MétaCan
Menu
Back to cohort
Record W2128802367 · doi:10.1306/05020605171

Seismic expression of fracture-swarm sweet spots, Upper Cretaceous tight-gas reservoirs, San Juan Basin

2006· article· en· W2128802367 on OpenAlexaff
Bruce S. Hart

Bibliographic record

VenueAAPG Bulletin · 2006
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMcGill University
Fundersnot available
KeywordsCretaceousGeologyTight gasStructural basinSweet spotFracture (geology)SeismologyPaleontologyHydraulic fracturingShear (geology)

Abstract

fetched live from OpenAlex

Abstract Fracture swarms associated with subtle structures greatly enhance production from tight-gas sandstones of the Mesaverde Group and Dakota Formation in the San Juan Basin. The structures include grabens, horsts, and normal faults, and they can be identified using curvature analyses of horizons mapped in three-dimensional seismic data. Their orientations and styles are consistent with the orientation of fractures that have been identified by other authors using outcrop, core, borehole imagery, and production analyses. Integration of production data (rate-versus-time plots) demonstrates the existence of a drainage interference for wells located on some of the structures. This observation further testifies to a positive correlation between the presence of subtle structures, high fracture intensity, and high fracture permeability. The methods and results described herein can be directly applied to other areas. However, because natural fractures can both enhance and retard hydrocarbon production depending on their character, calibration of seismic, engineering, and other data types will be needed to determine whether subtle structures should be considered as drilling targets, or whether they are to be avoided.

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)0.000
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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.091
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0100.001

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 head0.008
GPT teacher head0.201
Teacher spread0.193 · 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 designNot applicable
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

Citations45
Published2006
Admission routes1
Has abstractyes

Explore more

Same venueAAPG BulletinSame topicSeismic Imaging and Inversion TechniquesFrench-language works237,207