Quantitative Geosciences Data Analytics Geostatistics Reservoir Characterization And Modeling

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 646 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 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 Data Analytics in Reservoir Engineering written by Sathish Sankaran and published by . This book was released on 2020-10-29 with total page 108 pages. Available in PDF, EPUB and Kindle. Book excerpt: Data Analytics in Reservoir Engineering describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering.

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 Seismic Reservoir Modeling written by Dario Grana and published by John Wiley & Sons. This book was released on 2021-05-04 with total page 256 pages. Available in PDF, EPUB and Kindle. Book excerpt: Seismic reservoir characterization aims to build 3-dimensional models of rock and fluid properties, including elastic and petrophysical variables, to describe and monitor the state of the subsurface for hydrocarbon exploration and production and for CO2 sequestration. Rock physics modeling and seismic wave propagation theory provide a set of physical equations to predict the seismic response of subsurface rocks based on their elastic and petrophysical properties. However, the rock and fluid properties are generally unknown and surface geophysical measurements are often the only available data to constrain reservoir models far away from well control. Therefore, reservoir properties are generally estimated from geophysical data as a solution of an inverse problem, by combining rock physics and seismic models with inverse theory and geostatistical methods, in the context of the geological modeling of the subsurface. A probabilistic approach to the inverse problem provides the probability distribution of rock and fluid properties given the measured geophysical data and allows quantifying the uncertainty of the predicted results. The reservoir characterization problem includes both discrete properties, such as facies or rock types, and continuous properties, such as porosity, mineral volumes, fluid saturations, seismic velocities and density. Seismic Reservoir Modeling: Theory, Examples and Algorithms presents the main concepts and methods of seismic reservoir characterization. The book presents an overview of rock physics models that link the petrophysical properties to the elastic properties in porous rocks and a review of the most common geostatistical methods to interpolate and simulate multiple realizations of subsurface properties conditioned on a limited number of direct and indirect measurements based on spatial correlation models. The core of the book focuses on Bayesian inverse methods for the prediction of elastic petrophysical properties from seismic data using analytical and numerical statistical methods. The authors present basic and advanced methodologies of the current state of the art in seismic reservoir characterization and illustrate them through expository examples as well as real data applications to hydrocarbon reservoirs and CO2 sequestration studies.

Download or read book Multiple-point Geostatistics written by Professor Gregoire Mariethoz and published by John Wiley & Sons. This book was released on 2014-12-31 with total page 376 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides a comprehensive introduction to multiple-point geostatistics, where spatial continuity is described using training images. Multiple-point geostatistics aims at bridging the gap between physical modelling/realism and spatio-temporal stochastic modelling. The book provides an overview of this new field in three parts. Part I presents a conceptual comparison between traditional random function theory and stochastic modelling based on training images, where random function theory is not always used. Part II covers in detail various algorithms and methodologies starting from basic building blocks in statistical science and computer science. Concepts such as non-stationary and multi-variate modeling, consistency between data and model, the construction of training images and inverse modelling are treated. Part III covers three example application areas, namely, reservoir modelling, mineral resources modelling and climate model downscaling. This book will be an invaluable reference for students, researchers and practitioners of all areas of the Earth Sciences where forecasting based on spatio-temporal data is performed.