Service Modelling

The essential resource to an integrated approach to reservoir modelling by highlighting both the input of data and the modelling results Reservoir Modelling offers a comprehensive guide to the procedures and workflow for building a 3-D model. Designed to be practical, the principles outlined can be applied to any modelling project regardless of the software used. The author – a noted practitioner in the field – captures the heterogeneity due to structure, stratigraphy and sedimentology that has an impact on flow in the reservoir. This essential guide follows a general workflow from data QC and project management, structural modelling, facies and property modelling to upscaling and the requirements for dynamic modelling. The author discusses structural elements of a model and reviews both seismic interpretation and depth conversion, which are known to contribute most to volumetric uncertainty and shows how large-scale stratigraphic relationships are integrated into the reservoir framework. The text puts the focus on geostatistical modelling of facies and heterogeneities that constrain the distribution of reservoir properties including porosity, permeability and water saturation. In addition, the author discusses the role of uncertainty analysis in the static model and its impact on volumetric estimation. The text also addresses some typical approaches to modelling specific reservoirs through a mix of case studies and illustrative examples and: Offers a practical guide to the use of data to build a successful reservoir model Draws on the latest advances in 3-D modelling software Reviews facies modelling, the different methods and the need for understanding the geological interpretation of cores and logs Presents information on upscaling both the structure and the properties of a fine-scale geological model for dynamic simulation Stresses the importance of an interdisciplinary team-based approach Written for geophysicists, reservoir geologists and petroleum engineers, Reservoir Modelling offers the essential information needed to understand a reservoir for modelling and contains the multidisciplinary nature of a reservoir modelling project.

Already the market leader in the field, Modelling Transport has become still more indispensible following a thorough and detailed update. Enhancements include two entirely new chapters on modelling for private sector projects and on activity-based modelling; a new section on dynamic assignment and micro-simulation; and sizeable updates to sections on disaggregate modelling and stated preference design and analysis. It also tackles topical issues such as valuation of externalities and the role of GPS in travel time surveys. Providing unrivalled depth and breadth of coverage, each topic is approached as a modelling exercise with discussion of the roles of theory, data, model specification, estimation, validation and application. The authors present the state of the art and its practical application in a pedagogic manner, easily understandable to both students and practitioners. Follows on from the highly successful third edition universally acknowledged as the leading text on transport modelling techniques and applications Includes two new chapters on modelling for private sector projects and activity based modeling, and numerous updates to existing chapters Incorporates treatment of recent issues and concerns like risk analysis and the dynamic interaction between land use and transport Provides comprehensive and rigorous information and guidance, enabling readers to make practical use of every available technique Relates the topics to new external factors and technologies such as global warming, valuation of externalities and global positioning systems (GPS).

Simulation models are an established method used to investigate processes and solve practical problems in a wide variety of disciplines. Central to the concept of this second edition is the idea that environmental systems are complex, open systems. The authors present the diversity of approaches to dealing with environmental complexity and then encourage readers to make comparisons between these approaches and between different disciplines. Environmental Modelling: Finding Simplicity in Complexity 2nd edition is divided into four main sections: An overview of methods and approaches to modelling. State of the art for modelling environmental processes Tools used and models for management Current and future developments. The second edition evolves from the first by providing additional emphasis and material for those students wishing to specialize in environmental modelling. This edition: Focuses on simplifying complex environmental systems. Reviews current software, tools and techniques for modelling. Gives practical examples from a wide variety of disciplines, e.g. climatology, ecology, hydrology, geomorphology and engineering. Has an associated website containing colour images, links to WWW resources and chapter support pages, including data sets relating to case studies, exercises and model animations. This book is suitable for final year undergraduates and postgraduates in environmental modelling, environmental science, civil engineering and biology who will already be familiar with the subject and are moving on to specialize in the field. It is also designed to appeal to professionals interested in the environmental sciences, including environmental consultants, government employees, civil engineers, geographers, ecologists, meteorologists, and geochemists.

Rainfall-Runoff Modelling: The Primer, Second Edition is the follow-up of this popular and authoritative text, first published in 2001. The book provides both a primer for the novice and detailed descriptions of techniques for more advanced practitioners, covering rainfall-runoff models and their practical applications. This new edition extends these aims to include additional chapters dealing with prediction in ungauged basins, predicting residence time distributions, predicting the impacts of change and the next generation of hydrological models. Giving a comprehensive summary of available techniques based on established practices and recent research the book offers a thorough and accessible overview of the area. Rainfall-Runoff Modelling: The Primer Second Edition focuses on predicting hydrographs using models based on data and on representations of hydrological process. Dealing with the history of the development of rainfall-runoff models, uncertainty in mode predictions, good and bad practice and ending with a look at how to predict future catchment hydrological responses this book provides an essential underpinning of rainfall-runoff modelling topics. Fully revised and updated version of this highly popular text Suitable for both novices in the area and for more advanced users and developers Written by a leading expert in the field Guide to internet sources for rainfall-runoff modelling software

Queueing analysis is a vital tool used in the evaluation of system performance. Applications of queueing analysis cover a wide spectrum from bank automated teller machines to transportation and communications data networks. Fully revised, this second edition of a popular book contains the significant addition of a new chapter on Flow & Congestion Control and a section on Network Calculus among other new sections that have been added to remaining chapters. An introductory text, Queueing Modelling Fundamentals focuses on queueing modelling techniques and applications of data networks, examining the underlying principles of isolated queueing systems. This book introduces the complex queueing theory in simple language/proofs to enable the reader to quickly pick up an overview to queueing theory without utilizing the diverse necessary mathematical tools. It incorporates a rich set of worked examples on its applications to communication networks. Features include: Fully revised and updated edition with significant new chapter on Flow and Congestion Control as-well-as a new section on Network Calculus A comprehensive text which highlights both the theoretical models and their applications through a rich set of worked examples, examples of applications to data networks and performance curves Provides an insight into the underlying queuing principles and features step-by-step derivation of queueing results Written by experienced Professors in the field Queueing Modelling Fundamentals is an introductory text for undergraduate or entry-level post-graduate students who are taking courses on network performance analysis as well as those practicing network administrators who want to understand the essentials of network operations. The detailed step-by-step derivation of queueing results also makes it an excellent text for professional engineers.

Bayesian methods combine the evidence from the data at hand with previous quantitative knowledge to analyse practical problems in a wide range of areas. The calculations were previously complex, but it is now possible to routinely apply Bayesian methods due to advances in computing technology and the use of new sampling methods for estimating parameters. Such developments together with the availability of freeware such as WINBUGS and R have facilitated a rapid growth in the use of Bayesian methods, allowing their application in many scientific disciplines, including applied statistics, public health research, medical science, the social sciences and economics. Following the success of the first edition, this reworked and updated book provides an accessible approach to Bayesian computing and analysis, with an emphasis on the principles of prior selection, identification and the interpretation of real data sets. The second edition: Provides an integrated presentation of theory, examples, applications and computer algorithms. Discusses the role of Markov Chain Monte Carlo methods in computing and estimation. Includes a wide range of interdisciplinary applications, and a large selection of worked examples from the health and social sciences. Features a comprehensive range of methodologies and modelling techniques, and examines model fitting in practice using Bayesian principles. Provides exercises designed to help reinforce the reader’s knowledge and a supplementary website containing data sets and relevant programs. Bayesian Statistical Modelling is ideal for researchers in applied statistics, medical science, public health and the social sciences, who will benefit greatly from the examples and applications featured. The book will also appeal to graduate students of applied statistics, data analysis and Bayesian methods, and will provide a great source of reference for both researchers and students. Praise for the First Edition: “It is a remarkable achievement to have carried out such a range of analysis on such a range of data sets. I found this book comprehensive and stimulating, and was thoroughly impressed with both the depth and the range of the discussions it contains.” – ISI – Short Book Reviews “This is an excellent introductory book on Bayesian modelling techniques and data analysis” – Biometrics “The book fills an important niche in the statistical literature and should be a very valuable resource for students and professionals who are utilizing Bayesian methods.” – Journal of Mathematical Psychology

Mixed modelling is one of the most promising and exciting areas of statistical analysis, enabling more powerful interpretation of data through the recognition of random effects. However, many perceive mixed modelling as an intimidating and specialized technique. This book introduces mixed modelling analysis in a simple and straightforward way, allowing the reader to apply the technique confidently in a wide range of situations. Introduction to Mixed Modelling shows that mixed modelling is a natural extension of the more familiar statistical methods of regression analysis and analysis of variance. In doing so, it provides the ideal introduction to this important statistical technique for those engaged in the statistical analysis of data. This essential book: Demonstrates the power of mixed modelling in a wide range of disciplines, including industrial research, social sciences, genetics, clinical research, ecology and agricultural research. Illustrates how the capabilities of regression analysis can be combined with those of ANOVA by the specification of a mixed model. Introduces the criterion of Restricted Maximum Likelihood (REML) for the fitting of a mixed model to data. Presents the application of mixed model analysis to a wide range of situations and explains how to obtain and interpret Best Linear Unbiased Predictors (BLUPs). Features a supplementary website containing solutions to exercises, further examples, and links to the computer software systems GenStat and R. This book provides a comprehensive introduction to mixed modelling, ideal for final year undergraduate students, postgraduate students and professional researchers alike. Readers will come from a wide range of scientific disciplines including statistics, biology, bioinformatics, medicine, agriculture, engineering, economics, and social sciences.

As a consequence of recent increased awareness of the social and political dimensions of climate, many non-specialists discover a need for information about the variety of available climate models. A Climate Modelling Primer, Third Edition explains the basis and mechanisms of all types of current physically-based climate models. A thoroughly revised and updated edition, this book assists the reader in understanding the complexities and applicabilities of today’s wide range of climate models. Topics covered include the latest techniques for modelling the coupled biosphere-ocean-atmosphere system, information on current practical aspects of climate modelling and ways to evaluate and exploit the results, discussion of Earth System Models of Intermediate Complexity (EMICs), and interactive exercises based on Energy Balance Model (EBM) and the Daisyworld model. Source codes and results from a range of model types allows readers to make their own climate simulations and to view the results of the latest high resolution models. The accompanying CD contains: A suite of resources for those wishing to learn more about climate modelling. A range of model visualisations. Data from climate models for use in the classroom. Windows and Macintosh programs for an Energy Balance Model. Selected figures from the book for inclusion in presentations and lectures. Suitable for 3rd/4th year undergraduates taking courses in climate modelling, economic forecasting, computer science, environmental science, geography and oceanography. Also of relevance to researchers and professionals working in related disciplines with climate models or who need accessible technical background to climate modelling predictions.

Financial Modelling in Practice: A Concise Guide for Intermediate and Advanced Level is a practical, comprehensive and in-depth guide to financial modelling designed to cover the modelling issues that are relevant to facilitate the construction of robust and readily understandable models. Based on the authors extensive experience of building models in business and finance, and of training others how to do so this book starts with a review of Excel functions that are generally most relevant for building intermediate and advanced level models (such as Lookup functions, database and statistical functions and so on). It then discusses the principles involved in designing, structuring and building relevant, accurate and readily understandable models (including the use of sensitivity analysis techniques) before covering key application areas, such as the modelling of financial statements, of cash flow valuation, risk analysis, options and real options. Finally, the topic of financial modelling using VBA is treated. Practical examples are used throughout and model examples are included in the attached CD-ROM. Aimed at intermediate and advanced level modellers in Excel who wish to extend and consolidate their knowledge, this book is focused, practical, and application-driven, facilitating knowledge to build or audit a much wider range of financial models. Note: CD-ROM/DVD and other supplementary materials are not included as part of eBook file.

Presenting a concise, basic introduction to modelling and computational chemistry this text includes relevant introductory material to ensure greater accessibility to the subject. Provides a comprehensive introduction to this evolving and developing field Focuses on MM, MC, and MD with an entire chapter devoted to QSAR and Discovery Chemistry. Includes many real chemical applications combined with worked problems and solutions provided in each chapter Ensures that up-to-date treatment of a variety of chemical modeling techniques are introduced.