Download or read book Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization and Modeling written by Y. Z. Ma and published by Springer. This book was released on 2019-07-15 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt: Earth science is becoming increasingly quantitative in the digital age. Quantification of geoscience and engineering problems underpins many of the applications of big data and artificial intelligence. This book presents quantitative geosciences in three parts. Part 1 presents data analytics using probability, statistical and machine-learning methods. Part 2 covers reservoir characterization using several geoscience disciplines: including geology, geophysics, petrophysics and geostatistics. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. As the petroleum industry is heading towards operating oil fields digitally, a multidisciplinary skillset is a must for geoscientists who need to use data analytics to resolve inconsistencies in various sources of data, model reservoir properties, evaluate uncertainties, and quantify risk for decision making. This book intends to serve as a bridge for advancing the multidisciplinary integration for digital fields. The goal is to move beyond using quantitative methods individually to an integrated descriptive-quantitative analysis. In big data, everything tells us something, but nothing tells us everything. This book emphasizes the integrated, multidisciplinary solutions for practical problems in resource evaluation and field development.

Download or read book Reservoir Characterization Modeling and Quantitative Interpretation written by Shib Sankar Ganguli and published by Elsevier. This book was released on 2023-10-27 with total page 518 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir Characterization, Modeling and Quantitative Interpretation: Recent Workflows to Emerging Technologies offers a wide spectrum of reservoir characterization techniques and technologies, focusing on the latest breakthroughs and most efficient methodologies in hydrocarbon exploration and development. Topics covered include 4D seismic technologies, AVAz inversion, fracture characterization, multiscale imaging technologies, static and dynamic reservoir characterization, among others. The content is delivered through an inductive approach, which will help readers gain comprehensive insights on advanced practices and be able to relate them to other subareas of reservoir characterization, including CO2 storage and data-driven modeling. This will be especially useful for field scientists in collecting and analyzing field data, prospect evaluation, developing reservoir models, and adopting new technologies to mitigate exploration risk. They will be able to solve the practical and challenging problems faced in the field of reservoir characterization, as it will offer systematic industrial workflows covering every aspect of this branch of Earth Science, including subsurface geoscientific perspectives of carbon geosequestration. This resource is a 21st Century guide for exploration geologists, geoscience students at postgraduate level and above, and petrophysicists working in the oil and gas industry. - Covers the latest and most effective technologies in reservoir characterization, including Avo analysis, AVAz inversion, wave field separation and Machine Learning techniques - Provides a balanced blend of both theoretical and practical approaches for solving challenges in reservoir characterization - Includes detailed industry-standard practical workflows, along with code structures for algorithms and practice exercises

Download or read book Applied Statistical Modeling and Data Analytics written by Srikanta Mishra and published by Elsevier. This book was released on 2017-10-27 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Statistical Modeling and Data Analytics: A Practical Guide for the Petroleum Geosciences provides a practical guide to many of the classical and modern statistical techniques that have become established for oil and gas professionals in recent years. It serves as a "how to" reference volume for the practicing petroleum engineer or geoscientist interested in applying statistical methods in formation evaluation, reservoir characterization, reservoir modeling and management, and uncertainty quantification. Beginning with a foundational discussion of exploratory data analysis, probability distributions and linear regression modeling, the book focuses on fundamentals and practical examples of such key topics as multivariate analysis, uncertainty quantification, data-driven modeling, and experimental design and response surface analysis. Data sets from the petroleum geosciences are extensively used to demonstrate the applicability of these techniques. The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal. - Authored by internationally renowned experts in developing and applying statistical methods for oil & gas and other subsurface problem domains - Written by practitioners for practitioners - Presents an easy to follow narrative which progresses from simple concepts to more challenging ones - Includes online resources with software applications and practical examples for the most relevant and popular statistical methods, using data sets from the petroleum geosciences - Addresses the theory and practice of statistical modeling and data analytics from the perspective of petroleum geoscience applications

Download or read book Reservoir Characterization written by Larry Lake and published by Elsevier. This book was released on 2012-12-02 with total page 680 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir Characterization is a collection of papers presented at the Reservoir Characterization Technical Conference, held at the Westin Hotel-Galleria in Dallas on April 29-May 1, 1985. Conference held April 29-May 1, 1985, at the Westin Hotel—Galleria in Dallas. The conference was sponsored by the National Institute for Petroleum and Energy Research, Bartlesville, Oklahoma. Reservoir characterization is a process for quantitatively assigning reservoir properties, recognizing geologic information and uncertainties in spatial variability. This book contains 19 chapters, and begins with the geological characterization of sandstone reservoir, followed by the geological prediction of shale distribution within the Prudhoe Bay field. The subsequent chapters are devoted to determination of reservoir properties, such as porosity, mineral occurrence, and permeability variation estimation. The discussion then shifts to the utility of a Bayesian-type formalism to delineate qualitative ""soft"" information and expert interpretation of reservoir description data. This topic is followed by papers concerning reservoir simulation, parameter assignment, and method of calculation of wetting phase relative permeability. This text also deals with the role of discontinuous vertical flow barriers in reservoir engineering. The last chapters focus on the effect of reservoir heterogeneity on oil reservoir. Petroleum engineers, scientists, and researchers will find this book of great value.

Download or read book Geostatistical Methods for Reservoir Geophysics written by Leonardo Azevedo and published by Springer. This book was released on 2017-04-07 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents a geostatistical framework for data integration into subsurface Earth modeling. It offers extensive geostatistical background information, including detailed descriptions of the main geostatistical tools traditionally used in Earth related sciences to infer the spatial distribution of a given property of interest. This framework is then directly linked with applications in the oil and gas industry and how it can be used as the basis to simultaneously integrate geophysical data (e.g. seismic reflection data) and well-log data into reservoir modeling and characterization. All of the cutting-edge methodologies presented here are first approached from a theoretical point of view and then supplemented by sample applications from real case studies involving different geological scenarios and different challenges. The book offers a valuable resource for students who are interested in learning more about the fascinating world of geostatistics and reservoir modeling and characterization. It offers them a deeper understanding of the main geostatistical concepts and how geostatistics can be used to achieve better data integration and reservoir modeling.

Download or read book Stochastic Modeling and Geostatistics written by Timothy C. Coburn and published by AAPG. This book was released on 2005-12-10 with total page 406 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Geostatistical Reservoir Modeling written by Michael J. Pyrcz and published by Oxford University Press. This book was released on 2014-04-16 with total page 449 pages. Available in PDF, EPUB and Kindle. Book excerpt: Published in 2002, the first edition of Geostatistical Reservoir Modeling brought the practice of petroleum geostatistics into a coherent framework, focusing on tools, techniques, examples, and guidance. It emphasized the interaction between geophysicists, geologists, and engineers, and was received well by professionals, academics, and both graduate and undergraduate students. In this revised second edition, Deutsch collaborates with co-author Michael Pyrcz to provide an expanded (in coverage and format), full color illustrated, more comprehensive treatment of the subject with a full update on the latest tools, methods, practice, and research in the field of petroleum Geostatistics. Key geostatistical concepts such as integration of geologic data and concepts, scale considerations, and uncertainty models receive greater attention, and new comprehensive sections are provided on preliminary geological modeling concepts, data inventory, conceptual model, problem formulation, large scale modeling, multiple point-based simulation and event-based modeling. Geostatistical methods are extensively illustrated through enhanced schematics, work flows and examples with discussion on method capabilities and selection. For example, this expanded second edition includes extensive discussion on the process of moving from an inventory of data and concepts through conceptual model to problem formulation to solve practical reservoir problems. A greater number of examples are included, with a set of practical geostatistical studies developed to illustrate the steps from data analysis and cleaning to post-processing, and ranking. New methods, which have developed in the field since the publication of the first edition, are discussed, such as models for integration of diverse data sources, multiple point-based simulation, event-based simulation, spatial bootstrap and methods to summarize geostatistical realizations.

Download or read book Stratigraphic Reservoir Characterization for Petroleum Geologists Geophysicists and Engineers written by Fuge Zou and published by Elsevier Inc. Chapters. This book was released on 2013-11-21 with total page 51 pages. Available in PDF, EPUB and Kindle. Book excerpt: In this chapter, the principles of reservoir modeling, workflows and their applications have been summarized. Reservoir modeling is a multi-disciplinary process that requires cooperation from geologists, geophysicists, reservoir engineers, petrophysics and financial individuals, working in a team setting. The best model is one that provides quantitative properties of the reservoir, though this is often difficult to achieve. There are three broad steps in the modeling process. The team needs to first evaluate the data quality, plan the proper modeling workflow, and understand the range of uncertainties of the reservoir. The second step is data preparation and interpretation, which can be a long, tedious, but essential process, which may include multiple iterations of quality control, interpretation, calibration and tests. The third step is determining whether to build a deterministic (single, data-based model) or stochastic (multiple geostatistical iterations) model. The modeling approach may be decided by the quality and quantity of the data. There is no single rule of thumb because no two reservoirs are identical. Object-based stochastic modeling is the most widely used modeling method today. The modeling results need to be constrained and refined by both geologic and mathematical validation. Variogram analysis is very important in quality control of object-based stochastic modeling. Outcrops are excellent sources of continuous data which can be incorporated into subsurface reservoir modeling either by 1) building an outcrop “reservoir” model, or 2) identifying and developing outcrop analogs of subsurface reservoirs. Significant upscaling of a reservoir model for flow simulation may well result in an erroneous history match because the upscaling process often deletes lateral and vertical heterogeneities which may control or affect reservoir performance, particularly in a deterministic model. Reservoir uncertainties are easier to manipulate by object-based stochastic models. Choosing the best realization approach for the reservoir model is the key to predicting reservoir performance in the management of reservoirs.

Download or read book Stratigraphic reservoir characterization for petroleum geologists geophysicists and engineers written by Roger M. Slatt and published by Elsevier. This book was released on 2006-11-03 with total page 493 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir characterization as a discipline grew out of the recognition that more oil and gas could be extracted from reservoirs if the geology of the reservoir was understood. Prior to that awakening, reservoir development and production were the realm of the petroleum engineer. In fact, geologists of that time would have felt slighted if asked by corporate management to move from an exciting exploration assignment to a more mundane assignment working with an engineer to improve a reservoir's performance. Slowly, reservoir characterization came into its own as a quantitative, multidisciplinary endeavor requiring a vast array of skills and knowledge sets. Perhaps the biggest attractor to becoming a reservoir geologist was the advent of fast computing, followed by visualization programs and theaters, all of which allow young geoscientists to practice their computing skills in a highly technical work environment. Also, the discipline grew in parallel with the evolution of data integration and the advent of asset teams in the petroleum industry. Finally, reservoir characterization flourished with the quantum improvements that have occurred in geophysical acquisition and processing techniques and that allow geophysicists to image internal reservoir complexities.

Download or read book XV International Scientific Conference INTERAGROMASH 2022 written by Alexey Beskopylny and published by Springer Nature. This book was released on 2023-02-24 with total page 3148 pages. Available in PDF, EPUB and Kindle. Book excerpt: The book contains proceedings of the XV International Scientific Conference INTERAGROMASH 2022, Rostov-on-Don, Russia. This conference is dedicated to the innovations in the field of precision agriculture, robotics and machines, as well as agriculture biotechnologies and soil management. It is a collection of original and fundamental research in such areas as follows: unmanned aerial systems, satellite-based applications, proximal and remote sensing of soil and crop, positioning systems, geostatistics, mapping and spatial data analysis, robotics, and automation. Potential and prospects for the use of hydrogen in agriculture, for example, in high-performance tractors with hybrid electric transmission, are disclosed in the research works of scientists from all over the world. It also includes such topics as precision horticulture, precision crop protection, differential harvest, precision livestock farming, controlling environment in animal husbandry, and other topics. One of the important issues raised in the book is to ensure the autonomy of local farms. The topic of the impact of the agro-industrial sector on the environment also received wide coverage. Ways to reduce the burden on the environment are proposed, and the use of alternative fuels and fertilizers is suggested. The research results presented in this book cover the experience and the latest studies on the sustainable functioning of agribusiness in several climatic zones. The tundra and taiga, forest-steppe, the steppe and semi-desert—all this is a unique and incredibly demanded bank of information, the main value of which is the real experience of the functioning of agribusiness in difficult climatic and geographic conditions. These materials are of interest for professionals and practitioners, for researchers, scholars, and producers. They are used in the educational process at specific agricultural universities or during vocational training at enterprises and also become an indispensable helper to farm managers in making the best agronomic decisions.

Download or read book A Primer on Machine Learning in Subsurface Geosciences written by Shuvajit Bhattacharya and published by Springer Nature. This book was released on 2021-05-03 with total page 172 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides readers with a timely review and discussion of the success, promise, and perils of machine learning in geosciences. It explores the fundamentals of data science and machine learning, and how their advances have disrupted the traditional workflows used in the industry and academia, including geology, geophysics, petrophysics, geomechanics, and geochemistry. It then presents the real-world applications and explains that, while this disruption has affected the top-level executives, geoscientists as well as field operators in the industry and academia, machine learning will ultimately benefit these users. The book is written by a practitioner of machine learning and statistics, keeping geoscientists in mind. It highlights the need to go beyond concepts covered in STAT 101 courses and embrace new computational tools to solve complex problems in geosciences. It also offers practitioners, researchers, and academics insights into how to identify, develop, deploy, and recommend fit-for-purpose machine learning models to solve real-world problems in subsurface geosciences.

Download or read book Uncertainty Analysis and Reservoir Modeling written by Y. Zee Ma and published by AAPG. This book was released on 2011-12-20 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Practical Geostatistics for Reservoir Modeling written by Jeffrey M. Yarus and published by Newnes. This book was released on 2013-09-12 with total page 0 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir modeling today combines the empirical conceptual ideas developed by geologists over the past 300 years with the rigor of formal statistical analysis to capture the uncertainty inherent in predicting reservoir properties in the inter-well space. In particular, this volume addresses the application of geostatistical methods that have emerged over the past two decades and are now found embedded in petroleum reservoir characterization and simulation software. The popularity of this specialized statistics for spatially related data has occurred because of its ability to successfully analyze and integrate different types of data, provide meaningful results for model building, and quantitatively assess uncertainty for risk management. Additionally, this modeling approach is applicable to both geoscientists and engineers thereby lending itself to the concept of a shared earth model and a multidisciplinary workforce. However, the technology is not intuitive and has been implemented at a pace that has left many geoscientists and engineers wanting. This book is designed for front-line modelers who want to better understand the fundamentals of spatial statistics and their application to reservoir modeling. It describes the five basic steps and their important methodologies necessary to creating reliable reservoir models; exploratory data analysis, spatial modeling, modeling of key reservoir properties including facies and petrophysics, uncertainty assessment, and preparation for flow simulation.

Download or read book Applied Techniques to Integrated Oil and Gas Reservoir Characterization written by Enwenode Onajite and published by Elsevier. This book was released on 2021-04-14 with total page 438 pages. Available in PDF, EPUB and Kindle. Book excerpt: Applied Techniques to Integrated Oil and Gas Reservoir Characterization: A Problem-Solution Discussion with Experts presents challenging questions encountered by geoscientists in their day-to-day work in the exploration and development of oil and gas fields and provides potential solutions from experts working in the field. Covers Amplitude Versus Offset (AVO), well-to-seismic tie, phase of seismic data, seismic inversion studies, pore pressure prediction, rock physics and exploration geological. The text examines challenges in the industry as well as the solutions and techniques used to overcome those challenges. Over the past several years there has been a growing integration of geophysical, geological, and reservoir engineering, production and petrophysical data to predict and determine reservoir properties. This includes reservoir extent and sand development away from the well bore, as well as in unpenetrated prospects, leading to optimization planning for field development. As such, geoscientists now must learn the technology, processes and challenges involved within their specific functions in order to complete day-to-day activities. Presents a thorough understanding of the requirements and issues of various disciplines in characterizing a wide spectrum of reservoirs Includes real-life problems and challenging questions encountered by geoscientists in their day-to-day work, along with answers from experts working in the field Provides an integrated approach among different disciplines (geology, geophysics, petrophysics, and petroleum engineering)

Download or read book Petroleum Reservoir Modeling and Simulation Geology Geostatistics and Performance Prediction written by Juliana Y. Leung and published by McGraw Hill Professional. This book was released on 2022-01-28 with total page 465 pages. Available in PDF, EPUB and Kindle. Book excerpt: Reservoir engineering fundamentals and applications along with well testing procedures This practical resource lays out the tools and techniques necessary to successfully construct petroleum reservoir models of all types and sizes. You will learn how to improve reserve estimations and make development decisions that will optimize well performance. Written by a pair of experts, Petroleum Reservoir Modeling and Simulation: Geology, Geostatistics, and Performance Prediction offers comprehensive coverage of quantitative modeling, geostatistics, well testing principles, upscaled models, and history matching. Throughout, special attention is paid to shale, carbonate, and subsea formations. Coverage includes: An overview of reservoir engineering Spatial correlation Spatial estimation Spatial simulation Geostatistical simulation constrained to higher-order statistics Numerical schemes for flow simulation Gridding schemes for flow simulation Upscaling of reservoir models History matching Dynamic data integration

Download or read book Quantitative Analysis of Mineral and Energy Resources written by C.F. Chung and published by Springer Science & Business Media. This book was released on 2012-12-06 with total page 737 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume contains the edited papers prepared by lecturers and participants of the NATO Advanced Study Institute on "Statistical Treatments for Estimation of Mineral and Energy Resources" held at II Ciocco (Lucca), Italy, June 22 - July 4, 1986. During the past twenty years, tremendous efforts have been made to acquire quantitative geoscience information from ore deposits, geochemical, geophys ical and remotely-sensed measurements. In October 1981, a two-day symposium on "Quantitative Resource Evaluation" and a three-day workshop on "Interactive Systems for Multivariate Analysis and Image Processing for Resource Evaluation" were held in Ottawa, jointly sponsored by the Geological Survey of Canada, the International Association for Mathematical Geology, and the International Geological Correlation Programme. Thirty scientists from different countries in Europe and North America were invited to form a forum for the discussion of quantitative methods for mineral and energy resource assessment. Since then, not only a multitude of research projects directed toward quantitative analysis in the Earth Sciences, but also recent advances in hardware and software technology, such as high-resolution graphics, data-base management systems and statistical packages on mini and micro-computers, made it possible to study large geoscience data sets. In addition, methods of image analysis have been utilized to capture data in digital form and to supply a variety of tools for charaterizing natural phenomena.

Download or read book Advances in Subsurface Data Analytics written by Shuvajit Bhattacharya and published by Elsevier. This book was released on 2022-05-18 with total page 378 pages. Available in PDF, EPUB and Kindle. Book excerpt: Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches brings together the fundamentals of popular and emerging machine learning (ML) algorithms with their applications in subsurface analysis, including geology, geophysics, petrophysics, and reservoir engineering. The book is divided into four parts: traditional ML, deep learning, physics-based ML, and new directions, with an increasing level of diversity and complexity of topics. Each chapter focuses on one ML algorithm with a detailed workflow for a specific application in geosciences. Some chapters also compare the results from an algorithm with others to better equip the readers with different strategies to implement automated workflows for subsurface analysis. Advances in Subsurface Data Analytics: Traditional and Physics-Based Approaches will help researchers in academia and professional geoscientists working on the subsurface-related problems (oil and gas, geothermal, carbon sequestration, and seismology) at different scales to understand and appreciate current trends in ML approaches, their applications, advances and limitations, and future potential in geosciences by bringing together several contributions in a single volume. - Covers fundamentals of simple machine learning and deep learning algorithms, and physics-based approaches written by practitioners in academia and industry - Presents detailed case studies of individual machine learning algorithms and optimal strategies in subsurface characterization around the world - Offers an analysis of future trends in machine learning in geosciences