[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-121395-en":3,"doc-seo-121395-105":29,"detail-sidebar-cat-0-en-105":90},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":11,"language":21,"language_code":22,"site_id":23,"html_lang":22,"table_of_contents":24,"faqs":25,"seo_title":26,"seo_description":14,"update_tm":27,"read_time":28},121395,1374391974468,"Eden","https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0",8,"Research & Report","Viscosity Modeling and Prediction of Amorphophallus oncophyllus and Sapindus rarak Using Machine Learning Methods - Study","Viscosity governs fluid mobility in reservoir chemical flooding, directly influencing oil sweep efficiency and overall oil recovery. This study applies machine learning models—ANN and ANFIS—to build correlations for viscosity of polymer solutions prepared from Amorphophallus oncophyllus and Sapindus rarak. Viscosity data from 21 samples with varying concentration and salinity are digitized for modeling. Both methods accurately predict viscosity, achieving average correlation coefficients of 0.997240 (ANN) and 0.995124 (ANFIS).","JFA (JURNAL FISIKA DAN APLIKASINYA) VOLUME 21, NUMBER 1, JANUARY 2025  \nViscosity Modeling and Prediction of Amorphophallus oncophyllus and Sapindus rarakusing Machine Learning Methods  \nMuhammad Taufiq Fathaddin*, Dwi Atty Mardiana, Andrian Sutiadi, and Fajri Maulida  \nDepartment of Petroleum Engineering, Universitas Trisakti, Jl. Kyai Tapa No. 1, Jakarta, 11440  \nAbstract: Viscosity plays an important role in regulating the mobility of fluids injected into the reservoir to increase the efficiency of oil sweeping. This study discusses the application of Machine Learning methods, namely ANN and ANFIS, to model the correlation of physical properties of Amorphophallus oncophyllus and Sapindus rarak solutions. The purpose of this study is to obtain a correlation to determine the viscosity of the polymer solutions. The data used include viscosity measurements for 21 samples of Amorphophallus oncophyllus and Sapindus rarak solutions with variations in concentration and salinity. The data is augmented by digitization for modeling. The results show that both Machine Learning methods can estimate viscosity values well. Very accurate results are achieved by applying ANN and ANFIS with average correlation coefficients of 0.997240 and 0.995124, respectively.  \nKeywords: Chemical flooding; concentration; oil recovery; salinity; viscosity  \n*Corresponding author: muh.taufi[q@trisakti.ac.id](q@trisakti.ac.id)  \n[http://dx.doi.org/10.12962/j24604682.v21i1.21953](http://dx.doi.org/10.12962/j24604682.v21i1.21953)  \n[2460-4682](2460-4682) 􀀍cDepartemen Fisika, FSAD-ITS  \nI. INTRODUCTION  \nViscosity plays an important role in regulating the mobility of fluids injected into oil reservoirs. To maximize oil sweep, the mobility of the injected fluid should be lower than that of the displaced fluid. The mobility of the injected fluid that is higher than that of the displaced fluid (oil) will cause a fingering phenomenon, where the injected fluid penetrates into the displaced oil zone. This phenomenon causes the injected fluid to bypass the oil zone, so that the oil sweep is not optimal, which causes a low oil recovery factor. Chemical substances such as polymers and surfactants added to the injected fluid will affect its viscosity. The amount of substances added to the injected fluid must be appropriate. These substances are needed to increase the viscosity of the injected fluid so that the mobility of the injected fluid is lower than that of the displaced fluid, but the addition of the viscosity of the injected fluid should not be too high, which causes the mobility to be too low. The viscosity of the injected fluid that is too high also causes a low oil recovery factor. High viscosity can make it difficult to flow fluids. Therefore, to flow fluids requires a higher injection pressure. High injection pressure risks damaging reservoir rocks and injection equipment. In addition, mobility that is too low risks causing the deposition of these chemicals in the pores of the rock. This results in a decrease in the concentration of substances in the solution and results in a decrease in rock permeability [1-6] .  \nChemical substances such as polymers and surfactants can be obtained from natural or artificial materials. In this study, porang and lerak were used as polymers and surfactants. Porang (Amorphophallus oncophyllus) is one of the indigenous  \nIndonesian Amorphophallus plants whose tubers are very potential as a source of glucomannan. Yellow porang tubers (Amorphophallus oncophyllus Pr) contain around 55% glucomannan, while white porang tubers (Amorphophallus variabilis Bl) contain around 44% glucomannan [7-8] .  \nGlucomannan is used as a thickener, gel former, texture improver, water binder, stabilizer and emulsifier [9] . Glucomannan from porang tubers has been cultivated in Indonesia, but the number of studies is still relatively small on its properties and potential applications [7] .  \nLerak (Sapindus rarak) are plants that are used as raw materials for natural soap because","cbCaipMfy72D7DKN","https://ap.wps.com/l/cbCaipMfy72D7DKN","pdf",1119384,1,"English","en",105,"# Introduction\n## Viscosity role in oil reservoir mobility and chemical flooding\n## Natural polymer and surfactant sources (porang and lerak)\n## Motivation for machine learning viscosity correlations\n# Methods and Modeling\n## ANN and ANFIS for viscosity prediction\n## Data preparation and augmentation\n# Results and Performance\n## Prediction accuracy using correlation coefficients\n# Conclusion\n## Effectiveness of ANN and ANFIS for viscosity estimation","[{\"question\":\"Why is viscosity important in chemical flooding for oil recovery?\",\"answer\":\"Viscosity controls the mobility of injected fluid compared with displaced oil. If injected mobility is too high, it causes fingering that reduces sweep efficiency and lowers oil recovery; if too low, it can cause excessive chemical deposition and reduced permeability.\"},{\"question\":\"What machine learning methods are used to predict viscosity in this study?\",\"answer\":\"The study uses two machine learning approaches: ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System) to model the viscosity of the polymer solutions.\"},{\"question\":\"How is the dataset prepared for modeling viscosity?\",\"answer\":\"Viscosity measurements from 21 samples of Amorphophallus oncophyllus and Sapindus rarak solutions are collected with variations in concentration and salinity. The data is digitized and used to train and evaluate the ANN and ANFIS models.\"}]","Viscosity Modeling and Prediction of Amorphophallus oncophyllus and Sapindus rarak Using Machine Learning Methods - Study | PDF",1785735485,20,{"code":4,"msg":30,"data":31},"ok",{"site_id":23,"language":22,"slug":32,"title":13,"keywords":33,"description":14,"schema_data":34,"social_meta":85,"head_meta":87,"extra_data":89,"updated_unix":27},"viscosity-modeling-and-prediction-of-amorphophallus-oncophyllus-and-sapindus-rarak-using-machine-learning-methods-study","",{"@graph":35,"@context":84},[36,53,67],{"@type":37,"itemListElement":38},"BreadcrumbList",[39,43,47,50],{"item":40,"name":41,"@type":42,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":44,"name":45,"@type":42,"position":46},"https://docshare.wps.com/document/","Document",2,{"item":48,"name":12,"@type":42,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":42,"position":52},"https://docshare.wps.com/document/viscosity-modeling-and-prediction-of-amorphophallus-oncophyllus-and-sapindus-rarak-using-machine-learning-methods-study/121395/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":22,"description":14,"dateModified":61,"datePublished":61,"encodingFormat":60,"isAccessibleForFree":62,"interactionStatistic":63},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":40,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":64,"interactionType":65,"userInteractionCount":4},"InteractionCounter",{"@type":66},"ViewAction",{"@type":68,"mainEntity":69},"FAQPage",[70,76,80],{"name":71,"@type":72,"acceptedAnswer":73},"Why is viscosity important in chemical flooding for oil recovery?","Question",{"text":74,"@type":75},"Viscosity controls the mobility of injected fluid compared with displaced oil. If injected mobility is too high, it causes fingering that reduces sweep efficiency and lowers oil recovery; if too low, it can cause excessive chemical deposition and reduced permeability.","Answer",{"name":77,"@type":72,"acceptedAnswer":78},"What machine learning methods are used to predict viscosity in this study?",{"text":79,"@type":75},"The study uses two machine learning approaches: ANN (Artificial Neural Network) and ANFIS (Adaptive Neuro-Fuzzy Inference System) to model the viscosity of the polymer solutions.",{"name":81,"@type":72,"acceptedAnswer":82},"How is the dataset prepared for modeling viscosity?",{"text":83,"@type":75},"Viscosity measurements from 21 samples of Amorphophallus oncophyllus and Sapindus rarak solutions are collected with variations in concentration and salinity. The data is digitized and used to train and evaluate the ANN and ANFIS models.","https://schema.org",{"og:url":51,"og:type":86,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":88,"canonical":51},"index,follow",{"doc_id":7,"site_id":23},{"code":4,"msg":5,"data":91},[92,96,100,104,109,114,119,122,126,129,133],{"id":20,"doc_module":4,"doc_module_name":45,"category_name":93,"show_sort_weight":94,"slug":95},"Story & Novel",90,"story-novel",{"id":46,"doc_module":4,"doc_module_name":45,"category_name":97,"show_sort_weight":98,"slug":99},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":45,"category_name":101,"show_sort_weight":102,"slug":103},"Exam",70,"exam",{"id":105,"doc_module":4,"doc_module_name":45,"category_name":106,"show_sort_weight":107,"slug":108},5,"Comic",60,"comic",{"id":110,"doc_module":4,"doc_module_name":45,"category_name":111,"show_sort_weight":112,"slug":113},6,"Technology",50,"technology",{"id":115,"doc_module":4,"doc_module_name":45,"category_name":116,"show_sort_weight":117,"slug":118},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":45,"category_name":12,"show_sort_weight":120,"slug":121},30,"research-report",{"id":123,"doc_module":4,"doc_module_name":45,"category_name":124,"show_sort_weight":28,"slug":125},9,"Religion & Spirituality","religion-spirituality",{"id":28,"doc_module":4,"doc_module_name":45,"category_name":127,"show_sort_weight":28,"slug":128},"World Cup","world-cup",{"id":130,"doc_module":4,"doc_module_name":45,"category_name":131,"show_sort_weight":130,"slug":132},10,"Lifestyle","lifestyle",{"id":134,"doc_module":4,"doc_module_name":45,"category_name":135,"show_sort_weight":105,"slug":136},19,"General","general"]