The title of this book intrigues. The text explains that
big data are data sets that are so large and complex that they are difficult to process using current conventional data processing methods, and
analytics is the process of finding meaningful patterns within these data sets.
Data sets are growing in size, in part because of the ability of modern information-sensing devices to collect vast quantities of data such as with seismic acquisition. The sizes are mind boggling with single data sets going up to maybe soon exabytes (1018). Analytics uses massive parallel computer software to uncover hidden patterns. The output of 'hidden' knowledge is often visualised in tables and graphics.
The practical aspect of analytics is needed for the oil and gas industry because the new generation of managers and geoscientists who are replacing the retiring 'old school' lack their experience of vision, but have an appreciation of statistics and soft computing methodologies. Analytics can show otherwise hidden patterns and may be able to retain the lost experience and enhance decisions.
Harness Oil and Gas Big Data with Analytics provides a complete view of big data and analytics techniques as they are applied to the oil and gas industry. After two chapters outlining the processes the book moves to chapters of specific case studies where data analytics have been used within exploration and production. Applications using case histories of seismic attribute analysis give guidance on reservoir characterisation, other chapters explore drilling and completion optimisation, reservoir management production forecasting and optimisation, and exploratory predictive analysis. Analytics suggest better-informed models of subsurface reservoir characterization and decisions for drilling/production optimisation for conventional and unconventional fields.
This book, written by an industry practitioner, is a description of the subject rather like the technical information found in service company literature. The text mentions, but does not detail the mathematics or algorithms of the methods commonly applied, such as neural networks, decision trees, genetic algorithms, data mining and artificial intelligence. Unfortunately many of the figures are disappointing and unhelpful, with many taken from papers which were originally in colour but printed in greyscale. Some are almost unreadable. I suspect too the vocabulary might be difficult for some. A fuller glossary giving more definitions of the acronyms and terms scattered within the text would be helpful for the 'old school’.
Harness Oil and Gas Big Data with Analytics is not going to turn the reader into a digital oilfield expert, but should give an idea of where/how analytics might be beneficial
Reviewed by Richard Dawe
HARNESS OIL AND GAS BIG DATA WITH ANALYTICS
KEITH R HOLDAWAY. Published by John Wiley & sons, 2014. ISBN 978-1-118-77931-6 hbk; ISBN 978-1-118-91095-5 epdf ; ISBN 978-1-118-91094-5 epub.
list price for hbk: £50.00 W: www.wiley.com