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Record W4384303187 · doi:10.3997/2214-4609.202310448

Time-lapse seismic analysis using ACROSS source and DAS at the Aquistore CO2 storage site

2023· article· en· W4384303187 on OpenAlexaffabout
Y. Kitawaki, Hiroshi Shimizu, Naoyuki Shimoda, Y. Nakayama, Hajime Tanaka, Yoshitomo Konishi, Don White, Erik Nickel

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEarth and Planetary Sciences
TopicSeismic Waves and Analysis
Canadian institutionsPetroleum Technology Research CentreGeological Survey of Canada
Fundersnot available
KeywordsSeismologyTime domainGeologySIGNAL (programming language)Data processingFrequency domainAmplitudeSignal processingNoise (video)Vertical seismic profileGeodesyComputer scienceEngineeringElectronic engineeringDigital signal processingOptics

Abstract

fetched live from OpenAlex

Summary Herein we investigate the effectiveness of reservoir monitoring using a permanent seismic source (accurately controlled, routinely operated signal system: ACROSS) and permanent receivers (distributed acoustic sensing: DAS) at the Aquistore CO₂ storage site in southern Saskatchewan, Canada. Baseline and monitoring vertical seismic profile (VSP) data using ACROSS source and DAS were acquired in December 2016, March 2018, April 2019 and January 2020. DAS recording data with a fiber optic cable are output in the strain rate domain in the direction of the cable due to the measurement principle. Although previous VSP processing was performed in the strain rate domain, we converted the strain rate data into particle velocity and performed unified processing including ACROSS signal processing, data matching, VSP data processing and time-lapse noise suppression for four data vintages to compare with the log-based synthetic and other seismic data in the same domain. In addition to the difference between migration cross sections, normalized root mean square (NRMS) amplitude difference was calculated to evaluate the time-lapse seismic responses relative to the December 2016 data. The anomalies are identified at the target level in the NRMS cross sections and may be a sign of seismic response changes associated with CO₂ injection.

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 categoriesInsufficient payload (model declined to judge)
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 score0.140
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.001

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 head0.015
GPT teacher head0.249
Teacher spread0.234 · 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; both teacher heads agree on what is shown here.

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

Citations1
Published2023
Admission routes2
Has abstractyes

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