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Over the past several years, there has been a growing integration of data – geophysical, geological, petrophysical, engineering-related, and production-related – in predicting and determining reservoir properties. As such, geoscientists now must learn the technology, processes, and challenges involved within their specific functions in order to optimize planning for oil field development. Applied Techniques to Integrated Oil and Gas Reservoir Characterization 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. From basin analysis of conventional and unconventional reservoirs, to seismic attributes analysis, NMR for reservoir characterization, amplitude versus offset (AVO), well-to-seismic tie, seismic inversion studies, rock physics, pore pressure prediction, and 4D for reservoir monitoring, the text examines challenges in the industry as well as the techniques used to overcome those challenges. This book includes valuable contributions from global industry experts: Brian Schulte (Schiefer Reservoir Consulting), Dr. Neil W. Craigie (Saudi Aramco), Matthijs van der Molen (Shell International E&P), Dr. Fred W. Schroeder (ExxonMobil, retired), Dr. Tharwat Hassane (Schlumberger & BP, retired), and others. - Presents a thorough understanding of the requirements 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) - Offers advice from industry experts to geoscience students, including career guides and interview tips
F. Jerry Lucia, working in America’s main oil-rich state, has produced a work that goes after one of the holy grails of oil prospecting. One main target in petroleum recovery is the description of the three-dimensional distribution of petrophysical properties on the interwell scale in carbonate reservoirs. Doing so would improve performance predictions by means of fluid-flow computer simulations. Lucia’s book focuses on the improvement of geological, petrophysical, and geostatistical methods, describes the basic petrophysical properties, important geology parameters, and rock fabrics from cores, and discusses their spatial distribution. A closing chapter deals with reservoir models as an input into flow simulators.
Geostatistics is used not only in reservoir characterization but also in velocity analysis, time-to-depth conversion, seismic inversion, uncertainty quantification, and data integration in earth models. This book includes covariance and the variogram, interpolation, heterogeneity modelling, uncertainty quantification, and geostatistical inversion.
In the middle of the 20th century, Genrich Altshuller, a Russian engineer, analysed hundreds of thousands of patents and scientific publications. From this analysis, he developed TRIZ (G. Altshuller, "40 Principles: TRIZ Keys to Technical Innovation. TRIZ Tools," Volume 1, First Edition, Technical Innovation Center, Inc. , Worcester, MA, January 1998; Y. Salamatov, "TRIZ: The Right Solution at the Right Time. A Guide to Innovative Problem Solving. " Insytec B. V. , 1999), the theory of inventive problem solving, together with a series of practical tools for helping engineers solving technical problems. Among these tools and theories, the substance-field theory gives a structured way of representing problems, the patterns of evolution show the lifecycle of technical systems, the contradiction matrix tells you how to resolve technical contradictions, using the forty principles that describe common ways of improving technical systems. For example, if you want to increase the strength of a device, without adding too much extra weight to it, the contradiction matrix tells you that you can use "Principle 1: Segmentation," or "Principle 8: Counterweight," or "Principle 15: Dynamicity," or "Principle 40: Composite Materials. " I really like two particular ones: "Principle 1: Segmentation," and Principle 15: Dynamicity. " "Segmentation" shows how systems evolve from an initial monolithic form into a set of independent parts, then eventually increasing the number of parts until each part becomes small enough that it cannot be identified anymore.
Includes discussions of fundamental concepts, explained using heuristic descriptions of seismic modelling, deconvolution, depth migration, and tomography; processing and contouring pitfalls; and developments in time-lapse seismology, borehole geophysics, multicomponent seismology, and integrated reservoir characterization.
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.
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.
This book offers a compact guide to geological core analysis, covering both theoretical and practical aspects of geological studies of reservoir cores. It equips the reader with the knowledge needed to precisely and accurately analyse cores. The book begins by providing a description of a coring plan, coring, and core sampling and continues with a sample preparation for geological analysis. It then goes on to explain how the samples are named, classified and integrated in order to understand the geological properties that dictate reservoir characteristics. Subsequently, porosity and permeability data derived from routine experiments are combined to define geological rock types and reduce reservoir heterogeneity. Sequence stratigraphy is introduced for reservoir zonation. Core log preparation is also covered, allowing reservoirs to be analysed even more accurately. As the study of core samples is the only way to accurately gauge reservoir properties, this book provides a useful guide for all geologists and engineers working with subsurface samples.
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.
Useful attributes capture and quantify key components of the seismic amplitude and texture for subsequent integration with well log, microseismic, and production data through either interactive visualization or machine learning. Although both approaches can accelerate and facilitate the interpretation process, they can by no means replace the interpreter. Interpreter “grayware” includes the incorporation and validation of depositional, diagenetic, and tectonic deformation models, the integration of rock physics systematics, and the recognition of unanticipated opportunities and hazards. This book is written to accompany and complement the 2018 SEG Distinguished Instructor Short Course that provides a rapid overview of how 3D seismic attributes provide a framework for data integration over the life of the oil and gas field. Key concepts are illustrated by example, showing modern workflows based on interactive interpretation and display as well as those aided by machine learning.