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Record W3034689780 · doi:10.1190/int-2019-0243.1

Conglomerate petrology characterization using high-definition borehole electrical images in the Upper Urho Formation at well JL42, Zhongguai Uplift, Junggar Basin, China

2020· article· en· W3034689780 on OpenAlex
Rui Yuan, Bo Yang, Chunfu Pan, Wenjun He, Youlun Feng, Kang Zhao

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

VenueInterpretation · 2020
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
FundersNational Natural Science Foundation of China
KeywordsGeologyFaciesConglomerateSedimentary depositional environmentBoreholePetrologySedimentary rockStructural basinFluvialPaleontology

Abstract

fetched live from OpenAlex

Abstract Cores drilled from wells are significant resources for understanding the geologic characteristics of petroleum reservoirs. However, due to the high cost and long rig time involved, it is impossible to obtain cores from the entire sedimentary formation in a drilling well. Furthermore, core breakage limits the amount of information that can be obtained in the vertical deposition environment of deep-buried formations. Therefore, we have used ultrahigh-resolution and high-quality borehole electrical images obtained by a borehole electrical imaging tool, High-Definition Formation MicroImager (FMI-HD), to supplement “core” information and characterize the petrologic features, such as grain size and sedimentary structure, of conglomeratic formations in the Permian Upper Urho Formation at well JL42, Zhongguai Uplift, Junggar Basin, China. We have observed conglomeratic cores at 95.92 m in well JL42 and recorded various petrologic features of the core cylinders. In the cored interval, the FMI-HD images were compared with core photos in detail; grain size results from the FMI-HD images and cores were very similar. However, there were major differences in the structural results due to core interruption. In addition, the high-resolution depositional facies of the Upper Urho Formation at well JL42 were dissected in terms of the distributive fluvial system, not the fan-delta system, using vertical grain size features derived from FMI-HD images. Boulders, cobbles, coarse pebbles, and fine pebbles were developed in thick gravelly channels in the lower proximal facies, whereas fine pebbles and granules were developed in thin channels in the upper medial facies. Therefore, FMI-HD images can be efficiently used to supplement cores and sedimentary information, which provides important insights on the paleogeology of conglomeratic formations and in turn on the exploration potential of petroleum systems.

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: Simulation or modeling · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.739
Threshold uncertainty score0.599

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
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 head0.011
GPT teacher head0.212
Teacher spread0.202 · 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