Modeling The Earth For Oil Exploration

This volume presents an overview of the results of a European Union integrated program in which approximately two hundred earth scientists participated, drawn from all fields related to exploration. Two classes of modeling were addressed - geological modeling - the relationship between the conditions of sedimentation and the resulting reservoir conditions; and wave-propagation modeling - the investigation of wave-propagation through media of various degrees of complexity. Wave-propagation modeling was carried out either mathematically or physically with the most modern tools. An important aspect of the project was the inversion of seismic data, that is the determination of the parameters of the medium from observations. This problem is closely related to modeling since it is based on the inversion of the mathematical steps and often uses modeling for verification and updating. The geological data presents novel concepts with a coverage that is both broad in area and in discipline. The geophysical investigations are at the leading edge of current research. Although detailed results have been published separately by investigators, this volume is the only source of reference which summarises the results; but incorporating sufficient detail to enable the reader to follow the scientific reasoning.

Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two geophysicists with a combined 30 years in the industry, this book shows you how to leverage continually maturing computational intelligence to gain deeper insight from specific exploration data. Case studies illustrate the value propositions of this alternative analytical workflow, and in-depth discussion addresses the many Big Data issues in geophysics and petrophysics. From data collection and context through real-world everyday applications, this book provides an essential resource for anyone involved in oil and gas exploration. Recent and continual advances in machine learning are driving a rapid increase in empirical modeling capabilities. This book shows you how these new tools and methodologies can enhance geophysical and petrophysical data analysis, increasing the value of your exploration data. Apply data-driven modeling concepts in a geophysical and petrophysical context Learn how to get more information out of models and simulations Add value to everyday tasks with the appropriate Big Data application Adjust methodology to suit diverse geophysical and petrophysical contexts Data-driven modeling focuses on analyzing the total data within a system, with the goal of uncovering connections between input and output without definitive knowledge of the system's physical behavior. This multi-faceted approach pushes the boundaries of conventional modeling, and brings diverse fields of study together to apply new information and technology in new and more valuable ways. Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models takes you beyond traditional deterministic interpretation to the future of exploration data analysis.

Over the last two decades, earth modeling has become a major investigative tool for evaluating the potential of hydrocarbon reservoirs. Earth modelling must now face new challenges since petroleum exploration no longer consists in only investigating newly identified resources, but also in re-evaluating the potential of previously investigated reservoirs in the light of new prospecting data and of revised interpretations. Earth models incorporate a variety of different interpretations made on various types of data at successive steps of the modeling process. However, current modeling procedures provide no way to link a range of data and interpretations with a final earth model. For this reason, sharing and exchanging information about the model building process is at present a major difficulty. Recently, the term “Shared Earth Modeling” has been used for expressing the idea that earth models should be built in such a way that experts and end users can have access, at any time, to all the information incorporated into the model. This information does not only concern the data, but also the knowledge that geoscientists produce by interpreting these data. Accordingly, practical solutions must be studied for operating a knowledge-driven approach of Shared Earth Modeling. This is the goal of this book. This study of earth subsurface modeling is intended for several categories of readers. It concerns in the first place geologists, engineers and managers involved in the study and evaluation of subsurface reservoirs and hydrocarbon exploration. Relying on recent progress in various fields of computer sciences, the authors present innovative solutions for solving the critical issue of knowledge exchange at key steps of the modeling process. This book will also be of interest to researchers in computer science and, more generally, to engineers, researchers and students who wish to apply advanced knowledge-based techniques to complex engineering problems. Contents : Part I. Earth Models. 1. Earth models as subsurface representations. 2. Earth models for underground resource exploration and estimation. 3. Earth models used in petroleum industry: current practice and future challenges. Part II. Knowledge oriented solutions. 4. Knowledge based approach of a data intensive problem: seismic interpretation. 5. Individual surface representations and optimization. 6. Geological surface assemblage. 7. 3D Meshes for structural, stratigraphy and reservoir frameworks. 8. The data extension issue: geological constraints applied in geostatistical processes. Part III. Knowledge formalization. 9. Ontologies and their use for geological knowledge formalization. 10. Ontologies for Interpreting geochronological relationships. 11. Building ontologies for analyzing data expressed in natural language. 12. Ontology-based rock description and interpretation. Part IV. Knowledge management & applications. 13. Ontology integration and management within data intensive engineering systems. 14. Earth modeling using web services. 15. Full scale example of a knowledge-based method for building and managing an earth model. Part V. Conclusion. Appendix. Glossary.

The reasons for writing this book are very simple. We use and teach com puter aided techniques of mathematical simulation and of pattern recogni tion. Life would be much simpler if we had a suitable text book with methods and computer programmes which we could keep referring to. Therefore, we have presented here material that is essential for mathematical modelling of some complex geological situations, with which earth scientists are often confronted. The reader is introduced not only to the essentials of computer modelling, data analysis and pattern recognition, but is also made familiar with the basic understanding with which they can plunge into when solving related and more complex problems. This book first makes a case for seismic stratigraphy and then for pattern recognition. Chapter 1 provides an extensive review of applications of pattern recognition methods in oil exploration. Simulation procedures are presented with examples that are fairly simple to understand and easy to use on the computer. Several geological situations can be formulated and simulated using the Monte Carlo method. The binary lithologic sequences, discussed in Chapter 2, consist of alternating layers of any two of sand, shale and coal.

Introduction to shared earth modeling -- Geology -- Petrophysics -- Well logging -- Geophysics -- Fluid properties -- Measures of rock-fluid interactions -- Applications of rock-fluid interactions -- Fluid flow equations -- Fundamentals of reservoir characterization -- Modern reservoir characterization Techniques -- Well testing -- Production analysis -- Reservoir flow simulation -- Reservoir management -- Improved recovery.

Innovative Exploration Methods for Mineral, Oil, Gas, and Groundwater for Sustainable Development provides an integrated approach to exploration encompassing geology, geophysics, mining, and mineral processing. In addition, groundwater exploration is included, as it is central to the development of earth resources. As the demand for coal, minerals, oil and gas, and water continues to grow globally, researchers must prioritize sustainable exploration methods. Old technologies are being replaced speedily and exploration work has become fast, focused, meaningful, and readily reproducible keeping in pace with the changing global scenario. The themes of exploration of energy resources, exploration of minerals, groundwater exploration and processing and mineral engineering are separated out into sections and chapters included in these sections include case studies focusing on tools and techniques for exploration. Innovative Exploration Methods for Mineral, Oil, Gas, and Groundwater for Sustainable Development gives insight to modern concepts of exploration for those working in the various fields of energy, mineral, and groundwater exploration. Presents innovative research that will both challenge and complement the traditional concepts of exploration Covers a wide range of instruments and their applications, as well as the tools and processes that need to be followed for modern exploration work Includes research on groundwater exploration with a focus on conservation and sustainable exploration and development

This book provides an overview of the major changes induced by hydrocarbons (HCs) affecting rocks and surface sediments and their implications for non-seismic exploration methods, particularly for marine territories near Cuba. It examines the use of a digital elevation model (DEM) at 90x90m resolution for the detection of subtle, positive geomorphic anomalies related to hydrocarbon microseepage (vertical migration) on possible oil and gas targets. The results support the conclusion that the DEM data provides a low cost and fast offshore oil and gas preliminary exploration strategy. This data is useful serving to focus prospective areas with supplementary unconventional methods such as magnetic-induced polarization (MIP), useful to propose more expensive volumes for detailed 2D–3D seismic surveys.

Simulations are the fastest developing branch in geostatistics, and simulating the acies inside reservoirs and ore bodies is the most exciting part of this. Several methods have been developed to do this (sequential indicator simulations, Boolean methods, Markov chains and plurigaussian simulations). This book focusses on the last type of simulation. It develops the theory required to understand the method together and presents practical examples of applications in mining and petroleum, plus tutorial examples. An accompanying CD-ROM featuring demonstration software and color images complements the printed book.