z-logo
open-access-imgOpen Access
Application of unsupervised machine learning approach for characteristics of microseismic events at a CO2 injection site.
Author(s) -
Rachel A. Willis,
Hongkyu Yoon
Publication year - 2020
Publication title -
osti oai (u.s. department of energy office of scientific and technical information)
Language(s) - English
Resource type - Conference proceedings
DOI - 10.2172/1833167
Subject(s) - microseism , computer science , waveform , unsupervised learning , cluster analysis , artificial intelligence , noise (video) , machine learning , pattern recognition (psychology) , noisy data , fuzzy logic , volume (thermodynamics) , data mining , geology , seismology , telecommunications , radar , physics , quantum mechanics , image (mathematics)

The content you want is available to Zendy users.

Already have an account? Click here to sign in.
Having issues? You can contact us here
Accelerating Research

Address

John Eccles House
Robert Robinson Avenue,
Oxford Science Park, Oxford
OX4 4GP, United Kingdom