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All Journal Jurnal Profesi Kependidikan Teknik Mesin "TEKNOLOGI" Communications in Science and Technology JURTEKSI SULTANIST: Jurnal Manajemen dan Keuangan Otopro Jurnal Sistem Komputer & Kecerdasan Buatan Cassowary Jurnal Jendela Pendidikan Journal of Tourism Sustainability Kibas Cenderawasih : Jurnal Ilmiah Kebahasaan dan Kesastraan Journal Hotspot (jh) Jurnal Pengabdian Masyarakat Bhinneka INOVASI: Jurnal Hasil Pengabdian Masyarakat Journal of Vocational Instruction Jurnal Pengabdian Masyarakat Jurnal Abdi Citra Journal of Multidisciplinary Inquiry in Science, Technology and Educational Research SITEDI (Sistem Informasi dan Teknologi Digital) Jurnal Ilmu Pemerintahan Jurnal Teknologi Rekayasa Informasi dan Komputer
Kurniawan, Ahmad
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Agriculture, Biological Sciences & Forestry Arts Humanities Automotive Engineering Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Energy Engineering Environmental Science Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Materials Science & Nanotechnology Mathematics Mechanical Engineering Public Health Social Sciences Other

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Journal : Communications in Science and Technology

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Maximizing oil recovery in sandstone reservoirs through optimized ASP injection using the super learner algorithm Putra, Dike Fitriansyah; Jaafar, Mohd Zaidi; Khalif, Ku Muhd Na’im; Siswanto, Apri; Lukman, Ichsan; Kurniawan, Ahmad
Communications in Science and Technology Vol 10 No 1 (2025)
Publisher : Komunitas Ilmuwan dan Profesional Muslim Indonesia

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.21924/cst.10.1.2025.1649

Abstract

Optimizing the Alkaline-Surfactant-Polymer (ASP) injection process remains a persistent challenge in Enhanced Oil Recovery (EOR), particularly in heterogeneous sandstone reservoirs where traditional reservoir simulators are constrained by high computational demands and limited flexibility. This study introduces a novel application of the Super Learner (SL) ensemble, a stacking-based machine learning algorithm integrating multiple base models (XGBoost, SVR, BRR, and Decision Tree), to systematically predict and optimize ASP injection parameters. Unlike previous approaches, our method blends high-fidelity CMOST simulation data with machine learning precision in which it enables real-time optimization with field-scale relevance. Using 500 simulation scenarios validated by laboratory input, the SL model achieved exceptional predictive performance (R² = 0.988, RMSE = 0.304), outperforming all individual learners. The optimal recovery factor (RF) of 79.49% was obtained with the finely tuned concentrations of surfactant (5483.29 ppm), polymer (2242.61 ppm), SO?²? (5610.15 ppm), CO?²? (7053.59 ppm), and Na? (9939.35 ppm). Remarkably, the SL approach could reduce optimization time from 10 hours (CMOST) to under 1 minute; this underscored its potential for real-time operational deployment. The novelty of this work lies in its integrated use of ensemble learning to capture the complex and non-linear interactions between ionic chemistry and oil mobilization behavior, offering a field-ready AI framework for rapid and adaptive EOR design. This approach paves the way for the intelligent optimization of ASP schemes by minimizing the reliance on computationally intensive simulations while ensuring chemical and economic efficiency in marginal or complex reservoirs.
Co-Authors -, Fajar -, Syapril A. Daniel, Mohammad Ikbal Rizki Achmad Romadin Amirullah -, Amirullah Apri Siswanto Apriani Apriani Azhar Azhar Budi Wibowo Butsiarah Darwin Lie Dedi Harianto Dimas Prasaja, Dimas Djohan, Muhammad Iqbal Dyastari, Letizia Efendi Efendi Ernawati, Helni Fadhela, Rahmi Fahri, Anwar Febby Madonna Yuma Gunawan, M. Zuhri Hamka, Buya Handayani Ujianti, Mutiara Handika Fikri Pratama, Handika Fikri Harsa W, Aliffia Hasim, Muhammad Hasriani Hasriani, Hasriani Hazisma, Suhairi Helmiah, Fauriatun Hendrawaty Hendrawaty, Hendrawaty Idris, Adam Ikbal Riski A. Danial, Mohamad Ilhidda, Inul Iqbal, Muhmmad Jaafar, Mohd Zaidi K, Ahmad Yani Kartini harahap Khalif, Ku Muhd Na’im Kurniasih, Surti Lestari, Adhe Utami Lukman, Ichsan Mansyur Mansyur Mohamad, Mohamad Rafli Munarti, Munarti Parenrengi, Syafiuddin Pramita, Resti Dinda Putra, Dike Fitriansyah Putri, Sukma Rahmadani Rahmadani, Nur Asmi Suci Romizal, Alba Sahtiani Jahrir, Andi Santiara S.R, Revinta Soiswaty, Dwi Purnama Sudarmanto Jayanegara Syam, Nurlaily Titis Setyabudi Wabdillah Wabdillah, Wabdillah Yahyaddin, Muh Yahyaddin, Muhmmad Yusuf, Andi Zulfikar