Aceh International Journal of Science and Technology
Vol 12, No 2 (2023): August 2023

Comparison Of Facies Estimation Using Support Vector Machine (SVM) And K-Nearest Neighbor (KNN) Algorithm Based On Well Log Data

Urip Nurwijayanto Prabowo (Department of Physics, FMIPA, Universitas Jenderal Soedirman, Jl. dr. Soeparno 61, Purwokerto 53123, Indonesia)
Akmal Ferdiyan (Department of Physics, FMIPA, Universitas Jenderal Soedirman, Jl. dr. Soeparno 61, Purwokerto 53123, Indonesia)
Sukmaji Anom Raharjo (Department of Physics, FMIPA, Universitas Jenderal Soedirman, Jl. dr. Soeparno 61, Purwokerto 53123, Indonesia)
Sehah Sehah (Department of Physics, FMIPA, Universitas Jenderal Soedirman, Jl. dr. Soeparno 61, Purwokerto 53123, Indonesia)
Arya Dwi Candra (Oil and Gas Production Engineering Department, Politeknik Energi dan Mineral Akamigas, 58315, Indonesia)

Article Info

Publish Date
29 Aug 2023

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.

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Journal Info
Aceh International Journal of Science and Technology
Website

Abbrev

AIJST

Publisher

Universitas Syiah Kuala

Subject

Agriculture, Biological Sciences & Forestry Chemical Engineering, Chemistry & Bioengineering Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences

Description

Aceh International Journal of Science & Technology (AIJST) is published by the Graduate School of Syiah Kuala University (PPs Unsyiah) and the Indonesian Soil Science Association (Himpunan Ilmu Tanah Indonesia, Komda Aceh). It is devoted to identifying, mapping, understanding, and interpreting new ...