CN105510204A - Permeability predication method based on CT (computed tomography) images - Google Patents
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- 230000035699 permeability Effects 0.000 title claims abstract description 60
- 238000000034 method Methods 0.000 title claims abstract description 23
- 238000002591 computed tomography Methods 0.000 title claims abstract description 11
- 239000011435 rock Substances 0.000 claims abstract description 36
- 238000004088 simulation Methods 0.000 claims abstract description 11
- 239000011148 porous material Substances 0.000 claims abstract description 7
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004422 calculation algorithm Methods 0.000 claims description 6
- 239000011159 matrix material Substances 0.000 claims description 3
- 238000009877 rendering Methods 0.000 claims description 3
- 238000005259 measurement Methods 0.000 abstract description 6
- 239000007787 solid Substances 0.000 abstract description 4
- 230000000704 physical effect Effects 0.000 abstract description 3
- 238000000691 measurement method Methods 0.000 abstract 2
- 239000003208 petroleum Substances 0.000 abstract 1
- 239000012530 fluid Substances 0.000 description 2
- 238000012360 testing method Methods 0.000 description 2
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N15/00—Investigating characteristics of particles; Investigating permeability, pore-volume or surface-area of porous materials
- G01N15/08—Investigating permeability, pore-volume, or surface area of porous materials
- G01N15/088—Investigating volume, surface area, size or distribution of pores; Porosimetry
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Abstract
The invention belongs to the technical field of petroleum and geological science and provides a permeability predication method based on CT (computed tomography) images. The method comprises steps as follows: CT scanning: an actual rock sample is scanned through industrial x-ray CT, and a digital rock core image of the actual rock sample is obtained and is cut; the digital rock core image is subjected to binarization, and a skeleton and pores of the digital rock core image are obtained; a representative elementary volume of the digital rock core image is determined; seepage simulation: an absolute permeability value and a relative permeability value are predication values of actual rock permeability. According to the permeability predication method, the process is simple, and multiple measurement times of the rock permeability under different geological conditions are easy to realize; by means of the measurement method, the permeability of rock with anisotropy can be accurately predicated; a measurement result can be directly taken as an input parameter of numerical simulation, and the measurement method is applicable to rock permeability predication of any gas-liquid-solid or liquid-liquid-solid three-phase or multi-phase system. The method can also be popularized to predication of other physical properties of rock.
Description
Technical field
The invention belongs to oil, geological sciences technical field, relate to a kind of Permeability Prediction method based on CT image.
Background technology
Porous media flows is the subject matter of the association area researchs such as geological sciences, reservoir engineering and groundwater contamination always.Wherein, rock permeability, as affecting one of most important factor of porous media flows, is the main physical parameter carrying out rock evaluation.Rock permeability comprises absolute permeability and relative permeability, and they directly determine the accumulating ability of rock, fluid flowing law, fluid distrbution and flow stability etc.In addition permeability also can have an impact to other important physical parameter of rock (as capillary force distribution).Therefore, the development of Accurate Prediction rock permeability to association area is significant.
Conventional rock permeability obtains primarily of methods such as earthquake, core analysis, well logging and well testings, but they have following shortcoming: one, measurement result and surveying instrument precision have much relations, and different surveying instruments and measuring method can produce the experimental result of larger difference; Its two, many method of testings also can only be measured for sample, and measuring process is consuming time.Its three, although the large scale measuring method measurement results such as well logging, well testing are accurate, not easy to operate, take time and effort, also cannot evaluate rock microcosmic physical property to the impact of permeability; Its four, for have anisotropic rock permeability survey difficulty.
Summary of the invention
In order to the limitation solving conventional rock permeability survey method is with not enough, the present invention's a kind of Permeability Prediction method based on CT image of proposition, object is absolute permeability value in order to obtain rock fast and accurately and relative permeability value.Measuring method mainly comprises 3 processes: CT scan, and rock Representative Elementary Volume is determined and seepage simulation.
Technical scheme of the present invention is: a kind of Permeability Prediction method based on CT image, comprises the following steps:
1.CT scans
Utilize Industrial X-ray CT to scan actual rock, obtain digital core image and cutting is carried out to image; By digital core image binaryzation, obtain skeleton and the hole of digital core image;
2. determine the Representative Elementary Volume of digital core image
(1) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the factor of porosity of every subvolumes and record; Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the factor of porosity newly obtaining sub-volume, until the factor of porosity relative size of all sub-volume is greater than 95%, recording the volume V1 of now sub-volume; Wherein, the porosity calculation formula of sub-volume is:
(φ represents factor of porosity, sum
porerepresent sub-volume hole pixel sum, sum
grainrepresent sub-volume Skeleton pixel point sum).
(2) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the fractal dimension of every subvolumes and record.Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the fractal dimension newly obtaining sub-volume, until the fractal dimension relative size of all sub-volume is greater than 95%, recording the volume V2 of now sub-volume.Wherein, the fractal dimension of sub-volume can utilize meter box algorithm idea, uses the fractal box algorithm based on 3D rendering to calculate.
(3) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the permeability tensor of every subvolumes and record.Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the permeability tensor newly obtaining sub-volume, until its matrix respective value relative size of the permeability tensor of all sub-volume is all greater than 90%, record the volume V3 of now sub-volume.Wherein, the permeability tensor of sub-volume can, based on generalized Darcy's law and mass-conservation equation, utilize finite element theory to calculate.
(4) compare V1, V2, V3, maximum volume is wherein exactly Representative Elementary Volume.
3. seepage simulation: the Representative Elementary Volume random selecting Representative Elementary Volume from digital core image obtained according to step (4), calculation model of permeability is utilized to carry out flow event numerical simulation (as pore network model to Representative Elementary Volume, CFD model etc.), obtain absolute permeability and the relative permeability of Representative Elementary Volume, absolute permeability value now and relative permeability value just can be used as the predicted value of actual rock permeability.
The invention has the beneficial effects as follows:
1. process is simple, is easy to realize the repetitive measurement of rock permeability under different geological conditions.
2. measuring method can carry out Accurate Prediction to the permeability with anisotropic rock.
3. measurement result can directly as the input parameter of numerical simulation, and measuring method is applicable to any gas-liquid-solid or liquid-liquid-solid three-phase or heterogeneous system rock permeability and predicts.
4. present invention also extends to the prediction of other physical property of rock.
Accompanying drawing explanation
Fig. 1 is the schematic diagram that industrial X-ray CT scan rock obtains digital core image.
Fig. 2 is the schematic flow sheet that Representative Elementary Volume obtains.
In figure: 1 Industrial X-ray CT; 2 actual rock samples; 3 digital core images; 4 sub-volume;
5 computing machines; 6 Representative Elementary Volumes.
Embodiment
The specific embodiment of the present invention is described in detail below in conjunction with technical scheme and accompanying drawing.
Embodiment
CT scan
Utilize Industrial X-ray CT 1 to scan actual rock sample 2, obtain digital core image 3 and cutting is carried out to image; By digital core image 3 binaryzation, obtain skeleton and the hole of digital core image 3.
Representative Elementary Volume is determined
(1) from 1% core volume to digital core image 3 random selecting at least 10 subvolumes 4, utilize computing machine 5 to calculate the factor of porosity of every subvolumes 4 and record.Then progressively synchronously expand every subvolumes 4 with the speed of 2% core volume and record the factor of porosity newly obtaining sub-volume 4, until the factor of porosity relative size of all sub-volume 4 is greater than 95%, recording the volume V1 of now sub-volume 4; Wherein, the porosity calculation formula of sub-volume 4 is:
(φ represents factor of porosity, sum
porerepresent sub-volume hole pixel sum, sum
grainrepresent sub-volume Skeleton pixel point sum).
(2) from 1% core volume to the sub-volume 4 of digital core image 3 random selecting at least 10 1% core volumes, utilize computing machine 5 to calculate the fractal dimension of every subvolumes 4 and record.Then progressively synchronously expand every subvolumes 4 with the speed of 2% core volume and record the fractal dimension newly obtaining sub-volume 4, until the fractal dimension relative size of all sub-volume 4 is greater than 95%, recording the volume V2 of now sub-volume 4.Wherein, the fractal dimension of sub-volume 4 can utilize meter box algorithm idea, uses the fractal box algorithm based on 3D rendering to calculate.
(3) from 1% core volume to the sub-volume 4 of digital core image 3 random selecting at least 10 1% core volumes, utilize computing machine 5 to calculate the permeability tensor of every subvolumes 4 and record.Then progressively synchronously expand every subvolumes 4 with the speed of 2% core volume and record the permeability tensor newly obtaining sub-volume 4, until its matrix respective value relative size of the permeability tensor of all sub-volume 4 is all greater than 90%, record the volume V3 of now sub-volume 4.Wherein, the permeability tensor of sub-volume 4 can, based on generalized Darcy's law and mass-conservation equation, utilize finite element theory to calculate.
(4) compare V1, the size of V2, V3, maximum volume is wherein exactly the size of Representative Elementary Volume 6.
Seepage simulation
According to size random selecting Representative Elementary Volume 6 from digital core image of the Representative Elementary Volume 6 that step (4) obtains, calculation model of permeability is utilized to carry out flow event numerical simulation (as pore network model to Representative Elementary Volume 6, CFD model etc.), obtain absolute permeability and the relative permeability of Representative Elementary Volume 6, absolute permeability value now and relative permeability value just can be used as the predicted value of actual rock sample 2 permeability.
Claims (2)
1., based on a Permeability Prediction method for CT image, it is characterized in that, step is as follows:
(1) CT scan
Utilize Industrial X-ray CT to scan actual rock sample, obtain the digital core image of actual rock sample and cutting is carried out to image; By digital core image binaryzation, obtain skeleton and the hole of digital core image;
(2) Representative Elementary Volume of digital core image is determined
1) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the factor of porosity of every subvolumes and record; Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the factor of porosity newly obtaining sub-volume, until the factor of porosity relative size of all sub-volume is all greater than 95%, recording the volume V1 of now sub-volume; Wherein, the porosity calculation formula of sub-volume is:
φ is factor of porosity, sum
porefor sub-volume hole pixel sum, sum
grainfor sub-volume Skeleton pixel point sum;
2) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the fractal dimension of every subvolumes and record; Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the fractal dimension newly obtaining sub-volume, until the fractal dimension relative size of all sub-volume is all greater than 95%, recording the volume V2 of now sub-volume; Wherein, the fractal dimension of sub-volume utilizes meter box algorithm, uses the fractal box algorithm based on 3D rendering to draw;
3) from 1% core volume to the sub-volume of digital core image random selecting at least 10 1% core volumes, calculate the permeability tensor of every subvolumes and record; Then progressively synchronously expand every subvolumes with the speed of 2% core volume and record the permeability tensor newly obtaining sub-volume, until its matrix respective value relative size of the permeability tensor of all sub-volume is all greater than 90%, record the volume V3 of now sub-volume; Wherein, the permeability tensor of sub-volume, based on generalized Darcy's law and mass-conservation equation, utilizes FEM (finite element) calculation to obtain;
4) compare V1, V2 and V3, maximum volume is wherein exactly Representative Elementary Volume;
(3) seepage simulation
According to step 4) Representative Elementary Volume random selecting Representative Elementary Volume from digital core image of determining, calculation model of permeability is utilized to carry out flow event numerical simulation to Representative Elementary Volume, obtain absolute permeability and the relative permeability of Representative Elementary Volume, absolute permeability value and relative permeability value are the predicted value of actual rock permeability.
2. Permeability Prediction method according to claim 1, is characterized in that, described flow event method for numerical simulation is pore network model or CFD model.
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Cited By (14)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107657610A (en) * | 2017-09-29 | 2018-02-02 | 哈尔滨工业大学 | A kind of CT scan interpretation of result method based on meter cassette method |
| CN108729908A (en) * | 2018-05-21 | 2018-11-02 | 中国石油大学(华东) | A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method |
| CN108868756A (en) * | 2018-06-22 | 2018-11-23 | 西南石油大学 | A kind of coal seam reservoirs rock texture complexity evaluation method based on well logging information |
| CN108896446A (en) * | 2018-08-30 | 2018-11-27 | 中国石油大学(北京) | Permeability determines method and system |
| CN109191423A (en) * | 2018-07-18 | 2019-01-11 | 中国矿业大学 | A kind of porous media Permeability Prediction method based on machine image intelligence learning |
| CN109211666A (en) * | 2018-08-31 | 2019-01-15 | 山东科技大学 | The method of coal body permeability under predicted stresses loading environment based on CT scan |
| CN110865011A (en) * | 2019-11-14 | 2020-03-06 | 西南石油大学 | Method for calculating relative permeability of compact rock core based on digital imaging technology |
| CN110992331A (en) * | 2019-11-27 | 2020-04-10 | 中国地质大学（武汉） | Quantitative evaluation device and method for pore structure characteristics of two-dimensional porous medium |
| WO2020215524A1 (en) * | 2019-04-24 | 2020-10-29 | 山东科技大学 | Method for predicting coal porosity and permeability parameters based on fractal theory and ct scanning |
| CN112394072A (en) * | 2020-11-26 | 2021-02-23 | 西安石油大学 | Micro-CT-based core broadband dielectric constant characterization method and device |
| CN112816388A (en) * | 2020-12-31 | 2021-05-18 | 中国石油大学(北京) | Oil sand seepage performance testing method based on CT and digital core three-dimensional reconstruction |
| CN112986090A (en) * | 2019-12-17 | 2021-06-18 | 中国石油天然气股份有限公司 | Permeability detection device and method |
| CN114609010A (en) * | 2022-03-02 | 2022-06-10 | 中国石油大学(华东) | Method and device for measuring oil-water relative permeability of shale reservoir |
| CN118095021A (en) * | 2024-04-28 | 2024-05-28 | 中国石油大学(华东) | Efficient calculation method for permeability of large-size digital rock core |
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Cited By (20)
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|---|---|---|---|---|
| CN107657610B (en) * | 2017-09-29 | 2020-10-16 | 哈尔滨工业大学 | CT scanning result analysis method based on box counting method |
| CN107657610A (en) * | 2017-09-29 | 2018-02-02 | 哈尔滨工业大学 | A kind of CT scan interpretation of result method based on meter cassette method |
| CN108729908A (en) * | 2018-05-21 | 2018-11-02 | 中国石油大学(华东) | A kind of oily flow simulating of densification based on pore network model and Permeability Prediction method |
| CN108868756A (en) * | 2018-06-22 | 2018-11-23 | 西南石油大学 | A kind of coal seam reservoirs rock texture complexity evaluation method based on well logging information |
| CN108868756B (en) * | 2018-06-22 | 2021-11-02 | 西南石油大学 | Coal reservoir rock structure complexity evaluation method based on logging information |
| CN109191423A (en) * | 2018-07-18 | 2019-01-11 | 中国矿业大学 | A kind of porous media Permeability Prediction method based on machine image intelligence learning |
| CN109191423B (en) * | 2018-07-18 | 2019-07-02 | 中国矿业大学 | A kind of porous media Permeability Prediction method based on machine image intelligence learning |
| CN108896446A (en) * | 2018-08-30 | 2018-11-27 | 中国石油大学(北京) | Permeability determines method and system |
| CN109211666A (en) * | 2018-08-31 | 2019-01-15 | 山东科技大学 | The method of coal body permeability under predicted stresses loading environment based on CT scan |
| WO2020215524A1 (en) * | 2019-04-24 | 2020-10-29 | 山东科技大学 | Method for predicting coal porosity and permeability parameters based on fractal theory and ct scanning |
| CN110865011A (en) * | 2019-11-14 | 2020-03-06 | 西南石油大学 | Method for calculating relative permeability of compact rock core based on digital imaging technology |
| CN110992331A (en) * | 2019-11-27 | 2020-04-10 | 中国地质大学（武汉） | Quantitative evaluation device and method for pore structure characteristics of two-dimensional porous medium |
| CN112986090A (en) * | 2019-12-17 | 2021-06-18 | 中国石油天然气股份有限公司 | Permeability detection device and method |
| CN112986090B (en) * | 2019-12-17 | 2024-05-28 | 中国石油天然气股份有限公司 | Permeability detection device and method |
| CN112394072A (en) * | 2020-11-26 | 2021-02-23 | 西安石油大学 | Micro-CT-based core broadband dielectric constant characterization method and device |
| CN112394072B (en) * | 2020-11-26 | 2021-10-22 | 西安石油大学 | Micro-CT-based core broadband dielectric constant characterization method and device |
| CN112816388A (en) * | 2020-12-31 | 2021-05-18 | 中国石油大学(北京) | Oil sand seepage performance testing method based on CT and digital core three-dimensional reconstruction |
| CN114609010A (en) * | 2022-03-02 | 2022-06-10 | 中国石油大学(华东) | Method and device for measuring oil-water relative permeability of shale reservoir |
| CN114609010B (en) * | 2022-03-02 | 2024-02-02 | 中国石油大学(华东) | Method and device for measuring oil-water relative permeability of shale reservoir |
| CN118095021A (en) * | 2024-04-28 | 2024-05-28 | 中国石油大学(华东) | Efficient calculation method for permeability of large-size digital rock core |
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