Fluvial & Eolian Research Group University of Leeds
A database approach for constraining object- and pixel-based
stochastic simulations of fluvial sedimentary architecture:example
application to quantification of connectivity Luca Colombera, Nigel
P. Mountney, William D. McCaffrey, Fabrizio Felletti Fluvial &
Eolian Research Group University of Leeds Overview Creation of a
relational database for the digitization of fluvial sedimentary
architecture : the Fluvial Architecture Knowledge Transfer System
(FAKTS) Quantitative characterization of fluvial architecture
applicable to: determination of importance of controlling factors
develop quantitative synthetic depositional models derive
constraints on subsurface predictions identify modern and ancient
reservoir analogues Approach to DB design The sedimentary and
geomorphic architecture of preserved ancient successions and modern
rivers is translated into the database schema by subdividing it
into geological objects common to the stratigraphic and geomorphic
realms which belong to different scales of observation nested in a
hierarchical fashion. FAKTSconceptual and logical schemes after
Colombera et al. (2012) Genetic units classifications
Implementation Genetic units classifications DEPOSITIONAL ELEMENTS
ARCHITECTURAL ELEMENTS FACIES UNITS 2 classes: Channel-complex
Floodplain 14 classes of subenvironments: Genetic bodies/facies
associations with geomorphic significance 25 textural structural
classes largely based on Mialls (1996) scheme Dataset/subset
classifications METADATA INTERNAL PARAMETERS EXTERNAL CONTROLS
Authors/reference Basin Lithostratigraphic unit River Age
Methods/data type Data Quality Index etc Basin gradient Discharge
regime River pattern Drainage pattern Aggradation rates Load-type
dominance Relative distality etc Subsidence rates/types
Basin/catchment climate Basin/catchment vegetation Relative
eustatic change Catchment lithologies Catchment uplift rates
Catchment geomorphic processes etc Data Entry Cain (2009) Amorosi
et al. (2008) Cain (2009) Robinson & McCabe(1997) North (1996):
at present, much is being published in the format of multiple
vertical profiles, photomontages and line drawings because we still
do not really know how to handle all the available facts. Database
Output unit proportions
North (1996): at present, much is being published in the format of
multiple vertical profiles, photomontages and line drawings because
we still do not really know how to handle all the available facts.
Database Output unit DIMENSIONS
Miall & Jones (2003): the database on large-scale fluvial
architecture, especially sandbody width and length, remains
extremely small Database Output unit Transitions Transition count
matrices
COUNT (Z) Sh Sl Sm Sp Sr Ss St 555 116 218 145 211 59 169 122 283
151 89 25 33 121 215 142 561 119 51 103 143 87 106 350 56 22 155
152 19 50 37 4 76 68 55 16 20 7 58 57 208 124 137 42 698 Facies
transition within 4th order channel-fills N = 1024
Reservoir/aquifer analogue selection
FAKTS contains now: 4,285 classified large-scale depositional
elements, 3,446 classified architectural elements, 20,101 facies
units; from 111 case studies, including : 25 modern rivers, 65
ancient successions, 2 other published composite databases.
UP-TO-DATE FIGURES Synthetic analogues Subsurface
applications
North & Prosser (1993): Are the results from outcrop and modern
environment studies being translated into predictive tools suitable
for modelling subsurface geology? de Marsily et al. (2005): future
work should be focused on improving the facies models [] A
world-wide catalog of facies geometry and properties, which could
combine site genesis and description with methods used to assess
the system, would be of great value for practical applications.
QUANTITATIVE INFORMATION FROM: identified modern and ancient
reservoir analogues synthetic depositional models used as synthetic
analogues TO BE USED FOR: guiding subsurface correlations deriving
static-connectivity models obtaining constraints to stochastic
facies modelling: genetic/material unit: proportions, absolute and
relative dimensional parameters, Indicator auto- and
cross-variograms, transition probabilities/rates FAKTS
facies-modelling applications
MODEL-CONDITIONING PROBLEMS after Deutsch & Tran (2002) after
Guo & Deutsch (2010) after Mariethoz et al. (2009) FAKTS
facies-modelling applications
OVERVIEW FAKTS provides a wealth of quantitative data from several
classified case studies with which to fully constrain stochastic
structure-imitating simulations of fluvial reservoir/aquifer
architecture, overcoming the main problems encountered when relying
on traditional databases. Geometrical parameters
FAKTS facies-modeling applications OBJECT-BASEDSIMULATION
CONSTRAINTS Geometrical parameters FLUVSIM (Deutsch & Tran
2002) simulations after Colombera et al. (In press) Relative
dimensional parameters
FAKTS facies-modelling applications OBJECT-BASEDSIMULATION
CONSTRAINTS Relative dimensional parameters Relative dimensional
parameters can be derived as FAKTS stores genetic-unit absolute
sizes, transitions and hierarchical nesting. after Colombera et al.
(In press) CH FF CS FLUVSIM (Deutsch & Tran 2002) simulations
FAKTS facies-modelling applications
PIXEL-BASEDSIMULATION CONSTRAINTS Material units Material units
defined on any categorical and/or continuous variable: flexibility
in the choice of reservoir-quality categories. after Colombera et
al. (In press) Indicator auto-variograms
FAKTS facies-modelling applications PIXEL-BASEDSIMULATION
CONSTRAINTS Indicator auto-variograms It is possible to inform
indicator auto-variogram model form and parameters on material-unit
proportions and modality, mean and variance in size, for each FAKTS
direction. Indicator cross-variograms
FAKTS facies-modelling applications PIXEL-BASEDSIMULATION
CONSTRAINTS Indicator cross-variograms Indicator cross-variograms
can be informed on FAKTS-derived: Proportions p Transition rates r
(from transition frequency and mean size) after Colombera et al.
(In press) Transition probabilities/rates and lithotype rules
FAKTS facies-modelling applications PIXEL-BASEDSIMULATION
CONSTRAINTS Transition probabilities/rates and lithotype rules
Possibility to derive parameters that enable the simulation of
genetic- and material-unit spatialrelationships and juxtapositional
trends. FAKTS facies-modelling applications
INCLUDING BOUNDING-SURFACE INFORMATION Connectivity function
Static-connectivity studies MULTI-SCALE CONNECTIVITY ANALYSIS OF
CLASSIFIED FLUVIAL SYSTEMS Connectivity function Downstream
direction Possibility to investigate the impact of several scales
of heterogeneity on reservoir static connectivity and its
variability associated with types of fluvial depositional systems.
Static-connectivity studies
MULTI-SCALE CONNECTIVITY ANALYSIS OF CLASSIFIED FLUVIAL SYSTEMS
Possibility to investigate the impact of several scales of
heterogeneity on reservoir static connectivity and its variability
associated with types of fluvial depositional systems. Vertical
Horizontal Future work Dynamic-connectivity studies for
assessingarchitectural controls and N:G threshold between
connectivity-limited and permeability-heterogeneity-limited
reservoirs for a range of different classified fluvial systems.
Inclusion of porosity and permeability data for every order of
genetic units. After Anderson et al. (1999) FAKTS major advantages
for conditioning facies modelling:
Conclusions FAKTS major advantages for conditioning facies
modelling: possibility to choose different modelling categories
corresponding todifferent scales of heterogeneity, and adopt a
multi-scale approach; possibility to define any type of material
units (on any categorical and/orcontinuous variable) to be used as
modelling categories; possibility to derive absolute and relative
dimensional parameters withwhich to condition object-based
simulations; possibility to generate models of indicator auto- and
cross-variogramswith which to constrain variogram-based
simulations; possibility to obtain transition frequency/probability
matrices withwhich to constrain Markov chain-based simulations or
with which toestablish lithotype rules or contact matrices for
plurigaussian simulations; possibility to employ database output to
fully constrainunconditionalsimulations of fluvial architecture and
to use the resulting realizations as3D training images for
multiple-point-statistics simulations. Thank you for you
attention
We thank our sponsors IAS is thanked for travel grant