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All Journal Bulletin of Scientific Contribution : Geology Jurnal Cahaya Mandalika Journal of Geoscience Engineering and Energy (JOGEE) JURNAL ABDI MASYARAKAT INDONESIA (JAMIN) Aceh International Journal of Science and Technology Jurnal Migasian
Firman Herdiansyah, Firman
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Agriculture, Biological Sciences & Forestry Humanities Chemical Engineering, Chemistry & Bioengineering Chemistry Civil Engineering, Building, Construction & Architecture Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Education Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Physics Other

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Journal : Aceh International Journal of Science and Technology

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Utilization of Acoustic Wave Velocity for Permeability Estimation in Static Reservoir Modeling: A Field Case Prakoso*, Suryo; Burhannudinnur, Muhammad; Irano, Teddy; Herdiansyah, Firman
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.20328

Abstract

Several researches have shown that P-wave velocity carries information on the complexity of the rock's pore geometry and pore structure. Their complexity can be characterized by critical porosity. Therefore, the P-wave velocity is used to estimate permeability. This research uses data taken from the Tomori formation from Banggai-Sula basin, Central Sulawesi, which is a carbonate rock reservoir. Also, this research aims to obtain a 3D permeability model by using acoustic wave velocity cube data. The results show that permeability can be modeled well using acoustic wave velocity data. Furthermore, compared to the raw data log of permeability, the modeling results using wave velocity based on critical porosity show good results. This method is another alternative to permeability modeling if acoustic wave velocity cube data is available.
The Implementation of Machine Learning in Lithofacies Classification using Multi Well Logs Data Saroji*, Sudarmaji; Winata, Ekrar; Hidayat, Putra Pratama Wahyu; Prakoso, Suryo; Herdiansyah, Firman
Aceh International Journal of Science and Technology Vol 10, No 1 (2021): April 2021
Publisher : Graduate School of Universitas Syiah Kuala

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.13170/aijst.10.1.18749

Abstract

Lithofacies classification is a process to identify rock lithology by indirect measurements. Usually, the classification is processed manually by an experienced geoscientist. This research presents an automated lithofacies classification using a machine learning method to increase computational power in shortening the lithofacies classification process's time consumption. The support vector machine (SVM) algorithm has been applied successfully to the Damar field, Indonesia. The machine learning input is various well-log data sets, e.g., gamma-ray, density, resistivity, neutron porosity, and effective porosity. Machine learning can classify seven lithofacies and depositional environments, including channel, bar sand, beach sand, carbonate, volcanic, and shale. The classification accuracy in the verification phase with trained lithofacies class data reached more than 90%, while the accuracy in the validation phase with beyond trained data reached 65%. The classified lithofacies then can be used as the input for describing lateral and vertical rock distribution patterns.
Co-Authors Abdurrokhim ⠀ Adhitama, Ramadhan Athallah, Fahd Nibel Benyamin Benyamin, Benyamin Budi Wijaya Eko Widianto Ekrar Winata Fahlevi, Muhammad Rubby Gabrielle, Juan Ghanima Yasmaniar Hafiz, Surya Darma Havidh Pramadika Hidayat, Putra Pratama Wahyu Husla, Ridha Ildrem Syafri Irano, Teddy Jambak, Moeh Ali Jambak, Moehammad Ali khadafi, Dafa KHADAFI, MUHAMMAD Koesmawardani, Wildan Tri Lestari, Arini Dian Listiana Satiawati, Listiana Maharani, Suci Mazaya, Faza Auliya Moeh. Ali Jambak, Moeh. Ali Muhammad Burhannudinnur Muhammad, Fachry Napitupulu, Togar Alam Nasal, Fernando Pangeran, Ragha Jabat Prakoso*, Suryo Pramudita, Dylan Mahesa Putri, Alya Zauza Rendy Rendy Saroji*, Sudarmaji Setyorini, Dyah Ayu Silia Yuslim Suryo Prakoso, Suryo Syavitri, Dewi Wastu, Apriandi Rizkina Rangga Widya Permana, Made Deva