WO2021203611A1 - 一种纳米级孔隙结构变化的判断方法及应用 - Google Patents

一种纳米级孔隙结构变化的判断方法及应用 Download PDF

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WO2021203611A1
WO2021203611A1 PCT/CN2020/111476 CN2020111476W WO2021203611A1 WO 2021203611 A1 WO2021203611 A1 WO 2021203611A1 CN 2020111476 W CN2020111476 W CN 2020111476W WO 2021203611 A1 WO2021203611 A1 WO 2021203611A1
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sample
pore structure
mesh
ssa
nano
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PCT/CN2020/111476
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French (fr)
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张金川
魏晓亮
韩美玲
唐玄
苔丝
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中国地质大学（北京）
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Priority to GB2213108.0A priority Critical patent/GB2607836A/en
Publication of WO2021203611A1 publication Critical patent/WO2021203611A1/zh

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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
    • G01N15/0893—Investigating volume, surface area, size or distribution of pores; Porosimetry by measuring weight or volume of sorbed fluid, e.g. B.E.T. method

Definitions

  • This scheme involves a method for judging the change of nano-scale pore structure and its application.
  • Oil and natural gas are mainly stored and seeped in the nano-scale pore and fracture system in tight reservoirs (such as shale cores obtained during drilling and mining). Therefore, effective and reasonable evaluation and judgment of the pore and fracture system of tight reservoirs are important for tight reservoirs.
  • the exploration and development of oil and gas is of great significance.
  • Porous media is composed of many pores and solid matrix, and the pores develop in the solid matrix.
  • the specific surface area of a porous medium is the total area of the porous medium per unit mass; the pore volume is the total volume of pores per unit mass of the porous medium; the pore size distribution refers to the number or volume of the various pore sizes in the porous medium. percentage.
  • the microscopic pores of porous media can be divided into three categories: micropores ( ⁇ 2nm), mesopores (2-50nm), and macropores (pores >50nm).
  • Existing experimental methods for characterizing pores in porous media include low-temperature nitrogen adsorption method and mercury intrusion method.
  • the measured specific surface area, pore volume, and pore size distribution can directly reflect some characteristics of microscopic pores in porous media.
  • a tight reservoir is a kind of porous medium.
  • different experimental conditions are usually changed, such as measuring the micro pores of tight reservoirs under different lithology, different mesh numbers, and different temperature and pressure conditions.
  • the characterization parameters are compared horizontally and vertically to indirectly reflect the influence of different experimental conditions on the microscopic pore structure of tight reservoirs.
  • This solution provides a method and application for judging changes in nano-scale pore structure.
  • the method for judging the change of nano-scale pore structure includes the following steps:
  • the vacuum degassing temperature in step a is 90-120°C.
  • the vacuum degassing time in step a is ⁇ 9h.
  • step b an adsorption isotherm curve in the range of 0.05 ⁇ P/P 0 ⁇ 0.35 is selected, and the nitrogen volume V m required for monolayer adsorption is obtained from the slope s and the intercept i.
  • the selection of the adsorption isotherm curve within the above range can further reduce the error of the judgment method.
  • step c a value in the range of 0.01 ⁇ P/P 0 ⁇ 0.995 is selected, and the pore volume of the micropores, mesopores and macropores is obtained by statistics of the ASiQ software according to the NLDFT density function theory method.
  • step d the change of the nano-scale pore structure in the sample is judged according to the change of the SSA/PV value when the particle size of the sample is crushed from 20 mesh to 200 mesh.
  • the solution also provides the application of the judgment method for judging the influence of the sample preparation damage process on the nano-scale pore structure of the tight reservoir.
  • the method for judging nano-scale pore structure changes provided by this solution is to characterize the specific surface area, pore volume and pore size distribution of the microscopic pores of tight rocks, and to qualitatively judge the nano-level of tight reservoirs by the changes of SSA/PV under different crushed particle sizes of samples.
  • the microscopic pore structure changes caused by pores in the process of structural damage ie sample crushing
  • the SSA/PV value changes significantly with the change of the crushing mesh, it can be judged that the sample preparation damage process has different degrees of influence on the nano-scale pore structure of the tight reservoir.
  • the solution also provides the application of the judgment method for judging the accuracy of the pore structure test characterization data of the nano-scale pore structure sample of the tight reservoir. Judging the error size and correcting it through the change rate of SSA/PV can improve the accuracy of traditional qualitative and quantitative research methods of nano-scale pores in tight reservoirs.
  • the SSA/PV value becomes smaller and the correlation coefficient R 2 of the SSA/PV value changes with the pulverized mesh number is above 0.6, indicating the compactness
  • the pore structure test characterization data of the reservoir nano-scale pore structure sample has certain errors that need to be corrected.
  • the correlation coefficient R 2 of the SSA/PV value of different samples with the change of the crushing mesh is also different, indicating that it is also related to the type of sample. Oil and natural gas are mainly stored and seeped in the nano-scale pores and fractures system in tight reservoirs.
  • the SSA/PV value becomes smaller and the SSA/PV value changes with the crushing mesh. If the correlation coefficient R 2 of the change is above 0.6, the error in the detection of the traditional tight reservoir nano-scale pore structure test characterization data will affect or even mislead the effective and reasonable evaluation and judgment of the pore and fracture system of the tight reservoir, which is not conducive to Effective exploration and development of oil and gas resources.
  • This solution provides the establishment of a nitrogen adsorption isotherm curve that changes with P/P 0 , selects the isotherm adsorption curve in the range of 0.05 ⁇ P/P 0 ⁇ 0.35, calculates the nitrogen volume V m required for monolayer adsorption, and then passes
  • the BET specific surface area formula calculates the specific surface SSA of the sample, and the specific surface SSA value of the sample with higher accuracy under different crushing meshes can be obtained.
  • the critical P/P 0 values of micropores, mesopores and macropores are selected for statistical analysis to obtain the pore volume of micropores, mesopores and macropores, and the pore volume of different types of pores in the sample is obtained as a function of the crushed particle size. Increased changes. Finally, the change of nano-scale pore structure was judged by the change of SSA/PV under different crushed particle sizes of the sample.
  • the judgment method of this scheme accurately detects the specific surface area SSA and total pore volume PV of samples under different crushed particle sizes, which can not only judge the influence of sample preparation damage process on the nano-scale pore structure in tight reservoir samples, but also accurately judge the traditional
  • the qualitative and quantitative research methods of nano-scale pores in tight reservoirs are of great significance to the exploration and development of tight oil and gas resources due to the influence of pore structure changes on the research results during the sample preparation process.
  • Figure 1 is a graph showing the adsorption isotherm of sample No. 1 under different crushing meshes in an embodiment of the present invention
  • Figure 2 is a graph showing the adsorption isotherm of sample No. 2 under different crushing meshes in an embodiment of the present invention
  • Figure 3 is a graph showing the adsorption isotherm of sample No. 3 under different crushing meshes in an embodiment of the present invention
  • Fig. 5 is a graph showing the adsorption isotherm of sample No. 5 under different crushing meshes in an embodiment of the present invention
  • Fig. 6 is a graph showing the adsorption isotherm of sample No. 6 under different crushing meshes in an embodiment of the present invention
  • Fig. 7 is a graph showing the change of SSA value of 6 samples under different crushing meshes in the embodiment of the present invention.
  • Fig. 8 is a graph showing the growth rate of SAA under different crushing meshes for 6 samples in the embodiment of the present invention.
  • Fig. 9 is a graph showing the change of the pore volume of the micropores under different crushing meshes for 6 samples in the embodiment of the present invention.
  • Figure 10 is a graph showing the pore volume change curve of mesopores under different crushing meshes for 6 samples in an embodiment of the present invention.
  • Figure 11 is a graph showing the pore volume change curve of macropores under different crushing meshes for 6 samples in the embodiment of the present invention.
  • Fig. 12 is a graph showing the variation of PV values of 6 samples under different crushing meshes in the embodiment of the present invention.
  • Fig. 13 is a graph showing the growth rate of PV value of 6 samples under different crushing meshes in the embodiment of the present invention.
  • Fig. 14 is a graph showing the change of SSA/PV value of 6 samples under different crushing meshes in the embodiment of the present invention.
  • the sample was degassed under vacuum for 9h at a temperature of 100°C.
  • the mass W of the sample after vacuum degassing is obtained by calculating the difference between the mass of the sample tube after degassing and the mass of the empty tube before degassing. Place the degassed sample in liquid nitrogen, measure the nitrogen adsorption capacity of the sample at multiple pre-set pressure points, and obtain the sample isotherm adsorption curve.
  • the isotherm adsorption curve of 6 samples under different crushing meshes is shown in the figure Shown in 1-6.
  • the pore volume of the micropores, mesopores and macropores in the sample is obtained through statistics by ASiQ software, and then the micropores, mesopores and macropores in the sample are obtained.
  • the total pore volume PV of the pores, the calculated pore volume of micropores, mesopores and macropores and the total pore volume PV value of 6 samples under different crushing meshes, and the calculated pore volume of micropores, mesopores and macropores The values are shown in Table 3.
  • the pore volume change curve of micropores is shown in Fig.
  • SSA has not changed much, but PV has increased greatly. That is, under the experimental conditions, the process of crushing the shale sample from 20 mesh to 80 mesh and then to 200 mesh has little change in the micropores in the rock sample. Therefore, the content of micropore-level pores does not change much.
  • the number of crushing meshes increases, the number of mesopores and macropores in the sample increases. There are two reasons for the increase in the number of macropores: a. The mesopores are destroyed and the pores are connected to become macropores; b. New microcracks are generated, which connect the previously closed pores.
  • the SSA/PV value has a certain correlation with the crushing mesh (R 2 varies in the range of 0.6-0.8) in the process of increasing the sample size from 20 mesh to 80 mesh and then to 200 mesh.
  • SSA/PV keeps decreasing with the crushing mesh. It shows that as the number of crushing meshes increases during the sample preparation process, the interconnected pores in the pore system are increased, and new pores and fractures are created, which increases the pore volume and damages the nano-scale pore structure of the shale core.
  • test results further verify the feasibility of using the change of SSA/PV with the number of meshes to determine the microscopic pore structure changes of tight reservoirs during the sample preparation process and to determine the accuracy of the pore structure test characterization data of tight reservoir nano-scale pore structure samples. .

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Abstract

一种纳米级孔隙结构变化的判断方法和应用，该判断方法包括：a、将真空脱气后的纳米级孔隙结构样品置于液氮中，获得样品的氮气吸附量随相对压力P/P 0变化的等温吸附曲线；b、根据等温吸附曲线，利用BET比表面积公式计算样品的比表面积SSA；c、根据NLDFT密度函数理论法，得到样品中不同尺度孔隙的孔体积之和PV；d、根据SSA/PV的值随粉碎目数的变化情况判断粉碎过程对纳米级孔隙结构的影响。该判断方法可准确判断出制样损伤过程对致密储层纳米级孔隙结构影响，并可用于判断传统的致密储层纳米级孔隙定性与定量研究方法中由于制样过程中孔隙结构变化对研究结果产生的误差影响。

Description

一种纳米级孔隙结构变化的判断方法及应用
本发明专利申请要求于2020年04月10日提交的中国专利申请NO.CN202010281035.2的优先权。在先申请的公开内容通过整体引用并入本申请。
技术领域
本方案涉及到一种纳米级孔隙结构变化的判断方法及应用。
 背景技术
随着全球能源需求的不断增长以及油气开发技术的不断提高，致密油气资源逐渐成为许多国家勘探和开发的重点。石油和天然气主要在致密储层（例如钻井开采过程中获得的页岩岩心）中的纳米级孔缝***赋存与渗流，因此对致密储层的孔缝***进行有效合理的评价和判断对于致密油气的勘探和开发具有重要意义。
多孔介质是由许多孔隙和固体基质组成的，孔隙发育在固体基质中。多孔介质的比表面积是单位质量的多孔介质所具有的总面积；孔容即单位质量多孔介质所具有的细孔总容积；孔径分布是指多孔介质中存在的各级孔径按数量或体积计算的百分率。多孔介质的微观孔隙可以划分为三类：微孔（<2nm），介孔（2-50nm），宏孔（>50nm的孔缝）。现有的多孔介质中孔隙表征实验方法包括低温氮气吸附法和压汞法等，主要通过其测得的比表面积、孔容以及孔径分布等参数可以直接反映多孔介质中微观孔隙的一些特征。致密储层即为一种多孔介质，在现有的孔隙表征实验方法的基础上，通常通过改变不同实验条件，如测量不同岩性、不同目数、不同温压等条件下致密储层微观孔隙的表征参数，进行横纵向对比，来间接反映不同的实验条件对致密储层微观孔隙结构产生的影响。目前我们常用一些典型的岩石力学参数，如杨氏模量、泊松比来评价致密储层中裂缝发育的难易程度。但是，上述方法均存在忽略了制样损伤过程所造成的孔隙结构变化对致密储层微观孔隙的定性与定量研究产生的误差影响。因此，建立一种可以判断致密储层纳米级孔隙在结构损伤过程中产生的微观孔隙结构变化的方法具有重要意义。
 技术问题
本方案提供一种纳米级孔隙结构变化的判断方法和应用。
 技术解决方案
该纳米级孔隙结构变化的判断方法，包括如下步骤：
a、将真空脱气后的纳米级孔隙结构的样品置于液氮中，在预先设定的多个压力值P下检测所述样品的氮气吸附量，获得所述样品的氮气吸附量随相对压力P/P 0变化的等温吸附曲线，其中，P 0为吸附温度下氮气的饱和蒸气压；
b、选取0.05<P/P 0<0.35范围内的等温吸附曲线，通过斜率s和截距i求得单层吸附需要的氮气体积V m；利用BET比表面积公式计算样品的比表面SSA；所述BET比表面积公式为SAA=（V m×σ）/22400W，式中：σ为被吸附气体的截面积；W为真空脱气后的样品质量；
c、根据NLDFT密度函数理论法，分别计算出微孔、介孔和宏孔的孔体积，进而得到样品中所述微孔、介孔和宏孔的孔体积之和PV以及PV随粉碎目数的变化趋势；
d、计算样品不同粉碎粒径下SSA/PV的值，根据所述SSA/PV的值随粉碎目数增加的变化趋势判断粉碎过程对样品中纳米级孔隙结构变化的影响。
作为一种实施例，步骤a中所述真空脱气温度为90-120℃。
作为一种实施例，步骤a中所述真空脱气时间≥9h。
作为一种实施例，步骤b中选取0.05<P/P 0<0.35范围内的等温吸附曲线，通过斜率s和截距i求得单层吸附需要的氮气体积V m。上述范围内的等温吸附曲线的选择，可以进一步减小判断方法的误差。
作为一种实施例，步骤b中所述V m与所述斜率s和所述截距i的关系为：V m=1/（s+i）。所述V m与0.05<P/P 0<0.35范围内的等温吸附曲线的斜率s的关系为：s=（C-1）/(Vm×C)，式中：C为BET常数；所述V m与0.05<P/P 0<0.35范围内的等温吸附曲线的截距i的关系为：i=1/(Vm×C)，式中：C为BET常数；进而得出V m=1/（s+i）。
作为一种实施例，步骤c中选取0.01≤P/P 0≤0.995范围内的数值，根据NLDFT密度函数理论法，通过ASiQ软件统计得到所述微孔、介孔和宏孔的孔体积。
作为一种实施例，步骤d中根据样品粉碎粒径由20目到200目时SSA/PV值的变化来判断样品中纳米级孔隙结构的变化。
本方案还提供了所述判断方法用于判断制样损伤过程对致密储层纳米级孔隙结构影响的应用。本方案提供的纳米级孔隙结构变化的判断方法通过表征致密岩石微观孔隙的比表面积、孔容和孔径分布等参数，通过样品不同粉碎粒径下SSA/PV的变化可定性判断致密储层纳米级孔隙在结构损伤（即样品粉碎）过程中产生的微观孔隙结构变化，避免传统的致密储层纳米级孔隙定性与定量研究方法中忽略制样过程中孔隙结构变化对研究结果产生的误差影响。若所述SSA/PV值随着粉碎目数变化而产生了较为明显的变化，则可判断出制样损伤过程对致密储层纳米级孔隙结构产生了不同程度的影响。
本方案还提供了所述判断方法用于判断致密储层纳米级孔隙结构样品的孔隙结构试验表征数据准确度中的应用。通过SSA/PV的变化率的大小判断出误差大小并进行矫正，可提高传统的致密储层纳米级孔隙定性与定量研究方法的准确性。
作为一种实施例，若样品粉碎粒径由20目到200目时，SSA/PV值变小且SSA/PV值随粉碎目数变化的相关性系数R 2在0.6以上，则说明所述致密储层纳米级孔隙结构样品的所述孔隙结构试验表征数据存在一定的误差需要矫正。不同样品的SSA/PV值随粉碎目数变化的相关性系数R 2也有所差别，说明了还与样品的类型有关。石油和天然气主要在致密储层中的纳米级孔缝***赋存与渗流，若致密储层样品粉碎粒径由20目到200目时SSA/PV值变小且SSA/PV值随粉碎目数变化的相关性系数R 2在0.6以上，则传统的致密储层纳米级孔隙结构试验表征数据的检测存在的误差会影响甚至误导对致密储层的孔缝***进行有效合理评价和判断，不利于油气资源的有效勘探和开发。
有益效果
本方案提供的通过建立氮气吸附量随P/P 0变化的等温吸附曲线，选择0.05<P/P 0<0.35范围内的等温吸附曲线，计算出单层吸附需要的氮气体积V m，再通过BET比表面积公式计算样品的比表面SSA，可得到不同粉碎目数下准确性较高的样品的比表面SSA值。根据NLDFT密度函数理论法，选择微孔、介孔和宏孔的临界P/P 0值分统计得到微孔、介孔和宏孔的孔体积，进而得到样品中不同类型孔隙的孔体积随粉碎粒径增加的变化情况。最后通过样品不同粉碎粒径下SSA/PV的变化判断纳米级孔隙结构变化。
本方案的判断方法准确检测出不同粉碎粒径下样品的比表面积SSA和总孔体积PV，既可判断制样损伤过程对致密储层样品中纳米级孔隙结构的影响，又可准确判断出传统的致密储层纳米级孔隙定性与定量研究方法中由于制样过程中孔隙结构变化对研究结果产生的误差影响，对密油气资源的勘探和开发具有重要意义。
 附图说明
图1是本发明实施例中1号样品在不同粉碎目数下的等温吸附曲线图；
图2是本发明实施例中2号样品在不同粉碎目数下的等温吸附曲线图；
图3是本发明实施例中3号样品在不同粉碎目数下的等温吸附曲线图；
图4是本发明实施例中4号样品在不同粉碎目数下的等温吸附曲线图；
图5是本发明实施例中5号样品在不同粉碎目数下的等温吸附曲线图；
图6是本发明实施例中6号样品在不同粉碎目数下的等温吸附曲线图；
图7是本发明实施例中6个样品在不同粉碎目数下SSA值的变化曲线图；
图8是本发明实施例中6个样品在不同粉碎目数下SAA的增长率曲线图；
图9是本发明实施例中6个样品在不同粉碎目数下微孔的孔体积变化曲线图；
图10是本发明实施例中6个样品在不同粉碎目数下介孔的孔体积变化曲线图；
图11是本发明实施例中6个样品在不同粉碎目数下宏孔的孔体积变化曲线图；
图12是本发明实施例中6个样品在不同粉碎目数下PV值的变化曲线图；
图13是本发明实施例中6个样品在不同粉碎目数下PV值的增长率曲线图；
图14是本发明实施例中6个样品在不同粉碎目数下SSA/PV值的变化曲线图。
 本发明的实施方式
实施例
1、设备
低温氮气吸附仪。
2、样品
钻井获得的页岩岩心，取6块页岩岩心样品，分别将其粉碎成20目、80目和200目。
3、判断方法
样品在温度为100℃下，真空脱气9h。通过计算脱气后样品管质量与脱气前空管的质量之差得到经过真空脱气后样品的质量W。将脱气后的样品置于液氮中，测定在预先设定的多个压力点下样品的氮气吸附量，获得样品等温吸附曲线，6块样品在不同粉碎目数下的等温吸附曲线如图1-6所示。
选取0.1≤P/P 0≤0.3范围内的等温吸附曲线，通过斜率s和截距i求得单层吸附需要的氮气体积V m，V m=1/（s+i）；利用BET比表面积公式计算样品的比表面SSA；所述BET比表面积公式为SAA=（V m×σ）/22400W，式中：σ为被吸附气体的截面积；W为真空脱气后的样品质量；6块样品在不同粉碎目数下的计算得到的比表面SSA值如表1所示，6块样品在不同粉碎目数下SSA值的变化曲线如图7所示。
表1 6块样品不同粉碎目数下的SSA值
样品编号 SSA值（m2/g） 20目 SSA值（m2/g） 80目 SSA值（m2/g） 200目
1 6.897 6.778 6.471
2 8.168 7.223 6.748
3 4.414 7.384 7.212
4 8.18 9.993 6.185
5 2.703 2.186 2.387
6 4.09 4.99 4.413
根据表1中样品不同粉碎目数下的SSA值计算出6块样品随粉碎目数的增加SAA的增量和增长率，计算结果如表2所示，SAA的增长率曲线如图8所示。
表2 SAA的增量和增长率
样品序号 20-80目SAA的增量 80-200目SAA的增量 20-80目SAA的增长率 80-200目SAA的增长率
1 -0.119 -0.307 -1.73% -4.53%
2 -0.945 -0.475 -11.57 -6.58%
3 2.790 -0.172 67.29% -2.33%
4 1.813 -3.808 22.16% -38.11%
5 -0.517 0.201 -19.13% 9.19%
6 0.900 -0.577 22.00% -11.56%
选取0.01≤P/P 0≤0.995范围内的数值，根据NLDFT密度函数理论法，通过ASiQ软件统计得出样品中微孔、介孔和宏孔的孔体积，进而得到样品中微孔、介孔和宏孔的总孔体积PV，6块样品在不同粉碎目数下的计算得到的微孔、介孔和宏孔的孔体积以及总孔体积PV值，计算得到的微孔、介孔和宏孔的孔体积值如表3所示，微孔的孔体积变化曲线如图9所示，介孔的孔体积变化曲线如图10所示，宏孔的孔体积变化曲线如图11所示，计算得到的总孔体积PV值如表4所示，PV值的变化曲线如图12所示。
表3 微孔、介孔和宏孔的孔体积
样品序号 粉碎目数 微孔孔隙体积cc/g 介孔孔隙体积cc/g 宏孔孔隙体积cc/g
1 20 0.00261 0.012181 0.003309
1 80 0.002831 0.013422 0.010147
1 200 0.002505 0.01237 0.006675
2 20 0.003489 0.011512 0.003069
2 80 0.002907 0.014975 0.012348
2 200 0.002646 0.016932 0.016272
3 20 0.001684 0.003281 0.002929
3 80 0.002899 0.011326 0.014595
3 200 0.002899 0.015749 0.013612
4 20 0.003625 0.0047156 0.0029594
4 80 0.003898 0.012406 0.022646
4 200 0.0025 0.019966 0.022064
5 20 0.0007351 0.0032649 0.000752
5 80 0.0007948 0.0052052 0.00671
5 200 0.0008545 0.0054411 0.0066644
6 20 0.001542 0.0054033 0.0017597
6 80 0.001916 0.010672 0.013082
6 200 0.001712 0.012501 0.017957
表4 6块样品不同粉碎目数下的总孔体积PV值
样品编号 PV值（cc/g） 20目 PV值（cc/g） 80目 PV值（cc/g） 200目
1 0.018100 0.026400 0.02155
2 0.018070 0.030230 0.03585
3 0.007894 0.028820 0.03226
4 0.011300 0.038950 0.04453
5 0.004752 0.012710 0.01296
6 0.008705 0.025670 0.03217
根据表3中样品不同粉碎目数下的总孔体积PV值计算出6块样品随粉碎目数的增加PV的增量和增长率，计算结果如表5所示，绘制出6块样品随粉碎目数的增加PV的增长率曲线如图13所示。
表5 PV的增量和增长率
样品序号 20-80目PV的增量 80-200目PV的增量 20-80目PV的增长率 80-200目PV的增长率
1 0.008300 -0.004850 45.86% -18.37%
2 0.012160 0.005620 67.29% 18.59%
3 0.020926 0.003440 265.09% 11.94%
4 0.027650 0.005580 244.69% 14.33%
5 0.007958 0.000250 167.47% 1.97%
6 0.016965 0.006500 194.89% 25.32%
由表1-2和表4-5中的数据以及图7-8和图12-13可知，随着样品粉碎目数由20目增加到80目再到200目，岩石样品孔缝***中，SSA与PV的变化情况如下：
1）SSA变化不大，PV增加较大。即在实验条件下，将页岩样品由20目粉碎至80目再到200目的过程中，对岩石样品中微孔的改变较少，因此，微孔级别孔隙的含量变化幅度不大。在制样过程中，反而随着粉碎目数的增加，增加了样品中介孔和宏孔的数量。宏孔数量增加的原因可以为两类：a、介孔受到破坏，孔隙被连通成为宏孔；b、产生了新的微裂缝，连通了先前封闭的孔隙。
2）从80目到200目的粉碎过程中，PV的增长率相比于20目到80目的变化过程较小。即在20目到80目这个粉碎过程对页岩样品的破坏大幅增加了孔缝***中的连通孔隙，使得PV值增长幅度较大。而从80目到200目这个对页岩样品的破环过程，新增加的连通孔隙较少，且微孔的变化不大，即20目到80目这个粉碎过程页岩样品的孔隙结构基本上被破坏，继续粉碎已无法产生更多的新孔缝。
因此，在样品粉碎制样过程中随着粉碎目数的增加，页岩样品中会产生了新的连通孔隙，这些连通孔隙通过增加的微裂缝开启，但这种增大的趋势并不是一直进行的，当粉碎粒径达到某一特定值时，样品的孔隙体积增长幅度减小，即此时，页岩样品的微观孔隙结构基本被破坏导致无法产生更多的新孔缝。
3）对SSA/PV数据进行统计分析，结果如表6所示。
表6 样品由20目到80目再到200目SSA/PV值及变化率
样品序号 20目SSA/PV 80目SSA/PV 200目SSA/PV 20-80目SSA/PV增长率 80-200目SSA/PV增长率
6 381.0497 256.7424 300.2784 -32.6223% 16.9571%
13 452.0199 238.9348 188.2287 -47.1406% -21.2217%
25 559.1589 256.2110 223.5586 -54.1792% -12.7443%
44 723.8938 256.5597 138.8951 -64.5584% -45.8625%
46 568.8131 171.9906 184.1821 -69.7633% 7.0885%
52 469.8449 194.3903 137.1775 -58.6267% -29.4319%
根据表6中的数据绘制出6块样品的SSA/PV在80目到200目之间的变化曲线，SSA/PV的变化曲线如图14所示。
由表6和图14可知，样品粉碎目数由20目增加到80目再到200目的过程中，SSA/PV值与粉碎目数具有一定的相关性（R 2变化范围在0.6-0.8），SSA/PV随粉碎目数一直保持减小的趋势。说明制样过程随着粉碎目数的增加，增加了孔隙***内部的连通孔隙，产生了新的孔缝，使得孔隙体积增加，对页岩岩心的纳米级孔隙结构产生了损伤。通过对比不同类型样品的SSA/PV值的变化率，可说明制样损伤程度使传统孔隙结构试验表征数据产生较大误差，影响油气勘探结果，需要对相关表征数据进行矫正。
上述检测结果进一步验证了用SSA/PV随目数的变化情况作为判断制样过程中致密储层微观孔隙结构变化以及判断致密储层纳米级孔隙结构样品的孔隙结构试验表征数据准确度的可行性。
以上所述仅为本方案的较佳实施例而已，并不用以限制本方案，凡在本方案的精神和原则之内所作的任何修改、等同替换或改进等，均应包含在本方案的保护范围之内。

Claims (10)

  1. 一种纳米级孔隙结构变化的判断方法，包括如下步骤：
    a、将真空脱气后的纳米级孔隙结构样品置于液氮中，在预先设定的多个压力值P下检测所述样品的氮气吸附量，获得所述样品的氮气吸附量随相对压力P/P 0变化的等温吸附曲线，所述P 0为吸附温度下氮气的饱和蒸气压；
    b、选取0.05≤P/P 0≤0.35范围内的等温吸附曲线，通过斜率s和截距i求得单层吸附需要的氮气体积V m；利用BET比表面积公式计算样品的比表面SSA；所述BET比表面积公式为SAA=（V m×σ）/22400W，式中：σ为被吸附气体的截面积；W为真空脱气后的样品质量；
    c、根据NLDFT密度函数理论法，分别计算出微孔、介孔和宏孔的孔体积，进而得到样品中所述微孔、介孔和宏孔的孔体积之和PV；
    d、计算样品不同粉碎粒径下SSA/PV的值，根据所述SSA/PV的值随粉碎目数增加的变化趋势判断粉碎过程对样品中纳米级孔隙结构变化的影响。
  2. 根据权利要求1所述的判断方法，其特征在于，步骤a中所述的真空脱气的温度为90-120℃。
  3. 根据权利要求1所述的判断方法，其特征在于，步骤a中所述的真空脱气的时间≥9h。
  4. 根据权利要求1所述的判断方法，其特征在于，步骤b中选取0.1≤P/P 0≤0.3范围内的等温吸附曲线，通过斜率s和截距i求得单层吸附需要的氮气体积V m。
  5. 根据权利要求1所述的判断方法，其特征在于，步骤b中所述V m与所述斜率s和所述截距i的关系为：V m=1/（s+i）。
  6. 根据权利要求1所述的判断方法，其特征在于，步骤c中选取0.01≤P/P 0≤0.995范围内的数值，根据NLDFT密度函数理论法，通过ASiQ软件统计得到所述微孔、介孔和宏孔的孔体积。
  7. 根据权利要求1所述的判断方法，其特征在于，步骤d中根据样品粉碎粒径由20目到200目时SSA/PV值的变化来判断所述样品中纳米级孔隙结构的变化。
  8. 权利要求1-7任一项所述的判断方法用于判断制样损伤过程对致密储层纳米级孔隙结构影响的应用。
  9. 权利要求1-7任一项所述的判断方法用于判断致密储层纳米级孔隙结构样品的孔隙结构试验表征数据准确度中的应用。
  10. 根据权利要求9所述的应用，其特征在于：若样品粉碎粒径由20目到200目时，SSA/PV值变小且SSA/PV值随粉碎目数变化的相关性系数R 2在0.6以上，则说明所述致密储层纳米级孔隙结构样品的所述孔隙结构试验表征数据存在误差且需要矫正。
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