石油与天然气地质 ›› 2024, Vol. 45 ›› Issue (6): 1720-1735.doi: 10.11743/ogg20240617

• 油气地质 • 上一篇    下一篇

四川盆地泸州区块五峰组-龙马溪组页岩气储层孔隙连通性特征及模式

赵圣贤1,2(), 刘勇3, 李博1,2(), 陈鑫1,2, 刘东晨1,2, 尹美璇1,2, 常莹1,2, 蒋睿1,2   

  1. 1.中国石油 西南油气田分公司 页岩气研究院，四川 成都 610051
    2.页岩气评价与开采 四川省重点实验室，四川 成都 610051
    3.中国石油 西南油气田分公司，四川 成都 610051
  • 收稿日期:2024-03-04 修回日期:2024-09-30 出版日期:2024-12-30 发布日期:2024-12-31
  • 通讯作者: 李博 E-mail:zhaoshengxian@petrochina.com.cn;lib_2021@petrochina.com.cn
  • 第一作者简介:赵圣贤（1987—），男，高级工程师，页岩气勘探与开发。E-mail： zhaoshengxian@petrochina.com.cn。
  • 基金项目:
    中国石油股份公司科技专项(2023ZZ21);中国石油西南油气田公司科研项目(20220304-19)

Characteristics and patterns of the pore connectivity in shale gas reservoirs in the Wufeng-Longmaxi formations， Luzhou block， Sichuan Basin

Shengxian ZHAO1,2(), Yong LIU3, Bo LI1,2(), Xin CHEN1,2, Dongchen LIU1,2, Meixuan YIN1,2, Ying CHANG1,2, Rui JIANG1,2   

  1. 1.Shale Gas Research Institute，Southwest Oil & Gasfield Company，PetroChina，Chengdu，Sichuan 610051，China
    2.Shale Gas Evaluation and Exploitation Key Laboratory of Sichuan Province，Chengdu，Sichuan 610051，China
    3.Southwest Oil & Gasfield Company，PetroChina，Chengdu，Sichuan 610051，China
  • Received:2024-03-04 Revised:2024-09-30 Online:2024-12-30 Published:2024-12-31
  • Contact: Bo LI E-mail:zhaoshengxian@petrochina.com.cn;lib_2021@petrochina.com.cn

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摘要：

依据传统靶体优选指标优选的页岩甜点仍然存在产量低的情况，诸多学者和工程师认为是孔隙连通性制约了产能。虽然水力压裂能够扩大页岩储层开发的有效面积，但页岩气从基质向水力裂缝中的运移完全取决于页岩孔隙的连通性。揭示四川盆地泸州区块页岩储层的孔隙连通性，建立页岩储层识别评价模式对页岩储层孔隙连通性判断和靶体优选具有重要指导作用。选取典型钻井样品，利用核磁共振（NMR）、压汞法（MIP）、聚焦离子束扫描电镜（FIB-SEM）和大面积图像拼接技术（MAPS）实验测试方法，以连通性孔隙度和连通性孔隙占比为依据，将泸州区块五峰组-龙马溪组页岩储层孔隙连通性划分为3级：A类储层（连通性孔隙体积>0.006 7 cm3/g；连通孔隙度>1.75 %）NMR孔径分布曲线基本呈三峰分布，小孔、中孔和大孔之间的连通性好，发育大量连通性气胀型有机质孔和大量无机矿物孔隙；B类储层（连通性孔隙体积=0.005 7 ~ 0.006 7 cm³/g；连通孔隙度=1.55 % ~ 1.70 %）NMR孔径分布曲线呈近似双峰分布，小孔和中孔之间的连通性较好，但中孔和大孔之间的连通性差，以发育孤立海绵状有机质孔隙为主，同时发育大量无机矿物孔隙；C类储层（连通性孔隙体积<0.005 7 cm³/g；连通孔隙度<1.55 %）NMR孔径分布曲线呈单峰分布，不同孔径孔隙之间的连通性差，有机质多不发育孔隙，无机矿物孔隙也不甚发育。研究结果表明：①不同孔径孔隙之间的合理配置有助于页岩孔隙连通性的改善，大量发育的无机矿物孔隙起到了沟通各局部连通的有机质孔隙的作用，共同构成了页岩的连通性孔隙网络。②为富泥硅质页岩相的孔隙连通性最好。③基于储层孔隙连通性特征与MAPS和FIB-SEM数据建立的页岩储层孔隙连通性定性-定量识别图版及揭示的3类页岩储层孔隙连通性模式，将为今后页岩储层孔隙连通性判断提供依据和为优质页岩储层靶体优选提供支撑。

关键词: 连通性模式, 孔隙连通性, 页岩气储层, 五峰组-龙马溪组, 泸州区块, 四川盆地

Abstract:

Some shale gas sweet spots preferentially selected based on traditional selection criteria are still of low production， the reason for which has been attributed to poor pore connectivity according to many researchers and engineers. Although hydraulic fracturing can enhance the effective exploitation area of shale reservoirs， the migration of shale gas from the matrix to hydraulic fractures depends solely on the pore connectivity within. For shale reservoirs in the Luzhou block of the Sichuan Basin， revealing the pore connectivity of the reservoirs and establishing reservoir identification and assessment model are crucial to guiding the pore connectivity assessment and selecting optimal target zones. In this study， we analyze typical shale samples collected from wells in the Luzhou block using experiments and tests， including nuclear magnetic resonance （NMR）， mercury intrusion porosimetry （MIP）， focused ion beam-scanning electron microscopy （FIB-SEM）， and large-field splicing scanning electron microscopy （MAPS）. Based on connected porosity and the proportion of connected pores， the shale reservoirs in the Wufeng-Longmaxi formations in the Luzhou block are categorized into types A， B， and C in terms of pore connectivity. Type A reservoirs with connected pore volume exceeding 0.006 7 cm3/g and connected porosity going beyond 1.75 %， generally exhibit trimodal NMR-derived pore size distribution curves， suggesting high connectivity among small pores， mesopores， and macropores， together with well-developed connected， gas-expansion-type， organic matter-hosted pores， and inorganic mineral-hosted pores. Type B reservoirs， as characterized by connected pore volume ranging from 0.005 7 to 0.006 7 cm3/g and connected porosity from 1.55 % to 1.70 %， exhibit approximate bimodal NMR-derived pore size distribution curves， reflecting high connectivity among small pores and mesopores but low connectivity among mesopores and macropores. The pores in these reservoirs are dominated by isolated， sponge-like organic matter-hosted pores， with the presence of substantial inorganic mineral-hosted pores. Type C reservoirs， featuring connected pore volume of less than 0.005 7 cm3/g and connected porosity below 1.55 %， manifest unimodal NMR-derived pore size distribution curves， reflecting an absence of connectivity among pores with different sizes. In these reservoirs， organic matter generally contains no pores， and inorganic mineral-hosted pores are also poorly developed. The results of this study indicate that a reasonable configuration of pores with varying sizes contributes to pore connectivity improvement in shales. The extensively distributed inorganic mineral-hosted pores play a role in connecting locally connected organic matter-hosted pores， ultimately forming the interconnected pore networks in the shales. Among various shale facies， clay-rich siliceous shales demonstrate the highest pore connectivity. The chart for the qualitative and quantitative identification of the pore connectivity of shale reservoirs， established based on reservoir connectivity characteristics， and MAPS and FIB-SEM data， along with the three classes of pore connectivity pattern， provide a basis for determining the pore connectivity of shale reservoirs and offer support for selecting the optimal target zones of high-quality shale reservoirs in the future.

Key words: connectivity pattern, pore connectivity, shale gas reservoir, Wufeng-Longmaxi formations, Luzhou block, Sichuan Basin

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