Organic and Inorganic Pore Structure Analysis in Shale Rocks with Superposition Method
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Transcript of Organic and Inorganic Pore Structure Analysis in Shale Rocks with Superposition Method
RESERVOIR SIMULATION GROUPSlide 1
Organic and Inorganic Pore Structure Analysis in Shale Rocks with Superposition
MethodDr. Chenchen Wang
Prof. Zhangxing (John) Chen
University of Calgary
06/14/2014
RESERVOIR SIMULATION GROUPSlide 2
Results and Discussions
Methodology
1
2
3
4 Conclusions
5 Future Research
Introduction
Outline
RESERVOIR SIMULATION GROUPSlide 3
1. Introduction
Typical shale matrix SEM image with organic and inorganic pores
Shale rocks are inherently heterogeneous and the shale matrix pores can
be divided into organic and inorganic pores. The organic and inorganic
pores are distributed with each other in the shale matrix.
Shale matrix(Organic pores + few inorganic pores)Organic matter: 3%-15%
Inorganic matter(Inorganic pores)
RESERVOIR SIMULATION GROUPSlide 4
1. Introduction
While the organic pores and inorganic pores in shale rocks are at different scales,
and the transport mechanisms of shale gas in organic and inorganic pores are
different, it is necessary to describe the nanoscopic organic and inorganic pore
characteristics of shale rocks with a method, such as superposition, based on a
digital rock analysis technology.
Different Scale Resolution Images Digital Rock Analysis Technology
RESERVOIR SIMULATION GROUPSlide 5
Results and Discussions
Methodology
1
2
3
4 Conclusions
5 Future Research
Introduction
Outline
RESERVOIR SIMULATION GROUPSlide 6
2. Methodology
2.1 Image analysis and 3D digital rock reconstruction
Low resolution inorganic pore image High resolution organic pore image
SEM images
Binary images
Inorganic pore binary image Organic pore binary image0: skeleton (white)1: pore (black)
Resolution: 25nm Resolution: 5nm
RESERVOIR SIMULATION GROUPSlide 7
2. Methodology
Markov Chain Monte Carlo (MCMC) Method
Inorganic pore digital rock216×216×216
Organic pore digital rock500×500×500
2.1 Image analysis and 3D digital rock reconstruction
xy
yz
xz
RESERVOIR SIMULATION GROUPSlide 8
2. Methodology
2.2 Shale matrix digital rock superposition method
1 2 1 2
1 2
1 2
1 2
skeleton skeleton skeleton
organic pore skeleton pore
inorganic pore pore skeleton
inorganic pore pore pore
Superposition algorithm:
Step 1. Superposition of representative shale organic matter digital rocks
Ω: shale organic matter digital rockΩ1: inorganic pore digital rockΩ2: organic pore digital rock
The sectional inorganic pore digital rock100×100×100
The sectional inorganic pore digital rock500×500×500
Inorganic pore digital rock216×216×216
RESERVOIR SIMULATION GROUPSlide 9
2. Methodology
2.2 Shale matrix digital rock superposition method
Step 1. Superposition of representative shale organic matter digital rocks
The sectional inorganic pore digital rock500×500×500
Representative shale organic matter digital rock
500×500×500
Organic pore digital rock500×500×500
RESERVOIR SIMULATION GROUPSlide 10
2. Methodology
2.2 Shale matrix digital rock superposition method
Step 2. Integration of representative shale matrix digital rocks
The remaining inorganic pore digital rock
Representative shale organic matter digital rock
Representative shale matrix digital rock
RESERVOIR SIMULATION GROUPSlide 11
Results and Discussions
Methodology
1
2
3
4 Conclusions
5 Future Research
Introduction
Outline
RESERVOIR SIMULATION GROUPSlide 12
3. Results and Discussions
Organic pore digital rock Representative shale matrix digital rockInorganic pore digital rock
RESERVOIR SIMULATION GROUPSlide 13
Inorganic Pore Digital Rock
Organic Pore Digital Rock
Shale Matrix Digital Rock
Rock Size 5.4μm×5.4μm×5.4μm 2.5μm×2.5μm×2.5μm 5.4μm×5.4μm×5.4μm
Pores Number 5,158 92,226 96,541
Throats Number 7,182 154,848 160,096
Average Connection Number 2.7644 3.34573 3.99445
Net Porosity 0.0783 0.192 0.102
Absolute Permeability (nD) 19.6 135 61.2
3. Results and Discussions
RESERVOIR SIMULATION GROUPSlide 14
The representative shale matrix digital rock with the superposition method has a
bimodal pore volume distribution; the first mode reflects the inorganic pores with
relatively larger pore sizes, while the second mode reflects the organic pores with
relatively smaller pore sizes.
Pore size distribution Pore size volume distribution
3. Results and Discussions
RESERVOIR SIMULATION GROUPSlide 15
3. Results and Discussions
RESERVOIR SIMULATION GROUPSlide 16
Results and Discussions
Methodology
1
2
3
4 Conclusions
5 Future Research
Introduction
Outline
RESERVOIR SIMULATION GROUPSlide 17
4. Conclusions
(1) A two-step superposition method is introduced to construct the
representative shale matrix digital rock, and a comparison of the pore structure
properties among the three digital rocks shows that the superposition shale
matrix digital rock can characterize the inorganic pore and organic pore
properties simultaneously.
(2) This method provides a research platform for the study of different pore
structure characteristics in shale rocks, and it can also be used as input for the
nanoscopic flow simulation in pores with different wettability.
RESERVOIR SIMULATION GROUPSlide 18
Results and Discussions
Methodology
1
2
3
4 Conclusions
5 Future Research
Introduction
Outline
RESERVOIR SIMULATION GROUPSlide 19
5. Future Research
5.1 Wettability Analysis
Organic Pore: Oil-wetInorganic Pore: Water-wet
RESERVOIR SIMULATION GROUPSlide 20
5. Future Research
5.2 Fracture Description
Aperture
Regular Fracture-Digital Rock
Number DipOccurrence
Orientation
RESERVOIR SIMULATION GROUPSlide 21
5. Future Research
5.2 Fracture Description Regular Fracture-Pore Network
RESERVOIR SIMULATION GROUPSlide 22
Sponsors