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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.
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