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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Data analytics has been broadly applied to a variety of areas within the oil and gas industry including applications in geoscience, drilling, completions, reservoir, production, facility, and operations. However, we limit our discussion here primarily to reservoir engineering applications.
This book describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering. It also outlines the methodology and guidelines for building robust models for reporting, diagnosis, prediction, and recommendations, and it provides an overview with examples of successful applications of data analytics in reservoir engineering and illustrate advantages and pitfalls these methods
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This title is printed to order. This book may have been self-published. If so, we cannot guarantee the quality of the content. In the main most books will have gone through the editing process however some may not. We therefore suggest that you be aware of this before ordering this book. If in doubt check either the author or publisher’s details as we are unable to accept any returns unless they are faulty. Please contact us if you have any questions.
Data analytics has been broadly applied to a variety of areas within the oil and gas industry including applications in geoscience, drilling, completions, reservoir, production, facility, and operations. However, we limit our discussion here primarily to reservoir engineering applications.
This book describes the relevance of data analytics for the oil and gas industry, with particular emphasis on reservoir engineering. It also outlines the methodology and guidelines for building robust models for reporting, diagnosis, prediction, and recommendations, and it provides an overview with examples of successful applications of data analytics in reservoir engineering and illustrate advantages and pitfalls these methods