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All Journal Jurnal Migasian Akamigas Balongan Indramayu Petro : Jurnal Ilmiah Teknik Perminyakan
Weny Astuti
Universitas Pertamina
Earth & Planetary Sciences Economics, Econometrics & Finance Energy Engineering Health Professions Public Health

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Identifikasi Batuan Berdasarkan Data Well Log Menggunakan K-Means Clustering Meredita Susanty; Prinsislamsheeny Brilliantdianty Ebelaristra; Ahmad Fauzan Rahman; Ade Irawan; Ikri Madrinovella; Weny Astuti
Jurnal Migasian Vol 4 No 1 (2020): Jurnal Migasian
Publisher : LPPM Akademi Minyak dan Gas Balongan Indramayu

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.36601/jurnal-migasian.v4i1.96

Abstract

One of the stages in oil and gas exploration is a Petrophysical analysis, which aims to determine the structure of rock layers below the earth's surface. The petrophysical analysis uses physical properties in a well-log to determine the rock type below the surface. Nowadays, the software for conducting petrophysical analysis has utilized a machine-learning approach to predict rock types. Most of the software uses the supervised learning method to classify rock types. This research uses a different approach, unsupervised learning, to group rock types based on various features in a well-log. Using a publicly available well-log in Stafford, United States, and the k-means clustering algorithm, this study groups the data into 3 clusters. The result is compared with manual analysis interpretation and shows an alignment between them. From the result, it shows that the unsupervised learning method effectively predicts limestone, shale, and evaporites in the well. It classifies the dataset into useful clusters, generates useful lithologies, provides useful rock characterization, and less time-consuming.
ANALISA PREDIKSI TEKANAN PORI FORMASI MENGGUNAKAN PERSAMAAN EATON Weny Astuti; Raka Sudira Wardana; Jan Friadi Sinaga
PETRO:Jurnal Ilmiah Teknik Perminyakan Vol. 8 No. 3 (2019): SEPTEMBER
Publisher : Jurusan Teknik Perminyakan Fakultas Teknologi Kebumian dan Energi Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1600.432 KB) | DOI: 10.25105/petro.v8i3.5515

Abstract

Prediksi tekanan abnormal formasi merupakan hal yang  penting pada operasi pengeboran. Prediksi tekanan pori formasi yang tepat bisa mencegah terjadinya permasalahan pada pengeboran seperti pipe sticking, lost circulation, kick hingga blowout. Tekanan pori formasi bisa diukur secara langsung melalui Repeat Formation Tester (RFT) atau Modular Dynamic Tester (MDT), namun hal ini proses ini tidak dilakukan di setiap kedalaman dan hanya bisa dilakukan setelah proses pengeboran selesai dilakukan. Untuk itu perlu dilakukannya prediksi tekanan pori formasi dengan menggunakan data – data logging menggunakan persamaan empiris. Salah satu persamaan yang umum digunakan yaitu persamaan Eaton (1975). Pada paper ini dibahas analisa prediksi tekanan formasi menggunaan persamaan Eaton untuk sumur X di lapangan Y. Hasil prediksi menunjukkan adanya zona tekanan pori abnormal pada sumur X.
Co-Authors Ade Irawan Ahmad Fauzan Rahman Ikri Madrinovella Jan Friadi Sinaga Meredita Susanty Prinsislamsheeny Brilliantdianty Ebelaristra RAKA SUDIRA WARDANA