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作者简介:

田伟(1987—),男,山东日照人,在读博士研究生,从事非常规油气渗流规律研究。联系电话:(010)89739037,E-mail:cupbkev-in@163.com。

中图分类号:TE122.2+3

文献标识码:A

文章编号:1009-9603(2019)04-0024-09

DOI:10.13673/j.cnki.cn37-1359/te.2019.04.004

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目录contents

    摘要

    综合利用高压压汞、恒速压汞和扫描电镜技术对吉木萨尔凹陷芦草沟组致密油储层岩石的微观孔隙结构进行研究。恒速压汞技术可以定量地区分样品的孔道和喉道,对大孔孔径测定准确,但是受限于较低的进汞压力,无法探测到较小的孔径。高压压汞技术因其较高的进汞压力可以准确地测定样品小孔隙的孔径。在共同的可测量区间内,通过插值计算方法求得两种测定技术的结合点,利用联合高压压汞与恒速压汞技术的方法计算获得了储层岩样的全尺度孔径分布曲线。结果表明:吉木萨尔凹陷芦草沟组致密油储层岩石样品的孔隙类型主要为粒间孔隙、残余孔隙及晶间微孔隙。样品的毛管压力曲线均不存在中间平缓段,孔隙结构复杂,分选性较差。计算得到的吉木萨尔凹陷芦草沟组致密油储层岩石孔径分布呈双峰态。根据LOUCKS等提出的孔分类法,样品孔径为0.07~ 1 μm的纳米孔非常发育,中孔孔径为 120~150 μm,微孔不发育。高压压汞技术与恒速压汞技术具有物理模型一致性,两者的结合是一种准确求取致密砂岩储层岩石全尺度孔径分布的有效方法。

    Abstract

    The microscopic pore structure of tight oil reservoir rocks in Lucaogou Formation was investigated using high pressure mercury intrusion(HPMI),rate-controlled mercury intrusion(RCMI),and scanning electron microscopy(SEM). RCMI can quantitatively distinguish the pore body and pore throat of the sample,and can accurately determine the pore size of the large pores. However,because of its lower mercury intrusion pressure,the RCMI cannot detect the small pores in the samples. HPMI with a higher mercury intrusion pressure can accurately determine the pore size of small pores of sam- ples. The connected points of two techniques were obtained using interpolation method in the common measurable interval, and then the combination of HPMI and RCMI was used to obtain the overall pore size distribution of the tight oil reservoir rocks of Lucaogou Formation. The results demonstrate that the types of pores of the tight oil reservoirs in Lucaogou Forma- tion are mainly intergranular pore,residual interparticle pores,and intercrystalline micropores. All the capillary pressure curves of these rock samples have no intermediate gentle section. The pore structure of these samples is complex,and the sorting is poor. The pore size distribution pattern of the tight oil reservoirs of Lucaogou Formation in Jimusaer Sag are bi- modal. According to the pore size classification scheme proposed by LOUCKS,the nanopores with radii ranging between 0.07 and 1 μm are abundant. The radii of mesopores are around 120-150 μm,and the micropores are rare compared to nanopores and mesopores. Because HPMI and RCMI are based on the same physical procedure-mercury intrusion,the com- bination of these two techniques is an effective method to accurately obtain the overall pore size distribution of the tight oil reservoir rocks.

  • 致密油是一种重要的非常规油气资源,在中国分布广泛、潜力巨大[1]。近年来,准噶尔盆地吉木萨尔凹陷二叠系芦草沟组致密油资源的勘探开发取得重大突破,成为中国目前致密油资源勘探开发的重点对象之一[2-4]。孔隙结构控制储层的物性特征[5-7],孔隙结构研究对于认识储层的储集空间和流体在储层内的渗流规律至关重要。吉木萨尔凹陷芦草沟组致密储层岩性复杂多变,孔隙类型多样,孔喉结构复杂,这对于利用常规手段研究其孔隙结构带来了很大挑战。目前关于其致密油储层的岩石和孔隙结构特征的研究还相对比较薄弱[8-9]

  • 致密油储层广泛发育纳米级孔隙,孔隙半径范围跨度比较大,展现出从纳米级到微米级的分布[10-11]。单一的孔隙结构研究方法不能准确地展现整个孔隙空间的全尺度孔径分布规律,具有很大的局限性[12]。目前,对于孔隙结构的研究,主要的测试技术有扫描电镜、氮气吸附、核磁共振、高压压汞和恒速压汞等技术。但是每一项技术都存在着无法规避的劣势,只能适应于对某一特定孔径范围内的孔隙结构进行研究,因此对于研究致密油储层孔隙半径的全尺度展布都有一定的不足之处。扫描电镜技术通过观察局部孔隙形态,给出孔隙结构的定性或者半定量分析,统计代表性差[13-15]。氮气吸附技术测试孔径范围有限,只能有效的反映微孔的孔径分布[16-17]。核磁共振技术受仪器最小回波间隔的限制,对微小孔隙的测试不够准确[18-19]。由于小孔喉对与其连通的大孔隙的屏蔽效应,高压压汞技术对大孔的孔径分布解释不够准确[20-21]。恒速压汞技术可以定量地区分孔道和喉道,但是其最高进汞压力较低,无法对孔隙结构进行全面测试[22]

  • 很多研究者尝试利用多种技术相结合的方法来研究致密储层的孔隙结构。SCHMITT 等利用氮气吸附与压汞技术相结合的方法研究了致密砂岩储层从纳米到微米尺度的孔隙结构[23];LAI 等结合高压压汞与核磁共振技术研究了四川盆地须家河组致密砂岩的微观孔隙结构[24];肖佃师等联合核磁共振和恒速压汞技术测定了致密砂岩孔喉结构[25]。但是从原理上来说,不同的测试技术使用的计算模型完全是不同的物理模型,计算得到的孔径全尺度分布仅仅是数学上的简单拼接,并没有明确的物理意义。利用联合高压压汞技术与恒速压汞技术的新方法可以准确地获得致密油储层的孔隙半径全尺度分布[26]。高压压汞技术用来测试小孔孔径分布,恒速压汞技术用来测试大孔孔径分布。因为这两种技术揭示的都是汞侵入岩样这一相同的物理过程,因此两种技术获得的孔径分布的结合具有明确的物理意义。为此,笔者通过改进联合高压压汞与恒速压汞技术的分析方法,系统研究了吉木萨尔凹陷芦草沟组致密油储层岩石的微观孔隙结构,获得了储层岩石孔隙的全尺度孔径分布,以期为正确认识储层特征、指导致密油资源的勘探开发提供依据。

  • 1 区域地质概况

  • 准噶尔盆地位于新疆的北部,是中国第二大内陆盆地,吉木萨尔凹陷总体位于准噶尔盆地的东部向东南缘位置。吉木萨尔凹陷经历了多期的构造运动,凹陷边缘的特征非常明显,东部临古西凸起,西部临北三台凸起,南部与阜康断裂带相临,北部临沙奇凸起与北三台凸起[2],其总体构造单元的面积可达 1 278 km2,是一个典型的西深东浅且西断东超的箕状凹陷。芦草沟组储层广泛分布在整个凹陷内,储层厚度超过 200 m 的面积可达 806 km2,呈现源-储一体和近源成藏的特征;储层纵向上整体含油,是凹陷内重要的致密油勘探开发层位。

  • 2 实验方法

  • 本次研究选取的3块致密油储层岩石样品来自 J174,J176 和 J31 这 3 口油井的现场取心,岩性主要是泥质粉砂岩、砂屑云岩、云质粉砂岩、云屑砂岩。

  • 扫描电镜技术 扫描电镜技术能提供岩石孔隙内充填物的矿物类型、大小、产状的直观资料,是研究孔隙结构的重要手段。将岩样抽提清洗干净,加工出新鲜面作为观察面,用导电胶固定在样品桩上,自然晾干,最后在真空镀膜机上镀金,使样品具有良好的导电性能。用细聚焦电子束在样品表面上由点到行(逐行)扫描,激发出能够反映样品表面特征的电信号,经探测器放大处理后显示出样品的电子图像。本次实验采用的仪器型号为 TESCANVEGAII LMU。

  • 高压压汞技术 高压压汞法以毛管束模型为基础,假设多孔介质是由直径大小不相等的毛管束组成。汞不润湿岩石表面,是非润湿相,相对来说,岩石孔隙中的空气或汞蒸气就是润湿相。往岩石孔隙中压注汞就是用非润湿相驱替润湿相。当注入压力高于与孔隙相对应的毛管压力时,汞即进入孔隙之中,此时注入压力就相当于毛管压力,所对应的毛管半径为孔隙半径,利用 WASHBURN 方程[27] 计算。本次实验仪器为美国康塔公司Poremas⁃ ter压汞仪。所有样品测试前均在105℃下烘干至恒重,压汞实验包括加压进汞、减压退汞过程,最高实验压力为200 MPa。

  • 恒速压汞技术 以非常低的恒定速度使汞进入岩石孔隙,就可以观察到系统毛管压力的变化过程。恒定低速使得进汞过程可以近似为准静态过程。在此过程中,界面张力与接触角保持不变;汞的前缘所经历的每一处孔隙形状的变化都会引起弯月面形状的改变,从而引起系统毛管压力的改变。根据进汞端弯月面在经过不同的微观孔隙形状时发生的自然压力涨落来确定孔隙的微观结构。恒速压汞技术能够把喉道和孔道分辨开来,分别测得孔道半径分布和喉道半径分布,真正得到具有力学意义的孔喉比参数。除了能够得到常规的毛管压力曲线外,还可以进一步分为喉道毛管压力曲线和孔道毛管压力曲线[28-29]。本次实验采用的仪器为美国 Coretest Systems 公司生产的 ASPE-730 型恒速压汞装置。该装置中内置的高精度泵可以维持低速、恒定的进汞速度(0.000 05 mL/min);高分辨率的压力感应及采集设备可以分辨 0.001 psi;高性能计算机可以对每个实验记录 30~50 万个数据点,并进行处理。

  • 3 实验结果

  • 3.1 高压压汞技术

  • 3.1.1 曲线特征

  • 从3块样品的压汞曲线(图1)可以看出,其毛管压力曲线均不存在中间平缓段,而是随着汞饱和度的增加,毛管压力不断上升,表明孔隙的分选性较差。根据毛管压力曲线特征,可将样品分为2类,Ⅰ 类包括 J31 和 J176,Ⅱ类包括 J174。Ⅰ类样品的平均排驱压力为4.12 MPa,高于Ⅱ类样品(0.47 MPa); Ⅱ类样品毛管压力曲线的阈压较低,表明其孔隙半径较大;所有样品的最大进汞饱和度均大于 90% (表1)。Ⅰ类样品的退汞效率较高,可能是以小喉道为主,大孔隙较少。Ⅱ类样品的退汞效率较低,残余汞饱和度为 64.78%。Ⅱ类样品捕集滞后现象严重,可能反映其孔隙结构主要为大孔小喉的墨水瓶孔形状。因此,高压压汞曲线计算得到的孔径分布可能会因为小孔喉对大孔隙的屏蔽效应而使得大孔隙的数量减少。

  • 图1 3块样品的高压压汞曲线

  • Fig.1 HPMI curves of three rock samples

  • 表1 3块样品的高压压汞实验结果

  • Table1 Experimental results of HPMI of three rock samples

  • 3.1.2 渗透率贡献

  • 致密砂岩中孔喉的大小及分布频率是影响储层渗流能力的重要因素[30-32]。根据高压压汞实验计算得到的孔喉分布频率与渗透率贡献值(图2)可知,对Ⅰ类样品J176渗流起主要贡献的孔隙孔径集中在 0.025~0.25 μm,提供了几乎全部的渗透率贡献值(图2a);渗透率分布峰位位于0.16 μm处,峰值为 44.050%。对 J31 渗流起主要贡献的孔隙孔径集中在 0.01~0.10 μm;渗透率分布峰位位于 0.10 μm 处,峰值为 54.535%(图2b)。对Ⅱ类样品 J174渗流起主要贡献的孔隙孔径集中在 0.1~1 μm;渗透率分布峰位位于1 μm处,峰值为51.901%(图2c)。结合样品的孔喉分布频率结果可以发现,致密油储层的渗透率主要由占据小部分孔隙体积的较大孔隙所贡献。

  • 图2 3块样品孔喉分布频率与渗透率贡献值

  • Fig.2 Pore throat distribution frequency and permeability contribution of three rock samples

  • 3.2 扫描电镜技术

  • 由扫描电镜图像可以看出,Ⅰ类样品孔隙类型主要包括粒间残余孔隙、晶间微孔隙,连通较差(图3a,3b);胶结物主要为粒间铁白云石、绿/蒙混层;常见自生长石。Ⅱ类样品孔隙发育,连通好。孔隙类型主要包括粒间孔隙及残余孔隙、晶间微孔隙,少量溶蚀孔隙(图3c)。胶结物主要为粒间绿泥石、绿/ 蒙混层、方解石。常见石英加大Ⅰ-Ⅲ级、自生长石,少量长石淋滤。

  • 3.3 恒速压汞技术

  • 3.3.1 曲线特征

  • 3块样品的恒速压汞实验得到的特征参数值见表2。通过恒速压汞实验,得到3块样品的总毛管压力曲线、孔隙进汞曲线和喉道进汞曲线。2 类样品的恒速压汞曲线表现出明显的不同。Ⅰ类样品的恒速压汞曲线特征(图4a,4b)是:总毛管压力曲线始终与喉道进汞曲线一致,最终的孔隙进汞饱和度非常低,排驱压力均大于 1 MPa。该类样品中较大的孔隙较少,喉道的控制起主要作用。这也与高压压汞实验的测试结果相一致。由于恒速压汞的最大进汞压力较低,仅为6.2 MPa,对于致密砂岩而言,该技术无法探测到样品中较小的孔隙,特别是对渗透性较差的样品,其局限性更加明显(图4b)。Ⅱ类样品的恒速压汞曲线特征(图4c)是:在进汞初期,总毛管压力曲线和孔隙进汞曲线相一致,说明汞首先进入阻力较小的大孔隙,此时喉道的影响并不明显。随着进汞压力增大,汞逐步进入由小喉道控制的孔隙,此时毛管压力急剧增大,但是孔隙的进汞饱和度却增长缓慢,孔隙进汞曲线急剧上翘,总毛管压力曲线与喉道进汞曲线趋势相一致,此时喉道起主要控制作用。进一步增大进汞压力,汞进一步占据喉道,喉道进汞饱和度增大,而孔隙进汞饱和度基本不再变化。此类样品的排驱压力低于 1 MPa,说明渗透性较好,这与实验测得的样品渗透率相一致。

  • 图3 3块样品的扫描电镜图像

  • Fig.3 SEM images of three rock samples

  • 表2 3块样品的恒速压汞实验结果

  • Table2 Experimental results of RCMI of three rock samples

  • 3.3.2 孔径分布

  • 通过恒速压汞实验计算得到样品的喉道半径与孔隙半径分布,由于样品J31的进汞饱和度较低,无法准确反映孔隙结构特征,因此未予展示。两类样品的喉道半径分布表现出明显的不同,样品 J176 的喉道半径主要为0.13~0.23 μm,平均为0.17 μm。样品 J174 的喉道半径主要为 0.4~1.4 μm,平均为 0.98 μm。与喉道半径分布不同,两类样品的孔隙半径分布相对均一。孔隙半径均为 100~200 μm,主峰主要分布在120 μm左右(图5)。

  • 3.3.3 孔喉连通关系

  • 致密砂岩孔隙结构的显著特征是大孔细喉,具有较大的孔喉比。从图6可以看出,样品 J174的孔喉比约为 100~300,平均为 221.7。样品 J176 的孔喉比约为800~1 000,平均为844.5。比较样品J174 和J176的孔喉比曲线可以看出,致密砂岩样品都具有较大的孔喉比,同时两类样品的孔喉比也存在非常大的区别,Ⅰ类样品的喉道极其细小,反映其渗透能力较差,渗透率较低。

  • 图4 3块样品的恒速压汞曲线

  • Fig.4 RCMI curves of three rock samples

  • 图5 2块样品的喉道和孔隙半径分布

  • Fig.5 Pore and throat size distribution of two rock samples

  • 图6 2块样品的孔喉比分布

  • Fig.6 Pore-throat ratio distribution of two rock samples

  • 4 讨论

  • 4.1 孔径全尺度展布

  • ZHAO等利用联合恒速压汞技术和高压压汞技术计算致密砂岩的孔径全尺度展布时,并未讨论两种技术计算得到的孔径分布的结合点问题,是在恒速压汞技术能够探测到的最小喉道半径处进行直接的拼接[26]。根据笔者的计算经验,在恒速压汞中由于数据区间的选取原因,使得更多的进汞体积累加到了最后一个数据区间,造成在 0.12 μm 处的数值偏大,因此得到的结果是微孔占优势的部分都是处于 0.12 μm 左右,这样计算得到的结果可能与实际不符。笔者将结合点选择为两种技术的共同可测量区间内的交点,其中交点利用插值的方法计算求得。根据实验的计算结果,高压压汞与恒速压汞的交点多发生在1 μm左右,因此交点落在高压压汞与恒速压汞的共同可测量区间内,在这一区间内计算选取的模型都是 WASHBURN 方程[27],因此两种测量技术的结合具有物理模型一致性。而且根据 LOUCKS等提出的孔分类方法[33],1 μm以下属于纳米孔区,在这一区间内高压压汞技术的测量在一定程度上是比较准确的,可以避免孔的屏蔽效应。因此笔者提出的计算孔径全尺度分布的方法可以更加合理准确地反映致密砂岩的孔隙空间分布规律。

  • 从本质上讲,孔径分布规律的表达主要有孔体积增量法和孔体积增量微分法 2 种方法[34],以进汞饱和度表达的孔径分布规律[26] 即为孔体积增量法,此时计算得到的孔径分布规律结果依赖于实验点间隔的选取。因为在一个大的孔径区间内,更多的体积会被累加。而孔体积增量微分法可以消除这一影响。因此选择以孔体积增量微分法来表达孔径分布规律。

  • 从两类样品的全尺度孔径分布曲线可以看出: Ⅱ类样品的孔径全尺度展布呈现出比较明显的双峰态,第 1 个峰出现在 0.1~1 μm 处,第 2 个峰出现在 150 μm 左右,小孔的分布范围较宽,大孔的分布范围较为集中(图7a);Ⅰ类样品的孔径全尺度展布呈现出弱双峰态,主峰出现在0.07 μm处,弱峰出现在 120 μm 处(图7b);两类样品中 10~100 μm 的孔隙都不发育。

  • 4.2 孔的分类

  • 不同于 IUPAC 的孔分类法,LOUCKS 等根据油气储层的实际,提出了一种更加适合于石油工业应用的新的孔分类法,孔径为 1 nm~1 μm 是纳米孔区,1~62.5 μm 是微孔区,62.5 μm~4 mm 是中孔区[33]。Ⅰ类样品以纳米孔为主,中孔不占优势;Ⅱ 类样品以纳米孔和中孔为主。两类样品中微孔都不发育。以上结果可能与样品中孔隙类型的发育情形有关。根据扫描电镜实验结果,2 类样品中粒间残余孔隙均较为发育,这些孔隙的孔径多大于 100 μm。2类样品中的纳米孔主要由晶间微孔隙所贡献,孔径在十几至几百纳米之间。相对于粒间残余孔隙及晶间微孔隙,样品中其他类型的孔隙数量较少,这可能是2类样品中微孔不发育的主要原因。

  • 图7 2块样品全尺度孔径分布曲线

  • Fig.7 Overall pore size distribution of two rock samples

  • 5 结论

  • 准噶尔盆地吉木萨尔凹陷芦草沟组致密油储层岩石样品的高压压汞曲线不存在中间平缓段,说明其孔隙结构复杂,孔隙分选性较差。孔隙类型主要为粒间孔隙及残余孔隙、晶间微孔隙,渗透率主要由占据小部分孔隙体积的较大孔隙所贡献。高压压汞可以比较准确地探测小孔隙,而恒速压汞可以比较准确的探测较大的孔隙,联合高压压汞与恒速压汞技术可以比较准确地计算得到致密砂岩储层的全尺度孔径分布。两种技术的结合点选择为共同可测量区间内的交点。样品的全尺度孔径分布曲线呈双峰态,小孔孔径主要为 0.07~1 μm 左右,大孔孔径主要为 120~150 μm 左右。根据LOUCKS 等提出的孔分类方法,研究区芦草沟组致密油储层岩石发育大量的纳米孔隙,微孔不发育。

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    • [18] YAO Y,LIU D,CHE Y,et al.Petrophysical characterization of coals by low-field nuclear magnetic resonance(NMR)[J].Fuel,2010,89(7):1 371-1 380.

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    • [20] KAUFMANN J,LOSER R,LEEMANN A.Analysis of cementbonded materials by multi-cycle mercury intrusion and nitrogen sorption[J].Journal of Colloid and Interface Science,2009,336(2):730-737.

    • [21] RIGBY S P,FLETCHER R S,RILEY S N.Characterisation of po⁃ rous solids using integrated nitrogen sorption and mercury poro⁃ simetry[J].Chemical Engineering Science,2004,59(1):41-51.

    • [22] XIAO D,LU Z,JIANG S,et al.Comparison and integration of ex⁃ perimental methods to characterize the full-range pore features of tight gas sandstone-a case study in Songliao Basin of China[J].Journal of Natural Gas Science and Engineering,2016,34:1 412-1 421.

    • [23] SCHMITT M,FERNANDES C P,WOLF F G,et al.Characteriza⁃ tion of Brazilian tight gas sandstones relating permeability and Angstrom-to micron-scale pore structures[J].Journal of Natural Gas Science and Engineering,2015,27:785-807.

    • [24] LAI J,WANG G,FAN Z,et al.Insight into the pore structure of tight sandstones using NMR and HPMI measurements[J].Energy & Fuels,2016,30(12):10 200-10 214.

    • [25] 肖佃师,卢双舫,陆正元,等.联合核磁共振和恒速压汞方法测定致密砂岩孔喉结构[J].石油勘探与开发,2016,43(6):961-970.XIAO Dianshi,LU Shuangfang,LU Zhengyuan,et al.Combining nuclear magnetic resonance and rate-controlled porosimetry to probe the pore-throat structure of tight sandstones[J].Petroleum Exploration and Development,2016,43(6):961-970.

    • [26] ZHAO Huawei,NING Zhengfu,WANG Qing,et al.Petrophysical characterization of tight oil reservoirs using pressure-controlled porosimetry combined with rate-controlled porosimetry[J].Fuel,2015,154:233-242.

    • [27] WASHBURN E W.The dynamics of capillary flow[J].Physical re⁃ view,1921,17(3):273.

    • [28] YUAN H H,SWANSON B F.Resolving pore-space characteris⁃ tics by rate-controlled porosimetry[J].SPE Formation Evaluation,1989,4(1):17-24.

    • [29] 王新江.恒速法-岩石毛管压力曲线测定标准方法探讨[J].中国石油和化工标准与质量,2013,33(20):79,83.WANG Xinjiang.Discussion on standard method for measuring capillary pressure curve of rock by constant velocity method[J].China Petroleum and Chemical Standard and Quality,2013,33(20):79,83.

    • [30] 宋磊,宁正福,孙一丹,等.联合压汞法表征致密油储层孔隙结构[J].石油实验地质,2017,39(5):700-705.SONG Lei,NING Zhengfu,SUN Yidan,et al.Pore structure char⁃ acterization of tight oil reservoirs by a combined mercury method [J].Petroleum Geology & Experiment,2017,39(5):700-705.

    • [31] 王凤娇,刘义坤,于苏浩.苏里格气田东区致密砂岩储层特征 [J].油气地质与采收率,2017,24(6):43-47,53.WANG Fengjiao,LIU Yikun,YU Suhao.Reservoir characteristics of tight sandstone in the eastern Sulige Gas Field[J].Petroleum Geology and Recovery Efficiency,2017,24(6):43-47,53.

    • [32] 朱永才,姜懿洋,吴俊军,等.吉木萨尔凹陷致密油储层物性定量预测[J].特种油气藏,2017,24(4):42-47.ZHU Yongcai,JIANG Yiyang,WU Junjun,et al.Quantitative pre⁃ diction of tight oil reservoir properties in Jumusar Depression[J].Special Oil & Gas Reservoirs,2017,24(4):42-47.

    • [33] LOUCKS R G,REED R M,RUPPEL S C,et al.Spectrum of pore types and networks in mudrocks and a descriptive classification for matrix-related mudrock pores[J].AAPG Bulletin,2012,96(6):1 071-1 098.

    • [34] MEYER K,KLOBES P.Comparison between different presenta⁃ tions of pore size distribution in porous materials[J].Fresenius’ Journal of Analytical Chemistry,1999,363(2):174-178.

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