[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-124642-en":3,"doc-seo-124642-105":30,"detail-sidebar-cat-0-en-105":91},{"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":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},124642,549758146520,"Patrick","https://ap-avatar.wpscdn.com/avatar/80002397d8c0411e94?_k=1775819394049821470",8,"Research & Report","Hydraulic Fracturing Treatment Optimization Using Machine Learning","Friction reducer (FR) additives reduce friction between fracturing fluid and wellbore walls to overcome tubular drag during high-rate hydraulic fracturing. This work focuses on hydraulic fracturing friction reducer performance across a broad FR concentration range in completion stages of eight horizontal Marcellus Shale wells, where optimal concentration is often insufficiently studied. Machine learning methods evaluate data from over 400 stages, using Boggess pad readings, to determine the minimum effective FR amount. An economic analysis then quantifies net present value and stage-wise FR cost savings.","Graduate Theses, Dissertations, and Problem Reports  \n2023  \nHydraulic Fracturing Treatment Optimization Using Machine Learning  \nAbdullah Johar  \n[aj0055@mix.wvu.edu](aj0055@mix.wvu.edu)  \nFollow this and additional works at: [https://researchrepository.wvu.edu/etd](https://researchrepository.wvu.edu/etd)  \n Part of the Engineering Commons  \nRecommended Citation  \nJohar, Abdullah, \"Hydraulic Fracturing Treatment Optimization Using Machine Learning\" (2023) . Graduate Theses, Dissertations, and Problem Reports. 11697.  \n[https://researchrepository.wvu.edu/etd/1](https://researchrepository.wvu.edu/etd/1)1697  \nThis Thesis is protected by copyright and/or related rights. It has been brought to you by the The Research Repository @ WVU with permission from the rights-holder(s) . You are free to use this Thesis in any way that is permitted by the copyright and related rights legislation that applies to your use. For other uses you must obtain permission from the rights-holder(s) directly, unless additional rights are indicated by a Creative Commons license in the record and/ or on the work itself. This Thesis has been accepted for inclusion in WVU Graduate Theses, Dissertations, and Problem Reports collection by an authorized administrator of The Research Repository @ WVU. For more information, please contact [researchrepository@mail.wvu.edu](researchrepository@mail.wvu.edu).  \nHydraulic Fracturing Treatment Optimization Using Machine Learning  \nAbdullah Johar  \nThesis submitted  \nto the Benjamin M. Statler College of Engineering and Mineral Resources  \nat West Virginia University  \nIn partial fulfillment of the requirements for the degree of  \nMaster of Science  \nIn  \nPetroleum and Natural Gas Engineering  \nEbrahim Fathi, Ph.D., Chair  \nSamuel Ameri, Ph.D.  \nKashy Aminian, Ph.D.  \nDepartment of Petroleum and Natural Gas Engineering  \nMorgantown, West Virginia  \n2023  \nKeywords: Marcellus Shale, Boggess, Machine Learning, Hydraulic Fracture Treatment,  \nOptimization, Artificial Intelligence  \n1-ABSTRACT  \nHydraulic Fracturing Treatment Optimization Using Machine Learning  \nAbdullah Johar  \nFriction reducer (FR) is a chemical additive that is used in hydraulic fracturing operations to reduce friction between the fracturing fluid and the walls of the wellbore in order to overcome the tubular drag while pumping at a high flow rate in stimulation treatments. In recent years, the oil and gas industry tend to use a high viscosity Friction reducer (HVFR) in fracturing fluids for operational and economic reasons. Slick water fracturing fluids have low concentrations of friction reducers. The concentration of the FR used in shale gas reservoirs varies between 0.5 and 2.0 gallons per thousand gallons (gpt) . However, the optimum FR concentration required for each stage is not extensively studied. Most of the oil and gas companies are relying on previous practicesand they generally use more FR concentrations than required simply to make sure they can achieve the designed injection rate and avoid screening out. This resulted in excess FR concentration used in stimulation practices that will result in major economic loss. Excess FR means the amount of FR that is beyond required, which is only a waste of money.  \nThe primary goal of this proposal is to fully comprehend and quantify the performance of the Hydraulic Fracturing Friction Reducer in a wide range of concentrations used in the completion of eight horizontal Marcellus Shale wells, as well as to optimize the amount of friction reducer required to complete the job and reduce the cost associated with it. Several machine learning approaches will be employed, and data from over 400 hydraulic fracturing stages will be evaluated to optimize the amount of friction reducer. Finally, an economic analysis will determine the project's net present value (NPV) and accumulated savings ofFR cost per stage.  \nData collected from Boggess pad from the MSEEL project including Boggess 1H, 3H, 5H, 9H, and 17H","cbCaifJSdw3tap2S","https://ap.wps.com/l/cbCaifJSdw3tap2S","pdf",3853281,1,90,"English","en",105,"# Abstract\n# Introduction\n# Project Overview\n## Data collection\n## Data Preprocessing\n## Data Visualization\n## Data imputation\n## Dropping NA","[{\"question\":\"What is the role of friction reducer in hydraulic fracturing treatments?\",\"answer\":\"Friction reducer (FR) lowers friction between fracturing fluid and the wellbore wall, helping pumps overcome tubular drag during stimulation at high flow rates.\"},{\"question\":\"Why is optimizing FR concentration important in this thesis?\",\"answer\":\"Most operations rely on prior practices and tend to use more FR than required, which increases costs and can lead to major economic loss due to excess FR.\"},{\"question\":\"How does the thesis determine an optimal FR concentration and its economic impact?\",\"answer\":\"It applies multiple machine learning approaches to evaluate data from over 400 hydraulic fracturing stages, then performs an economic analysis using NPV to estimate accumulated FR cost savings per stage.\"}]","Hydraulic Fracturing Treatment Optimization Using Machine Learning | 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is the role of friction reducer in hydraulic fracturing treatments?","Question",{"text":75,"@type":76},"Friction reducer (FR) lowers friction between fracturing fluid and the wellbore wall, helping pumps overcome tubular drag during stimulation at high flow rates.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"Why is optimizing FR concentration important in this thesis?",{"text":80,"@type":76},"Most operations rely on prior practices and tend to use more FR than required, which increases costs and can lead to major economic loss due to excess FR.",{"name":82,"@type":73,"acceptedAnswer":83},"How does the thesis determine an optimal FR concentration and its economic impact?",{"text":84,"@type":76},"It applies multiple machine learning approaches to evaluate data from over 400 hydraulic fracturing stages, then performs an economic analysis using NPV to estimate accumulated FR cost savings per 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