Siddharth Misra – författare
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3 produkter
3 produkter
1 341 kr
Skickas inom 10-15 vardagar
Machine Learning for Subsurface Characterization develops and applies neural networks, random forests, deep learning, unsupervised learning, Bayesian frameworks, and clustering methods for subsurface characterization. Machine learning (ML) focusses on developing computational methods/algorithms that learn to recognize patterns and quantify functional relationships by processing large data sets, also referred to as the "big data." Deep learning (DL) is a subset of machine learning that processes "big data" to construct numerous layers of abstraction to accomplish the learning task. DL methods do not require the manual step of extracting/engineering features; however, it requires us to provide large amounts of data along with high-performance computing to obtain reliable results in a timely manner. This reference helps the engineers, geophysicists, and geoscientists get familiar with data science and analytics terminology relevant to subsurface characterization and demonstrates the use of data-driven methods for outlier detection, geomechanical/electromagnetic characterization, image analysis, fluid saturation estimation, and pore-scale characterization in the subsurface. Learn from 13 practical case studies using field, laboratory, and simulation data Become knowledgeable with data science and analytics terminology relevant to subsurface characterization Learn frameworks, concepts, and methods important for the engineer's and geoscientist's toolbox needed to support
Multifrequency Electromagnetic Data Interpretation for Subsurface Characterization
Häftad, Engelska, 2021
1 438 kr
Skickas inom 10-15 vardagar
Multifrequency Electromagnetic Data Interpretation for Subsurface Characterization focuses on the development and application of electromagnetic measurement methodologies and their interpretation techniques for subsurface characterization. The book guides readers on how to characterize and understand materials using electromagnetic measurements, including dielectric permittivity, resistivity and conductivity measurements. This reference will be useful for subsurface engineers, petrophysicists, subsurface data analysts, geophysicists, hydrogeologists, and geoscientists who want to know how to develop tools and techniques of electromagnetic measurements and interpretation for subsurface characterization. Includes case studies to add additional color to the presented content Provides codes for the mechanistic modeling of multi-frequency conductivity and relative permittivity of porous geomaterials Presents detailed descriptions of multifrequency electromagnetic data interpretation models and inversion algorithm
1 923 kr
Kommande
Epsilon to Omega: The Frontiers of Clean Energy explores the forefront of artificial intelligence (AI) technology and its pivotal role in revolutionizing the energy sector towards sustainable development. By delving into the convergence of AI, energy, and decarbonization, the book presents a diverse range of innovative ideas and million-dollar concepts to address pressing global energy challenges. Through comprehensive case studies, readers are offered in-depth technical insights and future implications, empowering entrepreneurs, engineers, researchers, and policymakers to drive transformative change in the field. The book's detailed exploration unfolds across seven chapters, each delving into a distinct aspect of the AI-driven energy revolution. From the emergence of smart machines and AI engineers of tomorrow to trailblazing advancements in AI-powered science and machine intelligence fueling the infinite-energy future, readers are guided through a journey of cutting-edge technologies and applications. The chapters explore intelligent agents paving the way to a zero-carbon planet, going beyond zero to the frontiers of carbon negativity, and unleashing the potential of a sustainable energy future, offering a comprehensive overview of the transformative potential of AI in shaping the future of energy.Explores the cutting-edge intersection of artificial intelligence (AI), energy, and decarbonization to address global energy challengesProvides comprehensive case studies with in-depth technical insights and future implications for entrepreneurs, engineers, researchers, and policymakersDiscusses innovative ideas and million-dollar concepts that inspire transformative change and drive sustainable development in the energy sectorShowcases the potential of AI to revolutionize energy systems, optimize renewable energy integration, and advance carbon capture technologiesEmpowers readers to apply practical guidance on utilizing AI for energy solutions, from engineering and science to business and policy-making, shaping a more sustainable future