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SCRF 24th Annual Meeting May 4‐5 2011
Stanford Center for Reservoir Forecasting
Annual Meeting 2011
SCRF 2011 2
SCRF 24th Annual Meeting
•SCRF Overview
•2011 Research Highlights
SCRF 2011 3
SCRF Mission
Leading research in quantitative reservoir modeling with a focus on data integration and assessing uncertainty
SCRF Overview
SCRF 2011 4
• Quantitative modeling of geological heterogeneity
• Modeling uncertainty
• Building 3D/4D models accounting for scale and accuracy of geological, geophysical and reservoir engineering data
SCRF Overview
SCRF 2011 5
SCRF Research topics
• Modeling uncertainty• Uncertainty of global reservoir parameters• Modeling integrated uncertainty in metric space• Distance‐Kernel Method
• Multiple‐point geostatistics • How to quantify geological concepts / Training images ?• Stochastic simulation of (geo)patterns• Design of fast and robust geostatistical algorithms• Application to actual reservoirs, carbonate and clastic• Hybridization with surface and object‐based methods
SCRF 2011 6
SCRF Research topics• Seismic reservoir characterization
• Statistical Rock physics• Interpretation of facies from seismic data• Dealing with sub‐seismic scale• Integrating different types of geophysical data• Seismic constraints for Basin Modeling
• History matching & 4D seismic• Geologically consistent HM• Workflows for integrating 4D seismic• Streamline‐based HM
• Value of Information• Decision driven modeling of uncertainty
SCRF 2011 7
SCRF: Students, Staff, and Faculty• Graduate students (~10)
• Research Associates, Post‐docsCeline Scheidt
• Staff Thuy Nguyen, Joleen Castro
• Faculty• Jef Caers
• Tapan Mukerji
• Alexandre Boucher
Work closely with other research groups in the School of Earth Sciences
SCRF 2011 8
•SRBRock Physics
•SUPRI/Smart FieldsFlow simulation
•SEP Seismic Imaging
•SPODDSDeep Water Systems
•BPSMBasin Modeling
SCRF: Stanford Collaborations
SCRF: Affiliate Members
SCRF 2011 9
Long‐term research goals are made possible throughcontinuous funding of most major oil, service and software companies
New sponsors:BPGDF SuezUniversite de Neuchatel
SCRF: Membership Benefits
• Graduates
• Facilitated access to research• Reports
• Theses
• Software
• Annual Meeting
• Visits
• Research collaborations
SCRF 2011 10
SCRF 2011 11
SCRF 24th Annual Meeting
2011 Research and Results: Highlights
SCRF 2011 12
1.Modeling Uncertainty in Metric Space and
Distance Kernel Methods
Multidimensional Scaling (MDS)Caers et al., 2009
Map a set of N earth models using a pair wise distance between them.
1.
Scheidt & Caers
1.
1.Kwangwon Park, Ph.D. Thesis
Modeling Uncertainty in Metric Space
Reformulation of non‐linear inverse problems in metric space
SCRF 2011 15
1.
SCRF 2011 16
Scheidt & Caers
How many models?
1.
SCRF 2011 17
Time
Water produ
ction
Scheidt & Caers
P25‐P75 Interval
Adaptive sequential space filling design for geostatistical simulations
SCRF 2011 18
1.Distance based sensitivity analysis for fractured reservoirs
Fenwick & Park
SCRF 2011 19
1.Distance based modeling of structural uncertainty
Addy Satija
Faults and well placement uncertainty
SCRF 2011 20
1.Distance based modeling of uncertain geologic scenarios
Park and Caers
P( geologic scenario | data)
SCRF 2011 21
2.Multiple Point Geostatistics
Algorithms
SCRF 2011 22
2.Mehrdad Honarkhah, Ph.D. thesis
Stochastic Simulation of Patterns using Distance‐Based Pattern Modeling
DISPAT
SCRF 2011 23
2.Mehrdad Honarkhah, Ph.D. thesisModeling non‐stationarity
2‐D Gabor filter
SCRF 2011 24
2.
Mehrdad Honarkhah, Ph.D. thesis
Modeling non‐stationarity
Gabor filter bank
orientation
freq
uency
SCRF 2011 25
2.Mehrdad Honarkhah, Ph.D. thesis
Convolution with Gabor filter
Extracted features used for clustering and automatic segmentation
SCRF 2011 26
2.Mehrdad Honarkhah, Ph.D. thesisMPS with non‐stationarity
SCRF 2011 27
3.Seismic Reservoir Characterization
Quantitative seismic interpretation
Seismic inversion for facies and fluids
SCRF 2011 28
3.
Data Integration
CoreWell logsSeismic data
3.
Seismic Impedance, Molasse Basin, Austria
Stright et al.
Multi‐attribute, multi‐scale calibration for reservoir characterization
3.Stright et al.
3.Stright et al.
Tetris/SGeMS
Geostatistical modeling of sub‐seismic scale sandstone packages.
SCRF 2011 32
3.Seismic inversion for facies and fluids
SCRF 2011 33
3.
Cascaded or multi‐step approach
SCRF 2011 34
3.
Cascaded or multi‐step approach
SCRF 2011 35
3.
Geostats
Cascaded or multi‐step approach
SCRF 2011 36
3.
Geostats
Simultaneous or single‐loop approach
SCRF 2011 37
3.
Geostats
Simultaneous or single‐loop approach
SCRF 2011 38
3.
Geostats
Simultaneous or single‐loop approach
SCRF 2011 39
3.
Perturb the initial modelGeostats
Simultaneous or single‐loop approach
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3.Dario Grana
Two angle stacks:
• Near = 20°• Far = 44°
Well data
Single‐loop inversion using probability perturbation method
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3.Dario Grana
Litho‐fluid classes
Single‐loop inversion using probability perturbation method
SCRF 2011 42
3.
Iterative Spatial ResamplingApplied to Single Loop Seismic Inversion
Cheolkyun JeongGregoire Mariethoz
SCRF 2011 43
3.Iterative Spatial Resampling (ISR)
Gregoire Mariethoz et al.
ISR perturbs realizations of a spatially dependent variable while preserving its spatial structure.
SCRF 2011 44
3.Adaptive Spatial Resampling (ASR) Cheolkyun Jeong
Gregoire Mariethoz
SCRF 2011 45
Log1
0RM
SE
Iterations
3.ASR optimization
Reference model
Cheolkyun JeongGregoire Mariethoz
SCRF 2011 46
4.Seismic History Matching
Production dataTime‐lapse seismic data
SCRF 2011 47
Integration of production and time lapse Seismic data: Norne field Amit Suman
4.
Southern part of Norwegian sea
C
D
EG
C
D
EG
Norne Field Segment E
4.
• Well logs
• Horizons
• Well data
‐ Oil , gas and water flow rate
‐ BHP (Bottom hole pressure)
4.
Time Lapse Seismic Data
Near, Mid , Far and Full stack 3D seismic Q – Marine Seismic
2001 2003 2004 2006
4.
Generatemultiplemodels
Evaluatemisfit
.
Reservoir
Model
Observed flow and seismic response
Predicted flow and seismic response
Joint Inversion Loop
4.
What are the sensitive parameters in joint time‐lapse and production inversion loop?
– Flow response
– Seismic response
4.
SCRF 2011 53
5.Hybrid Geomodeling–Surface based models
–Generalized cellular automata
Two points
Multiple points
Object based
Surface based
Process based
Conditioning capabilities
Geological realism
Bertoncello et al.
5.
SCRF 2011 55
5.Hybrid Geomodeling
Holly Michael et al. 2008/2009Leiva, 2008
SCRF 2011 56
5.Conditioning surface based models to log data
Lobe‐by‐lobe optimization using genetic algorithm and Nelder‐Mead
Bertoncello et al.
SCRF 2011 57
5.Conditioning surface based models to log data: Application to Karoo dataset
Bertoncello et al.
9 wells2 sediment sources
Flow physics
Bed surface
processes
Fluid mechanics
(Physics equations)
Generalized cellular automata (Rule‐based)
Decomposition of the problem
5.Hybrid Geomodeling Siyao Xu
A coupled scheme
Generalized Cellular Automata Bed Surface Model
Local Flow EnergyLocal Bed Surface
Analytical Flow Equations
Lattice Boltzmann Flow Model
Discretize
Siyao Xu
5.
SCRF 2011 60
Research and Results: Highlights
1.Modeling Uncertainty ‐ Distance‐Kernel Methods
2.Multiple‐point simulation algorithms
3.Seismic reservoir characterization
4.Time‐lapse seismic history matching
5.Hybrid geomodeling
SCRF 2011 61
Guest Speakers
Lisa StrightUniversity of Utah
Gregoire MariethozUniversity of Texas, Austin
Darryl FenwickStreamsim
SCRF 2011 62
Research Report
Digital annual report with papers
Ph.D. Theses
Presentations: http://scrf.stanford.edu
SCRF 24th Annual Meeting May 4‐5 2011
Stanford Center for Reservoir Forecasting
Annual Meeting 2011
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