[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-123379-en":3,"doc-seo-123379-105":30,"detail-sidebar-cat-0-en-105":84},{"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":20,"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},123379,962075114101,"Seraphina","https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165",8,"Research & Report","Developing Ensemble Machine Learning Models to Predict Petrophysical Properties of Sandstone Reservoirs - Doctor of Philosophy Thesis","This doctoral thesis develops ensemble machine learning approaches for predicting petrophysical properties of sandstone reservoirs. The study frames petrophysical evaluation as a key need for both hydrocarbon production and carbon capture and storage, addressing limitations of conventional core analysis. It reviews sedimentary basin geology, reservoir rock characteristics, porosity, permeability, and fluid saturation, then motivates machine learning and ensemble learning as alternatives. The work examines research gaps through problem statement, questions, objectives, novelty, and contribution, and outlines the thesis structure for methodological development and validation.","Faculty of Engineering and Science  \nDeveloping Ensemble Machine Learning Models to Predict Petrophysical Properties of Sandstone Reservoirs  \nKushan Oshadi Sandunil Kohona Walawwe  \n0000-0001-5997-6516  \nThis thesis is presented for the Degree of  \nDoctor of Philosophy  \nof  \nCurtin University  \nJanuary 2025  \nDeclaration  \nTo the best of my knowledge and belief this thesis contains no material previously published by any other person except where due acknowledgment has been made. This thesis contains no material which has been accepted for the award of any other degree or diploma in any university.  \nSignature:  \nDate: 09/12/2024  \nAcknowledgement  \nAuthor would like to thank Curtin University Malaysia and Curtin Malaysia Postgraduate Research Scholarship (CMPRS) for hosting and allocating the research grant for the study. A special thanks would be given to Equinor and the Volve license partners for making the Volve field dataset available for scientific research. Author would like to thank Dr. Lionel Esteban and the Commonwealth Scientific and Industrial Research Organisation (CSIRO) in Australia for providing the Darling basin dataset. A special acknowledgement goes to Dr. Ziad Bennour, Dr. Saaveethya Sivakumar, Dr. Hisham Ben Mahmud and Dr. Ausama Giwelli for providing guidance and supervision throughout the research. Further, the author would like to thank Prof. Dr. Agus Saptoro for acting as the thesis chair and facilitating the research. A special thanks goes to Mr. Sheikh Zaffrullah for cooperation shown during the usage of the Petrel lab, Mrs. Christina Satim and Mr. Basil Jason John for assisting during documents preparation. Last but not least the author would like to thank his parents, fiancé , brother and friends for providing moral support throughout the research.  \nTable of Contents  \nDeclaration ...................................................................................................... ii  \nAcknowledgement.......................................................................................... iii  \nList of Figures .............................................................................................. viii  \nList Tables .................................................................................................... xii  \nList of Nomenclatures ................................................................................. xvii  \nAbstract....................................................................................................... xxii  \nPublications arising from the thesis............................................................ xxiv  \nJournal publications ................................................................................ xxiv  \nConference publications ......................................................................... xxiv  \nCHAPTER 1: INTRODUCTION ......................................................................1  \n1.1 Background .......................................................................................... 1  \n1.1.1 Importance of petrophysical properties in the hydrocarbon industry2  \n1.1.2 Importance of petrophysical properties in the carbon capture and storage sector.......................................................................................... 3  \n1.2 Petrophysical properties evaluation and challenges ............................. 6  \n1.3 Machine learning as an alternative to core analysis ............................. 7  \n1.4 Research gaps...................................................................................... 8  \n1.5 Problem Statement ............................................................................. 12  \n1.6 Research questions ............................................................................ 12  \n1.7 Objectives ........................................................................................... 12  \n1.8 Novelty and contribution .................................................","cbCaia0vWOt9KQsB","https://ap.wps.com/l/cbCaia0vWOt9KQsB","pdf",10865012,1,337,"English","en",105,"# Declaration\n# Acknowledgement\n# List of Figures\n# List Tables\n# List of Nomenclatures\n# Abstract\n# Publications arising from the thesis\n## Journal publications\n## Conference publications\n# CHAPTER 1: INTRODUCTION\n## 1.1 Background\n## 1.2 Petrophysical properties evaluation and challenges\n## 1.3 Machine learning as an alternative to core analysis\n## 1.4 Research gaps\n## 1.5 Problem Statement\n## 1.6 Research questions\n## 1.7 Objectives\n## 1.8 Novelty and contribution\n## 1.9 Rationale, justifications and limitations\n## 1.10 Outline of the thesis\n# CHAPTER 2: LITERATURE REVIEW\n## 2.1 Introduction\n## 2.2 Background\n## 2.2.7 Machine learning\n## 2.2.8 Ensemble machine learning\n## 2.2.9 Machine learning optimization\n## 2.3 Previous studies","[{\"question\":\"What research scope and goals does the thesis define?\",\"answer\":\"The thesis defines a problem statement and research questions, and states objectives, novelty, contribution, and the rationale including limitations, with a structured outline of the work.\"}]","Developing Ensemble Machine Learning Models to Predict Petrophysical Properties of Sandstone Reservoirs - 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