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Record W2071859844 · doi:10.1306/02220605065

Reconstructing the architecture and sequence stratigraphy of the preserved fluvial record as a tool for reservoir development: A reality check

2006· article· en· W2071859844 on OpenAlexaff
Andrew D. Miall

Bibliographic record

VenueAAPG Bulletin · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicGeological formations and processes
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsGeologyFluvialSequence stratigraphySequence (biology)StratigraphyArchitecturePaleontologyArchaeologyFaciesGeographyTectonics

Abstract

fetched live from OpenAlex

Abstract Driven in part by the need for better information about fluvial systems for the purpose of nonmarine reservoir evaluation and development, much valuable work is now being conducted on modern rivers and their deposits, aided by such techniques as ground-penetrating radar. However, studies of modern and recent systems cannot address the question of the long-term preservability of the present-day deposits. Only studies of the rock record itself can explore this issue. Two separate studies of ancient fluvial systems illustrate some of the problems. A study of the Hawkesbury Sandstone (Triassic, Sydney Basin, Australia), highlighted the difficulty in interpreting the dimensions of large sand bodies from comparisons with a modern analog, even when very large outcrops are available. A seismic time-slice study of Pliocene–Pleistocene fluvial systems in the Gulf of Thailand revealed major changes in channel size and fluvial style over short vertical intervals. Braided and meandering systems (meander-belt widths 4 to >10 km [2.5 to >6 mi]) are separated by a few tens of meters of section, or less, and are interbedded with the deposits of much smaller rivers, showing straight, meandering, and anastomosed patterns. Incised valleys and underfit streams are also present. These variations can be interpreted in terms of a sequence model, but they indicate the problems that could arise from the use of a single suite of dimensional variables as input into numerical reservoir heterogeneity and flow models. Most numerical simulation models make use of sets of equations relating such parameters as channel width, depth, and sinuosity, but most such equations are generalized across the whole spectrum of fluvial styles and can be conditioned to the reality of individual reservoirs only with difficulty. The application of the principles of sequence stratigraphy to fluvial deposits is rendered difficult by the complex response to allogenic forcing that characterizes fluvial systems. Episodes of aggradation and degradation that may be used to define sequences, and their bounding unconformities in the stratigraphic record may be the result of the complex interplay of several allogenic mechanisms governing varying stream power and sediment supply, mechanisms that may be operating at different time scales and may be out of phase with each other. In developing practical solutions for reservoir development, numerical modeling and simulation may provide generalized starting points for the analysis. History matching commonly demonstrates inaccuracies in many initial models. Further progress may be made by direct study of the reservoir itself, using three-dimensional (3-D) seismic and surveillance techniques. There is a continuing role for the study of ancient analogs as providing a realistic database on the long-term preservation styles of fluvial reservoir 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)0.003
metaresearch head score (Gemma)0.005
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 score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0010.001
Scholarly communication0.0020.002
Open science0.0010.001
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0020.001

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 head0.027
GPT teacher head0.224
Teacher spread0.197 · 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

Citations174
Published2006
Admission routes1
Has abstractyes

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