Understanding Pore Space through Log Measurements (eBook)

This book Understanding Pore Space through Log Measurements deals with porosity, insight on pore shape connectedness, grain size, grain aspect ratio, permeability etc. Most of the published literature is focused on permeability from log measurements and log analytic techniques for porosity and fluid saturation determination. On the other hand, this book aims at looking at porosity distribution, pore shape, and pore connectedness using log measurements and thus bringing pore space into focus. A compilation of available knowledge from this perspective will lead the reader to better understanding of reservoir characterization takeaways, which exploration and exploitation managers and workers will be looking for. - Offers insight into influence of pore attributes on macroscopic pore space descriptors - Grain characters that influence the properties of the pore space - Guides on how to best model the inversion of log data into these attributes

K. Meenakshi Sundaram holds a Master's Degree from Andhra University in nuclear physics with specialization in theoretical nuclear physics. He joined ONGC India in 1976 and held several key positions in G&G before retiring in 2012 as Executive Director (Geophysics). He has 19 years of experience in log data acquisition and 17 years of experience in reservoir characterization through logs. He has co-authored 28 technical papers on different subjects including image log interpretation NMR applications, geo-mechanics, and mineralogy, grain size and permeability prediction from logs. He has also guided eight M.Tech. dissertation projects.

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This book Understanding Pore Space through Log Measurements deals with porosity, insight on pore shape connectedness, grain size, grain aspect ratio, permeability etc. Most of the published literature is focused on permeability from log measurements and log analytic techniques for porosity and fluid saturation determination. On the other hand, this book aims at looking at porosity distribution, pore shape, and pore connectedness using log measurements and thus bringing pore space into focus. A compilation of available knowledge from this perspective will lead the reader to better understanding of reservoir characterization takeaways, which exploration and exploitation managers and workers will be looking for. - Offers insight into influence of pore attributes on macroscopic pore space descriptors- Grain characters that influence the properties of the pore space- Guides on how to best model the inversion of log data into these attributes