This book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics and geochemistry), data fusion, risk reduction and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry.

This book presents several intelligent approaches for tackling and solving challenging practical problems facing those in the petroleum geosciences and petroleum industry. Written by experienced academics, this book offers state-of-the-art working examples and provides the reader with exposure to the latest developments in the field of intelligent methods applied to oil and gas research, exploration and production. It also analyzes the strengths and weaknesses of each method presented using benchmarking, whilst also emphasizing essential parameters such as robustness, accuracy, speed of convergence, computer time, overlearning and the role of normalization. The intelligent approaches presented include artificial neural networks, fuzzy logic, active learning method, genetic algorithms and support vector machines, amongst others. Integration, handling data of immense size and uncertainty, and dealing with risk management are among crucial issues in petroleum geosciences. The problems we have to solve in this domain are becoming too complex to rely on a single discipline for effective solutions and the costs associated with poor predictions (e.g. dry holes) increase. Therefore, there is a need to establish a new approach aimed at proper integration of disciplines (such as petroleum engineering, geology, geophysics and geochemistry), data fusion, risk reduction and uncertainty management. These intelligent techniques can be used for uncertainty analysis, risk assessment, data fusion and mining, data analysis and interpretation, and knowledge discovery, from diverse data such as 3-D seismic, geological data, well logging, and production data. This book is intended for petroleum scientists, data miners, data scientists and professionals and post-graduate students involved in petroleum industry.

Today's oil and gas are at record prices, whilst global energy demand is increasing from population and economic development pressures. New and highly improved methods to detect, explore, and exploit new resources of oil and gas are necessary to maintain the world's energy needs toward sustainable economic development. This books aim is to offer the latest developments in several areas related to the above mentioned goals. As authors, it is our understanding and expectation, that interested readers will find plenty of useful, insightful, and reliable information for their energy-related tasks.

The book presents a full methodology for investigating heat flow and heat generation on a large scale (state). Detailed description of thermal conductivities measurements is given. Heat generation estimation is described. A thorough error analysis lends confidence to the final heat flow values. The book includes the first heat flow and heat generation maps of Oklahoma. The study is extended to the south central United States by incorporating additional heat flow data from neighboring states. Heat flow in Oklahoma appears to be consistent with that measured in other stable tectonic provinces of similar ages. The primary control on heat flow appears to be heat production in basement rocks, although it is difficult to establish a correlation because the heat flow and heat generation were measured at different sites. Factors such as tectonic transients and heat refraction appear to exert little influence on the present thermal regime. Although conduction seems to be the dominant mechanism of heat transport throughout the upper crust in most of Oklahoma, high heat flow in one section of east central Oklahoma may be related to regional groundwater flow.