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All Journal PENELITIAN DAN KARYA ILMIAH PROSIDING SEMINAR NASIONAL CENDEKIAWAN JOURNAL OF EARTH ENERGY ENGINEERING Prosiding Seminar Nasional Pakar Journal of Petroleum and Geothermal Technology SENADA : Semangat Nasional Dalam MengabdI Mechanical Engineering for Society and Industry Indonesian Community Journal JURNAL PENELITIAN DAN KARYA ILMIAH LEMBAGA PENELITIAN UNIVERSITAS TRISAKTI JUITECH: Jurnal Ilmiah Fakultas Teknik Universitas Quality Jurnal Offshore: Oil, Production Facilities, and Renewable Energy Jurnal Penelitian dan Karya Ilmiah Lembaga Penelitian Universitas Trisakti INDONESIAN JOURNAL OF URBAN AND ENVIRONMENTAL TECHNOLOGY Jurnal AKAL: Abdimas dan Kearifan Lokal Petro : Jurnal Ilmiah Teknik Perminyakan JURNAL ABDI MASYARAKAT INDONESIA (JAMIN) Journal of Earth Energy Science, Engineering, and Technology Jurnal Eksakta Kebumian Petrogas : Journal of Energy and Technology SENADA : Semangat Nasional Dalam Mengabdi Science and Technology: Jurnal Pengabdian Masyarakat Advance Sustainable Science, Engineering and Technology (ASSET) Scientific Contributions Oil and Gas
Rini Setiati
Teknik Perminyakan, FTKE, Universitas Trisakti
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Effectiveness of MES Palm Oil Surfactant using Core Flooding and Spontaneous Imbibition in EOR methods Setiati, Rini; Haryono, Muhammad Furqon; Ristawati, Arinda; Samsol; Akbar, Fahrurrozi; Bharoto; Sumirat, Iwan; Ramadhan, Ranggi Sahmura
Journal of Earth Energy Science, Engineering, and Technology Vol. 9 No. 1 (2026): JEESET VOL. 9 NO. 1 2026
Publisher : Penerbitan Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/mvpkat05

Abstract

Enhanced Oil Recovery (EOR) is one of the methods developed to optimize oil extraction from wells that still have reserve potential. This study focuses on the application of surfactant injection techniques using vegetable-based surfactants derived from Methil Ester Sulfonate (MES) from palm oil. The objective of this study is to evaluate the effectiveness of MES surfactants in increasing the recovery factor through two main testing methods, namely core flooding test and spontaneous imbibition. The tests were conducted under two variations of conditions, namely salinity of 5,000 ppm at a concentration of 0.5% and salinity of 10,000 ppm at a concentration of 2%. The test results showed that in the core flooding method, a salinity of 5,000 ppm with a concentration of 0.5% produced the highest recovery factor of 84.74%, while a salinity of 10,000 ppm with a concentration of 2% produced 62.63%. Meanwhile, in spontaneous imbibition testing, the recovery factor achieved was 51.94% for a concentration of 0.5% and 45.24% for a concentration of 2%. Based on these results, it can be concluded that the most optimal conditions for increasing oil recovery with palm oil MES surfactant are achieved in the core flooding test method with a salinity of 5,000 ppm and a concentration of 0.5%..
Viscosity Modeling of MES and SLS Using Machine Learning Method Fathaddin, Muhammad Taufiq; Setiati, Rini; Akbar, Fahrurrozi; Sumirat, Iwan; Bharoto; Ramadhan, Ranggi Sahmura; Onnie Ridaliani Prapansya; Ristawati, Arinda
Advance Sustainable Science Engineering and Technology Vol. 8 No. 2 (2026): February-April
Publisher : Science and Technology Research Centre Universitas PGRI Semarang

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.26877/asset.v8i2.2304

Abstract

Viscosity is crucial to improve the efficiency of injected fluids for oil displacement in reservoirs. Traditionally, research has focused on polymers that help reduce the mobility of injected fluids, while surfactant viscosity has received less consideration. This research investigated the viscosity behavior of methyl ester sulfonate (MES) and sodium lauryl sulfate (SLS) surfactant solutions using a machine learning method—adaptive neurofuzzy inference system (ANFIS). This study aimed to predict the viscosity of surfactant solutions. Experimental data included viscosity measurements of 36 MES and SLS samples at various concentrations and temperatures, obtained by digitizing viscosity curves. These data served as input and validation for the ANN and ANFIS models. The results showed that ANFIS predicted viscosity values ​​reliably, yielding only 1.33% and 0.43% differences for MES and SLS, respectively. Comparison of viscosity prediction with Artificial Neural Network (ANN) showed that ANFIS prediction was better, because ANN yielded two deviating predictions.
Co-Authors ABDUL HAMID Adira Natasha Annisa Aditya Rachman Aditya Rachman, Aditya Agus Guntoro Akbar, Fahrurrozi Alvita Kumala Sari Amri, Sulthoni Andreawan Santoso Andry Prima Anggela, Lilian Annisa, Adira Natasha Aqlyna Fattahanisa Ardak Yskak Ari Febriana Kabisat Ari Febriana Kabisat, Ari Febriana Arinda Ristawati Arinda Ristawati Asri Nugrahanti Astri Rinanti Audia, Winona Benyamin Benyamin Benyamin Berkah Hani Besila, Qurotu Aini Bharoto Boni Swadesi Caesar, Athifa Putri Christian Gerald Reza Christiane Patricia Manina Moruk Davy, Nandito Deana Wahyuningrum Diana Irvindiaty Hendarawan Djoko Sulistyanto Djoko Sulistyanto, Djoko Djunaedi Djunaedi Djunaedi Djunaedi Dwi Atty Mardiana Dyah Rini Ratnaningsih Fadliah Fathaddin, Muh. Taufiq Fidya Varayesi Ghani, Muhammad Hafiyyan Hamzah, Udi Syahnoedi Harin Widiyatni Hartono, Kartika Fajarwati Haryono, Muhammad Furqon Havidh Pramadika Hestuti Eni Iwan Sumirat Iwan Sumirat Jachanan Satriabudi Jochanan Satriabudi Joe Christian Alexander Juanda, Firdaus kartika fajarwati hartono Kevin Woe Kris Pudiastuti Lewis Khusmanto Listiana Satiawati M. Taufik Fathaddin M. Taufik Fathaddin, M. Taufik M. Taufiq Fathaddin M. Taufiq Fathaddin, M. Taufiq Maman Djumantara Mardiana, Dwi Atty Margaretha Marissa Thomas, Maulani, Mustamina Maulida, Fajri Melati Ferianita Fachrul MG. Sri Wahyuni Muayyad, Deden Misbahudin Muhammad Taufiq Fathaddin, Muhammad Taufiq Mukmin P. Tamsil Mulia Ginting Mulia Ginting, Mulia Mustamina Maulani Nida Muthia Lamis Oetomo, R. Hari Karyadi Oknovia Susanti Onnie Ridaliani Prapansya Onnie Ridaliani, Onnie Paramita Jaya Ratri Paulus Suryono Adisoemarta Poluan, Chris Elvano Pradhana, Renato Aditya Patria Pri Agung Rakhmant Pri Agung Rakhmanto Pri Agung Rakhmanto Pri Agung Rakhmanto Priagung Rakhmanto puri wijayanti Puri Wijayanti Puri Wijayanti, Puri Qurotu Aini Besila R. Hari Karyadi Oetomo Rahkmanto, Pri Agung Rakhmant, Pri Agung Rakhmanto, Pri Agung Rakhmanto, Priagung Ramadhan, Ranggi Sahmura Ratnaningsih, Dyah Rini Ratu Atikah Balqis Rayhan Irvan Renato Aditya Patria Pradhana Reno Pratiwi Reza Fadhlan Ridha Husla Ridha Husla Rifki Andriyan Ristawati, Arinda Riswati, Shabrina Sri Rizki Akbar Rizkina Rangga Wastu, Apriandi Rizky Satrio Putra Sanjaya S Kasmungin Sabrina S Riswati Samsol Samsol Samuel Melvern L P Samosir Sanjaya, Rizky Satrio Putra Satria Kamira Septoratno Siregar Septoratno Siregar Septoratno Siregar Shabrina Sri Riswati Siahaya, Jacob Simorangkir . Siti Nuraeni Sonny Irawan Sonny Irawan Sugiatmo Kasmungin Sugiatmo Kasmungin Suparwoto, Sugeng Suryo Prakoso, Suryo Sutiadi, Andrian Sutresno, Wahyu Syavitri, Dewi Tamsil, Mukmin P. Tarida Surya Marpaung Tarida Surya Marpaung Taufan Marhaendrajana, Taufan Udi Syahnoedi Hamzah Ulfah, Baiq Maulinda Valentino, Boy Candra Wahyuni, MG. Sri Widia Yanti Widia Yanti, Widia Winona Audia Yani Faozani Alli Zona Nuansa Antariksa