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Record W4281295957 · doi:10.1002/gj.4475

Indicators for identification of lacustrine sandstones of sandy debris‐flow origin: A case study of Es1 Member, Palaeogene Shahejie Formation, Nanpu Sag, Bohai Bay Basin, China

2022· article· en· W4281295957 on OpenAlexaff
Jingjun Zhang, Osman Salad Hersi, Shangming Shi, Yanfang Cao, Jiayue Sun

Bibliographic record

VenueGeological Journal · 2022
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Regina
FundersNatural Science Foundation of Heilongjiang ProvinceNational Natural Science Foundation of China
KeywordsGeologyFaciesClastic rockDebris flowPaleogeneGeochemistryLithologyFluvialSedimentary rockPetrologyGeomorphologyRiver mouthSource rockDiagenesisStructural basinDebrisSediment

Abstract

fetched live from OpenAlex

The first member of Shahejie Formation of Eocene–Early Oligocene (Es1, Nanpu Sag) consists of fluvio‐deltaic to deep lacustrine shale‐sandstone accumulations, and the deep lacustrine deposits include sandy debris flow (SDF), turbiditic and mudrock facies. In the process of hydrocarbon exploration, it was found that that SDF sandstones in the deep lacustrine deposits can constitute excellent hydrocarbon reservoirs. Therefore, the identification of these lithofacies, especially SDF sandstones, is crucial for hydrocarbon exploration. We document here parameters that discriminate lacustrine SDF sandstones from turbiditic and mudrock deposits. Data from cores, wireline logs, and seismic sections are integrated and interpreted. Core‐based identification indicators of the SDF sandstones include massive structures with upper and lower sharp contacts with interbedded mudrocks, lateral pinch‐outs, locally imbricated to floating pebble‐size grains, and elongated (teared) mudrock clasts within the middle and upper parts of normally‐ or inversely‐grading sandstone and poor to high matrix content. These properties are attributed to deposition of non‐Newtonian flows with sediment‐support mechanism of dispersive pressure, matrix strength and buoyancy, sediment‐transportation mechanism, and sediment‐settling properties (hindered settling and freezing of the SDF). Log‐facies identification indicators of the SDF sandstones are characterized by higher RLLD/RLLS values (40–80 Ω m), higher SP values (35–70 mV), lower Gamma ray (GR) values (70–120 API), and strongly serrated curve motifs. Seismic facies identification indicators of the SDF sandstones have mound‐like, lenticular, or wedge‐shaped external geometries, and interior worm‐like and fusiform chaotic reflections with medium to strong amplitude, medium to high frequency, and medium to low continuity. The results and interpretation of the integrated core‐log‐seismic data as identification indicators are useful tools for identifying SDF sandstones and effectively distinguishing them from other deep lacustrine deposits.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.142
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
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 head0.028
GPT teacher head0.261
Teacher spread0.233 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2022
Admission routes1
Has abstractyes

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