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Record W7071725235

Submarine Fan Systems: Proximal to Distal Reservoir Quality Controls

2021· dissertation· en· W7071725235 on OpenAlexaboutno aff

Bibliographic record

VenueDurham e-Theses (Durham University) · 2021
Typedissertation
Languageen
FieldEnvironmental Science
TopicRemote Sensing in Agriculture
Canadian institutionsnot available
Fundersnot available
KeywordsGrainstoneOverprintingQuality (philosophy)Erosion
DOInot available

Abstract

fetched live from OpenAlex

Submarine fans and related turbidite systems are important components of continental margins; they contain a stratigraphic record of environmental changes, host large accumulations of oil and gas, and offer potential sites for carbon capture and storage (CCS). The influence of grain size and sediment flux to submarine fans has been recognised as a primary control on the heterogeneity of deep-water facies. Predicting fan depositional facies, changes in clay matrix content from proximal to distal settings, and evaluating the role played by clay coatings on detrital grains are important challenges in the characterizations of submarine fan systems. In this study, a multi-technique approach is applied, including detailed petrography, burial history modelling, SEM, SEM-CL, SEM-EDS mapping, and hydrothermal reactor experiments. Extensive subsurface datasets (well logs, cores, and thin sections) from 13 wells and 191 samples are used from the Paleocene-Eocene Forties Sandstone Member of the Sele Formation, Central North Sea, UK. These data are used to assess the role played by clays (detrital and authigenic), depositional facies, and burial diagenesis in reservoir quality evolution in proximal to distal fan depositional settings. The study reveals that amalgamated sandstones facies of proximal fan of the Forties Sandstone Member have the best reservoir quality due to coarser grain size, less detrital clay matrix, and low ductile grains content (< 5%), whereas the distal fan, mud-prone heterolithic sandstones have the poorest reservoir quality due to finer grain size, high clay matrix, and high ductile grains content (> 5 %). The optimum pore-filling clays volume, which have a deleterious effect on reservoir quality, range from 10-30 %. Furthermore, detrital smectite, which was both inherited and emplaced during sediment dewatering, was the main source of grain-coating chlorite, illite-smectite, and illite. The optimum clay-coating coverage to inhibit quartz cementation ranges from 40 to 50 % (based on the present-day burial depths of 2200 - 3200 m TVDSS) and clay volume of up to 8 %. Average quartz cement volume decreases from 3.62 % in proximal fan to 1.78 % in distal fan settings, presumably due to impact of grain-coating and pore-filling clays. Grain size has no impact on clay-coating coverage, which suggests that the finer-grained distal fan sandstones could have good clay-coating coverage to arrest quartz cementation during burial and chemical compaction depths > 2500 m. Blocky kaolinite and fibrous illite as low as 2 % have been found to have detrimental effect on the sandstones reservoir quality, whereas pore-filling chlorite has a threshold value ranging from 3 to 10 %. A complimentary experimental study using an autoclave-engineers hydrothermal reactor has been undertaken using sand-rich turbidite channel facies samples from the Bute Inlet, British Columbia, Canada. The results demonstrate that the presence of detrital clay is crucial for the formation of authigenic clays. Channelised sand facies with < 1 % detrital clay have poorly-developed coatings coverage (max 47 %) post-experiment. In comparison, lobe facies with 6 % initial detrital clay formed well-developed coatings coverage (max 77 %), with clay volume ranging from 19 to 27 % post-experiment. These results can be used as input parameters for the assessment of reservoir potentials in carbon sequestration and storage, and in hydrocarbon exploration and production.

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)0.001
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 score0.033
Threshold uncertainty score0.066

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.013
GPT teacher head0.232
Teacher spread0.219 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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