首页|New Findings from University of Oklahoma in Machine Learning Provides New Insigh ts (Characterization of Seismic-scale Petrofacies Variability In the Arbuckle Gr oup Using Supervised Machine Learning: Wellington Field, Kansas)
New Findings from University of Oklahoma in Machine Learning Provides New Insigh ts (Characterization of Seismic-scale Petrofacies Variability In the Arbuckle Gr oup Using Supervised Machine Learning: Wellington Field, Kansas)
扫码查看
点击上方二维码区域，可以放大扫码查看
原文链接
NETL
NSTL
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – Researchers detail new data in Machine Learning. According to news reporting originating from Norman, Oklahoma, by New sRx correspondents, research stated, “The Arbuckle Group in southern Kansas has been investigated for carbon geosequestration-related studies. In this study, we evaluated the seismic-scale petrophysically defined facies variability of the A rbuckle Group at the Wellington Field, Kansas, using quantitative seismic interp retation and a supervised Random Forest classification approach.”
NETL
NSTL
