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All Journal PROSIDING SEMINAR NASIONAL CENDEKIAWAN Advance Sustainable Science, Engineering and Technology (ASSET)
Onnie Ridaliani Prapansya
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Chemistry Computer Science & IT Control & Systems Engineering Education Electrical & Electronics Engineering Industrial & Manufacturing Engineering

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KAJIAN LABORATORIUM PENGUJIAN PENGARUH POLIMER DENGAN CROSSLINKER TERHADAP RESISTANCE FACTOR Raden Himawan; Sugiatmo Kasmungin; Onnie Ridaliani Prapansya
PROSIDING SEMINAR NASIONAL CENDEKIAWAN Prosiding Seminar Nasional Cendekiawan 2017 Buku I
Publisher : Lembaga Penelitian Universitas Trisakti

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.25105/semnas.v0i0.2115

Abstract

Pada saat terjadi peristiwa water conning pada sumur, maka perlu ditambahkanzat kimia, yang dimana zat kimia tersebut dapat merubah sifat fisik dari fluida yangterkandung dalam reservoir, salah satunya zat kimia tersebut ialah menggunakan polimer.Yang dimana fungsi polimer ini untuk menaikan viskositas air formasi sehingga menahanair formasi untuk ikut terproduksi. Pengujian penambahan polimer dengan crosslinkermemiliki tujuan untuk mengetahui salinitas dan konsentrasi polimer yang paling tepatterhadap nilai resistance factor. Pengujian ini mengacu kepada penurunan permeabilitasyang disebabkan oleh kenaikan viskositas air. Pengujian menggunakan model reservoirberupa sandpack yang berisi pasir sillica ukuran 40-80 mesh. Pengujian menggunakantiga kenaikan salinitas yakni pada 3.000 ppm, 10.000 ppm, dan 15.000 ppm. Serta padatiga konsentrasi polimer yakni, 500 ppm, 1.000 ppm, 1.500 pppm, 2.000 ppm. Larutantersebut di saturasikan kedalam sandpack dengan dua kenaikan temperature yakni pada150°F dan 180°F. Pada hasil pengujian dibuktikan bahwa polimer memanglah sangatefektif untuk mereduksi jumlah air dengan cara menurunkan permeabilitas air itu sendiri.
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 Akbar, Fahrurrozi Asri Nugrahanti Bharoto Iwan Sumirat Muhammad Taufiq Fathaddin, Muhammad Taufiq Raden Himawan Ramadhan, Ranggi Sahmura Rini Setiati Ristawati, Arinda Sonny Irawan Sugiatmo Kasmungin Taufan Marhaendrajana, Taufan Yarra Sutadiwiria