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Record W2024529579 · doi:10.2118/98219-ms

Application of Microseismic Mapping and Modeling Analysis To Understand Hydraulic Fracture Growth Behavior

2006· article· en· W2024529579 on OpenAlex
Xuemei Liu, Youjie Xu, Zhiyong Zhao, Liu Mu, Jishan Liu, Z. Gho

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSPE International Symposium and Exhibition on Formation Damage Control · 2006
Typearticle
Languageen
FieldEngineering
TopicHydraulic Fracturing and Reservoir Analysis
Canadian institutionsPetro-Canada
Fundersnot available
KeywordsMicroseismFracture (geology)Hydraulic fracturingGeologySeismologyPetroleum engineeringGeotechnical engineering

Abstract

fetched live from OpenAlex

Abstract This paper presents a detailed case history of hydraulic fracture treatments in tight oil reservoirs in remote onshore locations in China. For cases presented in this study, microseismic mapping and fracture modeling approaches were applied to understand fracture growth behavior. This paper provides a brief summary of reservoir background, but focuses on microseismic mapping as well as fracture modeling analysis. Results from fracture modeling and microseismic mapping were employed to understand post-frac performance.

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.

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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.637
Threshold uncertainty score0.587

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 head0.006
GPT teacher head0.208
Teacher spread0.202 · 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