir engineeringCaveOil fieldFracture (geology)Petroleum reservoirGeotechnical engineeringPetrologyPetroleumPaleontology
DOInot available

Abstract

fetched live from OpenAlex

In recent years, the discovery of fractured carbonate reservoirs has made it become a hot spot for the development of such reservoirs. The oil field of south of Bohai is a typical fracture cavity reservoir, which is different from the land oil field. In this oil field, fluid reservoir space is mainly composed of fractures, but caves are not developed, at the same time the reservoir has strong heterogeneity. Oil water relationship and reservoir type are extremely complex and the percolation law is essentially different from the general marine sandstone reservoir. In view of the actual situation of the oil field, the volume of natural water body was studied by reservoir engineering method. By comparative analysis, the results obtained by reservoir engineering method are in agreement with the numerical simulation method. However, reservoir engineering method is simple and rapid, which has a certain reference value for the rapid assessment of water bodies in the same type of oil reservoir at sea.

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 score0.211
Threshold uncertainty score0.186

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 head0.012
GPT teacher head0.274
Teacher spread0.262 · 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
Published2017
Admission routes1
Has abstractyes

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