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Record W2314110134 · doi:10.1190/1.3603573

High precision 3D seismic exploration techniques of the large mining city zone in eastern China

2009· article· en· W2314110134 on OpenAlex
Yi Qiu, Xuming Bai

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicGeoscience and Mining Technology
Canadian institutionsHusky Energy (Canada)
Fundersnot available
KeywordsChinaGeologyMining engineeringSeismologyComputer scienceGeographyArchaeology

Abstract

fetched live from OpenAlex

Old oil fields in eastern China have high level of exploration and development, the main structural oil & gas reservoirs have been basically imaged. In order to realize the idea of continuous oilfield development and to find oil around and in the deep layers under old oilfields, researching the prospecting techniques, which are aimed at the complicated near-surface areas in oil-rich areas (the forbidden exploration area, for example, the urban zone), has to be increased In recent years, in the eastern China, a set of high precision 3D exploration techniques has been developed by carrying out the seismic work for the wide range of obstacles of old oil field - mining city zone (more than 20km2 mining area), including: special geometry design techniques based on the complex surfaces and deep objectives, geometry optimizing and implementing techniques based on the high — resolution satellite image, near-surface obstacles investigation techniques, city zone seismic shooting techniques, noise eliminating techniques for fixed source noise interference, migration imaging techniques based on energy balance, which could be provided reference for similar project.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.189

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 head0.013
GPT teacher head0.227
Teacher spread0.214 · 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

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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