Machine learning and data science in the oil and gas industry explains how machine learning can be specifically tailored to oil and gas use cases. Petroleum engineers will learn when to use machine learning, how it is already used in oil and gas operations, and how to manage the data stream moving forward. Practical in its approach, the book explains all aspects of a data science or machine learning project, including the managerial parts that are often the cause of failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guidebook, this manual will lead a practitioner through the journey of a data science project in the oil and gas industry, circumventing the pitfalls and articulating the business value.