Computational Methods in Geosciences

Computational Methods in Geosciences

Author: William Edward Fitzgibbon

Publisher: SIAM

Published: 1992-01-01

Total Pages: 222

ISBN-13: 9780898713015

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Discusses a dozen topics related to mathematical and computational issues in geophysical fluid and solid mechanics, including local grid refinement for reservoir simulation, a method of factoring long z-transform polynomials, and the finite element modelling of surface flow problems. See entry QC155


Fundamentals of Computational Geoscience

Fundamentals of Computational Geoscience

Author: Chongbin Zhao

Publisher: Springer Science & Business Media

Published: 2009-04-21

Total Pages: 248

ISBN-13: 3540897437

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Geoscience is a fundamental natural science discipline dealing with the origin, evolutionary history and behaviour of the planet Earth. As a result of its complicated and complex nature, the Earth system not only provides the necessary materials and environment for mankind to live, but also brings many types of natural disasters, such as earthquakes, volcanic eruptions, tsunamis, ?oods and tornadoes, to mention just a few. With the ever-increasing demand for improving our living standards, it has been recognized that the existing natural resources will be exhausted in the near future and that our living environments are, in fact, deteriorating. To maintain the sustainable development of our living standards and the further improvement of our living environments, an inevitable and challenging task that geoscientists are now confronting is how accurately to predict not only the occurrences of these natural disasters, but also the locations of large concealed natural resources in the deep Earth. For this reason, geoscientists must study the processes, rules and laws, by which the Earth system operates, instead of simply describing and observing g- science phenomena.


Computational Geosciences with Mathematica

Computational Geosciences with Mathematica

Author: William Haneberg

Publisher: Springer Science & Business Media

Published: 2004-07-20

Total Pages: 410

ISBN-13: 9783540402459

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Computational Geosciences with Mathematica is the only book written by a geologist specifically to show geologists and geoscientists how to use Mathematica to formulate and solve problems. It spans a broad range of geologic and mathematical topics, which are drawn from the author's extensive experience in research, consulting, and teaching. The reference and text leads readers step-by-step through geologic applications such as custom graphics programming, data input and output, linear and differential equations, linear and nonlinear regression, Monte Carlo simulation, time series and image analysis, and the visualization and analysis of geologic surfaces. It is packed with actual Mathematica output and includes boxed Computer Notes with tips and exploration suggestions.


Computational Methods for Geodynamics

Computational Methods for Geodynamics

Author: Alik Ismail-Zadeh

Publisher: Cambridge University Press

Published: 2010-07-22

Total Pages: 333

ISBN-13: 1139489356

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Written as both a textbook and a handy reference, this text deliberately avoids complex mathematics assuming only basic familiarity with geodynamic theory and calculus. Here, the authors have brought together the key numerical techniques for geodynamic modeling, demonstrations of how to solve problems including lithospheric deformation, mantle convection and the geodynamo. Building from a discussion of the fundamental principles of mathematical and numerical modeling, the text moves into critical examinations of each of the different techniques before concluding with a detailed analysis of specific geodynamic applications. Key differences between methods and their respective limitations are also discussed - showing readers when and how to apply a particular method in order to produce the most accurate results. This is an essential text for advanced courses on numerical and computational modeling in geodynamics and geophysics, and an invaluable resource for researchers looking to master cutting-edge techniques. Links to supplementary computer codes are available online.


Computing Risk for Oil Prospects: Principles and Programs

Computing Risk for Oil Prospects: Principles and Programs

Author: J.W. Harbaugh

Publisher: Elsevier

Published: 1995-11-22

Total Pages: 467

ISBN-13: 008052950X

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The petroleum industry is enduring difficult financial times because of the continuing depressed price of crude oil on the world market. This has caused major corporate restructuring and reductions in staff throughout the industry. Because oil exploration must now be done with fewer people under more difficult economic constraints, it is essential that the most effective and efficient procedures be used. Computing Risk for Oil Prospects describes how prospect risk assessment — predicting the distribution of financial gains or losses that may result from the drilling of an exploration well — can be done using objective procedures implemented on personal computers. The procedures include analyses of historical data, interpretation of geological and geophysical data, and financial calculations to yield a spectrum of the possible consequences of decisions. All aspects of petroleum risk assessment are covered, from evaluating regional resources, through delineating an individual prospect, to calculation of the financial consequences of alternative decisions and their possible results. The bottom lines are given both in terms of the probable volumes of oil that may be discovered and the expected monetary returns. Statistical procedures are linked with computer mapping and interpretation algorithms, which feed their results directly into routines for financial analysis. The programs in the included library of computer programs are tailored to fit seamlessly together, and are designed for ease and simplicity of operation. The two diskettes supplied are IBM compatible. Full information on loading is given in Appendix A - Software Installation. Risk I diskette contains data files and executables and Risk 2 diskette contains only executables. The authors contend that the explorationist who develops a prospect should be involved in every facet of its analysis, including risk and financial assessments. This book provides the tools necessary for these tasks.


Deep Learning for the Earth Sciences

Deep Learning for the Earth Sciences

Author: Gustau Camps-Valls

Publisher: John Wiley & Sons

Published: 2021-08-18

Total Pages: 436

ISBN-13: 1119646162

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DEEP LEARNING FOR THE EARTH SCIENCES Explore this insightful treatment of deep learning in the field of earth sciences, from four leading voices Deep learning is a fundamental technique in modern Artificial Intelligence and is being applied to disciplines across the scientific spectrum; earth science is no exception. Yet, the link between deep learning and Earth sciences has only recently entered academic curricula and thus has not yet proliferated. Deep Learning for the Earth Sciences delivers a unique perspective and treatment of the concepts, skills, and practices necessary to quickly become familiar with the application of deep learning techniques to the Earth sciences. The book prepares readers to be ready to use the technologies and principles described in their own research. The distinguished editors have also included resources that explain and provide new ideas and recommendations for new research especially useful to those involved in advanced research education or those seeking PhD thesis orientations. Readers will also benefit from the inclusion of: An introduction to deep learning for classification purposes, including advances in image segmentation and encoding priors, anomaly detection and target detection, and domain adaptation An exploration of learning representations and unsupervised deep learning, including deep learning image fusion, image retrieval, and matching and co-registration Practical discussions of regression, fitting, parameter retrieval, forecasting and interpolation An examination of physics-aware deep learning models, including emulation of complex codes and model parametrizations Perfect for PhD students and researchers in the fields of geosciences, image processing, remote sensing, electrical engineering and computer science, and machine learning, Deep Learning for the Earth Sciences will also earn a place in the libraries of machine learning and pattern recognition researchers, engineers, and scientists.


Geostatistics and Petroleum Geology

Geostatistics and Petroleum Geology

Author: Michael Hohn

Publisher: Springer Science & Business Media

Published: 2013-03-09

Total Pages: 274

ISBN-13: 1461571065

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This is the sixth contribution to the Computer Methods in the Geosciences series and it continues the tradition of being practical, germaine, and easy to read. Michael Hohn in his presentation, Geostatistics and Petroleum Geology, nicely compliments the other books in the series and brings to the readers some new techniques by which to analyze their data. New approaches always result in new ideas or enhancement of old ones. The French School of Geostatistiques (Fontainebleau, France) was founded and developed by Georges Matheron in response to problems in mining explo ration and exploitation. This approach has been used successfully in that industry since the mid-1960s, but only recently applied to similar problems in petroleum. Likewise, these applications have been successful in this applied field as well and here Hohn gives examples. Standard subjects of the field of geostatistics are explored and discussed-the semivariogram, kriging, cokriging, nonlinear and parametric estimation, and conditional simulation. These may be unrecognizable terms to the readers now, but upon completion of reading the book, they will be fimiliar ones. Each subject is discussed in detail with appropriate and pertinent case studies, taken from the author's own research or from the literature. The author notes the book is for working geologists in the petroleum industry.


Mathematical Geosciences

Mathematical Geosciences

Author: Joseph L. Awange

Publisher: Springer

Published: 2018-01-29

Total Pages: 615

ISBN-13: 3319673718

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This book showcases powerful new hybrid methods that combine numerical and symbolic algorithms. Hybrid algorithm research is currently one of the most promising directions in the context of geosciences mathematics and computer mathematics in general. One important topic addressed here with a broad range of applications is the solution of multivariate polynomial systems by means of resultants and Groebner bases. But that’s barely the beginning, as the authors proceed to discuss genetic algorithms, integer programming, symbolic regression, parallel computing, and many other topics. The book is strictly goal-oriented, focusing on the solution of fundamental problems in the geosciences, such as positioning and point cloud problems. As such, at no point does it discuss purely theoretical mathematics. "The book delivers hybrid symbolic-numeric solutions, which are a large and growing area at the boundary of mathematics and computer science." Dr. Daniel Li chtbau


Geographic Information Systems for Geoscientists

Geographic Information Systems for Geoscientists

Author: Graeme F. Bonham-Carter

Publisher: Elsevier

Published: 2014-05-18

Total Pages: 417

ISBN-13: 1483144941

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Geographic Information Systems for Geoscientists: Modelling with GIS provides an introduction to the ideas and practice of GIS to students and professionals from a variety of geoscience backgrounds. The emphasis in the book is to show how spatial data from various sources (principally paper maps, digital images and tabular data from point samples) can be captured in a GIS database, manipulated, and transformed to extract particular features in the data, and combined together to produce new derived maps, that are useful for decision-making and for understanding spatial interrelationship. The book begins by defining the meaning, purpose, and functions of GIS. It then illustrates a typical GIS application. Subsequent chapters discuss methods for organizing spatial data in a GIS; data input and data visualization; transformation of spatial data from one data structure to another; and the combination, analysis, and modeling of maps in both raster and vector formats. This book is intended as both a textbook for a course on GIS, and also for those professional geoscientists who wish to understand something about the subject. Readers with a mathematical bent will get more out of the later chapters, but relatively non-numerate individuals will understand the general purpose and approach, and will be able to apply methods of map modeling to clearly-defined problems.