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The
term petrofacies is defined in the sedimentary literature by
different meanings. The dominant part of the published work defines
petrofacies solely in terms of the major detrital composition of
sandstones and conglomerates, related to patterns of sedimentary
provenance (e.g., Stanley, 1976; Gandolfi et al., 1983; Ingersoll, 1990;
Large and Ingersoll, 1997; Trop and Ridgway, 1997; Critelli and Nilsen,
2000; Hendrix, 2000; Michaelsen and Henderson, 2000; Savoy et al., 2000;
Dickinson and Lawton, 2001; Marenssi et al., 2002). A few studies refer
to petrofacies as the major petrographic characteristics of carbonate,
evaporitic, or mudrocks (e.g., Kopaska-Merkel and Friedman, 1989; Kulick
and Theuerjahr, 1989; Ching and Friedman, 2000; Testa and Lugli, 2000).
Even
fewer studies define petrofacies solely in terms of petrophysical and
log characteristics, totally detached from petrographic characterization
(e.g., Watney et al., 1999; Bhattacharya et al., 2005). Our aim here is
to redefine petrofacies as a concept for reservoir characterization and
modeling.
Concept of Reservoir Petrofacies
Reservoir petrofacies are defined by the combination of specific
depositional structures, textures, and primary composition, with
dominant diagenetic processes. The combination of primary textural and
compositional aspects with specific diagenetic processes and products
correspond to defined value ranges of porosity and permeability, as well
as to characteristic log and seismic signatures. The concept of
reservoir petrofacies is a tool for the systematic recognition of these
main petrographic attributes that control the petrophysical and
geophysical behaviors, what ultimately define the evaluation of rocks,
rock bodies and units during petroleum  exploration and production.
Method for the Definition of Reservoir Petrofacies
The
recognition of reservoir petrofacies starts with a detailed petrography
of representative samples of the area/unit studied. Quantitative modal
analysis by counting 300 or more points is important, but not always
essential for petrofacies recognition, because in some cases the major
patterns can be directly recognized through a merely qualitative
description. The samples are separated into groups, first according to
sedimentary structures, texture, and fabric (grain size, sorting,
roundness, packing, and orientation).
These
primary attributes control the original porosity and permeability, which
in some cases were not substantially modified after deposition. However,
most reservoir successions show important modification of the original
quality by diagenesis. Therefore, compositional attributes, such as
types, volume, and location of primary constituents (which directly
affect the diagenetic processes), types, volume, location, habits, and
paragenetic relationships of diagenetic constituents and processes, and
the consequent pore types, location, and relationships must also be
evaluated. The samples must be thus grouped considering the
superposition of depositional structure/texture/fabric attributes with
major primary compositional categories, and with the distribution of the
most influential diagenetic processes. The attributes with larger impact
on porosity and permeability are recognized, and preliminary petrofacies
are assigned. The grouping of samples in the same petrofacies assumes
that they display similar petrophysical behavior. A same depositional
facies may correspond to several different reservoir petrofacies. For
example, a facies made of the same cross-stratified, medium- to
coarse-grained, moderately sorted braided-fluvial sandstones may be
grouped into different petrofacies, e.g., MetComp rich in
micaceous metamorphic rock fragments, consequently strongly compacted,
QzCem with a more quartzose composition, but strongly cemented by
quartz overgrowths, and QzPorous with similar composition to
QzCem but limited cementation, and consequently porous. The
reservoir petrofacies preliminarily defined according to the major
petrographic attributes are then checked against petrophysical and
petrographic quantitative parameters, by using statistical or neural
network tools. Threshold values are defined for the influential textural
and compositional attributes that constrain the significant reservoir
petrofacies.
Examples of Reservoir Petrofacies Application
Uerê Formation, Devonian, Solimões
Basin, Northern Brazil
Devonian sandstones of the Uerê Formation are important oil exploration
targets in the Solimões Basin, western Brazilian Amazonia (formerly
“Upper Amazonas Basin”)
(Figure 1).
Sharp-based, progradational sandstones, attributed to a storm-dominated
shelf complex formed during an overall transgressive systems tract, are
overlain by Frasnian-Famennian black shales. The sandstones are very
homogeneous in terms of depositional structures, texture, fabric, and
present-day detrital composition (subarkoses), but extremely
heterogeneous in terms of reservoir quality, due to intense diagenesis.
Three reservoir petrofacies were recognized, based on the packing,
porosity, and types of cementation (Lima and De Ros, 2002). Petrofacies
A, is represented by porous sandstones (>15%; up to 28%;
Figure 2), with porosity preservation due to
the inhibition of quartz overgrowth cementation and pressure-dissolution
by grain-rimming, eogenetic, microcrystalline quartz or chalcedony (Figure
2A). Early diagenetic silica precipitation was related to the
dissolution of sponge spicules, which were concentrated in
storm-reworked hybrid arenites and in interbedded spiculite deposits
(Lima and De Ros, 2002). Petrofacies B comprises tight (<10% porosity),
moderately quartz-cemented (< 5%) sandstones, strongly compacted through
intergranular pressure dissolution (Figure 2B).
Petrofacies C comprises moderately porous (10-15%), conspicuously
quartz-cemented (> 5%) sandstones (Figure 2C).
These
petrofacies can be effectively represented in a diagram of intergranular
volume versus volume of silica cements (Figure
2), showing different ranges of porosity and permeability and of log
parameters. Therefore, they can be used to display tri-dimensionally the
quality of the Uerê reservoirs in the oilfields under development, as
well as, combined with information on their burial and thermal
histories, to predict the quality of equivalent reservoirs in
exploration areas (Lima and De Ros, 2002).
Within the Carapebus Formation (Oligocene-Maastrichtian, with inclusion
of the related Ubatuba Formation—Rangel et al., 2003), four major
reservoir petrofacies were recognized in the sandstones and sandy
conglomerates in an oilfield of northern Campos Basin (Figures
1 3).The sandstones were deposited by high-density turbidity currents
in channelized lobe complexes. Petrofacies A comprises medium- to
coarse- grained, locally conglomeratic, poorly sorted feldspathic
sandstones (arkoses) and sandy conglomerates, which were pervasively
cemented by pre-compaction, coarsely-crystalline calcite (Figure
3A). Consequently, their porosity is commonly obliterated totally,
except for some dissolution porosity along fractures (average 3.2%; up
to 10%) and their permeability is very low. Petrofacies B represents the
best reservoirs, with good macroporosity (average 27.7%; up to 33.3%)
and permeability (up to 1.8 mD), comprising rocks with depositional
texture, fabric, and composition equivalent to Petrofacies A, but with
scarce carbonate cementation, constituted more commonly by blocky to
saddle dolomite. Secondary porosity due to dissolution of feldspars is
common (Figure 3B). Petrofacies C includes
coarse, commonly conglomeratic, poorly sorted sandstones and sandy
conglomerates rich in mud intraclasts and carbonaceous fragments, with
abundant pseudomatrix generated by the compaction of the soft
intraclasts (Figure 3C). Porosity is low
(average 12.1%; up to 13.3%), as is the permeability. Petrofacies D is
represented by very fine to fine, well-sorted sandstones rich in micas
and locally in small mud intraclasts (Figure 3D).
Macroporosity was heterogeneously reduced by the compaction (8.3 to
26.3%; average 18.4%), but permeability is always low (few tens to
fraction of mD). These reservoir petrofacies are easily recognized in
logs, and can therefore be used to represent tri-dimensionally the
quality and heterogeneity of the reservoirs in the field.
Concept
Application
Reservoir petrofacies defined by this methodology are consistent in
terms of petrophysical porosity and permeability, log and seismic
signatures. Consequently, they can be used for calibrating the logs for
realistic rock properties. The calibrated logs can then be applied to
the representation in 2D sections and 3D models of the true reservoir
quality and heterogeneity. Realistic reservoir models constructed
through this methodology can then be used in enhanced static and flow
simulations during the development and production of the oil and gas
fields. Reservoir petrofacies can be consistently linked to sequence
stratigraphic, provenance and/or burial history parameters for the
development of coherent and operational models for the prediction of
reservoir quality during hydrocarbon exploration.
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