Neural Networks And Other Soft Computing Techniques With Applications In The Oil Industry

Download or read book Neural Networks and Other Soft Computing Techniques with Applications in the Oil Industry written by Fred Aminzadeh and published by . This book was released on 2006 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Soft Computing and Intelligent Data Analysis in Oil Exploration written by M. Nikravesh and published by Elsevier. This book was released on 2003-04-22 with total page 755 pages. Available in PDF, EPUB and Kindle. Book excerpt: This comprehensive book highlights soft computing and geostatistics applications in hydrocarbon exploration and production, combining practical and theoretical aspects.It spans a wide spectrum of applications in the oil industry, crossing many discipline boundaries such as geophysics, geology, petrophysics and reservoir engineering. It is complemented by several tutorial chapters on fuzzy logic, neural networks and genetic algorithms and geostatistics to introduce these concepts to the uninitiated. The application areas include prediction of reservoir properties (porosity, sand thickness, lithology, fluid), seismic processing, seismic and bio stratigraphy, time lapse seismic and core analysis.There is a good balance between introducing soft computing and geostatistics methodologies that are not routinely used in the petroleum industry and various applications areas. The book can be used by many practitioners such as processing geophysicists, seismic interpreters, geologists, reservoir engineers, petrophysicist, geostatistians, asset mangers and technology application professionals. It will also be of interest to academics to assess the importance of, and contribute to, R&D efforts in relevant areas.

Download or read book Geophysics for Petroleum Engineers written by Fred Aminzadeh and published by Elsevier Inc. Chapters. This book was released on 2013-12-09 with total page 29 pages. Available in PDF, EPUB and Kindle. Book excerpt: In most oil exploration and production problems, we deal with limited and incomplete data. We are constantly trying to extrapolate information from sparse measurements, for example, sparse well data and limited core measurements on the one hand and large volumes of seismic data with limited spatial resolution on the other hand. We resort to statistical methods to accomplish the data extrapolation and the integration of diverse data sets in constructing a coherent and meaningful model of the subsurface. Traditional statistical methods both for spatial and temporal extrapolation have been used in E&P for several decades. One of the main uses of statistics has been for reservoir characterization through integrating information and data from various sources with varying degrees of uncertainty such as log, well tests, and seismic data. Other applications include establishing relationships between measurements and reservoir properties, and reserve estimation and oil field economics along with the associated risk factors.

Download or read book Meta-attributes and Artificial Networking written by Kalachand Sain and published by John Wiley & Sons. This book was released on 2022-06-24 with total page 292 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applying machine learning to the interpretation of seismic data Seismic data gathered on the surface can be used to generate numerous seismic attributes that enable better understanding of subsurface geological structures and stratigraphic features. With an ever-increasing volume of seismic data available, machine learning augments faster data processing and interpretation of complex subsurface geology. Meta-Attributes and Artificial Networking: A New Tool for Seismic Interpretation explores how artificial neural networks can be used for the automatic interpretation of 2D and 3D seismic data. Volume highlights include: Historic evolution of seismic attributes Overview of meta-attributes and how to design them Workflows for the computation of meta-attributes from seismic data Case studies demonstrating the application of meta-attributes Sets of exercises with solutions provided Sample data sets available for hands-on exercises The American Geophysical Union promotes discovery in Earth and space science for the benefit of humanity. Its publications disseminate scientific knowledge and provide resources for researchers, students, and professionals.

Download or read book Artificial intelligence and Soft computing written by Pradeep Sharma and published by Educreation Publishing. This book was released on 2019-01-30 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book is prepared for the engineering students pursuing degree in computer science and information technology branch. The main consideration in writing the book is to present the considerable requirements of the syllabus in a simple manner as possible. This book contains many solved examples which will help student to gain confidence in problem solving. Valuable suggestion is heartily welcome for further improvement of this book

Download or read book A Study of Business Decisions Under Uncertainty written by Andreas Stark and published by Universal-Publishers. This book was released on 2010-07 with total page 408 pages. Available in PDF, EPUB and Kindle. Book excerpt: This dissertation will discuss the uncertainty encountered in the daily operations of businesses. The concepts will be developed by first giving an overview of probability and statistics as used in our everyday activities, such as the basic principles of probability, univariate and multivariate statistics, data clustering and mapping, as well as time sequence and spectral analysis. The examples used will be from the oil and gas exploration industry because the risks taken in this industry are normally quite large and are ideal for showing the application of the various techniques for minimizing risk. Subsequently, the discussion will deal with basic risk analysis, spatial and time variations of risk, geotechnical risk analysis, risk aversion and how it is affected by personal biases, and how to use portfolios to hedge risk together with the application of real options. Next, fractal analysis and its application to economics and risk analysis will be examined, followed by some examples showing the change in the Value at Risk under Fractal Brownian Motions. Finally, a neural network application is shown whereby some of these risks and risk factors will be combined to forecast the best possible outcome given a certain knowledge base. The chapters will discuss: Basic probability techniques and uncertainty principles Analysis and diversification for exploration projects The value and risk of information in the decision process Simulation techniques and modeling of uncertainty Project valuation and project risk return Modeling risk propensity or preference analysis of exploration projects Application of fractals to risk analysis Simultaneous prediction of strategic risk and decision attributes using multivariate statistics and neural networks"

Download or read book Geophysical Applications of Artificial Neural Networks and Fuzzy Logic written by W. Sandham and published by Springer Science & Business Media. This book was released on 2013-06-29 with total page 336 pages. Available in PDF, EPUB and Kindle. Book excerpt: The past fifteen years has witnessed an explosive growth in the fundamental research and applications of artificial neural networks (ANNs) and fuzzy logic (FL). The main impetus behind this growth has been the ability of such methods to offer solutions not amenable to conventional techniques, particularly in application domains involving pattern recognition, prediction and control. Although the origins of ANNs and FL may be traced back to the 1940s and 1960s, respectively, the most rapid progress has only been achieved in the last fifteen years. This has been due to significant theoretical advances in our understanding of ANNs and FL, complemented by major technological developments in high-speed computing. In geophysics, ANNs and FL have enjoyed significant success and are now employed routinely in the following areas (amongst others): 1. Exploration Seismology. (a) Seismic data processing (trace editing; first break picking; deconvolution and multiple suppression; wavelet estimation; velocity analysis; noise identification/reduction; statics analysis; dataset matching/prediction, attenuation), (b) AVO analysis, (c) Chimneys, (d) Compression I dimensionality reduction, (e) Shear-wave analysis, (f) Interpretation (event tracking; lithology prediction and well-log analysis; prospect appraisal; hydrocarbon prediction; inversion; reservoir characterisation; quality assessment; tomography). 2. Earthquake Seismology and Subterranean Nuclear Explosions. 3. Mineral Exploration. 4. Electromagnetic I Potential Field Exploration. (a) Electromagnetic methods, (b) Potential field methods, (c) Ground penetrating radar, (d) Remote sensing, (e) inversion.