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Record W4223989164 · doi:10.1111/1755-6724.14938

Facies Analysis, Sequence Stratigraphy and Diagenetic Studies of the Jurassic Carbonates of the Kohat Basin, Northwest Pakistan: Reservoir Implications

2022· article· en· W4223989164 on OpenAlexaff
Emadullah Khan, Abbas Ali Naseem, Suleman Khan, Bilal Wadood, Faisal Rehman, Maryam Saleem, Mubashir Mehmood, Waqar Ahmad, Zubair Ahmed, Tahir Azeem

Bibliographic record

VenueActa Geologica Sinica - English Edition · 2022
Typearticle
Languageen
FieldEngineering
TopicHydrocarbon exploration and reservoir analysis
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsGeologyDiagenesisDolomitizationFaciesPetrographyShoalSedimentary depositional environmentCarbonateSequence stratigraphyGeochemistryDolomiteOutcropPaleontologyGeomorphologyStructural basin

Abstract

fetched live from OpenAlex

Abstract The present study deals with the depositional facies, diagenetic processes and sequence stratigraphy of the shallow marine carbonates of the Samana Suk Formation, Kohat Basin, in order to elucidate its reservoir quality. The Samana Suk Formation consists of thin to thick‐bedded, oolitic, bioclastic, dolomitic and fractured limestone. Based on the integration of outcrop, petrographic and biofacies analyses, the unit is thought to have been deposited on a gentle homoclinal ramp in peritidal, lagoonal and carbonate shoal settings. Frequent variations in microfacies based sea‐level curve have revealed seven Transgressive Systems Tracts (TSTs) and six Regressive Systems Tracts (RSTs). The unit has undergone various stages of diagenetic processes, including mechanical and chemical compaction, cementation, micritization, dissolution and dolomitization. The petrographic analyses show the evolution of porosity in various depositional and diagenetic phases. The fenestral porosity was mainly developed in peritidal carbonates during deposition, while the burial dissolution and diagenetic dolomitization have greatly enhanced the reservoir potential of the rock unit, as is further confirmed by the plug porosity and permeability analyses. The porosities and permeabilities were higher in shoal facies deposited in TSTs, as compared to lagoonal and peritidal facies, except for the dolomite in mudstone, deposited during RSTs. Hence good, moderate and poor reservoir potential is suggested for shoal, lagoonal and peritidal facies, respectively.

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 score0.094
Threshold uncertainty score0.187

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 studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.029
GPT teacher head0.266
Teacher spread0.237 · 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

Citations6
Published2022
Admission routes1
Has abstractyes

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Same venueActa Geologica Sinica - English EditionSame topicHydrocarbon exploration and reservoir analysisFrench-language works237,207