Data Science and Machine Learning Applications in Subsurface Engineering is popular PDF and ePub book, written by Daniel Asante Otchere in 2024-02-06, it is a fantastic choice for those who relish reading online the Science genre. Let's immerse ourselves in this engaging Science book by exploring the summary and details provided below. Remember, Data Science and Machine Learning Applications in Subsurface Engineering can be Read Online from any device for your convenience.
Data Science and Machine Learning Applications in Subsurface Engineering Book PDF Summary
This book covers unsupervised learning, supervised learning, clustering approaches, feature engineering, explainable AI and multioutput regression models for subsurface engineering problems. Processing voluminous and complex data sets are the primary focus of the field of machine learning (ML). ML aims to develop data-driven methods and computational algorithms that can learn to identify complex and non-linear patterns to understand and predict the relationships between variables by analysing extensive data. Although ML models provide the final output for predictions, several steps need to be performed to achieve accurate predictions. These steps, data pre-processing, feature selection, feature engineering and outlier removal, are all contained in this book. New models are also developed using existing ML architecture and learning theories to improve the performance of traditional ML models and handle small and big data without manual adjustments. This research-oriented book will help subsurface engineers, geophysicists, and geoscientists become familiar with data science and ML advances relevant to subsurface engineering. Additionally, it demonstrates the use of data-driven approaches for salt identification, seismic interpretation, estimating enhanced oil recovery factor, predicting pore fluid types, petrophysical property prediction, estimating pressure drop in pipelines, bubble point pressure prediction, enhancing drilling mud loss, smart well completion and synthetic well log predictions.
Detail Book of Data Science and Machine Learning Applications in Subsurface Engineering PDF
- Author : Daniel Asante Otchere
- Release : 06 February 2024
- Publisher : CRC Press
- ISBN : 9781003860228
- Genre : Science
- Total Page : 368 pages
- Language : English
- PDF File Size : 8,9 Mb
If you're still pondering over how to secure a PDF or EPUB version of the book Data Science and Machine Learning Applications in Subsurface Engineering by Daniel Asante Otchere, don't worry! All you have to do is click the 'Get Book' buttons below to kick off your Download or Read Online journey. Just a friendly reminder: we don't upload or host the files ourselves.