10.4122/1.1000000587
Gladkikh, Mikhail
Mikhail
Gladkikh
mikhail.gladkikh@bakerhughes.com
Mezzatesta, Alberto
Alberto
Mezzatesta
alberto.mezzatesta@bakerhughes.com
Gladkikh, Mikhail
Mikhail
Gladkikh
mikhail.gladkikh@bakerhughes.com
A Pore-Level Approach to Petrophysical Interpretation of Well Logging Measurements
XVI International Conference on Computational Methods in Water Resources
2006
2006
An accurate description of water- or oil-bearing reservoirs and the assessment of
reserves strongly depend on a robust determination of their petrophysical
parameters, e.g., porosity, permeability and fluid distribution, reflecting fluid
type, content, and mobility. Downhole measurements provide means to formation
evaluation; however, they do not directly provide the petrophysical properties of
interest. To interpret well logging data, a range of empirical models are usually
employed. These empirical relationships, however, lack scientific basis and usually
represent generalizations of the observed trends. To provide a link between a
detailed description of the physical processes occurring at the pore scale and the
macroscopic properties of sedimentary rocks, a new pore-level approach to
petrophysical interpretation of logging measurements is suggested in this work.
A powerful means to create such a link is to develop quantitative relationships
between the petrophysical properties and the geologic processes involved in forming
the rocks. Here we describe the use of simple but physically representative models
of the results of several rock-forming processes, e.g., sedimentation, cementation,
and the formation of authigenic clay minerals. The key feature of these models is
that they are geometrically determinate or precisely defined based on knowing the
location of every grain comprising the model rock and hence the morphology of the
pore space at the grain scale. We outline a method for computing macroscopic
petrophysical properties using the proposed rock models. Unlike many approaches to
pore-level modeling, our approach introduces no adjustable parameters and thus can
be used to produce quantitative, a priori predictions of the rock macroscopic
behavior. These a priori predictions, in turn, allow for successfully inverting and
interpreting logging data to obtain petrophysical parameters of sedimentary rocks,
such as absolute and relative permeabilities as well as capillary pressure curves.
For example, NMR (Nuclear Magnetic Resonance) logs contain information about grain
size, allowing for an accurate petrophysical interpretation by means of the pore-
level approach presented in this work.
The proposed methodology is also applied to real field data and the corresponding
interpretation results are included in this paper.