Geology Reference
In-Depth Information
14 Depositional Models, Facies Zones and Standard Microfacies
Preceding chapters of part 2 of this topic were focused
on defining microfacies types, recognizing paleoenvi-
ronmental constraints and using an integrated approach
to facies analysis. Chapter 14 introduces carbonate fa-
cies models, underlines the importance of environment-
controlled distribution patterns of organisms, and gives
an overview of Standard Microfacies Types and their
application to the facies analysis of limestones. The
latter topic is expanded in the case studies described in
Chap. 15.
•A
depositional facies
model
is the essence of the cri-
teria and controls extracted from case studies of mod-
ern and ancient sediments.
14.1.1.1 Conceptual Models
The first facies models proposed for carbonate rocks
were
conceptual models
trying to show spatial distri-
bution patterns of rock types and biota, usually along a
coast-basin traverse. These static models were strongly
influenced by the investigation of modern subtropical
and tropical carbonates. For a long time the Bahamas,
Florida and the Persian Gulf served as paradigms for
shallow-marine carbonate platforms. Starting with the
'X-Y-Z model' by Irwin (1965) new ideas were intro-
duced into carbonate models that were supposed to re-
flect the overall environmental controls on carbonate
deposition on shelves and include the differences be-
tween ancient depositional settings and modern settings.
Using the commonly observed successions of facies
belts of Holocene and Phanerozoic carbonates, Wilson
(1975) established a
Standard Facies Model
that de-
scribes Standard Facies Zones (FZ) of a
rimmed tropi-
cal carbonate platform
along a strongly generalized
shore-to-basin transect. This
Wilson model
(see Sect.
14.1.3) had a strong impact not only on the interpreta-
tion of the litho- and biofacies of carbonate rocks but
also on the use of microfacies types as indicators of
facies zones and depositional conditions. Extending the
generalizations made by Flügel (1972) for common
microfacies types of Triassic carbonates, Wilson intro-
duced a set of
'Standard Microfacies Types' (SMF)
which aimed at categorizing common and widely dis-
tributed Phanerozoic microfacies types.
About the same time, Ahr (1973) recognized the dif-
ficulties related to the application of the rimmed plat-
form concept to the facies distribution of many Paleo-
zoic and Mesozoic shelf carbonates and proposed the
carbonate ramp model.
This model summarizes the
facies distribution on a gently sloping surface from the
coast to deeper water without a morphological break at
the shelf edge. Ramps differ from rimmed shelves in
the absence of continuous shelf-marginal reef trends,
the location of high-energy deposits near the shoreline
and not at the shelf edge, and the lack of shallow-water
derived clasts in deep-water parts of the ramp.
Ginsburg and James (1974), Kendall and Schlager
(1981), Schlager (1981, 1992, 2000), Read (1982,
•
Facies zones
(FZ) are belts differentiated according
to the changes of sedimentological and biological
criteria across shelf-slope-basin transects.
•
Standard microfacies types
(SMF) are derived from
local microfacies types looking at joint paleontologi-
cal and/or sedimentological criteria. Associations of
SMFs are additional criteria for recognizing ancient
facies zones.
14.1 Depositional Facies Models
A facies model is a generalized summary of a given
depositional system (Walker 1992). The information
required for this summary is taken from local case stud-
ies of modern and ancient examples. Facies models
should act as norms for purposes of comparison, as a
framework and guideline for future observations, as a
predictor of new geological situations, and as an inte-
grated basis for the system that it represents. Sensitive
and predictive facies models are important in the ex-
ploration of hydrocarbons and limestone resources (see
Chap. 17 and 18).
14.1.1 Conceptual, Dynamic and Computer
Models
Carbonate facies models correspond to different cat-
egories and comprise conceptual, dynamic and numeri-
cal models.
