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Record W1978136817 · doi:10.1190/1.3609092

Effective VTI anisotropy for consistent monitoring of microseismic events

2011· article· en· W1978136817 on OpenAlexaff
Leo Eisner, Yang Zhang, Peter Duncan, Michael C. Mueller, Michael Thornton, Davide Gei

Bibliographic record

VenueThe Leading Edge · 2011
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Imaging and Inversion Techniques
Canadian institutionsMicrosemi (Canada)
Fundersnot available
KeywordsMicroseismAnisotropyGeologyHydraulic fracturingPermeability (electromagnetism)SeismologyFracture (geology)Economic geologyGeophysicsPetroleum engineeringGeotechnical engineeringVolcanismTectonicsOptics

Abstract

fetched live from OpenAlex

The monitoring of induced or triggered microseismic events increasingly is being used to inform the efficient production of unconventional reservoirs. A key aspect of economic production in these low-permeability rocks is hydraulic fracture stimulation, usually in horizontal wells. To evaluate the success of the stimulation, engineers rely on monitoring the induced (or triggered) microseismic events that are then interpreted to map the stimulated reservoir volume and likely drainage area of the well. These microseismic events can be mapped either from downhole or surface monitoring arrays. In this study, we discuss a newly developed methodology that allows economic and consistent mapping of microseismic events from multiple stimulated wells across an entire field. This approach allows better comparison of stimulation techniques between wells in order to optimize long-term development of the reservoir. As well, the method enables a relatively robust observation of velocity anisotropy that leads to better wave-propagation modeling and more accurate event locations

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.743
Threshold uncertainty score0.220

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)0.0000.000

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 head0.041
GPT teacher head0.252
Teacher spread0.211 · 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

Citations13
Published2011
Admission routes1
Has abstractyes

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