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Record W4408442281 · doi:10.5194/egusphere-egu25-2655

Diagenesis, reservoir-quality, and oil-bearing heterogeneity of the Eocene deep-lacustrine mudstone in the Qibei Sub-sag, Bohai Bay Basin, China

2025· preprint· en· W4408442281 on OpenAlexaff
Jiyang Wang, Jianhua Zhao, Xiugang Pu, Keyu Liu, Wei Zhang, Zhannan Shi, Wenzhong Han, Zhihao Wang

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldEarth and Planetary Sciences
TopicGeological and Geophysical Studies
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsDiagenesisGeologyStructural basinBayGeochemistryChinaGeomorphologyPetrologyOceanographyArchaeologyGeography

Abstract

fetched live from OpenAlex

Lacustrine organic-rich Eocene mudstones are well developed and demonstrates significant exploration potential for shale oil in the Qibei Sub-sag, Bohai Bay Basin, China. However, their oil content displays strong heterogeneity, which poses challenges for effective exploration and development. Diagenesis implicates compaction, cementation, dissolution/re-precipitation processes that raises critical questions regarding reservoir quality and oil-bearing heterogeneity.Integrated high‐resolution petrologic analysis, organic geochemistry, and pore throat structure characterization provide a powerful approach to investigate the diagenesis, reservoir and oil-bearing characteristics. The 50 samples were collected from the 111.39-m-thick Eocene the first Sub-member of the third Member of the Shahejie Formation lacustrine oil-prone source rock succession penetrated by the two wells in the Qibei Sub-sag. Six typical lithofacies were identified: laminated medium-grained calcareous shale, laminated fine-grained mixed shale, thin-bedded fine-grained mixed mudstone, thin-bedded medium-grained mixed mudstone, massive medium-grained mixed mudstone, and thin-bedded coarse-grained felsic mudstone.The micritic calcite laminae formed during the sedimentary stage underwent recrystallization during the early to middle diagenetic stages, transforming into granular sparry calcite. Potassium feldspar dissolution and clay mineral transformation resulted in the formation of authigenic albite and quartz. These diagenetic processes promoted the development and preservation of intercrystalline/interparticle pores. As a result, the laminated medium-grained calcareous and laminated fine-grained mixed shale reservoirs exhibit superior reservoir properties, primarily characterized by interparticle pores, intercrystalline pores, clay mineral-associated pores, and bedding fractures. With a median pore throat diameter of 11.6 nm and an average porosity of 6.53%, these reservoirs are classified as Type I. The thin-bedded fine-grained mixed shale primarily develops clay mineral-associated pores and interparticle pores, with some bedding fractures. Its median pore throat diameter is 9.2 nm, and the average porosity is 5.56%, classifying it as a Type II reservoir. The thin-bedded medium-grained mixed and massive medium-grained mixed mudstones mainly develop interparticle pores and clay mineral-associated pores. These have a median pore throat diameter of 12.6 nm and an average porosity of 4.3%, classifying them as Type III reservoirs. In felsic mudstone, calcite cementation significantly reduced porosity during the early diagenetic stage. This results in the poorest porosity development in the thin-beded coarse-grained felsic mudstone, which has a median pore throat diameter of 15.9 nm and an average porosity of 3.26%, classifying it as Type IV reservoir.The laminated medium-grained calcareous shale, laminated fine-grained mixed shale, and thin-bedded fine-grained mixed mudstone exhibit relatively high oil content and OSI values. The average oil content values are 2.48 mg/g, 2.64 mg/g, and 2.30 mg/g, respectively, and the average OSI values are 144 mg HC/g TOC, 163 mg HC/g TOC, and 168 mg HC/g TOC. These lithofacies are favorable for shale oil exploration and development. We suggest that addressing the challenges of mudstone diagenesis will significantly improve understanding and prediction of reservoir quality and oil-bearing heterogeneity in unconventional shale oil plays.

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)0.001
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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.032
Threshold uncertainty score0.970

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.037
GPT teacher head0.265
Teacher spread0.229 · 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 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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