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All Journal Aceh International Journal of Science and Technology
Akmal Ferdiyan
Department of Physics, FMIPA, Universitas Jenderal Soedirman, Jl. dr. Soeparno 61, Purwokerto 53123, Indonesia
Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences

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Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based On Well Log Data Urip Nurwijayanto Prabowo; Akmal Ferdiyan; Sukmaji Anom Raharjo; Sehah Sehah; Arya Dwi Candra
Aceh International Journal of Science and Technology Vol 12, No 2 (2023): August 2023
Publisher : Graduate Program of Syiah Kuala University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.12.2.28428

Abstract

Facies classification is the process of identifying rock lithology based on indirect measurements such as well log measurements. The facies classified manually by experienced geologists, so it takes a long time and is less efficient. Machine learning applications in facies classification can increase the effectiveness and efficiency of geophysical interpretation on complex data. The purpose of this study is to examine the application of machine learning algorithms SVM and KNN in facies estimation. The results showed that the KNN algorithm is better at estimating facies than the SVM algorithm.
Co-Authors Arya Dwi Candra Sehah Sehah Sukmaji Anom Raharjo Urip Nurwijayanto Prabowo