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All Journal Journal of Earth Energy Science, Engineering, and Technology Petrogas : Journal of Energy and Technology
Ulfah, Baiq Maulinda
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Chemical Engineering, Chemistry & Bioengineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Energy

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Microbial Enhanced Oil Recovery: Literature Review Ulfah, Baiq Maulinda; Fathaddin, Muhammad Taufiq; Setiati, Rini
PETROGAS: Journal of Energy and Technology Vol 6, No 1 (2024): PETROGAS: Journal of Energy and Technology
Publisher : Sekolah Tinggi Teknologi MIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58267/petrogas.v6i1.169

Abstract

The demand for fossil fuels continue to increase, this encourages the production of hydrocarbons to be increased as well. Enhanced Oil Recovery is one option that can be considered to overcome this high demand. Technical complexity and sophisticated technology are commonly used in EOR implementation. This has become one of the obstacles to implement EOR, one of which is the requirement relatively large funding. Microbial Enhanced Oil Recovery is one method that can be considered as a technology that can fulfill commercial production gains and the resulting environmental impact is lower than other EOR methods. MEOR uses micro-organisms whose metabolism results can change the physical properties in the reservoir so that oil production can be increased.
STUDI LABORATORIUM ANALISIS PENGARUH PENAMBAHAN FRACSEAL DAN KALSIUM KARBONAT (CACO3) UNTUK MENGATASI LOST CIRCULATION TERHADAP LUMPUR PEMBORAN Pasarrin, Yonatan Rumpang; Amiruddin, Amiruddin; Ulfah, Baiq Maulinda; Laby, Dharma Arung; Afifah, Rohima Sera
PETROGAS: Journal of Energy and Technology Vol 6, No 1 (2024): PETROGAS: Journal of Energy and Technology
Publisher : Sekolah Tinggi Teknologi MIGAS

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.58267/petrogas.v6i1.163

Abstract

Lumpur Pemboran merupakan salah satu sarana yang penting dalam operasi pemboransumur-sumur minyak dan gas bumi. Pada proses pemboran berlangsung biasanya terdapat berbagai kendala, salah satunya adalah terjadinya Lost Circulation. Lost Circulation adalah hilangnya sebagian atau seluruh fluida pemboran saat sirkulasi sedang berlangsung. Lost circulation terjadi karena rekahan pada dinding pemboran baik rekahan yang terjadi secara alami atau secondary. LCM (Lost Circulation Material) adalah suatu metode yang digunakan untuk menanggulangi Lost Circulation dengan menambahkan sejumlah material pemberat kedalam lumpur pemboran ataupun dengan cara memompakan sejumlah material pemberat kedalam formasi lost. LCM yang digunakan pada penelitian ini adalah Fracseal dan CaCO3. Cara Kerja dari CaCO3 dan Fracseal ini terhadap lost circulation adalah dengan cara menutup pori pori atau zona rekahan formasi sehingga fluida tidak masuk kedalam formasi. Pada penelitian ini, pengaruh LCM terhadap filtrat lumpur pemboran mengalami penurunan jumlah filtrat yang hilang, pada pengujian 3% LCM mengalami penurunan filtrat dari 7 ml/ 30 menit menjadi 5 ml/ 30 menit, dan untuk 5% LCM mengalami penurunan menjadi 4,6 ml/ 30 menit. 
Modeling of Shrimp Chitosan Polymer Adsorption Using Artificial Neural Network Fathaddin, Muhammad Taufiq; Mardiana, Dwi Atty; Sutiadi, Andrian; Maulida, Fajri; Ulfah, Baiq Maulinda
Journal of Earth Energy Science, Engineering, and Technology Vol. 7 No. 2 (2024): JEESET VOL. 7 NO. 2 2024
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/jvk2gg02

Abstract

One phenomenon that can occur when a polymer solution is injected into an oil reservoir is adsorption. Adsorption occurs due to interactions between polymer molecules and the reservoir pore surface. Adsorption causes some polymer molecules to be removed from solution. So, this process results in a reduction in the polymer concentration in the solution. In this study, an artificial neural network (ANN) model is used to estimate the adsorption of shrimp chitosan polymer on the surface of 40 mesh and 60 mesh sand grains. The ANN model can estimate adsorption more accurately than previous models. This is because previous models only predicted certain adsorption patterns, while the ANN model is able to predict adsorption with complex relationships. The comparison of the mean absolute relative errors (MAREs) of the ANN, Langmuir, Freundlich, Henry, and Harkins-Jura models is 5.7%, 15.9%, 14.6%, 15.2%, and 14.5%, respectively.
Co-Authors Amiruddin Amiruddin Laby, Dharma Arung Mardiana, Dwi Atty Maulida, Fajri Muhammad Taufiq Fathaddin, Muhammad Taufiq Pasarrin, Yonatan Rumpang Rini Setiati, Rini Rohima Sera Afifah Sutiadi, Andrian