CN108729908A - A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method - Google Patents
A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method Download PDFInfo
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Abstract
The oily flow simulating of densification and Permeability Prediction method that the present invention relates to a kind of based on pore network model, including steps are as follows：(1) compact rock core is scanned, obtains two-dimentional electron microscopic picture, obtain porous media interstitial space geological information：(2) reconstructed number rock core obtains the geometric data file of digital cores；(3) pore network model for extracting digital cores, obtains compact rock core pore network model data file；(4) volume flow at pressure and each pore throat at each hole is obtained, to obtain mobility status of the fluid in nanoscale pore network model；(5) the fluid volume flow Q for obtaining pore network model outlet end, the apparent permeability of pore network model is calculated according to Darcy's law.The pore network model that the present invention completely newly develops, which overcomes traditional pore network model, can not consider the characteristics such as boundary slip and the variation of fluid effective viscosity when fluid flows in nanoaperture.
Description
Technical field
The oily flow simulating of densification and Permeability Prediction method that the present invention relates to a kind of based on pore network model, belong to oil
The technical field of gas field development engineering numerical simulation.
Background technology
With the rapid development of various microtechnics (scanning electron microscope, CT etc.) and computer technology, foundation and reservoir rock
The preferable model of the internal feature goodness of fit, and using method for numerical simulation come Study of Fluid in porous media flow into order to
It may.Pore network model is the effective ways that fluid flows in microcosmic point research porous media, is to simulate fluid in rock core
Internal flowing provides important research platform.Compared to physics core experiment, and experiment low, easy to operate with experimental cost
Period short advantage.Compared to digital cores, pore network model has the characteristics that computational efficiency is high, hole only conduct when calculating
The storage space of fluid and not as the flowing space, the flowing in pore throat is directly calculated according to existing flow formula without mould
Quasi- specific flowing details.
Pore network model is replaced (such as round, arbitrary triangle or square pillar body) using simple solid
Hole in rock core and venturi, the spatial network formed with them represent the complicated interstitial space of rock.It much grinds at present
Study carefully and is proved the flowing that pore network model under specific circumstances can be with quantitative forecast fluid in porous media.But on condition that hole
Gap network model physically must really reflect the pore structure of their representative rocks, and the first flow equation of input
(pore throat conductivity equation) must be able to correctly describe flowing of the fluid in each pore throat.
There are the other hole of a large amount of hundred nano-scales, this makes hole wall and fluid for the one big i.e. reservoir of mark of fine and close oil
The interaction of molecule is more important than conventional reservoir.Many experiments show that the fluid flowing law in nanochannel deviates significantly from
Macroscopical flow equation, as the flow of the water in nanometer pipe is significantly higher than the volume flow that Hagen-Poiseuille equations are predicted
Amount.Nanoscale fluid flow with two significant differences of macroscopic fluid flow be velocity-slip on solid-liquid interface and by
The variation of fluid effective viscosity caused by the presence of boundary layer, simulation fluid is in compact reservoir nanoscale pore network
When flowing, then also need to consider diversified pore throat shape.
Traditional pore network model is when calculating the conductivity that fluid flows at pore throat, using finite element method
The N-S equations of no slip boundary condition obtain the fluid flow of single tube, to obtain conductivity (Xiucai's Zhao numbers at pore throat
Rock core and pore network model reconstructing method study [D]), there is no the characteristics of fluid flows in nanochannel is considered, rely on
Its pore network model developed can not flowing of the accurate description fluid in nanoporous medium.
Invention content
The oily flow simulating of densification and Permeability Prediction method that the present invention provides a kind of based on pore network model, overcome
Traditional pore network model can not consider boundary slip and the variation of fluid effective viscosity etc. when fluid flows in nanoaperture
Characteristic；
The present invention gives the single tube of different cross section shape in nanoscale item by computational fluid dynamics modeling analysis
Conductivity calculation formula under part, it is contemplated that fluid is in the velocity-slip of solid liquid interface and the variation of fluid effective viscosity.And
It is applied to pore network modeling analysis.
Term is explained：
1, conductivity：When fluid is along Capillary Flow, the volume flow under unit pressure gradient.
2, form factor：To characterize the cross sectional shape of hole and venturi in pore network model, expression formula is：
In formula, P is perimeter of section, and A is sectional area.
3, slip length：The extrapolation length when tangential component of velocity vector is 0 is characterization longitudinal slip effect to fluid in pipe
One measurement of flow effect, uses LsIt indicates.
4, dimensionless slip length：The ratio of slip length and 1/2 power of cross-sectional area, expression formula are：
The technical scheme is that：
A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method, including steps are as follows：
(1) compact rock core is scanned by scanning electron microscope, obtains two-dimentional electron microscopic picture, it is several to obtain porous media interstitial space
What information：Porous media interstitial space geological information includes pore constriction shape, size and its connection relation；
(2) it is based on the two-dimentional electron microscopic picture that step (1) obtains, using Markov chain-Monte Carlo method (MCMC) numerical value
Reconstructed number rock core obtains the geometric data file of digital cores；The geometric data file includes each pixel
Point and the corresponding geometry of the pixel, geometry include rock core hole and rock matrix；For example, the geometry number
0 and 1 are corresponded to respectively according to each pixel in file, and 0 indicates that current pixel point is interstitial space, and 1 expression current pixel point is
Rock matrix.The digital cores reconfiguration technique bibliography of wherein Markov chain-Monte Carlo method (MCMC) is：Wu K,
Dijke MIJV,Couples G D,et al.3D Stochastic Modelling of Heterogeneous Porous
Media–Applications to Reservoir Rocks[J].Transport in Porous Media,2006,65
(3):443-467.
(3) using the pore network model of maximum ball extraction step (2) described digital cores, compact rock core hole is obtained
Network model data file；The pore network model data file includes pore constriction shape factor of cross-section, pore constriction half
Diameter, pore constriction length, pore constriction position, pore constriction connection relation and pore throat average coordination number；Wherein, the biggest ball
The bibliography of algorithm is：Wang Chen morning carbonate rock medium basis of dual porosity network models structure theory and the Qingdao method [D]:China
Petroleum Univ. (East China), the 2nd chapter content of 2013. doctoral thesis；
(4) incompressible fluid must then be expired by carrying out the conservation of mass for each hole in pore network model
Sufficient volume conservation, as shown in formula (I)：
In formula (I), i, j refer to two holes of arbitrary neighborhood in pore network model；qijIt is by its interconnection
Throat flows into the volume flow of hole i, P from adjacent pores jiIt is the pressure in hole i, gijIt is connection hole i and hole j throat
Hydraulic conductivity；PjIt is the pressure in hole j；
Equation group is solved to obtain volume flow at pressure and each pore throat at each hole, is existed to obtain fluid
Mobility status in nanoscale pore network model；As shown in Fig. 2, LsFor slip length.
(5) the fluid volume flow Q for obtaining pore network model outlet end calculates pore network model according to Darcy's law
Apparent permeability.
According to currently preferred, in the step (4), the hydraulic conductivity g of hole i and hole j throat are connectedijPass through
Computational fluid dynamics modeling analysis obtains, and the velocity-slip on solid-liquid boundary is considered in modeling process and due to boundary layer
Presence caused by fluid effective viscosity variation, shown in calculation formula such as formula (II)：
In formula (II), A is cross-sectional area, and μ is fluid bulk viscosity；G is form factor, and k is interfacial layer thickness, P
For throatpiston perimeter, LsdFor nondimensional slip length, h is viscosity coefficient, it is boundary layer fluid viscosity and macrofluid
The ratio of viscosity；A, b, c, d, e, f are the empiricals that fitting data obtains, as G >=0.04, a=-0.16, b=0.12, c
=6.4, d=-0.0055, e=-50, f=1.7 work as G<When 0.04, a=-0.012, b=0.057, c=2, d=-0.0052,
E=-38, f=3.2.
According to currently preferred, the step (5), the apparent infiltration of pore network model is calculated according to Darcy's law
Rate；Shown in calculation formula such as formula (III)：
In formula (III), K is pore network model apparent permeability, and μ is fluid bulk viscosity, and L is model length, and A is stream
Dynamic area of section, △ P are flow differential pressures.
Beneficial effects of the present invention are：
1, the conductivity calculation formula that The present invention gives the single tubes of different cross section shape under the conditions of nanoscale considers
The shadow of the velocity-slip on solid-liquid boundary and the fluid effective viscosity variation fluid flow caused by the presence of boundary layer
It rings, and the conductivity calculation formula is used for pore network modeling analysis.The pore network model completely newly developed overcomes tradition
Pore network model can not consider the characteristics such as boundary slip and the variation of fluid effective viscosity when fluid flows in nanoaperture.
2, the pore network model that the present invention is established, which has evolved to, can simulate single-phase Newtonian fluid in tight rock
Flowing and Permeability Prediction, the apparent permeability predicted consider liquid longitudinal slip effect and fluid effective viscosity variation
It influences, more accurately describes flowing of the liquid in nanoporous medium.
Description of the drawings
Fig. 1 is the flow chart element the present invention is based on the oily flow simulating of the densification of pore network model and Permeability Prediction method
Figure；
Fig. 2 is that comparative example does not consider that fluid considers fluid in nanoscale flow in nanoscale flow characteristic, embodiment
The comparison diagram for the single-phase Newtonian fluid flow effect in nanochannel of simulation that characteristic obtains respectively；
The velocity field contrast schematic diagram that Fig. 3 is comparative example, embodiment flows in nanochannel.
Fig. 4 is permeability required by the pore network model of embodiment foundation and permeability contrast schematic diagram required by comparative example.
Specific implementation mode
The present invention is further qualified with embodiment with reference to the accompanying drawings of the specification, but not limited to this.
Embodiment
A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method, as shown in Figure 1, being applied to
Monophasic fluid flowing in the fine and close rock of simulation and Permeability Prediction, simulation original state are set as being saturated in pore network model
Then water sets periodic pressure boundary condition in X-direction, Y and Z-direction are without flow boundary, including steps are as follows：
(1) compact rock core is scanned by scanning electron microscope, obtains two-dimentional electron microscopic picture, it is several to obtain porous media interstitial space
What information：Porous media interstitial space geological information includes pore constriction shape, size and its connection relation；
(2) it is based on the two-dimentional electron microscopic picture that step (1) obtains, using Markov chain-Monte Carlo method (MCMC) numerical value
Reconstructed number rock core obtains the geometric data file of digital cores；The geometric data file includes each pixel
Point and the corresponding geometry of the pixel, geometry include rock core hole and rock matrix；For example, the geometry number
Include that each pixel corresponds to 0 and 1 respectively according to file, 0 indicates that current pixel point is interstitial space, and 1 indicates current pixel point
For rock matrix.The digital cores reconfiguration technique bibliography of wherein Markov chain-Monte Carlo method (MCMC) is：Wu K,
Dijke MIJV,Couples G D,et al.3D Stochastic Modelling of Heterogeneous Porous
Media–Applications to Reservoir Rocks[J].Transport in Porous Media,2006,65
(3):443-467.
(3) using the pore network model of maximum ball extraction step (2) described digital cores, compact rock core hole is obtained
Network model data file；The pore network model data file includes pore constriction shape factor of cross-section, pore constriction half
Diameter, pore constriction length, pore constriction position, pore constriction connection relation and pore throat average coordination number；Wherein, the biggest ball
The bibliography of algorithm is：Wang Chen morning carbonate rock medium basis of dual porosity network models structure theory and the Qingdao method [D]:China
Petroleum Univ. (East China), the 2nd chapter content of 2013. doctoral thesis；
(4) incompressible fluid must then be expired by carrying out the conservation of mass for each hole in pore network model
Sufficient volume conservation, as shown in formula (I)：
In formula (I), i, j refer to two holes of arbitrary neighborhood in pore network model；qijIt is by its interconnection
Throat flows into the volume flow of hole i, P from adjacent pores jiIt is the pressure in hole i, gijIt is connection hole i and hole j throat
Hydraulic conductivity；PjIt is the pressure in hole j.
Equation group is solved to obtain the pressure of each hole and the volume flow of each pore throat, is being received to obtain fluid
Mobility status in meter level pore network model；As shown in Fig. 2, b is that the single-phase Newtonian fluid of simulation that embodiment obtains exists in Fig. 2
The effect diagram of stream in nanometer porous medium；LsFor slip length.As shown in figure 3, b is that the present embodiment is being received in Fig. 3
The velocity field schematic diagram flowed in rice grain pattern road；
(5) fluid volume flow for obtaining pore network model outlet end calculates pore network model according to Darcy's law
Apparent permeability.Shown in calculation formula such as formula (III)：
In formula (III), K is pore network model apparent permeability, and μ is fluid bulk viscosity, and L is model length, and A is stream
Dynamic area of section, △ P are flow differential pressures.
In step (4), the hydraulic conductivity g of hole i and hole j throat are connectedijPass through computational fluid dynamics modeling point
Analysis obtains, and the velocity-slip and the fluid caused by the presence of boundary layer that solid-liquid boundary is considered in modeling process have
The variation of viscosity is imitated, shown in calculation formula such as formula (II)：
In formula (II), A is cross-sectional area, and μ is fluid bulk viscosity；G is form factor, and k is critical thickness, and P is
Throatpiston perimeter, LsdFor nondimensional slip length, h is viscosity coefficient, it is that boundary layer fluid viscosity and macrofluid are viscous
The ratio of degree；A, b, c, d, e, f are the empiricals that fitting data obtains, as G >=0.04, a=-0.16, b=0.12, c=
6.4, d=-0.0055, e=-50, f=1.7 work as G<When 0.04, a=-0.012, b=0.057, c=2, d=-0.0052, e
=-38, f=3.2.
Comparative example
The oily flow simulating of a kind of densification based on pore network model according to embodiment and Permeability Prediction method,
Its difference lies in,
Connection hole i and the hydraulic conductivity of hole j throat are：
Circular capillaries hydraulic conductivity is sought shown in formula such as formula (IV)：
Square capillary hydraulic conductivity is sought shown in formula such as formula (V)：
Triangular capillary hydraulic conductivity is sought shown in formula such as formula (VI)：
As shown in Fig. 2, a is that comparative example does not consider that the simulation that fluid is obtained in nanoscale flow characteristic is single-phase in Fig. 2
The effect diagram of stream of the Newtonian fluid in nanometer porous medium；Flow rate of liquid is 0 at solid liquid interface.
As shown in figure 3, a is the velocity field schematic diagram that this comparative example flows in nanochannel in Fig. 3；Other conditions are homogeneous
Together, only in the case of slip boundary condition difference, the single tube flow of comparative example is about the 1/2 of embodiment flow.
It the characteristics of when above-mentioned capillary conductivity does not consider fluid in nanoscale flow when calculating, that is, does not account for
The influence of boundary slip and fluid effective viscosity to flowing.Therefore the pore network model of its exploitation is relied on to be unable to Accurate Prediction nanometer
The permeability of porous media (such as fine and close oily reservoir).
Attached drawing 4 compared the difference of permeability and permeability required by comparative example required by the pore network model of embodiment foundation
It is different, and illustrate the influence of boundary slip and the variation of fluid effective viscosity to the apparent permeability of nanoporous medium.Comparative example
The apparent permeability of the pore network model of gained is the comparison basis for normalizing permeability.Comparison is found, more under sliding condition
The apparent permeability of hole medium is far above the apparent permeability under non-slip condition.And under sliding condition, the presence of boundary layer
The variation of caused fluid effective viscosity will make a significant impact the apparent permeability of porous media.Boundary slip is fine and close
The main reason for porous media (nanometer porous medium) permeability is higher than Darcy's law predicted permeability.
Claims (6)
1. a kind of oily flow simulating of densification based on pore network model and Permeability Prediction method, which is characterized in that including step
It is rapid as follows：
(1) compact rock core is scanned, obtains two-dimentional electron microscopic picture, obtain porous media interstitial space geological information：Porous media
Interstitial space geological information includes pore constriction shape, size and its connection relation；
(2) it is based on the two-dimentional electron microscopic picture that step (1) obtains, digital reconstruction digital cores obtain the geometry of digital cores
Data file；The geometric data file includes each pixel and the corresponding geometry of the pixel, geometry
Including rock core hole and rock matrix；
(3) pore network model of extraction step (2) described digital cores obtains compact rock core pore network model data text
Part；The pore network model data file includes that pore constriction shape factor of cross-section, pore constriction radius, pore constriction are long
Degree, pore constriction position, pore constriction connection relation and pore throat average coordination number；
(4) conservation of mass is carried out for each hole in pore network model and body then must satisfy for incompressible fluid
Product conservation, as shown in formula (I)：
In formula (I), i, j refer to two holes of arbitrary neighborhood in pore network model；qijIt is the throat by its interconnection
The volume flow of hole i, P are flowed into from adjacent pores jiIt is the pressure in hole i, gijIt is the water for connecting hole i and hole j throat
Power conductivity；PjIt is the pressure in hole j；
Equation group is solved to obtain the volume flow of pressure and each pore throat at each hole, to obtain fluid in nanometer
Mobility status in grade pore network model；
(5) the fluid volume flow Q for obtaining pore network model outlet end, the table of pore network model is calculated according to Darcy's law
See permeability.
2. a kind of densification oil flow simulating and Permeability Prediction side based on pore network model according to claim 1
Method, which is characterized in that in the step (4), connect the hydraulic conductivity g of hole i and hole j throatijIt is dynamic by calculating fluid
Mechanical modeling is analyzed to obtain, shown in calculation formula such as formula (II)：
In formula (II), A is cross-sectional area, and μ is fluid bulk viscosity；G is form factor, and k is critical thickness, and P is venturi
Perimeter of section, LsdFor nondimensional slip length, h is viscosity coefficient, it is boundary layer fluid viscosity and macrofluid viscosity
Ratio；A, b, c, d, e, f are the empiricals that fitting data obtains, as G >=0.04, a=-0.16, b=0.12, c=6.4,
D=-0.0055, e=-50, f=1.7 work as G<When 0.04, a=-0.012, b=0.057, c=2, d=-0.0052, e=-
38, f=3.2.
3. a kind of densification oil flow simulating and Permeability Prediction based on pore network model according to claim 1 or 2
Method, which is characterized in that the step (5) calculates the apparent permeability of pore network model according to Darcy's law；Calculation formula
As shown in formula (III)：
In formula (III), K is pore network model apparent permeability, and μ is fluid bulk viscosity, and L is model length, and A is that flowing is cut
Face area, △ P are flow differential pressures.
4. a kind of densification oil flow simulating and Permeability Prediction side based on pore network model according to claim 1
Method, which is characterized in that the step (1) scans compact rock core by scanning electron microscope, obtains two-dimentional electron microscopic picture.
5. a kind of densification oil flow simulating and Permeability Prediction side based on pore network model according to claim 1
Method, which is characterized in that the step (2) obtains number using Markov chain-Monte Carlo method digital reconstruction digital cores
The geometric data file of rock core.
6. a kind of densification oil flow simulating and Permeability Prediction side based on pore network model according to claim 1
Method, which is characterized in that using the pore network model of maximum ball extraction step (2) described digital cores, obtain compact rock core
Pore network model data file.
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Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103822865A (en) * | 2014-03-20 | 2014-05-28 | 中国石油大学(华东) | High-resolution three-dimensional digital rock core modeling method |
| CN104573198A (en) * | 2014-12-23 | 2015-04-29 | 长江大学 | Method for reconstructing digital rock core and pore network model based on random fractal theory |
| CN105021506A (en) * | 2015-07-09 | 2015-11-04 | 中国石油大学(华东) | Pore network model-based calculation method of three-phase relative permeability |
| CN105334293A (en) * | 2015-10-19 | 2016-02-17 | 中国石油天然气股份有限公司 | Flow state identification method and device of tight gas in multi mediums |
| CN105510204A (en) * | 2015-12-03 | 2016-04-20 | 大连理工大学 | Permeability predication method based on CT (computed tomography) images |
-
2018
- 2018-05-21 CN CN201810488392.9A patent/CN108729908B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103822865A (en) * | 2014-03-20 | 2014-05-28 | 中国石油大学(华东) | High-resolution three-dimensional digital rock core modeling method |
| CN104573198A (en) * | 2014-12-23 | 2015-04-29 | 长江大学 | Method for reconstructing digital rock core and pore network model based on random fractal theory |
| CN105021506A (en) * | 2015-07-09 | 2015-11-04 | 中国石油大学(华东) | Pore network model-based calculation method of three-phase relative permeability |
| CN105334293A (en) * | 2015-10-19 | 2016-02-17 | 中国石油天然气股份有限公司 | Flow state identification method and device of tight gas in multi mediums |
| CN105510204A (en) * | 2015-12-03 | 2016-04-20 | 大连理工大学 | Permeability predication method based on CT (computed tomography) images |
Non-Patent Citations (5)
| Title |
|---|
| 徐模: "数字岩心及孔隙网络模型的构建方法研究", 《中国优秀硕士学位论文全文数据库 工程科技1辑》 * |
| 戚涛等: "基于逾渗网络模型的弥散系数与渗透率关系研究", 《水动力学研究与进展》 * |
| 杨永飞等: "基于孔隙网络模型的三相相对渗透率模拟计算方法", 《中国科技论文》 * |
| 盛金昌等: "三维数字岩心的重构及孔隙网络模型的孔隙度分析", 《水电能源科学》 * |
| 雷健等: "基于数字岩心和孔隙网络模型的微观渗流模拟研究进展", 《地球物理学进展》 * |
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