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Record W1901530637 · doi:10.3968/5308

Application of Phase-Controlled Reservoir Prediction Technology in NB Oilfield of Bohai Bay

2014· article· en· W1901530637 on OpenAlexvenueno aff
Jun Ming, Mingchun Wang, Lv Tan, Tongxing Xia, Zijun Han

Bibliographic record

VenueAdvances in petroleum exploration and development · 2014
Typearticle
Languageen
FieldEngineering
TopicReservoir Engineering and Simulation Methods
Canadian institutionsnot available
Fundersnot available
KeywordsPetrophysicsGeologyFluvialPetroleum engineeringOil fieldFaciesPermeability (electromagnetism)PetrologyReservoir modelingGeotechnical engineeringGeomorphologyPorosity

Abstract

fetched live from OpenAlex

The shallow oil and gas fields of the Bohai Sea are dominated by fluvial deposition, large lateral variations of the reservoir, and a complex oil-water relationship. Horizontal wells must be deployed within the high quality reservoirs with good physical properties and high permeability so as to improve the productivity of the oil wells. Therefore, the reliability of reservoir prediction becomes extremely important. In this paper, on the basis of analyzing the petrophysical characteristics and seismic response characteristics of the reservoir, we proposed the phase-controlled reservoir prediction technology, which combines reservoir prediction and reservoir cause; studied the distribution law of the high quality reservoirs of the NB Oilfield by using phase-controlled reservoir prediction technology; deployed and drilled the development wells on this basis, and obtained good results. Key words : Fluvial facies; Reservoir prediction; Phase-controlled; Main parameters of seismic waves

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 score0.744
Threshold uncertainty score0.387

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 head0.011
GPT teacher head0.274
Teacher spread0.263 · 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

Citations1
Published2014
Admission routes1
Has abstractyes

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