Pore-scale studies of unconventional reservoir rocks H23F ......Dmitriy Silin, Jonathan...
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Pc [kPa] 0.20 0.15 0.10 118 117 116 115 114 113 112 111 110 Pore-scale studies of unconventional reservoir rocks Dmitriy Silin, Jonathan Ajo-Franklin, Stefano Cabrini, Timothy Kneafsey, Alastair MacDowell, Peter Nico, and Liviu Tomutsa Lawrence Berkeley National Laboratory Abstract Motivation Pore space geometry Conclusions Acknowledgments References Our overall objective is development of a technique for predicting reservoir behavior from the pore structure of low-permeability rock. Our approach is based on acquiring micro and nanometer-scale images of the pore structure of natural rocks using synchrotron X-ray computed microtomography (CT) at the Advanced Light Source and Focused Ion Beam (FIB) milling at the Molecular Foundry at Lawrence Berkeley National Laboratory. These techniques provide three dimensional images of the rich diversity of pore structures present in so called “unconventional resources.” Using these images as input data, Maximal Inscribed Spheres simulations are used to evaluate the two-phase flow properties of the rock. The project is supported by the Research Partnership to Secure Energy for America (RPSEA) Unconventional Resources Program. The reservoir samples have been provided by industrial partners: BP, Chevron, Schlumberger, and the Gas Technology Institute This work has been performed at Lawrence Berkeley National Laboratory of the U.S. Department of Energy operated by the University of California under Contract No. DE-AC03-76SF00098. Methods Gas shale and tight sands are examples of low-permeability formations containing enormous quantities of natural gas. As the availability of energy resources in conventional reservoirs is declining, the importance of these unconventional reservoirs is increasing. Unconventional production is the largest source of U.S. natural gas supply // U.S. EIA Annual Energy Outlook 2009 with Projections to 2030 U.S. estimated shale, tight sand, and CBM gas resources: over 8,000 Tcf // Holditch S.A.: SPE 103356 U.S. gas consumption: 22 Tcf / year // U.S. EIA X-ray microtomography (ALS) Focused ion beam (FIB) P c =p nw – p w = 2σ/r Gas Gas Brine Brine Maximal Inscribed Spheres (MIS) • Micron-scale voxel size • Large imaging area • High contrast • Nanometer-scale voxel size • Sequential milling and imaging • Capillary equilibrium • Fluid distribution • Capillary pressure curve • Porosimetry 1 mm Conventional (Frio) sandstone (ALS) 1 mm Tight sand (ALS) Gas shale (FIB/SEM) Voxel size = 14.6 nm 1 μm H23F-1018 3D reconstruction ≈100 micron Tight sand: zooming into the pores Shale Tight sand Water Gas Brine Loss of gas phase connectivity Local heterogeneity: Tight sand permeability 0 10 20 30 40 50 60 70 0 0.2 0.4 0.6 0.8 1 S P c variation within a core 0.0001 0.001 0.01 0.1 1 10 0.01 0.1 1 Permeability Porosity Local heterogeneity: Dense inclusions in shale Slippage: Pc variation with respect to the threshold ? Nanometer-scale porosity (FIB/SEM) Analysis Pressure and velocity distributions in the pores 1. Tomutsa, L., Silin, D., and Radmilovic, V. Nanometer-Scale Imaging and Pore-Scale Fluid Flow Modeling in Chalk, SPE Reservoir Evaluation and Engineering Journal, 2007, June, v. 10, 3, p. 285-293 2. Silin, D. B., and Patzek, T. W. Pore space morphology analysis using maximal inscribed spheres. Physica A, 371:336–360, 2006 Unconventional reservoir rocks is an umbrella term covering a rich variety of porous media. Each rock has features making it different from the others. X-ray micro-CT along with nanometer-scale FIB imaging characterize 3D pore space geometry. Flow and fluid distribution simulations on real pore space geometry may offer a viable alternative to core experiments, which are difficult and time-consuming due to the extremely low permeability of the rock. Uncertainties of the approach: Small sampling volume (scale up); Limited resolution; Binary data segmentation. MIS computations are efficient, robust with respect to the uncertainties of segmentation. Predictive capabilities are limited by sub-resolution-scale uncertainties. The model assumes capillary equilibrium and is sensitive to binary data noise. Finite-difference flow simulations can handle a variety of boundary conditions. Problem decoupling and distributed computations can reduce the computer power requirements and improve efficiency. 1.7 mm 1.6 mm Porosity
Transcript of Pore-scale studies of unconventional reservoir rocks H23F ......Dmitriy Silin, Jonathan...
Pc
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Pore-scale studies of unconventional reservoir rocksDmitriy Silin, Jonathan Ajo-Franklin, Stefano Cabrini, Timothy Kneafsey, Alastair MacDowell, Peter Nico, and Liviu Tomutsa
Lawrence Berkeley National Laboratory
Abstract
Motivation
Pore space geometry
Conclusions
Acknowledgments
References
Our overall objective is development of a technique for predicting reservoir behavior from the pore structure of low-permeability rock. Our approach is based on acquiring micro and nanometer-scale images of the pore structure of natural rocks using synchrotron X-ray computed microtomography (CT) at the Advanced Light Source and Focused Ion Beam (FIB) milling at the Molecular Foundry at Lawrence Berkeley National Laboratory. These techniques provide three dimensional images of the rich diversity of pore structures present in so called “unconventional resources.” Using these images as input data, Maximal Inscribed Spheres simulations are used to evaluate the two-phase flow properties of the rock.
The project is supported by the Research Partnership to Secure Energy for America (RPSEA) Unconventional Resources Program. The reservoirsamples have been provided by industrial partners: BP, Chevron, Schlumberger, and the Gas Technology Institute
This work has been performed at Lawrence Berkeley National Laboratory of the U.S. Department of Energy operated by the University of California under Contract No. DE-AC03-76SF00098.
Methods
Gas shale and tight sands are examples of low-permeability formations containing enormous quantities of natural gas. As the availability of energy resources in conventional reservoirs is declining, the importance of these unconventional reservoirs is increasing.
Unconventional production is the largest source of U.S. natural gas supply // U.S. EIA Annual Energy Outlook 2009 with Projections to 2030
U.S. estimated shale, tight sand, and CBM gas resources: over 8,000 Tcf // Holditch S.A.: SPE 103356
U.S. gas consumption: 22 Tcf / year // U.S. EIA
X-ray microtomography (ALS)
Focused ion beam (FIB)
Pc =pnw – pw = 2σ/r
GasGas
BrineBrine
Maximal Inscribed Spheres (MIS)
• Micron-scale voxel size
• Large imaging area
• High contrast
• Nanometer-scale voxel size
• Sequential milling and imaging
• Capillary equilibrium
• Fluid distribution
• Capillary pressure curve
• Porosimetry
1 mm
Conventional (Frio) sandstone (ALS)
1 mm
Tight sand (ALS)
Gas shale (FIB/SEM)
Voxel size = 14.6 nm1 µm
H23F-1018
3D reconstruction
≈100 micron
Tight sand: zooming into the pores
ShaleTight sand
WaterGas Brine
Loss of gas phase connectivity
Local heterogeneity:
Tight sand permeability
0
10
20
30
40
50
60
70
0 0.2 0.4 0.6 0.8 1
SPc variation within a core
0.0001
0.001
0.01
0.1
1
10
0.01 0.1 1
Per
mea
bilit
y
PorosityLocal heterogeneity:
Dense inclusions in shale
Slippage:
Pc variation with respect to the threshold
?
Nanometer-scale porosity (FIB/SEM)
Analysis
Pressure and velocity distributions in the pores
1. Tomutsa, L., Silin, D., and Radmilovic, V. Nanometer-Scale Imaging and Pore-Scale Fluid Flow Modeling in Chalk, SPE Reservoir Evaluation and Engineering Journal, 2007, June, v. 10, 3, p. 285-293
2. Silin, D. B., and Patzek, T. W. Pore space morphology analysis using maximal inscribed spheres. Physica A, 371:336–360, 2006
Unconventional reservoir rocks is an umbrella term covering a rich variety of porous media. Each rock has features making it different from the others. X-ray micro-CT along with nanometer-scale FIB imaging characterize 3D pore space geometry. Flow and fluid distribution simulations on real pore space geometry may offer a viable alternative to core experiments, which are difficult and time-consuming due to the extremely low permeability of the rock.
Uncertainties of the approach: Small sampling volume (scale up); Limited resolution; Binary data segmentation.
MIS computations are efficient, robust with respect to the uncertainties of segmentation. Predictive capabilities are limited by sub-resolution-scale uncertainties. The model assumes capillary equilibrium and is sensitive to binary data noise.
Finite-difference flow simulations can handle a variety of boundary conditions. Problem decoupling and distributed computations can reduce the computer power requirements and improve efficiency.
1.7 mm1.6 mm
Por
osity
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