A New Look At Nonlinear Regression In Well Testing

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A New Look At Nonlinear Regression In Well Testing

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Author : Aysegul Dastan
language : en
Publisher: Stanford University
Release Date : 2010

A New Look At Nonlinear Regression In Well Testing written by Aysegul Dastan and has been published by Stanford University this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010 with categories.

In this work we made significant improvements to nonlinear regression used in well test interpretation. Nonlinear regression was introduced to well testing more than three decades ago and quickly became a standard practice in the industry. However, limited improvement has been achieved for some time. This widely-used technique is vulnerable to issues commonly observed in real data sets, namely sensitivity to noise, parameter uncertainty (ambiguity), and dependence on starting guess. We developed several different methods that improved nonlinear regression significantly. We investigated the performance of these methods on a variety of field data to determine which method (or combination of methods) works best in particular well test situations. The techniques we developed can be considered in three groups: In the first group we considered parameter transformations. We developed techniques to find robust Cartesian transform pairs that worked very well with a variety of reservoir models. The Cartesian parameter transformations we proposed provided faster convergence, doubled the probability of convergence for a random starting guess, and revealed the ambiguities inherent in the data. In the second group, data space transformations, we analyzed the wavelet transform and the pressure derivative. We developed four different strategies to form a reduced wavelet basis and conducted nonlinear regression in the reduced basis rather than the original pressure data points. Using these strategies we achieved improved performance in terms of likelihood of convergence and narrower confidence intervals (reduced uncertainty). We also developed a novel interpretation technique for cyclic data analysis. The technique is based on the two-dimensional wavelet transform and takes into account the correlation between subsequent cycles for error correction. We also considered derivative curve analysis as another form of data space transformation. Derivative fitting was found to improve confidence intervals significantly and provide faster convergence for dual-porosity reservoirs. We also showed the necessity of using the Monte Carlo simulation technique for accurate computation of confidence intervals for dual-porosity reservoirs. In the third group of nonlinear regression techniques we considered alternative objective functions to regular least squares. We developed a robust total least squares (TLS) algorithm that considers and minimizes deviations in both time and pressure simultaneously, hence making interpretation results more accurate and more stable. When there are deviations in the time data TLS performs substantially better than least squares, giving much narrower confidence intervals. In addition, the total least squares approach was found to be less prone to time-shift errors and errors in the early time data. We also considered the least absolute value (LAV) technique as an alternative to the least squares objective function. Using orthogonal distance regression together with the least absolute value criterion, we achieved a robust estimator for data with time deviations and outliers. We developed an analysis technique based on the sum of square roots. The least square root technique was found to be robust against nonideality in data. We tested the techniques rigorously by using a large matrix of test cases made up of real and generated well test data sets. In the test matrix all possible combinations of different methods were applied to 20 real well test data sets from a selection of reservoir models and test scenarios, including dual-porosity and fractured reservoirs, reservoirs with rectangular boundaries, cyclic buildup-drawdown tests, and general multirate data. We determined the methods or combinations of methods that work best with a particular reservoir model. We expect that our techniques will provide more accurate estimation of reservoir parameters, allowing for better forecasting of reservoir performance.

Structural Health Monitoring Technologies And Next Generation Smart Composite Structures

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Author : Jayantha Ananda Epaarachchi
language : en
Publisher: CRC Press
Release Date : 2016-09-15

Structural Health Monitoring Technologies And Next Generation Smart Composite Structures written by Jayantha Ananda Epaarachchi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-09-15 with Technology & Engineering categories.

Due to the increased use of composite materials in aerospace, energy, automobile, and civil infrastructure applications, concern over composite material failures has grown, creating a need for smart composite structures that are able to self-diagnose and self-heal. Structural Health Monitoring Technologies and Next-Generation Smart Composite Structures provides valuable insight into cutting-edge advances in SHM, smart materials, and smart structures. Comprised of chapters authored by leading researchers in their respective fields, this edited book showcases exciting developments in general embedded sensor technologies, general sensor technologies, sensor response interrogation and data communication, damage matrix formulation, damage mechanics and analysis, smart materials and structures, and SHM in aerospace applications. Each chapter makes a significant contribution to the prevention of structural failures by describing methods that increase safety and reduce maintenance costs in a variety of SHM applications.

Nonlinear Regression With R

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Author : Christian Ritz
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-12-11

Nonlinear Regression With R written by Christian Ritz and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-12-11 with Mathematics categories.

- Coherent and unified treatment of nonlinear regression with R. - Example-based approach. - Wide area of application.

Proceedings Of The New Zealand Geothermal Workshop

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Author :
language : en
Publisher:
Release Date : 1986

Proceedings Of The New Zealand Geothermal Workshop written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1986 with Geothermal engineering categories.

Computational Systems Bioinformatics

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Author : Xiaobo Zhou
language : en
Publisher: World Scientific
Release Date : 2008

Computational Systems Bioinformatics written by Xiaobo Zhou and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008 with Science categories.

Computational systems biology is a new and rapidly developing field of research, concerned with understanding the structure and processes of biological systems at the molecular, cellular, tissue, and organ levels through computational modeling as well as novel information theoretic data and image analysis methods. By focusing on either information processing of biological data or on modeling physical and chemical processes of biosystems, and in combination with the recent breakthrough in deciphering the human genome, computational systems biology is guaranteed to play a central role in disease prediction and preventive medicine, gene technology and pharmaceuticals, and other biotechnology fields. This book begins by introducing the basic mathematical, statistical, and data mining principles of computational systems biology, and then presents bioinformatics technology in microarray and sequence analysis step-by-step. Offering an insightful look into the effectiveness of the systems approach in computational biology, it focuses on recurrent themes in bioinformatics, biomedical applications, and future directions for research.

Choice

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Author :
language : en
Publisher:
Release Date : 1997

Choice written by and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1997 with Academic libraries categories.

Neural Network Engineering In Dynamic Control Systems

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Author : Kenneth J. Hunt
language : en
Publisher: Springer Science & Business Media
Release Date : 2012-12-06

Neural Network Engineering In Dynamic Control Systems written by Kenneth J. Hunt and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2012-12-06 with Technology & Engineering categories.

The series Advances in Industrial Control aims to report and encourage technology transfer in control engineering. The rapid development of control technology impacts all areas of the control discipline. New theory, new controllers, actuators, sensors, new industrial processes, computer methods, new applications, new philosophies, .... , new challenges. Much of this development work resides in industrial reports, feasibility study papers and the reports of advanced collaborative projects. The series offers an opportunity for researchers to present an extended exposition of such new work in all aspects of industrial control for wider and rapid dissemination. Within the control community there has been much discussion of and interest in the new Emerging Technologies and Methods. Neural networks along with Fuzzy Logic and Expert Systems is an emerging methodology which has the potential to contribute to the development of intelligent control technologies. This volume of some thirteen chapters edited by Kenneth Hunt, George Irwin and Kevin Warwick makes a useful contribution to the literature of neural network methods and applications. The chapters are arranged systematically progressing from theoretical foundations, through the training aspects of neural nets and concluding with four chapters of applications. The applications include problems as diverse as oven tempera ture control, and energy/load forecasting routines. We hope this interesting but balanced mix of material appeals to a wide range of readers from the theoretician to the industrial applications engineer.

Machine Learning Mastery With Weka

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Author : Jason Brownlee
language : en
Publisher: Machine Learning Mastery
Release Date : 2016-06-23

Machine Learning Mastery With Weka written by Jason Brownlee and has been published by Machine Learning Mastery this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-06-23 with Computers categories.

Machine learning is not just for professors. Weka is a top machine learning platform that provides an easy-to-use graphical interface and state-of-the-art algorithms. In this Ebook, learn exactly how to get started with applied machine learning using the Weka platform.

Revisiting Targeting In Social Assistance

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Author : Margaret Grosh
language : en
Publisher: World Bank Publications
Release Date : 2022-06-02

Revisiting Targeting In Social Assistance written by Margaret Grosh and has been published by World Bank Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-06-02 with Business & Economics categories.

Targeting is a commonly used, but much debated, policy tool within global social assistance practice. Revisiting Targeting in Social Assistance: A New Look at Old Dilemmas examines the well-known dilemmas in light of the growing body of experience, new implementation capacities, and the potential to bring new data and data science to bear.The book begins by considering why or whether or how narrowly or broadly to target different parts of social assistance and updates the global empirics around the outcomes and costs of targeting. It illustrates the choices that must be made in moving from an abstract vision to implementable definitions and procedures, and in deciding how the choices should be informed by values, empirics, and context. The importance of delivery systems and processes to distributional outcomes are emphasized, and many facets with room for improvement are discussed. The book also explores the choices between targeting methods and how differences in purposes and contexts shape those. The know-how with respect to the data and inference used by the different household-specific targeting methods is summarized and comprehensively updated, including a focus on “big data” and machine learning. A primer on measurement issues is included.Key findings include the following: - Targeting selected categories, families, or individuals plays a valuable role within the framework of universal social protection. - Measuring the accuracy and cost of targeting can be done in many ways, and judicious choices require a range of metrics. - Weighing the relatively low costs of targeting against the potential gains is important. - Implementing inclusive delivery systems is critical for reducing errors of exclusion and inclusion. - Selecting and customizing the appropriate targeting method depends on purpose and context; there is no method preferred in all circumstances. - Leveraging advances in technology--ICT, big data, artificial intelligence, machine learning--can improve targeting accuracy, but they are not a panacea; better data matters more than sophistication in inference. - Targeting social protection should be a dynamic process.

Thermal Properties Of Nanofluids

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Author : Taher Armaghani
language : en
Publisher: CRC Press
Release Date : 2024-11-13

Thermal Properties Of Nanofluids written by Taher Armaghani and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-13 with Technology & Engineering categories.

Thermal Properties of Nanofluids presents emerging prospects for understanding and controlling thermophysical properties at the nanoscale. It covers a comprehensive study of recent progress concerning these properties from the solid state to colloids and, above all, a different look at the effect of temperature on nanofluids’ thermal conducting. Introducing various techniques for measuring solid-state properties, including thermal conductivity, thermal diffusivity, and specific heat capacity, this book presents modeling approaches developed for predicting these properties by molecular dynamic (MD) simulations. It discusses the main factors that affect solid-state properties, such as grain size, grain boundaries, surface interactions, doping, and temperature, and the effects of all these factors. This book will interest industry professionals and academic researchers studying the thermophysical behavior of nanomaterials and heat transfer applications of nanofluids. It will serve graduate engineering students studying advanced fluid mechanics, heat transfer, and nanomaterials.