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Record W4415567884 · doi:10.1190/int-2025-0026

Hydrocarbon source correlation and multiphase accumulation in the northern Kuqa Thrust Belt: Implications from geochemical fingerprinting and tectono-thermal evolution of the Dibei Field, NW China

2025· article· en· W4415567884 on OpenAlexaff
Caiyuan Dong, Liang Zhang, Jin Li, Chen Changchao

Bibliographic record

VenueInterpretation · 2025
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsSteraneSource rockHopanoidsProspectivity mappingPetrographyPetroleumHydrocarbon

Abstract

fetched live from OpenAlex

Abstract The Kuqa Depression, a prolific hydrocarbon province in China’s Tarim Basin, hosts a dual-source petroleum system with Jurassic coal-bearing and Triassic lacustrine strata. However, the origins and accumulation mechanisms of hydrocarbons in the Dibei Structural Belt remain contentious, particularly regarding contributions from Jurassic (J2kz, J1y) versus Triassic (T3h, T2-3k) source rocks, compounded by ambiguities in biomarker interpretations and uncalibrated thermal models. Advanced geochemical fingerprinting — including sterane distributions, gammacerane indices (GI; ratio of gammacerane to C30 hopane), and δ¹³C isotopes — was integrated with calibrated burial-thermal modeling and structural analysis, which allowed us to clarify source contributions, hydrocarbon charging history, and structural controls on accumulation. Geochemical results demonstrated that Yangxia Formation (Paleogene; a major regional seal and secondary reservoir unit within the Kuqa Depression) oils exhibit “inverted-L” sterane patterns (C27 < C29) and δ¹³C values of −26‰ to −23‰, confirming derivation from Jurassic coal measures. In contrast, Ahe Formation (Jurassic; a major regional sandstone reservoir unit within the Kuqa Depression) hydrocarbons displayed “V-shaped” sterane ratios (C27 > C29), δ¹³C values of −32‰ to −30‰, and elevated GI (0.21–0.32), indicative of Triassic lacustrine sources. Notably, the identification of Triassic-sourced hydrocarbons in deep Ahe reservoirs challenged previous Jurassic-centric models, resolving ambiguities through multiproxy integration. Burial-thermal modeling, constrained by fluid inclusion homogenization temperatures (80°C–160°C), revealed three charging phases: phase I (19–16 Ma, Jidike Fm.), phase II (16–12 Ma, Kangcun Fm.), and phase III (5–1 Ma, Kuqa Fm.), with phase III Himalayan tectonics critically reshaping paleo-accumulations into an inverted “gas-below-oil” stratification (phase reversal due to tectonic reorganization). Structural analysis revealed (1) two boundary-fault anticlinal traps (defined by opposed north- and south-dipping thrust faults) with vertical gas migration in Ahe sandstones and (2) fault-sealed tight gas accumulations controlled by reservoir quality. These findings highlighted the dominant contribution of Triassic sources to deep gas reservoirs in Dibei and underscored the importance of multiphase tectonic evolution and source–reservoir coupling. This study provided a predictive framework for hydrocarbon exploration in fold-and-thrust belts, advocating prioritized assessment of fault connectivity and Triassic saline lacustrine source 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 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: Empirical
Teacher disagreement score0.243
Threshold uncertainty score0.299

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 head0.005
GPT teacher head0.233
Teacher spread0.227 · 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

Citations0
Published2025
Admission routes1
Has abstractyes

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