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Record W4256555111 · doi:10.1306/13201169m892598

Characterization of a Sediment Core from Potential Gas-hydrate-bearing Reservoirs in the Sagavanirktok, Prince Creek, and Schrader Bluff Formations of Alaska's North Slope

2009· book-chapter· en· W4256555111 on OpenAlexaff
Richard Sigal, Chandra Rai, Carl Sondergeld, Bryan M. Spears, W. J. Ebanks, W. D. Zogg, N. Emery, G. McCardle, R. Schweizer, W. G. McLeod, J. Van Eerde

Bibliographic record

VenueAmerican Association of Petroleum Geologists eBooks · 2009
Typebook-chapter
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsAlberta Oil Sands Technology and Research Authority
Fundersnot available
KeywordsMemoirClathrate hydrateGeologyArchaeologyEarth scienceHistoryArt historyHydrateChemistry

Abstract

fetched live from OpenAlex

Abstract The Anadarko Hot Ice 1 well was cored as part of a project to study the occurrence of gas hydrate on the North Slope of Alaska. The observations and measurements made at the drill site along with the subsequent core analysis are described in five individual reports published in this Memoir. This report deals with the nuclear magnetic resonance (NMR) measurements made on the recovered core from the Hot Ice 1 gas-hydrate research well. Samples from sands recovered during phase I of the coring of the Hot Ice 1 well came from the permafrost zone. The NMR measurements were conducted on frozen core samples, samples in which the ice was allowed to completely melt, and samples that were cleaned, dried, and resaturated with brine. Not all measurements were done on all samples. For the low-field-strength system used to measure the NMR response, only hydrogen nuclei in unfrozen fluid contribute to the signal. Four core-derived samples were measured at a temperature of −5°C (23°F). They had NMR porosities of 7.1% (37% core-derived He porosity), 9.4% (40% core-derived He porosity), 9.8% (42.4% core-derived He porosity), and 11.6% (31.6% core-derived He porosity). The NMR spectra for all the frozen samples were very similar. The NMR porosities represent the percentage of the sample volume containing unfrozen brine. The He porosities were measured on cleaned and dried core plugs. Four models for the way ice could form when the unfrozen sample is frozen where investigated. For each model, the frozen NMR spectra were computed from the unfrozen spectra. None of the models provided a satisfactory match to the measured frozen spectra. An anomalous result of the study was a significant difference between NMR spectra measured on melted samples and the measurements done after cleaning and resaturation with brine. The differences are essentially a shift to slower relaxation times for the resaturated samples without any change in the shape of the spectrum. The simplest explanation for this is a reduction in surface relaxivity produced by cleaning and resaturation. For most sedimentary sandstones, the NMR geometrical mean decay time combined with porosity can be used to predict permeability. For the phase I recovered sandstones, the prediction is worse than commonly seen. Also, a commonly used default formula provides a very poor fit to the data and underestimates the permeability on average by a factor of 25. This suggests a much larger surface relaxivity than commonly seen. The phase I recovered sands, when water saturated, exhibit five different spectrum types. Most of the samples fall into the first two identified types, which differ only in the presence of a small percentage of faster relaxing small pores in type 2 and their absence in type 1. The unconsolidated sand samples recovered in phase II were recovered from unfrozen sediments. The NMR was done only on cleaned and dried samples. They had very similar spectra classes as the phase I samples. Unlike the phase I samples, an excellent permeability estimate can be obtained from the NMR measurements. It has the same form as the standard estimator, but the multiplicative constant is about 12 times the value used in the standard estimator. This is very likely caused by a much larger than normal surface relaxivity or large internal magnetic gradients.

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 score0.190
Threshold uncertainty score0.926

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 studies0.0000.001
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 head0.010
GPT teacher head0.205
Teacher spread0.195 · 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".

Quick stats

Citations0
Published2009
Admission routes1
Has abstractyes

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