{"product_id":"machine-learning-applications-in-subsurface-energy-resource-management-state-of-the-art-and-future-prognosis-9781032074528","title":"Machine Learning Applications in Subsurface Energy Resource Management: State of the Art and Future Prognosis","description":"\u003cp\u003e\u003c\/p\u003e\u003cblockquote\u003e\n\u003cbr\u003eThe book \"Machine Learning in Oil and Gas: Applications across Multiple Domains\" provides an overview of machine learning (ML) applications in the oil and gas industry, covering various domains such as reservoir characterization, drilling, production, reservoir modeling, preventative maintenance, and text mining. It highlights the emerging area of unstructured data analysis and offers perspectives from authors representing operating companies, universities, and research organizations. The book includes case studies illustrating the latest application of ML techniques in each application domain and a literature review of each state-of-art application domain. \u003c\/blockquote\u003e\u003cp\u003e\u003cstrong\u003eFormat\u003c\/strong\u003e: Hardback\u003cbr\u003e\u003cstrong\u003eLength\u003c\/strong\u003e: 360 pages\u003cbr\u003e\u003cstrong\u003ePublication date\u003c\/strong\u003e: 27 December 2022\u003cbr\u003e\u003cstrong\u003ePublisher\u003c\/strong\u003e: Taylor \u0026amp; Francis Ltd\u003cbr\u003e\u003c\/p\u003e \u003cp\u003e\u003cbr\u003eThe field of machine learning (ML) has seen significant growth in recent years, with applications across a wide range of application domains. This comprehensive book provides a detailed overview of ML applications in multiple domains, including reservoir characterization, drilling, production, reservoir modeling, preventative maintenance, and text mining.\u003cbr\u003e\u003cbr\u003eThe book begins by introducing the emerging area of unstructured (text and image) data analysis, which is applied across these diverse domains. It offers multiple perspectives from authors representing operating companies, universities, and research organizations, providing a comprehensive understanding of the current state-of-art in ML.\u003cbr\u003e\u003cbr\u003eEach chapter in the book includes a literature review of the state-of-art application domain, highlighting the key research papers and developments in the field. The case studies presented in the book illustrate the latest application of multiple ML techniques in each application domain, showcasing the practical benefits and challenges of ML in real-world scenarios.\u003cbr\u003e\u003cbr\u003eThe book is an invaluable resource for researchers, practitioners, and students interested in ML and its applications in various industries. It provides a comprehensive guide to the latest ML techniques and their applications, and serves as a reference for future research and development in the field.\u003cbr\u003e\u003cbr\u003eIn conclusion, this book is a must-read for anyone interested in ML and its applications in multiple domains. It offers a comprehensive overview of the current state-of-art in ML, provides valuable insights into the practical challenges and opportunities of ML, and serves as a valuable resource for researchers, practitioners, and students in the field.\u003c\/p\u003e\u003cp\u003e\u003cstrong\u003eWeight\u003c\/strong\u003e: 857g\u003cbr\u003e\u003cstrong\u003eDimension\u003c\/strong\u003e: 229 x 152 (mm)\u003cbr\u003e\u003cstrong\u003eISBN-13\u003c\/strong\u003e: 9781032074528\u003c\/p\u003e","brand":"Shulph Ink","offers":[{"title":"Hardback","offer_id":44104670118138,"sku":"9781032074528","price":126.88,"currency_code":"GBP","in_stock":true}],"thumbnail_url":"\/\/cdn.shopify.com\/s\/files\/1\/0522\/4297\/2845\/products\/1673619416716_book.jpg?v=1674085425","url":"https:\/\/shulphink.com\/products\/machine-learning-applications-in-subsurface-energy-resource-management-state-of-the-art-and-future-prognosis-9781032074528","provider":"Shulph Ink","version":"1.0","type":"link"}