渤中19-6孔店组砂砾岩孔隙结构和渗透率估算模型

宋晨; 杨兵; 张超谟; 朱博远; 张占松

doi:10.19509/j.cnki.dzkq.2022.0093

渤中19-6孔店组砂砾岩孔隙结构和渗透率估算模型

doi: 10.19509/j.cnki.dzkq.2022.0093

宋晨^1,,
杨兵²,
张超谟^1, ,,
朱博远¹,
张占松¹

1.
长江大学油气资源与勘探技术教育部重点实验室，武汉 430100
2.
中国石化华北油气分公司采气一厂，郑州 450006

基金项目:

国家科技重大专项 2017ZX05032-003-005

详细信息

作者简介:
宋晨(1997—)，女，现正攻读矿物学、岩石学、矿床学专业硕士学位，主要从事地球物理研究工作。E-mail: 390172641@qq.com

通讯作者:
张超谟(1962—)，男，教授，主要从事地球物理测井研究工作。E-mail: zhang7801@263.cn

中图分类号: TE122.23
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- 文章访问数: 1022
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出版历程
- 收稿日期: 2021-08-12

Investigation of pore structure and permeability estimation models of Kongdian Formation glutenites in the Bozhong 19-6 Gasfield

1.
Key Laboratory of Exploration Technologies for Oil and Gas Resources of Ministry of Education, Yangtze University, Wuhan 430100, China
2.
No.1 Gas Production Plant of Sinopec North China Oil and Gas Company, Zhengzhou 450006, China

摘要

摘要:
渤中19-6砂砾岩孔隙结构复杂，为提高渗透率的估算精度，需要从孔隙结构入手，找到与渗透率相关性最好的孔隙结构因素。以43块孔店组砂砾岩的孔隙结构和渗透率为研究对象，利用岩石铸体薄片确定发育的孔隙类型，通过高压压汞获取孔喉分布特征和孔隙结构参数。结合孔隙类型和孔隙结构参数分析孔隙结构和渗透率的关系，建立了基于孔隙结构参数的渗透率评价模型。研究表明，不同类型溶蚀孔隙的孔隙结构存在差异，粒内溶孔的孔隙结构最好，胶结物溶孔的孔隙结构最差。溶蚀孔隙类型发育不同，物性差异较大，以粒内溶孔为主且不发育胶结物溶孔的岩样物性最好。不同孔隙结构因素对渗透率控制程度不一致，其中基于孔喉大小、连通、配比和几何形状这4种因素建立的渗透率模型精度最高。渤中19-6气田孔店组砂砾岩粒内溶孔具有较大的孔喉半径和较好的连通性是促使该类岩石储集和渗流能力均较好的主要原因。平均孔喉半径、退汞效率、平均孔喉体积比和分形维数适用于估算孔隙结构复杂且(特)低孔渗的砂砾岩储层渗透率，以期为渤海湾盆地渤中凹陷砂砾岩储层的渗透率评价提供技术支持。
- 孔隙结构 /
- 渗透率 /
- 孔隙结构参数 /
- 高压压汞 /
- 砂砾岩 /
- 渤中19-6
Abstract:
The pore structure of glutenite in Bozhong 19-6 Gasfield is complicated. In order to improve the estimation accuracy of permeability, it is necessary to start with the pore structure and find the pore structure factor with the best correlation with permeability. Taking the pore structure and permeability of 43 Kongdian Formation glutenites as the research object, using rock casting thin slices to determine the pore types, and obtaining pore-throat size distribution characteristics and pore structure parameters through high-pressure mercury intrusion. Combining pore types and pore structure parameters to analyze the relationship between pore structure and permeability, a permeability evaluation model based on pore structure parameters was established. Studies have shown that there are differences in the pore structure between different types of dissolved pores. The pore structure of dissolved pores in the grain is the best, and the pore structure of dissolved pores in the cement is the worst. The physical properties of glutenite with different types of dissolution pores vary greatly. The rock samples with intragranular dissolution pores and no cement dissolution pores have the best physical properties. Different pore structure factors have inconsistent degrees of permeability control. Among them, the permeability model which based on pore throat size, connectivity, ratio and shape has the highest accuracy. The large pore throat radius and good connectivity of the dissolved pores in the glutenite grains of the Kongdian Formation of BZ19-6 Gasfield are the main reasons for the good reservoir and seepage capacity of this kind of rocks. The average pore throat radius, mercury removal efficiency, average pore throat volume ratio and fractal dimension are suitable for estimating the permeability of glutenite reservoirs with complex pore structures and (extremely) low porosity and permeability, in order to provide technical support for the permeability evaluation of glutenite reservoirs inBozhong Depression, Bohai Bay Basin.
- pore structure /
- permeability /
- pore structure parameters /
- high-pressure mercury injection /
- glutenite /
- Bozhong 19-6 Gasfield

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图 1 渤中19-6构造带位置^[26]及砂砾岩储层岩性

Figure 1. Location of Bozhong 19-6 structural belt and lithology of glutenite reservoirs

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图 2 恒速毛管压力进汞及进汞过程压力涨落

1~4.孔隙序号；Ⅰ~Ⅳ.压力降落等级；a~d.孔隙1~4的体积；e~f.喉道连接体积；rison.一个独立的喉道总是存在一个半径最小的截面，在汞到达这个最小截面之前毛管压力不断上升的过程; rhcon.汞突破最小的喉道进入较大喉道中所引起毛管压力突降的现象; subisou.在进汞压力未超过rhcon发生之前的压力时的过程

Figure 2. Pressure rises and falls during mercury intrusion and the mercury with drawal process

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图 3 孔隙度与渗透率交会图和不同类型样品的物性特征

Figure 3. Cross-plot of porosity versus permeability and different types of porosity and permeability

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图 4 铸体薄片观察的典型孔隙类型

a.1#，3 850.85 m，主要见粒内溶孔、胶结物溶孔和粒间溶孔；b.2#，4 050.5 m，主要见粒间溶孔、粒内溶孔和颗粒裂隙；c.3#，3 856.15 m，主要见粒内溶孔、粒间溶孔和颗粒裂隙；d.4#，3 850.47 m，主要见粒内溶孔、高岭石溶孔、粒间溶孔和颗粒裂隙；e.5#，4 047.63 m，主要见粒间溶孔、粒内溶孔；f.6#，3 856.84 m，主要见粒内溶孔、颗粒裂隙和粒间溶孔

Figure 4. Typical pore types observed in the thin sections

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图 5 从压汞数据获得的样品孔喉分布

Figure 5. Pore-throat size distribution obtained from high-pressure mercury injection

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图 6 压汞曲线和孔喉分布特征

Figure 6. Mercury injection curve and pore-throat size distribution characteristics

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图 7 孔隙结构影响渗流能力的机制示意图

Figure 7. Schematic diagram of the mechanism of pore structure affecting seepage capacity

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图 8 孔隙结构参数和渗透率的关系

Figure 8. Relationship between pore structure parameters and permeability

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图 9 不同渗透率模型估算渗透率与测试渗透率交会图

Figure 9. Cross-plot of the estimated and measured permeabilities for each permeability model

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图 10 孔隙结构对渗透率的控制程度

Figure 10. Effect of pore structure on permeability

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表 1 孔隙结构参数意义和分类

Table 1. Pore structure parameters and its physical meaning

符号	孔隙结构参数	物理意义	表示信息	参数计算方法
R_ave	平均孔喉半径/μm^[6]	衡量岩石的平均孔喉大小，反映物性好坏。其越大，储层物性越好	孔喉大小	$\sqrt{\left(\sum\limits_1^n r_i^{\prime 2} \cdot S_{\mathrm{hg}}\right) / \sum\limits_1^n \Delta S_{\mathrm{hg}}}$
R_apex	Swanson半径/μm^{[7, 18]}	岩石内部无效孔隙向有效连通的孔隙系统过渡时的孔喉半径大小，反映对流体流动作出贡献的有效孔隙空间的体积	孔喉大小	S_hg/P_c的最大值所对应的孔喉半径
S_p	分选系数^[8]	反映孔喉分布的分选性(集中程度)，表示以R_ave为中心的散布程度。高渗储层分选越好，渗流能力越强。低渗储层分选越差，渗流能力越强	孔喉分布	$\sqrt{\left[\sum\limits_1^n\left(r^{\prime}{ }_i-R_{\mathrm{ave}}\right)^2 \cdot \Delta S_{\mathrm{hg}}\right] / \sum\limits_1^n \Delta S_{\mathrm{hg}}}$
W_e	退汞效率/%^[9]	反映孔隙通过喉道相连接的墨水瓶现象。其越低，喉道对孔隙的控制作用越强，首先退出汞的喉道对孔隙空间连通性造成的破坏越大，渗流能力越差	孔喉连通	$\frac{S_{\max }-S_{\mathrm{r}}}{S_{\max }}$
R_pt	平均孔喉体积比^[10]	反映储集空间中孔隙和喉道的平均体积比。其越大，与孔隙相连的喉道半径越小，流体在孔隙空间中流动越容易发生卡断，不能形成连续相，渗流能力越差	孔喉配比	$\frac{{{S_{\rm{r}}}}}{{{S_{\max }} - {S_{\rm{r}}}}}$
D_f	分形维数^[5]	刻画孔喉几何形体复杂程度的定量参数。分形维数越大，孔隙和喉道的非均质性越强，渗流能力越差	孔喉几何	${S_{{\rm{hg}}}} \propto P_{\rm{c}}^{ - \left( {2 - {D_{\rm{f}}}} \right)}$
注：r′_i为某一进汞区间孔喉半径中值(μm)；ΔS_hg为r_i对应区间进汞饱和度增量(%)；S_r为残余汞饱和度(%)；S_max为最大汞饱和度(%)

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表 2 6块样品的孔渗和孔隙结构参数

Table 2. Porosity, permeability and pore structure parameters of the 6 samples

样品	深度/m	孔隙度/%	渗透率/10^-3 μm²	孔隙结构参数
样品	深度/m	孔隙度/%	渗透率/10^-3 μm²	R_ave/μm	R_apex/μm	S_p	W_e/%	R_pt	D_f
1#	3 850.84	9.80	0.05	0.373	0.720	0.641	19.610	4.099	2.276
2#	4 050.49	9.50	1.89	1.022	1.572	0.777	34.600	1.890	2.109
3#	3 856.16	9.90	2.41	1.288	2.237	1.203	35.808	1.793	2.104
4#	3 850.45	10.50	0.54	0.922	1.101	0.684	25.221	2.965	2.157
5#	4 047.65	10.60	1.74	0.825	1.564	0.745	36.966	1.705	2.124
6#	3 856.85	10.70	2.57	1.308	2.216	1.110	35.970	1.780	2.096

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表 3 考虑不同个数因素回归的渗透率模型以及相关性、均方根误差

Table 3. Permeability model considering the different factors, correlation coefficient and RMSE

模型编号	考虑因素	R²	均方根误差	回归模型
1	D_f	0.627 6	0.876 1	lgK=15.457-46.765·lgD_f
2	D_f, W_e	0.626 1	0.873 0	lgK=14.071-45.121·lgD_f+0.556·lgW_e
3	D_f, W_e, R_pt	0.633 8	0.865 6	lgK=17.860-1.401·lgR_pt-45.856·lgD_f-1.503·lgW_e
4	D_f, W_e, R_pt , R_ave	0.894 2	0.507 7	lgK=-11.595+1.809·lgR_ave+4.942·lgR_pt-9.174·lgD_f+8.720·lgW_e
5	D_f, W_e, R_pt, R_apex	0.845 5	0.613 7	lgK=3.142+1.110·lgR_apex+1.919·lgR_pt-28.473·lgD_f+3.618·lgW_e
6	D_f, W_e, R_pt, R_ave, S_p	0.889 1	0.527 0	lgK=-8.273+0.944·lgR_ave+4.770·lgR_pt-17.596·lgD_f+8.397·lgW_e+0.667·lgS_p
7	D_f, W_e, R_pt, R_ave, S_p, φ	0.830 7	0.649 1	lgK=-6.527+0.631·lgR_ave+4.266·lgR_pt-21.573·lgD_f+7.655·lgW_e+0.574·lgS_p+0.828·lgφ

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表 4 几种常用的压汞孔隙结构参数渗透率模型

Table 4. Several common permeability models built by pore structure parameters

常用回归模型	模型关键参数	岩性	渤中19-6回归公式	R²	均方根误差
Winland^[22]	φ，R₃₅	碎屑砂岩	lgK=-0.662+0.988·lgφ+0.646·lgR₃₅	0.742 8	0.755 7
Swanson^[18]	S_hg/P_c	砂岩，碳酸盐岩	lgK=-2.767+1.767·lg(S_hg/P_c)_max	0.777 6	0.864 4
Pittman^[20]	φ，R₂₅	砂岩	lgK=-0.577+0.621·lgφ+1.128·lgR₂₅	0.792 9	0.703 9
Capillary-Parachor^[19]	S_hg/P_c²	砂岩	lgK=-1.795+0.896·lg(S_hg/P_c²)_max	0.757 7	0.775 8
Rezaee^[35]	φ，R₅₀	碳酸盐岩	lgK=-2.236+2.611·lgφ+0.151·lgR₅₀	0.709 5	0.806 5
Rezaee^[21]	φ，R₁₀	致密砂岩	lgK=0.825-1.888·lgφ+2.768·lgR₁₀	0.781 3	0.929 4
Gao and Hu^[36]	R₅₀	砂岩、页岩	lgK=0.552+0.297·lgR₅₀	0.414 7	1.060 6
Liu^[37]	φ，S_hg/P_c²	砂岩	lgK=-2.025+0.431·lgφ+0.806lg(S_hg/P_c²)_max	0.768 7	0.752 9
本文	R_ave，R_pt，D_f，W_e	砂砾岩	lgK=-11.595+1.809·lgR_ave+4.942·lgR_pt-9.174·lgD_f+8.720·lgW_e	0.894 2	0.507 7
注：R₁₀为进汞饱和度为10%时对应的孔喉半径；R₅₀为进汞饱和度为50%时对应的孔喉半径；R₂₅为进汞饱和度为25%时对应的孔喉半径；Φ为孔隙度

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参考文献(37)

[1]	Chehrazi A, Rezaee R. A systematic method for permeability prediction, a Petro-Facies approach[J]. Journal of Petroleum Science and Engineering, 2012, 82/83(2): 1-16.
[2]	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. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201606014.htm Xiao D S, Lu S F, Lu Z Y, 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 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201606014.htm
[3]	韩玉娇, 周灿灿, 范宜仁, 等. 基于孔径组分的核磁共振测井渗透率计算新方法: 以中东A油田生物碎屑灰岩储集层为例[J]. 石油勘探与开发, 2018, 45(1): 170-178. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201801021.htm Han Y J, Zhou C C, Fan Y R, et al. A new permeability calculation method using nuclear magnetic resonance logging based on pore sizes: A case study of bioclastic limestone reservoirs in the A oilfield of the Mid-East[J]. Petroleum Exploration and Development, 2018, 45(1): 170-178 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201801021.htm
[4]	Lai J, Wang G W, Wang Z Y, et al. A review on pore structure characterization in tight sandstones[J]. Earth-Science Reviews, 2018, 177: 436-457. doi: 10.1016/j.earscirev.2017.12.003
[5]	王伟, 宋渊娟, 黄静, 等. 利用高压压汞实验研究致密砂岩孔喉结构分形特征[J]. 地质科技通报, 2021, 40(4): 22-30. doi: 10.19509/j.cnki.dzkq.2021.0402 Wan W, Song Y J, Huang J, et al. Fractal characteristics of pore-throat structure in tight sandstones using high-pressure mercury intrusion porosimetry[J]. Bulletin of Geological Science and Technology, 2021, 40(4): 22-30 (in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0402
[6]	汪新光, 张冲, 张辉, 等. 基于微观孔隙结构的低渗透砂岩储层分类评价[J]. 地质科技通报, 2021, 40(4): 93-103. doi: 10.19509/j.cnki.dzkq.2021.0429 Wang X G, Zhang C, Zhang H, et al. Classification and evaluation of low-permeability sand reservoir based on micro-pore structure[J]. Bulletin of Geological Science and Technology, 2021, 40(4): 93-103 (in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2021.0429
[7]	Wells J D, Amaefule J O. Capillary pressure and permeability relationships in tight gas sands[C]//Anon. Low permeability gas reservoirs symposium. [S. l. ]: Society of Petroleum Engineers, 1985.
[8]	窦文超, 刘洛夫, 吴康军, 等. 基于压汞实验研究低渗储层孔隙结构及其对渗透率的影响: 以鄂尔多斯盆地西南部三叠系延长组长7储层为例[J]. 地质论评, 2016, 62(2): 502-511. https://www.cnki.com.cn/Article/CJFDTOTAL-DZLP201602022.htm Dou W C, Liu L F, Wu K J, et al. Pore structure characteristics and its effect on permeability by mercury injection measurement: An example from Triassic Chang-7 reservoir, Southwest Ordos Basin[J]. Geological Review, 2016, 62(2): 502-511 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DZLP201602022.htm
[9]	Kaufmann J, Loser R, Leemann A. Analysis of cement-bonded materials by multi-cycle mercury intrusion and nitrogen sorption[J]. Journal of Colloid and Interface Science, 2009, 3(36): 730-737.
[10]	喻建, 马捷, 路俊刚, 等. 压汞-恒速压汞在致密储层微观孔喉结构定量表征中的应用: 以鄂尔多斯盆地华池-合水地区长7储层为例[J]. 石油实验地质, 2015, 37(6): 789-795. https://www.cnki.com.cn/Article/CJFDTOTAL-SYSD201506019.htm Yu J, Ma J, Lu J G, et al. Application of mercury injection and rate-controlled mercury penetration in quantitative characterization of microscopic pore structure of tight reservoirs: A case study of the Chang 7 reservoir in Huachi-Heshui area, the Ordos Basin[J]. Petroleum Geology and Experiment, 2015, 37(6): 789-795 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SYSD201506019.htm
[11]	Thien T, Nhan P, Natalie T. On permeability of corrugated pore membranes[J]. AIP Advances, 2020, 10: 045317. doi: 10.1063/5.0006017
[12]	Tang X L, Jiang Z X, Li Z, et al. The effect of the variation in material composition on the heterogeneous pore structure of high-maturity shale of the Silurian Longmaxi Formation in the southeastern Sichuan Basin, China[J]. Journal of Natural Gas Science and Engineering, 2015, 23: 464-473. doi: 10.1016/j.jngse.2015.02.031
[13]	Xi K, Cao Y, Haile B G, et al. How does the pore-throat size control the reservoir quality and oiliness of tight sandstones? The case of the Lower Cretaceous Quantou Formation in the southern Songliao Basin, China[J]. Marine and Petroleum Geology, 2016, 76: 1-15. doi: 10.1016/j.marpetgeo.2016.05.001
[14]	Clarkson C R, Solano N, Bustin R M. Pore structure characterization of North American shale gas reservoirs using USANS/SANS, gas adsorption, and mercury intrusion[J]. Fuel, 2013, 103: 606-616. doi: 10.1016/j.fuel.2012.06.119
[15]	Zhang L C, Lu S F, Xiao D S, et al. Characterization of full pore size distribution and its significance to macroscopic physical parameters in tight glutenites[J]. Journal of Natural Gas Science and Engineering, 2017, 38: 434-449. doi: 10.1016/j.jngse.2016.12.026
[16]	Guo X B, Huang Z L, Zhao L B, et al. Pore structure and multi-fractal analysis of tight sandstone using MIP, NMR and NMRC methods: A case study from the Kuqa Depression, China[J]. Journal of Petroleum Science and Engineering, 2019, 178: 544-558. doi: 10.1016/j.petrol.2019.03.069
[17]	Chen X J, Yao G Q, Herrero-Bervera E, et al. A new model of pore structure typing based on fractal geometry[J]. Marine and Petroleum Geology, 2018, 98: 291-305. doi: 10.1016/j.marpetgeo.2018.08.023
[18]	Swanson B F. A simple correlation between permeabilities and mercury capillary pressures[J]. Journal of Petroleum Technology, 1981, 33(12): 2498-2504.
[19]	Guo B Y, Ghalambor A, Duan S K. Correlation between sandstone permeability and capillary pressure curves[J]. Journal of Petroleum Science and Engineering, 2004, 43: 239-246.
[20]	Pittman E D. Relationship of porosity and permeability to various parameters derived from mercury injection-capillary pressure curves for sandstone[J]. The American Association of Petroleum Geologists Bulletin, 1992, 76(2): 191-198.
[21]	Rezaee R, Saeedi A, Clennell B. Tight gas sands permeability estimation from mercury injection capillary pressure and nuclear magnetic resonance data[J]. Journal of Petroleum Science and Engineering, 2012, 88/89: 92-99.
[22]	Kolodzie S. Analysis of pore throat size and use of the Waxman-Smits equation to determine OOIP in Spindle Field, Colorado[M]. [S. l. ]: National Academy of Sciences, 1980.
[23]	张铜耀, 郝鹏. 渤中凹陷深层特低孔特低渗砂砾岩储层储集空间精细表征[J]. 地质科技通报, 2020, 39(4): 117-124. doi: 10.19509/j.cnki.dzkq.2020.0415 Zhang T Y, Hao P. Fine characterization of the reservoir space in deep ultra-low porosity and ultra-low permeability glutenite in Bozhong Sag[J]. Bulletin of Geological Science and Technology, 2020, 39(4): 117-124 (in Chinese with English abstract). doi: 10.19509/j.cnki.dzkq.2020.0415
[24]	边会媛, 韩博华, 王飞, 等. 柴北缘牛东地区砂砾岩储层特征及分类评价[J]. 西安科技大学学报, 2020, 40(5): 148-155. https://www.cnki.com.cn/Article/CJFDTOTAL-XKXB202005020.htm Bian H Y, Han B H, Wang F, et al. Characteristics and classification of glutenite reservoirs in Niudong area, north margin of Qaidam Basin[J]. Journal of Xi'an University of Science and Technology, 2020, 40(5): 894-901. https://www.cnki.com.cn/Article/CJFDTOTAL-XKXB202005020.htm
[25]	万琳, 代黎明, 汤国民, 等. 湖相混积岩储层孔喉组合特征多尺度表征及评价[J]. 地球科学, 2020, 45(10): 337-348. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202010025.htm Wan L, Dai L M, Tang G M, et al. Multi-scale characterization and evaluation of pore-throat combination characteristics of lacustrine mixed rock reservoir[J]. Earth Science, 2020, 45(10): 337-348 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX202010025.htm
[26]	侯明才, 曹海洋, 李慧勇, 等. 渤海海域渤中19-6构造带深层潜山储层特征及其控制因素[J]. 天然气工业, 2019, 39(1): 33-44. https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201901005.htm Hou M C, Cao H Y, Li H Y, et al. Characteristics and controlling factors of deep buried-hill reservoirs in the BZ19-6 structural belt, Bohai Sea area[J]. Natural Gas Industry, 2019, 39(1): 33-44 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-TRQG201901005.htm
[27]	Soeder D J, Chowdlah P. Pore geometry in high and low permeability sandstones: Travis Peak Formation East Texas[J]. SPE Formation Evaluation, 1990, 5(4): 421-430.
[28]	张任风, 张占松, 张超谟, 等. 渤中19-6气田潜山变质岩储层类型特征与电成像测井识别[J]. 东北石油大学学报, 2019, 43(5): 58-65. https://www.cnki.com.cn/Article/CJFDTOTAL-DQSY201905007.htm Zhang R F, Zhang Z S, Zhang C M, et al. Reservoir type characteristics and identification by electrical imaging logging of buried hill in BZ19-6 Gas Field[J]. Journal of Northeast Petroleum University, 2019, 43(5): 58-65 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-DQSY201905007.htm
[29]	徐长贵, 于海波, 王军, 等. 渤海海域渤中19-6大型凝析气田形成条件与成藏特征[J]. 石油勘探与开发, 2019, 46(1): 25-38. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201901003.htm Xu C G, Yu H B, Wang J, et al. Formation conditions and accumulation characteristics of Bozhong 19-6 large condensate gas field in offshore Bohai Bay Basin[J]. Petroleum Exploration and Development, 2019, 46(1): 25-38 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK201901003.htm
[30]	Washburn E W. Note on a method of determining the distribution of pore sizes in a porous material[J]. Proceedings of the National Academy of Science, 1921, 7: 115-116.
[31]	熊生春, 储莎莎, 皮淑慧, 等. 致密油藏储层微观孔隙特征与可动用性评价[J]. 地球科学, 2017, 42(8): 1379-1385. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201708015.htm Xiong S C, Chu S S, Pi S H, et al. Micro-pore characteristics and recoverability of tight oil reservoirs[J]. Earth Science, 2017, 42(8): 1379-1385. https://www.cnki.com.cn/Article/CJFDTOTAL-DQKX201708015.htm
[32]	Sing K S, Everett D H, Haul R A W, et al. Reporting physisorption data for gas/solid systems with special reference to the determination of surface area and porosity[J]. Pure and Applied Chemistry, 1985, 57: 603-619.
[33]	熊钰, 傅希桐, 李骞, 等. 气体管流到达西流的缝高界限实验测试与理论计算[J]. 石油勘探与开发, 2022, 49(3): 538-547. https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK202203010.htm Xiong Y, Fu X T, Li Q, et al. Experimental test and theoretical calculation of the fracture height limit of gas pipe flow to Darcy flow[J]. Petroleum Explorationand Development, 2022, 49(3): 538-547(in Chinese with Englishabstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SKYK202203010.htm
[34]	肖忠祥, 肖亮, 张伟. 利用毛管压力曲线计算砂岩渗透率的新方法[J]. 石油物探, 2008, 47(2): 204-207. https://www.cnki.com.cn/Article/CJFDTOTAL-SYWT200802022.htm Xiao Z X, Xiao L, Zhang W. A new method for calculating sandstone permeability by using capillary pressure curves[J]. Geophysical Prospecting for Petroleum, 2008, 47(2): 204-207 (in Chinese with English abstract). https://www.cnki.com.cn/Article/CJFDTOTAL-SYWT200802022.htm
[35]	Rezaee M R, Jafari A, Kazemzadeh E. Relationships between permeability, porosity and pore throat size in carbonate rocks using regression analysis and neural networks[J]. Journal of Geophysics and Engineering, 2006, 3(4): 370-376.
[36]	Gao Z Y, Hu Q H. Estimating permeability using median pore-throat radius obtained from mercury intrusion porosimetry[J]. Journal of Geophysics and Engineering, 2013, 10(2): 025014.
[37]	Liu J Q, Zhang C M, Zhang Z S. Combine the capillary pressure curve data with the porosity to improve the prediction precision of permeability of sandstone reservoir[J]. Journal of Petroleum Science and Engineering, 2016, 139: 43-48.