Geostatistical Methods for Reservoir Geophysics
by Azevedo, L. and Soares, A.
Springer International Publishing AG, 2017
Michael Ed. Hohn
Received: 12 May 2018 / Accepted: 23 May 2018
© International Association for Mathematical Geosciences 2018
I enjoyed reading this book for its geostatistical content, extension to the area of geo-
physics, and for its production quality. The target audience is the petroleum engineer,
geophysicist, or numerically oriented geologist. In about 130 pages, the book moves
from basic geostatistical estimation to the creation of complex models of the subsurface
through inversion of 3D seismic data, well log data, and production histories. Topics
include spatial models, kriging in its many forms, simulation, creating simple models
from seismic reﬂection and well data, inferring petrophysical models, and incorpo-
rating controlled-source electromagnetic data and production history. Geostatistical
methods are key to ﬁnding optimal geophysical and geological models.
This book moves at a fairly even pace from simple geostatistical methods to ever
more complex applications in the ﬁnal chapter, although, in places, I would have liked
more detail. The level is somewhere between an elementary textbook and a scientiﬁc
journal. Motivation, theory, and the methodology of geostatistics are provided. The
authors assume a background in geophysics. This book would be appropriate for an
upper level undergraduate class and above.
Geostatistical Methods for Reservoir Geophysics comprises seven chapters: a short
introduction; two chapters on the fundamentals of spatial models, estimation, and
simulation; three chapters on the central problem of incorporating geophysical data
into subsurface models; and a brief afterword.
The second and third chapters cover basic geostatistical tools used in reservoir
geostatistics within about 50 of the book’s 141 pages. The pace is fast. Readers new to
Michael Ed. Hohn
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