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Harness Oil and Gas Big Data with Analytics: Optimize Exploration and Production with Data Driven Models by Keith Holdaway

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Chapter 1Fundamentals of Soft Computing

There are more things in heaven and earth, Horatio, than are dreamt of in your philosophy.

William Shakespeare: Hamlet

The oil and gas industry has witnessed a compelling argument over the past decade to adopt soft computing techniques as upstream problems become too complex to entrust siloed disciplines with deterministic and interpretation analysis methods. We find ourselves in the thick of a data avalanche across the exploration and production value chain that is transforming data-driven models from a professional curiosity into an industry imperative. At the core of the multidisciplinary analytical methodologies are data-mining techniques that provide descriptive and predictive models to complement conventional engineering analysis steeped in first principles. Advances in data aggregation, integration, quantification of uncertainties, and soft computing methods are enabling supplementary perspectives on the disparate upstream data to create more accurate reservoir models in a timelier manner. Soft computing is amenable, efficient, and robust as well as being less resource intensive than traditional interpretation based on mathematics, physics, and the experience of experts. We shall explore the multifaceted benefits garnered from the application of the rich array of soft computing techniques in the petroleum industry.

CURRENT LANDSCAPE IN UPSTREAM DATA ANALYSIS

What is human-level artificial intelligence? Precise definitions are ...

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