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Record W1486144199 · doi:10.2118/131792-pa

Challenges, Uncertainties, and Issues Facing Gas Production From Gas-Hydrate Deposits

2011· article· en· W1486144199 on OpenAlexaff
George J. Moridis

Bibliographic record

VenueSPE Reservoir Evaluation & Engineering · 2011
Typearticle
Languageen
FieldEnvironmental Science
TopicMethane Hydrates and Related Phenomena
Canadian institutionsUniversity of Calgary
FundersNational Energy Technology LaboratoryU.S. Department of Energy
KeywordsClathrate hydrateProspectingHydratePetroleumProduction (economics)Environmental sciencePetroleum engineeringGeologyMining engineeringChemistry

Abstract

fetched live from OpenAlex

Summary The current paper complements the Moridis et al. (2009) review of the status of the effort toward commercial gas production from hydrates. We aim to describe the concept of the gas-hydrate (GH) petroleum system; to discuss advances, requirements, and suggested practices in GH prospecting and GH deposit characterization; and to review the associated technical, economic, and environmental challenges and uncertainties, which include the following: accurate assessment of producible fractions of the GH resource; development of methods for identifying suitable production targets; sampling of hydrate-bearing sediments (HBS) and sample analysis; analysis and interpretation of geophysical surveys of GH reservoirs; well-testing methods; interpretation of well-testing results; geomechanical and reservoir/well stability concerns; well design, operation, and installation; field operations and extending production beyond sand-dominated GH reservoirs; monitoring production and geomechanical stability; laboratory investigations; fundamental knowledge of hydrate behavior; the economics of commercial gas production from hydrates; and associated environmental concerns.

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 categoriesInsufficient payload (model declined to judge)
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 score0.082
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0010.000

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 head0.060
GPT teacher head0.257
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 teacher head, not a consensus.

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

Citations10
Published2011
Admission routes1
Has abstractyes

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