Evidence map›Paper›PMID 33920498›Full record

ArticleSensors (Basel, Switzerland)2021

Underground Microseismic Event Monitoring and Localization within Sensor Networks.

Sili Wang, Mark P Panning, Steven D Vance, Wenzhan Song

Abstract read
In one paragraph

Article in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Sili WangCollege of Engineering, University of Georgia, Boyd Graduate Building 128, Athens, GA 30602, USA.ORCID 0000-0002-3672-1243
Mark P PanningJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA.
Steven D VanceJet Propulsion Laboratory, California Institute of Technology, Pasadena, CA 91109, USA.
Wenzhan SongCollege of Engineering, University of Georgia, Boyd Graduate Building 128, Athens, GA 30602, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Locating underground microseismic events is important for monitoring subsurface activity and understanding the planetary subsurface evolution. Due to bandwidth limitations, especially in applications involving planetarily-distributed sensor networks, networks should be designed to perform the localization algorithm in-situ, so that only the source location information needs to be sent out, not the raw data. In this paper, we propose a decentralized Gaussian beam time-reverse imaging (GB-TRI) algorithm that can be incorporated to the distributed sensors to detect and locate underground microseismic events with reduced usage of computational resources and communication bandwidth of the network. After the in-situ distributed computation, the final real-time location result is generated and delivered. We used a real-time simulation platform to test the performance of the system. We also evaluated the stability and accuracy of our proposed GB-TRI localization algorithm using extensive experiments and tests.

Indexed as

distributed sensor networkGaussian beam migrationreal-time seismic simulationseismic source localizationtime reverse imaging

Identifiers

PMID33920498
PMCPMC8073147

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.