GB2601238A - AFM-Based Shale Porosity Calculation And Component Pore Contribution Evaluation Method - Google Patents
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- 239000011148 porous material Substances 0.000 title claims abstract description 55
- 238000004364 calculation method Methods 0.000 title claims abstract description 28
- 238000011156 evaluation Methods 0.000 title claims abstract description 16
- 230000037332 pore function Effects 0.000 claims abstract description 27
- 238000000034 method Methods 0.000 claims abstract description 24
- 230000010354 integration Effects 0.000 claims abstract description 9
- 239000000463 material Substances 0.000 claims description 12
- 238000012876 topography Methods 0.000 claims description 2
- 239000000126 substance Substances 0.000 abstract 2
- 238000004630 atomic force microscopy Methods 0.000 description 22
- 239000000523 sample Substances 0.000 description 12
- 229910052500 inorganic mineral Inorganic materials 0.000 description 7
- 239000011707 mineral Substances 0.000 description 7
- 235000010755 mineral Nutrition 0.000 description 7
- 239000000203 mixture Substances 0.000 description 7
- 230000006872 improvement Effects 0.000 description 5
- 238000004458 analytical method Methods 0.000 description 4
- 229910001919 chlorite Inorganic materials 0.000 description 4
- 229910052619 chlorite group Inorganic materials 0.000 description 4
- QBWCMBCROVPCKQ-UHFFFAOYSA-N chlorous acid Chemical compound OCl=O QBWCMBCROVPCKQ-UHFFFAOYSA-N 0.000 description 4
- DLHONNLASJQAHX-UHFFFAOYSA-N aluminum;potassium;oxygen(2-);silicon(4+) Chemical compound [O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[O-2].[Al+3].[Si+4].[Si+4].[Si+4].[K+] DLHONNLASJQAHX-UHFFFAOYSA-N 0.000 description 3
- 238000000089 atomic force micrograph Methods 0.000 description 3
- 238000002474 experimental method Methods 0.000 description 3
- 239000010453 quartz Substances 0.000 description 3
- VYPSYNLAJGMNEJ-UHFFFAOYSA-N silicon dioxide Inorganic materials O=[Si]=O VYPSYNLAJGMNEJ-UHFFFAOYSA-N 0.000 description 3
- 238000001179 sorption measurement Methods 0.000 description 3
- 238000003491 array Methods 0.000 description 2
- 230000015572 biosynthetic process Effects 0.000 description 2
- 239000002734 clay mineral Substances 0.000 description 2
- 238000012937 correction Methods 0.000 description 2
- 239000005416 organic matter Substances 0.000 description 2
- 238000012545 processing Methods 0.000 description 2
- 230000009467 reduction Effects 0.000 description 2
- 230000011218 segmentation Effects 0.000 description 2
- 101100492805 Caenorhabditis elegans atm-1 gene Proteins 0.000 description 1
- KWYUFKZDYYNOTN-UHFFFAOYSA-M Potassium hydroxide Chemical compound [OH-].[K+] KWYUFKZDYYNOTN-UHFFFAOYSA-M 0.000 description 1
- 238000009825 accumulation Methods 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 230000007812 deficiency Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000018109 developmental process Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000002349 favourable effect Effects 0.000 description 1
- 239000010433 feldspar Substances 0.000 description 1
- 230000008676 import Effects 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 229940072033 potash Drugs 0.000 description 1
- BWHMMNNQKKPAPP-UHFFFAOYSA-L potassium carbonate Substances [K+].[K+].[O-]C([O-])=O BWHMMNNQKKPAPP-UHFFFAOYSA-L 0.000 description 1
- 235000015320 potassium carbonate Nutrition 0.000 description 1
- 230000008569 process Effects 0.000 description 1
- 235000012239 silicon dioxide Nutrition 0.000 description 1
- 239000000758 substrate Substances 0.000 description 1
- 230000033772 system development Effects 0.000 description 1
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- G01Q—SCANNING-PROBE TECHNIQUES OR APPARATUS; APPLICATIONS OF SCANNING-PROBE TECHNIQUES, e.g. SCANNING PROBE MICROSCOPY [SPM]
- G01Q80/00—Applications, other than SPM, of scanning-probe techniques
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- 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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- G—PHYSICS
- G01—MEASURING; TESTING
- G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
- G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
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Abstract
An AFM-based shale porosity calculation and component pore contribution evaluation method, comprising the following steps: S1, extracting shale surface three-dimensional elevation data and phase data by means of processed AFM data, and correcting the shale surface three-dimensional elevation data; S2, using a threshold method to select a height threshold, segmenting a pore function, solving the pore volume, and calculating the shale porosity according to porosity definition; and S3, obtaining a phase pore function by using a double-threshold discrete integration method, calculating the porosity in different phase intervals by using the phase pore function, performing linear fitting on the porosity in different phase intervals and the shale substance components, and calculating a correlation coefficient between the porosity and the shale substance components so as to evaluate the pore contribution of different components. The AFM-based shale porosity calculation and component pore contribution evaluation method widens the application range of the AFM in the field of unconventional oil and gas.
Description
AFM-Based Shale Porosity Calculation And Component Pore Contribution Evaluation Method
TECHNICAL FIELD
The invention relates to an AFM-based shale porosity calculation and component pore contribution evaluation method, belonging to the shale gas geological field. BACKGROUND Shale gas plays an increasingly important role in the world energy field. Shale gas reservoirs usually develop multi-scale micro-nano pore fractures, with complex pore structure and obvious micro-heterogeneity, which restricts the success rate of exploration and development. The material composition of shale is the basis of pore system development, but the contribution of different reservoir components to pores is still unclear. Understanding the pore structure of shale gas reservoir, and distinguishing the pore contribution of main material components are of great significance to accurately characterize shale gas reservoir, accurately evaluating shale gas resources, revealing the mechanism of shale gas accumulation and guiding the division of favorable areas.
Atomic force microscopy (AFM) can be used to qualitatively and quantitatively characterize shale pore structure, but AFM cannot directly measure shale porosity, which is an extremely important parameter for unconventional reservoir evaluation so it limits the extensive application of AFM in unconventional oil and gas fields to some extent. Studies have shown that the phase change of AFM is closely related to the material composition, which provides a theoretical basis for evaluating the pore contribution of the main material composition by AFM, but there is no relevant practice yet.
SUMMARY
In view of the above problems in the prior art, the invention provides an AFMbased shale porosity calculation and component pore contribution evaluation method, so as to make up for the deficiency of AFM in determining shale porosity and promote the combination of AFM's mineral analysis capability and pore structure determination capability.
In order to achieve the above purpose, the AFM-based shale porosity calculation and component pore contribution evaluation method adopted by the invention comprises the following steps: Si, extracting three-dimensional elevation data and phase data of shale surface through processed AFM data, and correcting the three-dimensional elevation data of shale surface; S2, adopting the threshold method, selecting the height threshold, segmenting the pore function, calculating the pore volume, and calculating shale porosity according to the definition of porosity; S3, obtaining the phase pore function by using the double-threshold discrete integration method, calculating the porosity in different phase intervals by using the phase pore function, linearly fitting the porosity and shale material components in different phase intervals and calculating the correlation coefficient between them, so as to evaluate the pore contribution of different components.
As an improvement, in Si, the elevation of the three-dimensional coordinate data of shale surface topography is corrected with the elevation of the lowest point of shale surface as zero reference elevation.
As an improvement, the specific step of calculating pore volume in S2 is: selecting an appropriate height threshold, segmenting the pore function, regarding the projection of the sample surface in x0y coordinate system as a virtual plane with negligible thickness, and using this virtual plane to cut the sample surface from bottom to top, then the volume enclosed by the virtual plane and the sample surface below this plane is the pore volume, and the calculation formula is: f f (x, y) I (x, T. I 0 if h -g(x, y)do- g(x,y)<h,v<-a,y <-1) 117-2 2 V (T)+ A(h -T) h > T s the pore function; f(x,y) is the elevation function; T is the height threshold, and the unit is m; 17 is the pore volume, and the unit is ni3; A is the projected area, and the unit is m2; h is elevation, and the unit is m; a and b are projection width and length, and the unit is m.
As an improvement, the step of calculating shale porosity in S2 is: the hole volume divided by the product of the projected area and the selected elevation, and the calculation formula is: V (h) 0(h)-Ah wherein, ill is porosity, and the unit is %.
As an improvement, the double threshold discrete integration method in S3 specifically means: performing the threshold method on the elevation data to calculate the porosity, then performing the threshold method on phase data, selecting phase threshold P, segmenting the phase pore function, and the calculation formula is: = 0, y)> TU c)(x,y)> P f(x, y) f (x, y) T n (0(x, y) 13.
wherein, (x,y) is the phase pore function; is the phase threshold, and the unit is ° As an improvement, in S3, the porosity in different phase intervals is calculated by using the phase pore function, specifically means: integrating the difference between elevation and phase pore function, and the result divided by the product of plane projection area and elevation threshold, and the formula is: =ØjJ[h-(x.y)1dc(Ah)' D c nx, y) g (x, y)<h (x,y)<P x < -CI y < -b; 2 2 wherein, 0,;:is phase porosity, and the unit is %.
Compared with the prior art, the invention has the following beneficial effects: 1. the AFNI-based shale porosity calculation and component pore contribution evaluation method provided by the invention broadens the application range of AFINI in unconventional oil and gas fields.
2. the invention provides a train of thought for studying the pore contribution of different material components in shale gas reservoirs and lays a theoretical foundation for accurately characterizing shale gas reservoir.
BRIEF DESCRIPTION OF THE FIGURES
FIG. I is a implementation flow chart of the invention; FIG. 2-a, FIG. 2-b and FIG. 2-c show schematic diagrams of cutting the sample surface from bottom to top with a virtual plane; the three figures from top to bottom show the relative positions of cutting bottom surface (FIG. 2-a), middle position (FIG. 2-b) and top surface (FIG. 2-c) in sequence; FIG. 3-a, FIG. 3-b, FIG. 3-c, FIG. 3-d and FIG. 3-e show the correlation between porosity and main material components in different phase intervals in the invention; FIG. 3-a shows the correlation between chlorite content and porosity in the phase interval of-20-5"; FIG. 3-b shows the correlation between potassium feldspar content and porosity in the phase interval-10-100; FIG. 3-c shows the correlation between quartz content and porosity in the phase interval-5-15'; FIG. 3-d shows the correlation between brittle mineral content and porosity in the phase interval of 0-100; FIG 3-e shows the correlation between organic matter content and total porosity; FIG. 4 is a comparison of porosity measured by the invention and low temperature N2 adsorption experiment.
DESCRIPTION OF THE INVENTION
In order to make the object, technical scheme and advantages of the invention clearer, the invention will be further explained in detail below. However, the specific embodiments described herein are only used to explain the invention, and are not used to limit the scope of the invention.
Unless otherwise defined, all technical terms and scientific terms used herein have the same meanings as those commonly understood by those who belong to the technical field of the invention, and the terms used herein in the specification of the invention are only for the purpose of describing specific embodiments, and are not intended to limit the invention.
As shown in FIG. 1, the AFM-based shale porosity calculation and component pore contribution evaluation method includes the following steps: 1) during AFM scanning, there will be experimental errors such as sample substrate skew caused by manual operation and bowl-shaped deformation of scanning surface and noise interference caused by AFM probe swing, so it is necessary to import AFNI files into NanoScope Analysis software, and perform noise reduction and flatten processing on the scanned images to minimize the experimental errors contained in AFM files; 2) using Gwyddion software to export 3D elevation data and phase data of shale surface; 3) placing the exported elevation data in a three-dimensional coordinate system, correcting the three-dimensional elevation data of shale surface with the image center as the coordinate origin and the lowest elevation of shale surface as the zero reference elevation; 4) using threshold method, determine the aperture function by judging whether the surface elevation function meets the requirement of elevation threshold, and then select the aperture in AFM image The threshold segmentation method can be expressed as the following formula: f (x, y) f (x, y) . o f (x, y)> T where n g(x,y) is the pore function; j(xy) is the elevation function; T is the height threshold, and the unit is m; 5) the projection of the sample surface in x0y coordinate system is regarded as a virtual plane with negligible thickness, and the virtual plane is used to cut the sample surface from bottom to top, then the volume enclosed by the virtual plane and the sample surface below the plane is the pore volume, and the calculation formula of pore volume is: h -g(x, y)do- f(x, y)I g(x, y) < h,x <t±2, y < -b2} I V (It) = g(x, y)= V(i/ ) A (h -I) h > T In which, V is the pore volume, and the unit is m3; A is the projected area, and the unit is m2; h is elevation, and the unit is m; a and h are projection width and length respectively, and the unit is m; 6) according to the definition of porosity, the hole volume divided by the product of the projected area and the selected elevation, so as to obtain the porosity, and the calculation formula is as follows: V(h) 0(h) A h Wherein, 95 is porosity, and the unit is %; 7) using the double threshold discrete integration method, that is, changing the phase threshold on the basis of the fixed elevation threshold to obtain the phase pore function, and the double threshold discrete integration method can be expressed by the following formula: y) _{.f (x, y) .t (x, y) T n 40(x, y) p o.f (x,y)> TU yo(x,y)> wherein, ffx,y) is the phase pore function; P is the phase threshold, and the unit is 0; 8) calculating the porosity under the control of phase threshold, and the calculation formula is: -e(x,Ado-*(,417)-1 y) g(x,y)<h,(x,y)<P,x <-61,y<-b 2 2 Wherein, c5,i is phase porosity, and the unit is %; 9) linearly fitting the porosity and material composition in different phase intervals and calculating the correlation coefficient between them, then obtaining the correlation between different components and porosity in different phase intervals, and clarifying the corresponding relationship between phase intervals and material composition, so as to evaluate the pore contribution of different components. ;Wherein, the flatten order in step 1) is generally 2 for shale samples. ;The correction method in step 3) is as follows: all elevation values minus the minimum of the elevation values to get the new elevation values. ;Example 1 ;In this example, the porosity of Longmaxi Formation shale in Wuxi 2 well in Northeast Chongqing is tested and the pore contribution of main minerals is evaluated based on AFM. The steps are as follows: L importing the data obtained from AFM scanning into NanoScope Analysis, and perform noise reduction and 2-level flatten processing on the scanned images to minimize the experimental errors contained in AFM files; 2. importing the AFM files processed by NanoScope Analysis into Gwyddion, select ZSensor mode, saving the file in xyz text data format, adding. txt suffix, and extracting the elevation data in AFM file; selecting Phase mode, saving the file in xyz text data format, adding. txt suffix, and extracting the phase data in AFM files; 3. importing the data obtained from AFM scanning into MATLAB for correction, and after importing, it will generate 1183 (n = Xp8 Yp; Xp and Yp are the number of pixels in the length and width direction of AFM image respectively) column arrays; splitting the three column arrays into X=n1, Y=n2, Z=n3, using the reshape function to transform each column array into Xp rows x Yp columns, so that each scan line can be called, adopting min function to find the minimum value Z.in in the Z array, and using MATLAB operation instruction Z1=Z-Z,,,,,,, the Z array of reservoir elevation data is used to correct the three-dimensional data of shale surface with the elevation of the lowest point of shale surface elevation as zero reference height; 4. using threshold method to determine the aperture function by judging whether the surface elevation function meets the requirement of elevation threshold, and then selecting the aperture in AFM image. The threshold segmentation method can be expressed as the following formula: 1./c(x,.1)) :ATM 1 0 f (x, y) > T wherein, g(r3) is the pore function; j(x,y) is the elevation function; T is the height threshold, and the unit is m; 5. regarding the projection of the sample surface in x0y coordinate system as a virtual plane with negligible thickness. The virtual plane is used to cut the sample surface from bottom to top, and the volume enclosed by the virtual plane and the sample surface below the plane is the pore volume (as shown in FIG. 2-a, FIG. 2-b and FIG. 2-c), and the calculation formula of pore volume can be expressed as follows: V(h) = h -g(x, y)d g(x,y)<h v<-a y<-1) 117- 1,7 (T) + A(h -T) 2 2 h > 1 wherein, V is the pore volume, and the unit is m3, A is the projected area, and the unit is m2; h is elevation, and the unit is m, a and b are projection width and length respectively, and the unit is m; 6. according to the definition of porosity, the pore volume divided by the product of the projected area and the selected elevation to obtain the porosity. The porosity calculation formula can be expressed as: 0(h) T (h) Ah wherein i is porosity, and the unit is (l/li; 7. using the double threshold discrete integration method, that is, changing the phase threshold on the basis of a fixed elevation threshold to obtain the phase pore function. The double threshold discrete integration method can be expressed by the following formula: y)-.f (x, y) .f (x, y) T n co(x, 0.f(x,y)> TU co(x,y)> P In which, N,y) is the phase pore function; P is the phase threshold, and the unit is 0; 8. calculating the porosity under the control of phase threshold, and the calculation process can be expressed as the formula: -j(x, y) Jelo-* (24h)-1 D e g (x, y)< h v <-6 2 " 21' wherein, yi,; is phase porosity, and the unit is %; 9, linearly fitting the porosity and material composition in different phase intervals and calculating the correlation coefficient between them, so as to obtain the correlation between different components and porosity in different phase intervals, and clarifying the corresponding relationship between phase intervals and material compositions, so as to evaluate the pore contribution of different components. As shown in FIG. 3-a, there is a positive correlation between chlorite content and porosity provided by phase interval-20--5°, which indicates that pores in this interval are mainly provided by chlorite; in FIG. 3-b, there is an obvious positive correlation between the content of potassium feldspar and the porosity provided by the phase interval-10-100 (R2 is 94.21%), which indicates that the pores in this interval are almost entirely provided by potassium feldspar; in FIG. 3-c, there is a good positive correlation between the porosity provided by the phase interval-S-150 and the quartz content, which indicates that the pores in this interval is mainly quartz-originated porosity; in FIG. 3-d, there is a positive correlation between the pores provided by the phase interval 0-10° and the content of brittle minerals, which indicates that many brittle mineral pores are developed in this phase interval; in FIG. 3-e, TOC content has a positive correlation with total porosity, and the correlation is good (R2 is 81.02%), which indicates that organic-originated pores are mainly developed in Longmaxi Formation shale, and organic-originated pores contribute in each phase interval. Generally speaking, clay minerals, organic matter and brittle minerals provide certain pores, among which chlorite is the main clay minerals and quartz and potash feldspar are the main brittle minerals.
In order to verify the accuracy of porosity calculated by the method, the porosity of shale samples in Wuxi 2 well calculated by the method of the invention is compared with the porosity obtained by low-temperature N2 adsorption experiment, and the result is shown in FIG. 4. It can be seen from analysis that the porosity calculated by AFNI is basically consistent with the porosity converted by low-temperature N2 adsorption experiment, indicating that the porosity calculation method based on MM proposed by the invention is reliable The above embodiments are only for explaining the technical concept and characteristics of the invention, and their purpose is to enable people familiar with the art to understand the content of the invention and implement it accordingly, but not to limit the scope of protection of the invention. All equivalent changes or modifications made according to the spirit of the invention shall be covered within the scope of protection of the invention.
Claims (6)
- CLAIMS: 1. An AFM-based shale porosity calculation and component pore contribution evaluation method, which comprises the following steps: Si, extracting three-dimensional elevation data and phase data of shale surface through processed AFM data, and correcting the three-dimensional elevation data of shale surface; S2, adopting the threshold method, selecting a height threshold, segmenting a pore function, calculating the pore volume, and calculating shale porosity according to the definition of porosity; S3, obtaining the phase pore function by using a double-threshold discrete integration method, calculating the porosity in different phase intervals by using the phase pore function, linearly fitting the porosity and shale material components in different phase intervals and calculating the correlation coefficient between them, so as to evaluate the pore contribution of different components.
- 2. The AIM-based shale porosity calculation and component pore contribution evaluation method according to claim 1, wherein in St, the elevation of the three-dimensional coordinate data of shale surface topography is corrected with the elevation of the lowest point of shale surface as zero reference elevation.
- 3. The AFM-based shale porosity calculation and component pore contribution evaluation method according to claim 1, wherein the specific step of calculating pore volume in S2 is: selecting an appropriate height threshold, segmenting the pore function, regarding the projection of the sample surface in x0y coordinate system as a virtual plane with negligible thickness, and using this virtual plane to cut the sample surface from bottom to top, then the volume enclosed by the virtual plane and the sample surface below this plane is the pore volume, and the calculation formula is: g(x,y)= )1.1(x, Y) f (x, I 0.f(x-,y)> T [JJh-g(xi;)da D c{(x,y) 17(T) A(h -T) h> T g(r,y) is the pore function; .ffx,y) is the elevation function T is the height threshold, and the unit is m; V is the pore volume, and the unit is m3; A is the projected area, and the unit is m2; h is elevation, and the unit is m; a and b are projection width and length, and the unit is m.
- 4. The AFN4-based shale porosity calculation and component pore contribution evaluation method according to claim I, wherein the step of calculating shale porosity in S2 is: the hole volume divided by the product of the projected area and the selected elevation, and the calculation formula is: r(h) 0(h) A h wherein, (I) is porosity, and the unit is °/0
- 5. The AFM-based shale porosity calculation and component pore contribution evaluation method according to claim 1, wherein the double threshold discrete integration method in S3 specifically means: performing the threshold method on the elevation data to calculate the porosity, then performing the threshold method on phase data, selecting phase threshold P, segmenting the phase pore function, and the calculation formula is: f (x, y) f (x,y) Trlyo(x,y) (v,.))) = 0..f (x,y)>TUq)(x,y)> P' wherein, c;(x,y) is the phase pore function; P is the phase threshold, amd the unit is °
- 6. The AFM-based shale porosity calculation and component pore contribution evaluation method according to claim 1, wherein in S3, the porosity in different phase intervals is calculated by using the phase pore function, specifically means: integrating the difference between elevation and phase pore function, and the result divided by the product of plane projection area and elevation threshold, and the formula is: ff -(xy)Jdo-* (Ah)-1 DE y) gcv, < y)<P,x. < v; 2 2 wherein, ci=is phase porosity, and the unit is %.
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| CN202010619791.1A CN111766407B (en) | 2020-06-30 | 2020-06-30 | Shale porosity calculation and component porosity contribution evaluation method based on AFM |
| PCT/CN2021/084376 WO2022001259A1 (en) | 2020-06-30 | 2021-03-31 | Afm-based shale porosity calculation and component pore contribution evaluation method |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2012118866A2 (en) * | 2011-02-28 | 2012-09-07 | Schlumberger Technology Corporation | Methods to build 3d digital models of porous media using a combination of high- and low-resolution data and multi-point statistics |
| US20140048694A1 (en) * | 2012-08-17 | 2014-02-20 | Schlumberger Technology Corporation | Method to characterize shales at high spatial resolution |
| US20190154597A1 (en) * | 2017-11-20 | 2019-05-23 | DigiM Solution LLC | System and Methods for Computing Physical Properties of Materials Using Imaging Data |
| US20200132657A1 (en) * | 2018-10-31 | 2020-04-30 | Hubert E. King, JR. | Microanalysis of Fine Grained Rock for Reservoir Quality Analysis |
| US20200325758A1 (en) * | 2019-04-15 | 2020-10-15 | Saudi Arabian Oil Company | System and Method to Evaluate Kerogen-Rich Shale |
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Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2012118866A2 (en) * | 2011-02-28 | 2012-09-07 | Schlumberger Technology Corporation | Methods to build 3d digital models of porous media using a combination of high- and low-resolution data and multi-point statistics |
| US20140048694A1 (en) * | 2012-08-17 | 2014-02-20 | Schlumberger Technology Corporation | Method to characterize shales at high spatial resolution |
| US20190154597A1 (en) * | 2017-11-20 | 2019-05-23 | DigiM Solution LLC | System and Methods for Computing Physical Properties of Materials Using Imaging Data |
| US20200132657A1 (en) * | 2018-10-31 | 2020-04-30 | Hubert E. King, JR. | Microanalysis of Fine Grained Rock for Reservoir Quality Analysis |
| US20200325758A1 (en) * | 2019-04-15 | 2020-10-15 | Saudi Arabian Oil Company | System and Method to Evaluate Kerogen-Rich Shale |
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| GB2601238B (en) | 2023-04-05 |
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