Geologic and Reservoir Characterization and Modeling

Scott M. Frailey and James Damico Illinois State Geological Survey

Midwest Geologic Sequestration Science Conference November 8th, 2011

Acknowledgements n  The Midwest Geological Sequestration Consortium is funded by the

U.S. Department of Energy through the National Energy Technology Laboratory (NETL) via the Regional Carbon Sequestration Partnership Program (contract number DE-FC26-05NT42588) and by a cost share agreement with the Illinois Department of Commerce and Economic Opportunity, Office of Coal Development through the Illinois Clean Coal Institute.

n  Landmark Graphics Software Donation via University Program and Schlumberger Carbon Service for technical support and consultation

Modeling Goal

n  To develop a representative reservoir model based on geology, petrophysical, and fluid properties to provide guidance to n  Pilot design n  Active CO2 injection operations n  Long-term sequestration strategies

n  Specifically n  Plume shape, size, and distribution n  Far-field pressure magnitude and distribution

Petrophysical Challenge: Predicting Permeability

n  Permeability is a function of porosity and packing arrangement/grain size

n  Cores with similar porosity can have significantly different permeability values

Depth, ft MD 6763 7045

φ, % 28.5 28.6

k, md 43.2 1440

CCS #1

Petrophysical Challenge: Permeability-Porosity Core Data

0.0001

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Cor

e Pe

rmea

bilit

y

Core Porosity

n  Porosity alone is not a good predictor of permeability

CCS #1

Petrophysical Characterization: Core φ-k Transform Based on Grain

Size n  Sub-divide core

data by grain size category

n  Better representation of the core data

n  How to pick transform based on log response?

0.0001

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e Pe

rmea

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y

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CCS #1

Petrophysical Characterization: Core φ-k Transform Based on

Grain Size

n  Grain size correlated to Archie’s cementation exponent “m” n  Resistivity and porosity logs n  In-situ brine resistivity

n  “m” correlated to grain-size based φ-k transforms

Schwartz and Kimminau, 1987

Geologic Characterization: Permeability Transform based on ‘m’

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Dep

th

K (md)

Injection Well (CCS #1) �

Dark blue line: predicted permeability using m

Pink squares: rotary sidewall core plug permeability

Injection Well: •  Worked well with laterolog •  Low invasion mud used

Verification Well: •  Different mud used and use of

laterolog failed •  Use of induction logs improved the

match, but under-predicted high permeability values

Geologic Characterization: Net Thickness

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Porosity

Dep

th (f

t)

8% 12%10% 14%

Gross and Net Thickness:

Porosity Cutoffs

What fraction of the gross

thickness of the Mt. Simon has storage and injectivity?

CCS #1

Geologic Characterization: Gross and Net Thickness

0 8 10 12 14 Gross Injection Well Net Thickness 1505 ft 1322 ft 1009 ft 744 ft 569 ft Gross Verification Well Net Thickness

1476 ft 1344 ft 1064 ft 782.5 ft 578 ft

Porosity Cutoff, %

Geologic Model: Objectives

n  Integrate petrophysical characteristics and conceptual geologic model

n  Approximate the geologic architecture for gridded reservoir simulation models

n  Develop multiple models based on reasonable geologic and petrophysical interpretations

Geologic Model: Monte Carlo Method

n  Random generation of petrophysical properties using probability functions

n  Generate numerous models quickly, but with little regard to geologic architecture

Geologic Model: Architecture and Facies

Both systems have same proportion of high permeability facies

Structured System: black are connected across model edges

Random System: black not connected across model edges

Higher Permeability Facies

Lower Permeability Facies Guin and Ritzi, 2008, Geophys. Res. Ltrs., (L10402)

Geologic Model: Petrophysical Properties Linked to Facies

n  Geostatistics well established for modeling facies’ geometry for specific geologic environments

n  Important to populate the geostatistically generated facies with petrophysical properties

Geologic Model: Plurigaussian Simulation

n  Grain size (m) used as a proxy for facies n  Maintains hierarchical relationships

between facies

Coarse: 38.3% Coarse-Medium: 6% Medium: 6.5% Medium-Fine: 6.1% Fine: 43.2%

Geologic Model: Plurigaussian Simulation

Next facies models n  geophysics and geologist

interpretation to build true facies model

n  Mt. Simon outcrop study planned to improve facies interpretation

Facies (grain size) model

Reservoir Model

n  Gridding n  Calibration n  Simulations

n  Plume management n  Pressure management

Reservoir Model: Vertical Gridding 5500

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Porosity

Dept

h (ft

)

CoarseMediumFineUltra Fine

Model # of Layers

hlayer

ft Coarse 6 250 Medium 28 53

Fine 108 15* Ultra Fine

322 5

n  Grid Selection: n  Honor geologic

architecture and facies

n  Understand geologic features influencing flow

n  Select grid to model these features

n  Grids chosen for computational reasons: for general guidance only

* 2-10 ft layers at injection zone

Reservoir Model: Gridding

n  Example: n  108 layer model n  Permeability (log10) n  2 miles x 2 miles by

1400-1500 ft n  Granite wash included

Reservoir Model: Pre-CO2 (Water) Calibration

n  CCS#1 Water Injection Pressure Transient Test n  25 ft perforated interval (injection/falloff, step-

rate test) n  25 ft + 30 ft perforated (injection/falloff)

n  Injection spinner logs infer no water injection into upper perfs

Reservoir Model: Water Pressure Transient Test

n  kh 185 md n  kv 2.45 md n  kv/kh 0.013

(over 75 ft interval)

 

10-­‐3 10-­‐2 10-­‐1 100 101

10-­‐3

10-­‐2

10-­‐1

Delta-­‐T  (hr)

DP  &  DERIVATIVE  (P

SI/S

TB/D)

UNIT  S LP

E NDWBS

S TABIL

S PHE R E

PPNS TB

2009/10/01-­‐2229  :  O IL

  Par t i a l   Penet r a t i on   Wel l

  wel l .   s t or age     =   . 205E-­‐ 02   BBL S / PS I   S k i n( mec h. )         =   -­‐ 1. 0738   S k i n( Gl oba l )       =   10. 499   per meabi l i t y       =   170. 87   MD   Per m-­‐ Thi c knes s   =   12815.   MD-­‐ FEET   Kv / Kh                     =   . 548E-­‐ 02   Ef f .   Thi c knes s   =   81. 402   F EET   P-­‐ ex t r ap.             =   3108. 30   PS I   R( i nv )   a t   26. 47   hr   =   908.   F EET   Smoot hi ng   Coef   =   0. 10, 0.

Type-­‐ Cur v e   Model   S t a t i c -­‐ Dat aPer f .   I nt er v a l   =   25. 0   F EET

S t at i c -­‐ Dat a   and   Cons t ant sVol ume-­‐ Fac t or     =   1. 000   v ol / v olThi c knes s             =   75. 00   F EETVi s c os i t y             =   1. 300   CPTot a l   Compr es s   =   . 1800E-­‐ 04   1/ PS IRat e                       =   -­‐ 6100.   S TB/ DS t or i v i t y             =   0. 0003240   FEET/ PS IDi f f us i v i t y         =   8023.   F EET^2/ HRGauge   Dept h         =   N/ A   F EETPer f .   Dept h         =   N/ A   F EETDat um   Dept h         =   N/ A   FEETAna l y s i s -­‐ Dat a     I D:   GAU001Bas ed   on   Gauge   I D:   GAU002PFA   S t ar t s :   2009-­‐ 09-­‐ 24   19: 04: 38PFA   Ends     :   2009-­‐ 10-­‐ 06   02: 29: 04

Partial Penetration/Completion Model

Comparison of Water PTA and Transformed Permeability

n  kh estimated every 0.5 ft

n  kv/kh of 0.85 used every 0.5 ft for kv

n  Harmonic average (series flow) used to calculate kv over 75 ft interval.

Log/ Core PTA

kh, md 182 185

kv, md 2.43 2.45

h, ft 78 75

Reservoir Simulation Pilot Design Applications

Plume Management n  Location of verification

well n  UIC permit specifications

Pressure Management n  Equipment and hardware

n  Injection equipment selection (centrifugal pump)

n  Maximum pressure ratings (valves and gauges)

Plume and Pressure Management n  Injection wellbore

n  Perforation interval selection n  Location of the packer in the injection

well

Reservoir Simulation: Plume Management Example

Single Perforated Interval: Year 1 Upper Perforated Interval: Year 2

Reservoir Simulation: Pressure Management Example

n  Bottomhole injection pressure compared to fracture pressure

n  Pore pressure below caprock and intermediate seals compared to capillary entry pressure

n  Far-field pressure and “regulated” area of review and pressure thresholds

Conclusions

n  Unique method used to transform core permeability to well log porosity

n  Realistic geologic model based on facies and architecture n  facies model populated with petrophysical

properties n  Water injection validated geologic model of

injection zone n  good agreement between core, logs and PTA

Conclusions, contd.

n  Model development n  Objective and data driven n  Not model driven

n  Model limitations and applications n  Geologic and petrophysical uncertainty n  Specific models not appropriate for all tasks

n  Realistic expectations of reservoir models

Geologic and Reservoir Characterization and Modeling

Scott M. Frailey and James Damico Illinois State Geological Survey

Midwest Geologic Sequestration Science Conference November 8th, 2011