NEXT, Schlumberger. Reservoir Enginnering Course Manual - Petrel

Wiley Balckwell, 2018. — 319 p. — ISBN: 9781119313465. Reservoir Modelling offers a comprehensive guide to the procedures and workflow for building a 3-D model. Designed to be practical, the principles outlined can be applied to any modelling project regardless of the software used. The author — a noted practitioner in the field — captures the heterogeneity due to structure,...

Wiley, 2018. — 361 p. — ISBN: 978-1-119-21510-3. Leverage Big Data analytics methodologies to add value to geophysical and petrophysical exploration data Enhance Oil & Gas Exploration with Data-Driven Geophysical and Petrophysical Models demonstrates a new approach to geophysics and petrophysics data analysis using the latest methods drawn from Big Data. Written by two...

Shlumberger, 2010, 3417 pages. Full description from seismic to simulation procedures of Shlumberger software. Petrel Geophysics Petrel Exploration Geophysics Petrel Classification and Estimation Petrel Seismic Interpretation Petrel Seismic Attribute Analysis Petrel Seismic Sampling Petrel Seismic Volume Rendering & Geobody Extraction Petrel Domain Conversion Petrel...

American Geophysical Union — Wiley, 2019. — 509 p. — (Geophysical Monograph 237). — ISBN: 978-1-119-38797-8. A comprehensive and practical guide to methods for solving complex petroleum engineering problems Petroleum engineering is guided by overarching scientific and mathematical principles, but there is sometimes a gap between theoretical knowledge and practical application....

Schlumberger, 2015. — 690 p. The overall objective of this course is to acquaint you with the interactive Petrel E&P Software Platform 2015 reservoir engineering tools used to construct simulation models. During the course, the practical application of most of the available tools in Petrel used for a typical reservoir enginnering workflow is discussed and ilustrated in the...

Gulf Professional Publishing, 2020. — 340 p. — ISBN: 0128209577. Reservoir Simulation: Machine Learning and Modeling helps the engineer step into the current and most popular advances in reservoir simulation, learning from current experiments and speeding up potential collaboration opportunities in research and technology. This reference explains common terminology, concepts,...