Matheson Gas Data Book

Matheson Gas Data Book
Author: Carl L. Yaws
Publisher: McGraw Hill Professional
Total Pages: 1004
Release: 2001
Genre: Science
ISBN: 9780071358545

The Proposed book is a new edition of the Matheson Gas Data book which is widely used in industrial facilities and research laboratories. The most recent edition sold 18,000 copies. The purpose of the new edition would provide expanded coverage of gases, and to cover more gases. The expanded coverage would encompass physical, thermodynamic, environmental, transport, safety, and health and related properties of gases of major importance. It will also cover known applications, government regulations, and first aid information. This book will be of interest to both the safety and engineering professional who use compressed gas.

Industrial Gas Handbook

Industrial Gas Handbook
Author: Frank G. Kerry
Publisher: CRC Press
Total Pages: 552
Release: 2007-02-22
Genre: Science
ISBN: 1420008269

Drawing on Frank G. Kerry's more than 60 years of experience as a practicing engineer, the Industrial Gas Handbook: Gas Separation and Purification provides from-the-trenches advice that helps practicing engineers master and advance in the field. It offers detailed discussions and up-to-date approaches to process cycles for cryogenic separation of

Handbook of Natural Gas Transmission and Processing

Handbook of Natural Gas Transmission and Processing
Author: Saeid Mokhatab
Publisher: Gulf Professional Publishing
Total Pages: 830
Release: 2012-07-02
Genre: Technology & Engineering
ISBN: 0123869145

A unique, well-documented, and forward-thinking work, the second edition of Handbook of Natural Gas Transmission and Processing continues to present a thoroughly updated, authoritative, and comprehensive description of all major aspects of natural gas transmission and processing. It provides an ideal platform for engineers, technologists, and operations personnel working in the natural gas industry to get a better understanding of any special requirements for optimal design and operations of natural gas transmission pipelines and processing plants. First book of its kind that covers all aspects of natural gas transmission and processing Provides pivotal updates on the latest technologies, which have not been addressed in-depth in any existing books Offers practical advice for design and operation based on sound engineering principles and established techniques Examines ways to select the best processing route for optimal design of gas-processing plants Contains new discussions on process modeling, control, and optimization in gas processing industry

Machine Learning and Data Science in the Oil and Gas Industry

Machine Learning and Data Science in the Oil and Gas Industry
Author: Patrick Bangert
Publisher: Gulf Professional Publishing
Total Pages: 290
Release: 2021-03-04
Genre: Science
ISBN: 0128209143

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 of it that are so often the cause for failure. Several real-life case studies round out the book with topics such as predictive maintenance, soft sensing, and forecasting. Viewed as a guide book, 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. - Chart an overview of the techniques and tools of machine learning including all the non-technological aspects necessary to be successful - Gain practical understanding of machine learning used in oil and gas operations through contributed case studies - Learn change management skills that will help gain confidence in pursuing the technology - Understand the workflow of a full-scale project and where machine learning benefits (and where it does not)

Standard Handbook of Petroleum & Natural Gas Engineering

Standard Handbook of Petroleum & Natural Gas Engineering
Author: William C. Lyons
Publisher: Gulf Professional Publishing
Total Pages: 1450
Release: 1996
Genre: Technology & Engineering
ISBN: 0884156427

Volume 1 presents the mathematics and general engineering and science of petroleum engineering. It also examines the auxiliary equipment and provides coverage of all aspects of drilling and well completion.

Machine Learning Guide for Oil and Gas Using Python

Machine Learning Guide for Oil and Gas Using Python
Author: Hoss Belyadi
Publisher: Gulf Professional Publishing
Total Pages: 478
Release: 2021-04-09
Genre: Science
ISBN: 0128219300

Machine Learning Guide for Oil and Gas Using Python: A Step-by-Step Breakdown with Data, Algorithms, Codes, and Applications delivers a critical training and resource tool to help engineers understand machine learning theory and practice, specifically referencing use cases in oil and gas. The reference moves from explaining how Python works to step-by-step examples of utilization in various oil and gas scenarios, such as well testing, shale reservoirs and production optimization. Petroleum engineers are quickly applying machine learning techniques to their data challenges, but there is a lack of references beyond the math or heavy theory of machine learning. Machine Learning Guide for Oil and Gas Using Python details the open-source tool Python by explaining how it works at an introductory level then bridging into how to apply the algorithms into different oil and gas scenarios. While similar resources are often too mathematical, this book balances theory with applications, including use cases that help solve different oil and gas data challenges. - Helps readers understand how open-source Python can be utilized in practical oil and gas challenges - Covers the most commonly used algorithms for both supervised and unsupervised learning - Presents a balanced approach of both theory and practicality while progressing from introductory to advanced analytical techniques

Pyrolysis - GC/MS Data Book of Synthetic Polymers

Pyrolysis - GC/MS Data Book of Synthetic Polymers
Author: Shin Tsuge
Publisher: Elsevier
Total Pages: 405
Release: 2011-08-02
Genre: Science
ISBN: 0444538933

In this data book, both conventional Py-GC/MS where thermal energy alone is used to cause fragmentation of given polymeric materials and reactive Py-GC/MS in the presence of organic alkaline for condensation polymers are compiled. Before going into detailed presentation of the data, however, acquiring a firm grip on the proper understanding about the situation of Py-GC/MS would promote better utilization of the following pyrolysis data for various polymers samples. This book incorporates recent technological advances in analytical pyrolysis methods especially useful for the characterization of 163 typical synthetic polymers. The book briefly reviews the instrumentation available in advanced analytical pyrolysis, and offers guidance to perform effectually this technique combining with gas chromatography and mass spectrometry. Main contents are comprehensive sample pyrograms, thermograms, identification tables, and representative mass spectra (MS) of pyrolyzates for synthetic polymers. This edition also highlights thermally-assisted hydrolysis and methylation technique effectively applied to 33 basic condensation polymers. - Coverage of Py-GC/MS data of conventional pyrograms and thermograms of basic 163 kinds of synthetic polymers together with MS and retention index data for pyrolyzates, enabling a quick identification - Additional coverage of the pyrograms and their related data for 33 basic condensation polymers obtained by the thermally-assisted hydrolysis and methylation technique - All compiled data measured under the same experimental conditions for pyrolysis, gas chromatography and mass spectrometry to facilitate peak identification - Surveyable instant information on two facing pages dedicated to the whole data of a given polymer sample