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作者简介:

姜瑞忠(1964—),男,江苏溧阳人,教授,博导,从事油气田开发研究与教学工作。联系电话:18678967281,E-mail:jrzhong@126.com。

中图分类号:TE32+8

文献标识码:A

文章编号:1009-9603(2019)04-0070-07

DOI:10.13673/j.cnki.cn37-1359/te.2019.04.010

参考文献 1
张东晓,杨婷云.页岩气开发综述[J].石油学报,2013,34(4):792-801.ZHANG Dongxiao,YANG Tingyun.An overview of shale-gas pro⁃ duction[J].Acta Petrolei Sinica,2013,34(4):792-801.
参考文献 2
唐颖,唐玄,王广源,等.页岩气开发水力压裂技术综述[J].地质通报,2011,30(2/3):393-399.TANG Ying,TANG Xuan,WANG Guangyuan,et al.Summary of hydraulic fracturing technology in shale gas development[J].Geo⁃ logical Bulletin of China,2011,30(2/3):393-399.
参考文献 3
王怒涛,陈仲良,祝明谦,等.页岩气压裂水平井产量递减组合模型分析[J].大庆石油地质与开发,2018,37(5):135-140.WANG Nutao,CHEN Zhongliang,ZHU Mingqian,et al.Analysis of the combined model for the production decline of the shale-gas fractured horizontal well[J].Petroleum Geology & Oilfield Devel⁃ opment in Daqing,2018,37(5):135-140.
参考文献 4
耿一凯,金振奎,赵建华,等.页岩储层孔隙类型控制因素研究——以川东焦石坝地区龙马溪组为例[J].石油实验地质,2017,39(1):71-78.GENG Yikai,JIN Zhenkui,ZHAO Jianhua,et al.Controlling fac⁃ tors of pore types in shale reservoirs:A case study from the Long⁃ maxi Formation in Jiaoshiba area,eastern Sichuan Basin[J].Pe⁃ troleum Geology & Experiment,2017,39(1):71-78.
参考文献 5
尉鹏飞,张金川,隆帅,等.四川盆地及周缘地区龙马溪组页岩微观孔隙结构及其发育主控因素[J].中国石油勘探,2016,21(5):42-51.WEI Pengfei,ZHANG Jinchuan,LONG Shuai,et al.Characteris⁃ tics and controlling factors of microscopic pore structure of Long⁃ maxi Formation in Sichuan Basin and its periphery[J].China Pe⁃ troleum Exploration,2016,21(5):42-51.
参考文献 6
李武广,杨胜来,殷丹丹,等.页岩气开发技术与策略综述[J].天然气与石油,2011,29(1):34-37.LI Wuguang,YANG Shenglai,YIN Dandan,et al.Development technology and strategy of shale gas[J].Natural Gas and Oil,2011,29(1):34-37.
参考文献 7
葛岩,万欢,黄志龙,等.页岩气储层微观孔隙结构影响因素及 “三元”耦合控制作用[J].油气地质与采收率,2018,25(5):17-23.GE Yan,WAN Huan,HUANG Zhilong,et al.Influencing factors and three-element coupled control on microscopic pore structure in shale gas reservoir[J].Petroleum Geology and Recovery Effi⁃ ciency,2018,25(5):17-23.
参考文献 8
JAVADPOUR F.Nanopores and apparent permeability of gas flow in mudrocks(shales and siltstone)[J].Journal of Canadian Petro⁃ leum Technology,2009,48(8):16-21.
参考文献 9
XIONG X,DEVEGOWDA D,VILLAZON M,et al.A fully-cou⁃ pled free and adsorptive phase transport model for shale gas reser⁃ voirs including non-Darcy flow effects[C].Texas:SPE Annual Technical Conference and Exhibition,2012.
参考文献 10
WANG J,LIU H,WANG L,et al.Apparent permeability for gas transport in nanopores of organic shale reservoirs including multi⁃ ple effects[J].International Journal of Coal Geology,2015,152(3):50-62.
参考文献 11
吴克柳,李相方,陈掌星.页岩纳米孔吸附气表面扩散机理和数学模型[J].中国科学:技术科学,2015,45(5):525-540.WU Keliu,LI Xiangfang,CHEN Zhangxing.The mechanism and mathematical model for the adsorbed gas surface diffusion innanopores of shale gas reservoirs[J].Scientia Sinica:Technologi⁃ ca,2015,45(5):525-540.
参考文献 12
吴明录,丁明才,姚军,等.考虑表面扩散的页岩气藏多级压裂水平井数值模拟[J].西安石油大学学报:自然科学版,2018,33(3):29-36.WU Minglu,DING Mingcai,YAO Jun,et al.Numerical simulation of multi-stage fracturing horizontal well in shale gas reservoir con⁃ sidering surface diffusion[J].Journal of Xi’an Shiyou University:Natural Science Edition,2018,33(3):29-36.
参考文献 13
赵谦平,王博涛,姜磊,等.页岩气多场耦合渗透率计算模型 [J].特种油气藏,2017,24(2):125-130.ZHAO Qianping,WANG Botao,JIANG Lei,et al.Computational model for multi-field coupling permeability of shale gas[J].Spe⁃ cial Oil & Gas Reservoirs,2017,24(2):125-130.
参考文献 14
JIANG Jiamin,YANG Jie.Coupled fluid flow and geomechanics modeling of stress-sensitive production behavior in fractured shale gas reservoirs[J].International Journal of Rock Mechanics and Mining Sciences,2018,101:1-12.
参考文献 15
XU Chunyuan,LI Peichao,LU Zhiwei,et al.Discrete fracture mod⁃ eling of shale gas flow considering rock deformation[J].Journal of Natural Gas Science & Engineering,2018,52:507-514.
参考文献 16
李凯,张浩,冉超,等.考虑应力敏感的页岩气产能预测模型研究——以川东南龙马溪组页岩气储层为例[J].西安石油大学学报:自然科学版,2016,31(3):57-61.LI Kai,ZHANG Hao,RAN Chao,et al.Productivity model of shale gas well with consideration of stress sensitivity:taking Long⁃ maxi Formation shale reservoir in southeastern Sichuan Basin as an example[J].Journal of Xi’an Shiyou University:Natural Sci⁃ ence Edition,2016,31(3):57-61.
参考文献 17
朱维耀,马东旭,朱华银,等.页岩储层应力敏感性及其对产能影响[J].天然气地球科学,2016,27(5):892-897.ZHU Weiyao,MA Dongxu,ZHU Huayin,et al.Stress sensitivity of shale gas reservoir and its influence on productivity[J].Natural Gas Geoscience,2016,27(5):892-897.
参考文献 18
糜利栋,姜汉桥,胡向阳,等.页岩气藏数值模拟方法评价及选择[J].中国科学:技术科学,2018,48(6):680-690.MI Lidong,JIANG Hanqiao,HU Xiangyang,et al.Evaluation and selection of numerical simulation methods for shale gas reservoirs [J].Scientia Sinica:Technologica,2018,48(6):680-690.
参考文献 19
徐春元.裂缝性油气藏离散裂缝数值模拟[D].合肥:中国科学技术大学,2017.XU Chunyuan.Discrete fracture modeling of fractured reservoirs [D].Hefei:University of Science and Technology of China,2017.
参考文献 20
LEE A L,GONZALEZ M H,EAKIN B E.The viscosity of natural gases[J].Journal of Petroleum Technology,1966,18(8):997-1 000.
参考文献 21
ZHU Guangpu,YAO J,SUN Hai,et al.The numerical simulation of thermal recovery based on hydraulic fracture heating technolo⁃ gy in shale gas reservoir[J].Journal of Natural Gas Science and Engineering,2016,28:305-316.
参考文献 22
姜瑞忠,原建伟,崔永正,等.基于TPHM的页岩气藏多级压裂水平井产能分析[J].天然气地球科学,2019,30(1):95-101.JIANG Ruizhong,YUAN Jianwei,CUI Yongzheng,et al.Produc⁃ tivity analysis of multifractured horizontal wells in shale gas reser⁃ voirs based on TPHM[J].Natural Gas Geoscience,2019,30(1):95-101.
参考文献 23
ZHAO Yulong,TANG Xuchuan,ZHANG Liehui,et al.Numerical solution of fractured horizontal wells in shale gas reservoirs con⁃ sidering multiple transport mechanisms[J].Journal of Geophysics and Engineering,2018,15(3):739-750.
参考文献 24
GENG Lidong,LI Gensheng,WANG Minsheng,et al.A fractal pro⁃ duction prediction model for shale gas reservoirs[J].Journal of Natural Gas Science and Engineering,2018,55:354-367.
参考文献 25
CAO Peng,LIU Jishan,LEONG Yee-Kwong.A fully coupled mul⁃ tiscale shale deformation-gas transport model for the evaluation of shale gas extraction[J].Fuel,2016,178:103-117.
目录contents

    摘要

    为了准确预测页岩气产能,指导实际生产,通过考虑岩石变形所造成的渗透率变化以及页岩气黏性流、表面扩散、Knudsen扩散等渗流机理,将地质力学效应与流体流动进行耦合,建立综合考虑应力敏感和页岩气多种渗流机理的数学模型,采用离散裂缝模型对地层微裂缝和水力裂缝进行描述,利用有限元方法进行求解。结果表明,在表面扩散与Knudsen扩散的作用下,页岩基质渗透率增加,使页岩气累积产气量增加,而应力敏感效应使得基质渗透率降低,从而导致累积产气量降低。表面扩散系数和 Langmuir体积越大或井底压力越低,页岩气累积产气量越高。对于 Langmuir体积越高的页岩气藏,通过降低井底压力进行开采,更有开发潜力。新建模型的模拟结果与实际历史生产数据拟合效果较好,验证了所建模型的准确性。

    Abstract

    In order to accurately predict the shale gas productivity and guide the actual production,in the consideration of the permeability change caused by rock deformation and the viscous flow,surface diffusion and Knudsen diffusion of shale gas,and by coupling the geomechanical effect with the fluid flow,a mathematical model that comprehensively considers the stress sensitivity and the various percolation mechanisms of shale gas was proposed. The discrete fracture model was used to describe the microfractures and hydraulic fractures in the formation,and it was solve by finite element method. The re- sults show that surface diffusion and Knudsen diffusion increase shale permeability and further increase the shale gas pro- duction. The stress-sensitive effect reduces the matrix permeability,resulting in a decrease in cumulative gas production. The larger surface diffusion coefficient and the Langmuir volume or the lower bottom hole pressure would increase the cu- mulative gas production of shale gas. For the shale gas reservoirs with a larger Langmuir volume,it is beneficial to reduce the pressure at the bottom of the well to reach a higher production potential. The simulation results of the model fit well with the actual historical production data,which verifies the correctness of the model.

  • 近年来,页岩气作为新型非常规能源受到世界各国的关注,页岩储层具有低孔低渗透的特性,开采必须进行压裂改造,水平井压裂技术及裂缝监测技术已经逐渐变得成熟。纳米级孔隙在页岩储层中占主导地位。通常,页岩气以游离态的形式存在于基质孔隙和裂缝中,而以吸附态的形式吸附在基质表面,因此,页岩气藏中特定的孔隙大小以及储气形式意味着页岩储层的渗流机理(黏性流、Knud⁃ sen扩散和表面扩散)应被全面考虑,这样才能使模拟更真实准确[1-7]

  • 针对表面扩散,JAVADPOUR 提出了基于表面扩散和Knudsen扩散线性叠加的页岩储层中气体流动的表观模型,并利用该模型模拟双连续页岩气藏[8]。XIONG 等分析了非 Darcy 流动效应和理想气体表面扩散对表观渗透率的影响[9]。WANG等讨论了多层吸附对表面扩散的影响以及表面扩散对表观渗透率的影响[10]。吴克柳等基于 Hwang模型,推导了页岩气表面扩散模型,并对影响表面扩散能力的因素进行了分析[11]。吴明录等基于吴克柳等的表面扩散模型,进行了页岩气藏多级压裂水平井数值模拟[12],证明了表面扩散对页岩气产量有很大的影响,但是所建模型缺乏对地层应力敏感的考虑,不能准确反映地层的实际情况。

  • 针对应力敏感效应,赵谦平等建立了考虑应力敏感的页岩气渗透率模型,并讨论了应力敏感对页岩气渗透率的影响[13]。JIANG等提出了完全耦合的流体流动和地质力学模型,用来模拟裂缝性页岩气藏中的复杂生产现象[14],但未考虑表面扩散对页岩气产能的影响。XU 等采用离散裂缝模型,研究了岩石变形对储层流动特性的影响,模型中考虑了由耦合地质力学得到的渗透率[15],同样,模型中未全面考虑页岩气的相关渗流机理。李凯等在幂律模型的基础上,建立了考虑应力敏感的页岩气产能预测模型,并确定了井的合理产量[16]。朱维耀等开展了应力敏感实验,并研究了应力敏感性对页岩气产能的影响,证明了在研究中必须考虑应力敏感[17]

  • 综上所述,尚未有人全面考虑页岩气黏性流、表面扩散及Knudsen扩散与应力敏感对页岩气产能的影响。为此,笔者通过耦合地质力学得到的页岩渗透率与考虑黏性流、表面扩散及 Knudsen 扩散得到的渗透率进行耦合,得到更为全面的页岩渗透率模型。离散裂缝模型可以更真实解释单个裂缝的特征[18],所以采用离散裂缝模型对微裂缝及水力裂缝进行描述,采用有限元求解,从而进行模拟研究,然后对相关因素进行敏感性因素分析,最后通过实例验证新建模型的准确性。

  • 1 页岩气渗流相关机理

  • 1.1 耦合地质力学

  • 在常规油气藏中,岩石的应力敏感性往往被忽略,但在页岩储层中,岩石的渗透率极低,以及异常高的孔隙压力会对岩石的变形产生显著影响,所以在页岩气开采过程中,孔隙压力降低将导致有效压力增加,从而使储层致密,降低了储层的孔隙度和固有渗透率;同时基质表面页岩气的解吸也会导致基质收缩,使得孔隙空间增大,从而造成渗透率增加。因此,有学者推导了耦合地质力学效应下的渗透率公式[1519],其表达式为:

  • Km1=Km0exp3Kp1+v3(1-v)p-p0-2E9(1-v)εs-εs0
    (1)
  • 页岩的吸附应变可以近似为 Langmuir 方程形式:

  • εs=εLppL+p
    (2)
  • 裂缝渗透率[15] 可以表示为:

  • Kf=Kf0exp3cfv1-vαBpf-p0
    (3)
  • 1.2 表面扩散

  • 表面扩散可以描述吸附气在孔隙中的运移,由表面扩散表征的页岩基质视渗透率[11-12] 为:

  • Ksf=ζmsDsCsμgpMg
    (4)
  • 其中:

  • ζms=ϕmτ1-1-radrt2
    (5)
  • Cs=4θMgπdM3NA
    (6)
  • θ=pp+pL
    (7)
  • Ds=Ds0×(1-θ)+12θ(2-θ)κ+12[H(1-κ)](1-κ)θ2κ1-θ+θκ22
    (8)
  • H(1-κ)=0 1κ1 0κ<1
    (9)
  • 1.3 页岩气黏度与压缩因子

  • 在页岩气开采过程中,温度与压力的变化将会影响气体的相关性质。传统的气体黏度模型已经不适用于页岩气的长期生产,LEE 等提出了计算气体黏度的相关公式[20],其表达式为:

  • K=(22.7+48.3)T1.5209+19000Mg+1.8TX=3.5+547.8T+10MgY=2.4-0.2Xμ=10-7KeX(0.001ρ)Y
    (10)
  • 压缩因子可以通过拟对比压力与拟对比温度计算[21],其计算式为:

  • Z=0.702e-2.5Tprppr2-5.524e-2.5Tprppr+0.044Tpr2-0.164Tpr+1.15
    (11)
  • 气体密度通过气体状态方程计算,其表达式为:

  • ρ=pMgZRT
    (12)
  • 1.4 页岩气吸附与解吸机理

  • 页岩中含有大量的有机质和黏土矿物,因此可以吸附大量的页岩气,一般用吸附气的体积含量来衡量页岩基质的吸附能力,一般用 Langmuir等温吸附定律来描述页岩气藏中基质表面吸附含量[22],其表达式为:

  • qad=ρrMgVstd×VLpp+pL
    (13)
  • 1.5 Knudsen扩散

  • 页岩气藏中,平均孔隙半径为 4~200 nm,与气体分子平均自由程相当,因此 Knudsen 扩散必须被考虑到气体的流动机制中,Knudsen 扩散产生的气体流量[18] 为:

  • Nk=-MgDkmCm=-MgDkmpmZRT=-ρmDkmpmpm
    (14)
  • 其中:

  • Dkm=4Km0ck2.81708Km0ϕmπRT2Mg
    (15)
  • 2 页岩气藏多级压裂水平井渗流模型

  • 2.1 物理模型

  • 如图1 所示,建立页岩气藏多级压裂水平井物理模型,取水平井上部分(下部分与其对称),四周为不渗透边界,使用离散裂缝描述天然裂缝和水力裂缝,建立综合考虑地质力学效应、Knudsen 扩散、表面扩散、吸附解吸的物理模型。其假设条件为: ①页岩储层为基质和离散天然裂缝双重介质。② 吸附气仅存在于基质表面,而游离气存在于基质孔隙、天然裂缝和水力裂缝中。③页岩气只有单一组分甲烷,且为等温渗流,不考虑重力作用。

  • 图1 页岩气双重介质离散裂缝模型

  • Fig.1 Dual media model of shale gas reservoir considering discrete fractures

  • 2.2 数学模型

  • 根据页岩气渗流相关机理及模型假设,采用质量守恒定律,分别建立基质、天然裂缝的连续性方程。

  • 2.2.1 基质

  • 在页岩基质中,页岩气以游离态的形式存在于基质孔隙中,以吸附态的形式吸附在页岩基质表面,所以建立页岩基质的连续性方程时,必须考虑页岩气黏性流动、Knudsen扩散、表面扩散和吸附解吸这些机理,根据质量守恒定律,得到的页岩基质的连续性方程为:

  • tρϕm+1-ϕmqad+-ρKmμmpm=-Q
    (16)
  • 则同时考虑页岩气Knudsen扩散、表面扩散、吸附解吸及应力敏感的页岩基质渗透率公式可表示为:

  • Km=Km2×Km1Km0
    (17)
  • 其中:

  • Km2=Km01+μmDkmpmKm0+ζmsDsCsμgpMg
    (18)
  • 2.2.2 天然裂缝

  • 在天然裂缝中,只有游离气存在,所以建立考虑应力敏感的页岩气扩散方程为:

  • ρϕft-ρKfμfpf=Q
    (19)
  • 2.2.3 初始条件与边界条件

  • 初始条件为:

  • pmt=0=pft=0=p0
    (20)
  • 边界条件为:

  • pmΓ1=phfΓ1=pw
    (21)
  • pmxx=L=pfxx=L=pmyy=h=pfyy=h
    (22)
  • 2.2.4 求解

  • 将基质和天然裂缝的数学模型进行联立,采用有限元方法进行求解,模型中所采用的参数主要包括:页岩基质初始渗透率为 2×10-18 m2,天然裂缝初始渗透率为 1×10-14 m2,泊松比为 0.25,地层初始压力为 25 MPa,井底压力为 3.5 MPa,杨氏模量为 8 GPa,Langmuir 压力为 5 MPa,Langmuir 体积为 0.003 m3 /kg,表面扩散系数为 8.29×10-9 m2 /s,吸附气拥塞率与迁移率之比为 0.5,页岩气平均摩尔质量为0.01 6 04 kg/mol,基质孔隙度为 0.05,纳米毛细管的迂曲度为 4.3,孔隙中心到吸附层距离为 1.9×10-10 m,平均孔隙半径为 1×10-9 m,地层温度为 423 K,页岩密度为 2 600 kg/m3,标况下页岩气摩尔体积为 0.022 4 m3 /mol,模拟时间为10 a,对模拟结果进行分析。

  • 3 结果与讨论

  • 3.1 地层压力分布

  • 通过对数学模型进行求解,可以得到开采过程中不同时间段的地层压力分布。由图2 可以看出,随着时间的增加,地层压力不断从多级压裂水平井附近沿着裂缝向边界降低,页岩气被采出。

  • 图2 不同时间段水平井附近地层压力变化

  • Fig.2 Formation pressure changes near horizontal wells at different time stages

  • 3.2 页岩气渗流机理对页岩气累积产气量的影响

  • 分析黏性流、表面扩散、Knudsen扩散和应力敏感对页岩气累积产气量的影响(图3)可以看出:表面扩散使得页岩气累积产气量增加近11.4%;Knud⁃ sen 扩散使页岩气累积产气量增加了 2.7%;而考虑应力敏感效应后页岩气累积产气量降低了约 3.24%;综合考虑页岩气黏性流、Knudsen扩散、表面扩散和应力敏感,比只考虑黏性流动时总产量增加了 20.2%。这是因为,在 Knudsen 扩散及表面扩散的作用下,页岩基质的视渗透率显著增加,使得页岩气更容易渗流,累积产气量增加;而应力敏感效应使页岩基质的渗透率随着地层压力降低而减小,导致页岩气的累积产气量减小。在实际生产中,应综合考虑这几种机理对产量的影响,缺一不可,从而更准确地预测页岩气的产量,指导生产。

  • 图3 不同页岩气渗流机理下的累积产气量

  • Fig.3 Cumulative gas production of different shale gas percolation mechanisms

  • 3.3 表面扩散系数对页岩气累积产气量的影响

  • 表面扩散系数对页岩气累积产气量的影响(图4)表明,随着表面扩散系数的增加,页岩气的累积产气量增加。这是由于,表面扩散系数越大,页岩气表面扩散表征的渗透率增加,从而页岩气的渗流能力增强,累积产气量增加。

  • 图4 不同表面扩散系数下的累积产气量

  • Fig.4 Cumulative gas production at different surface diffusion coefficients

  • 3.4 Langmuir体积对页岩气累积产气量的影响

  • Langmuir 体积对页岩气累积产气量的影响(图5)显示,Langmuir体积越大,累积产气量越大。这是由于,Langmuir 体积越大,页岩气吸附气含量就越高,从而在页岩气开采时,随着压力的降低,从基质表面解吸的吸附气含量就越高,从而表面扩散和 Knudsen扩散的吸附气就越多。

  • 图5 不同Langmuir体积下的累积产气量

  • Fig.5 Cumulative gas production at different Langmuir volumes

  • 3.5 井底压力对页岩气累积产气量的影响

  • 由图6可以看出,井底压力越低,页岩气的累积产气量越高。这是因为,井底压力降低,吸附在基质表面的吸附气越容易解吸,从而 Knudsen 扩散和表面扩散越容易,因此页岩气累积产气量越高。在实际生产中,应尽可能地降低井底压力,促进页岩气解吸,增加产能。

  • 图6 不同井底压力下的累积产气量

  • Fig.6 Cumulative gas production at different bottom hole pressures

  • 4 模型验证

  • 为了验证新建模型的准确性,选取Barnett页岩气藏一口井[23-25],相关参数包括:井底压力为 3.69 MPa,初始压力为 20.34 MPa,基质初始渗透率为 0.000 2 mD,裂缝初始渗透率为 50 mD,基质孔隙度为 0.03,储层温度为 352 K,Langmuir 体积为 0.002 72 m3 /kg,Langmuir压力为4.48 MPa,泊松比为 0.2。采用由黏性流、Knudsen扩散、表面扩散及应力敏感所表征的渗透率模型,模拟计算1 600 d的日产气量,并与 Barnett 页岩气藏实际日产气量进行比对。

  • 由图7 可知,本文模型模拟的结果与实际气藏的日产气量拟合效果较好,说明所建模型是准确的,表明在实际生产时,必须考虑 Knudsen 扩散、表面扩散和应力敏感对页岩气产量的影响,这样才能准确预测页岩气产能,指导开发。

  • 图7 模拟结果与实际产气量拟合结果

  • Fig.7 Comparison of simulation results with actual gas production results

  • 5 结论

  • 建立综合考虑页岩气黏性流、Knudsen扩散、表面扩散以及应力敏感的多级压裂水平井渗流模型,采用离散裂缝模型对微裂缝和水力裂缝进行描述,并进行有限元求解。

  • 表面扩散与 Knudsen 扩散使得页岩渗透率增加,从而使累积产气量增加,而应力敏感效应使得基质渗透率降低,从而使得累积产气量降低,所以实际生产中应综合考虑这几种因素对页岩气产能的影响,从而更准确预测产能,指导生产。

  • 表面扩散系数越大、Langmuir 体积越大及井底压力越低,页岩气累积产气量越高。Langmuir 体积越高的页岩气藏,通过降低井底压力开采,更有开发潜力。所建模型与实际历史生产数据拟合效果较好,验证了所建模型的准确性。

  • 符号解释

  • K m1——考虑岩石变形的基质渗透率,m2K m0——页岩基质初始渗透率,m2K p——孔隙的弹性模量,GPa;v ——泊松比;p ——地层压力,MPa;p 0——地层初始压力,MPa; E ——杨氏模量,GPa;εs ——页岩的吸附应变,即页岩气吸附 (解吸附)过程中岩石的相对变形;εs0——压力为 p 0 时页岩的吸附应变;εL——压力趋于无穷大时的吸附应变;p L—— Langmuir压力,当吸附气含量达到最大吸附量的50%时的地层压力,MPa;K f ——考虑岩石变形的天然裂缝渗透率,m2K f0——天然裂缝的初始渗透率,m2c f ——裂缝的压缩系数, 1/MPa;αB——BIOT 系数,本文取值近似为 1;p f ——裂缝压力,MPa;K sf ——表面扩散表征的页岩基质视渗透率,m2ζms ——页岩气藏纳米孔隙中的吸附气修正系数;D s ——表面扩散系数,m2 /s;C s ——吸附气的质量浓度,kg/m3μg——地层气体黏度,Pa·s;M g——页岩气平均气体摩尔质量,kg/ mol;ϕm——基质孔隙度;τ——纳米毛细管的迂曲度,无因次;r ad——孔隙中心到吸附层的距离,m;r t ——平均孔隙半径,m,θ ——天然气的覆盖率;d M——孔隙直径,m;N A—— 阿伏伽德罗常数,mol-1,其值为6.022×1023D s0——吸附气覆盖率为 0时的表面扩散系数,m2 /s;κ——吸附气拥塞率与迁移率之比;H (1-κ)——分段函数;T ——页岩储层的温度, K;XYK ——黏度表达式相关系数;μ——页岩气的黏度, mPa·s;ρ——页岩气的密度,kg/m3Z ——气体压缩因子; T pr ——天然气的拟对比温度;p pr ——天然气的拟对比压力; R ——理想气体常数,J/( kg·mol),取值为 8.314;q ad ——吸附气体积含量,kg/m3ρr ——页岩密度,m3 /kg;V std ——标况下页岩气摩尔体积,m3 /mol;V L ——Langmuir 体积,m3 /kg;N k —— Knudsen扩散产生的气体流量,kg/m3D km ——基质中扩散系数;C m ——气体摩尔浓度,mol/m3p m ——基质的压力,MPa; ρm——岩石的密度,kg/m3 c k ——常数,取值为 1;t ——模拟时间,a;K m ——同时考虑页岩气Knudsen扩散、表面扩散、吸附解吸及应力敏感的页岩基质渗透率,m2μm——基质中气体黏度,mPa·s;Q ——基质向裂缝的窜流量,kg/m3K m2—— 考虑黏性流、Knudsen 扩散及表面扩散的基质渗透率,m2Γ1——内边界条件;p hf ——水力裂缝压力,MPa;p w——井底压力,MPa;L ——储层长度,m;h ——储层高度,m。

  • 参考文献

    • [1] 张东晓,杨婷云.页岩气开发综述[J].石油学报,2013,34(4):792-801.ZHANG Dongxiao,YANG Tingyun.An overview of shale-gas pro⁃ duction[J].Acta Petrolei Sinica,2013,34(4):792-801.

    • [2] 唐颖,唐玄,王广源,等.页岩气开发水力压裂技术综述[J].地质通报,2011,30(2/3):393-399.TANG Ying,TANG Xuan,WANG Guangyuan,et al.Summary of hydraulic fracturing technology in shale gas development[J].Geo⁃ logical Bulletin of China,2011,30(2/3):393-399.

    • [3] 王怒涛,陈仲良,祝明谦,等.页岩气压裂水平井产量递减组合模型分析[J].大庆石油地质与开发,2018,37(5):135-140.WANG Nutao,CHEN Zhongliang,ZHU Mingqian,et al.Analysis of the combined model for the production decline of the shale-gas fractured horizontal well[J].Petroleum Geology & Oilfield Devel⁃ opment in Daqing,2018,37(5):135-140.

    • [4] 耿一凯,金振奎,赵建华,等.页岩储层孔隙类型控制因素研究——以川东焦石坝地区龙马溪组为例[J].石油实验地质,2017,39(1):71-78.GENG Yikai,JIN Zhenkui,ZHAO Jianhua,et al.Controlling fac⁃ tors of pore types in shale reservoirs:A case study from the Long⁃ maxi Formation in Jiaoshiba area,eastern Sichuan Basin[J].Pe⁃ troleum Geology & Experiment,2017,39(1):71-78.

    • [5] 尉鹏飞,张金川,隆帅,等.四川盆地及周缘地区龙马溪组页岩微观孔隙结构及其发育主控因素[J].中国石油勘探,2016,21(5):42-51.WEI Pengfei,ZHANG Jinchuan,LONG Shuai,et al.Characteris⁃ tics and controlling factors of microscopic pore structure of Long⁃ maxi Formation in Sichuan Basin and its periphery[J].China Pe⁃ troleum Exploration,2016,21(5):42-51.

    • [6] 李武广,杨胜来,殷丹丹,等.页岩气开发技术与策略综述[J].天然气与石油,2011,29(1):34-37.LI Wuguang,YANG Shenglai,YIN Dandan,et al.Development technology and strategy of shale gas[J].Natural Gas and Oil,2011,29(1):34-37.

    • [7] 葛岩,万欢,黄志龙,等.页岩气储层微观孔隙结构影响因素及 “三元”耦合控制作用[J].油气地质与采收率,2018,25(5):17-23.GE Yan,WAN Huan,HUANG Zhilong,et al.Influencing factors and three-element coupled control on microscopic pore structure in shale gas reservoir[J].Petroleum Geology and Recovery Effi⁃ ciency,2018,25(5):17-23.

    • [8] JAVADPOUR F.Nanopores and apparent permeability of gas flow in mudrocks(shales and siltstone)[J].Journal of Canadian Petro⁃ leum Technology,2009,48(8):16-21.

    • [9] XIONG X,DEVEGOWDA D,VILLAZON M,et al.A fully-cou⁃ pled free and adsorptive phase transport model for shale gas reser⁃ voirs including non-Darcy flow effects[C].Texas:SPE Annual Technical Conference and Exhibition,2012.

    • [10] WANG J,LIU H,WANG L,et al.Apparent permeability for gas transport in nanopores of organic shale reservoirs including multi⁃ ple effects[J].International Journal of Coal Geology,2015,152(3):50-62.

    • [11] 吴克柳,李相方,陈掌星.页岩纳米孔吸附气表面扩散机理和数学模型[J].中国科学:技术科学,2015,45(5):525-540.WU Keliu,LI Xiangfang,CHEN Zhangxing.The mechanism and mathematical model for the adsorbed gas surface diffusion innanopores of shale gas reservoirs[J].Scientia Sinica:Technologi⁃ ca,2015,45(5):525-540.

    • [12] 吴明录,丁明才,姚军,等.考虑表面扩散的页岩气藏多级压裂水平井数值模拟[J].西安石油大学学报:自然科学版,2018,33(3):29-36.WU Minglu,DING Mingcai,YAO Jun,et al.Numerical simulation of multi-stage fracturing horizontal well in shale gas reservoir con⁃ sidering surface diffusion[J].Journal of Xi’an Shiyou University:Natural Science Edition,2018,33(3):29-36.

    • [13] 赵谦平,王博涛,姜磊,等.页岩气多场耦合渗透率计算模型 [J].特种油气藏,2017,24(2):125-130.ZHAO Qianping,WANG Botao,JIANG Lei,et al.Computational model for multi-field coupling permeability of shale gas[J].Spe⁃ cial Oil & Gas Reservoirs,2017,24(2):125-130.

    • [14] JIANG Jiamin,YANG Jie.Coupled fluid flow and geomechanics modeling of stress-sensitive production behavior in fractured shale gas reservoirs[J].International Journal of Rock Mechanics and Mining Sciences,2018,101:1-12.

    • [15] XU Chunyuan,LI Peichao,LU Zhiwei,et al.Discrete fracture mod⁃ eling of shale gas flow considering rock deformation[J].Journal of Natural Gas Science & Engineering,2018,52:507-514.

    • [16] 李凯,张浩,冉超,等.考虑应力敏感的页岩气产能预测模型研究——以川东南龙马溪组页岩气储层为例[J].西安石油大学学报:自然科学版,2016,31(3):57-61.LI Kai,ZHANG Hao,RAN Chao,et al.Productivity model of shale gas well with consideration of stress sensitivity:taking Long⁃ maxi Formation shale reservoir in southeastern Sichuan Basin as an example[J].Journal of Xi’an Shiyou University:Natural Sci⁃ ence Edition,2016,31(3):57-61.

    • [17] 朱维耀,马东旭,朱华银,等.页岩储层应力敏感性及其对产能影响[J].天然气地球科学,2016,27(5):892-897.ZHU Weiyao,MA Dongxu,ZHU Huayin,et al.Stress sensitivity of shale gas reservoir and its influence on productivity[J].Natural Gas Geoscience,2016,27(5):892-897.

    • [18] 糜利栋,姜汉桥,胡向阳,等.页岩气藏数值模拟方法评价及选择[J].中国科学:技术科学,2018,48(6):680-690.MI Lidong,JIANG Hanqiao,HU Xiangyang,et al.Evaluation and selection of numerical simulation methods for shale gas reservoirs [J].Scientia Sinica:Technologica,2018,48(6):680-690.

    • [19] 徐春元.裂缝性油气藏离散裂缝数值模拟[D].合肥:中国科学技术大学,2017.XU Chunyuan.Discrete fracture modeling of fractured reservoirs [D].Hefei:University of Science and Technology of China,2017.

    • [20] LEE A L,GONZALEZ M H,EAKIN B E.The viscosity of natural gases[J].Journal of Petroleum Technology,1966,18(8):997-1 000.

    • [21] ZHU Guangpu,YAO J,SUN Hai,et al.The numerical simulation of thermal recovery based on hydraulic fracture heating technolo⁃ gy in shale gas reservoir[J].Journal of Natural Gas Science and Engineering,2016,28:305-316.

    • [22] 姜瑞忠,原建伟,崔永正,等.基于TPHM的页岩气藏多级压裂水平井产能分析[J].天然气地球科学,2019,30(1):95-101.JIANG Ruizhong,YUAN Jianwei,CUI Yongzheng,et al.Produc⁃ tivity analysis of multifractured horizontal wells in shale gas reser⁃ voirs based on TPHM[J].Natural Gas Geoscience,2019,30(1):95-101.

    • [23] ZHAO Yulong,TANG Xuchuan,ZHANG Liehui,et al.Numerical solution of fractured horizontal wells in shale gas reservoirs con⁃ sidering multiple transport mechanisms[J].Journal of Geophysics and Engineering,2018,15(3):739-750.

    • [24] GENG Lidong,LI Gensheng,WANG Minsheng,et al.A fractal pro⁃ duction prediction model for shale gas reservoirs[J].Journal of Natural Gas Science and Engineering,2018,55:354-367.

    • [25] CAO Peng,LIU Jishan,LEONG Yee-Kwong.A fully coupled mul⁃ tiscale shale deformation-gas transport model for the evaluation of shale gas extraction[J].Fuel,2016,178:103-117.

  • 参考文献

    • [1] 张东晓,杨婷云.页岩气开发综述[J].石油学报,2013,34(4):792-801.ZHANG Dongxiao,YANG Tingyun.An overview of shale-gas pro⁃ duction[J].Acta Petrolei Sinica,2013,34(4):792-801.

    • [2] 唐颖,唐玄,王广源,等.页岩气开发水力压裂技术综述[J].地质通报,2011,30(2/3):393-399.TANG Ying,TANG Xuan,WANG Guangyuan,et al.Summary of hydraulic fracturing technology in shale gas development[J].Geo⁃ logical Bulletin of China,2011,30(2/3):393-399.

    • [3] 王怒涛,陈仲良,祝明谦,等.页岩气压裂水平井产量递减组合模型分析[J].大庆石油地质与开发,2018,37(5):135-140.WANG Nutao,CHEN Zhongliang,ZHU Mingqian,et al.Analysis of the combined model for the production decline of the shale-gas fractured horizontal well[J].Petroleum Geology & Oilfield Devel⁃ opment in Daqing,2018,37(5):135-140.

    • [4] 耿一凯,金振奎,赵建华,等.页岩储层孔隙类型控制因素研究——以川东焦石坝地区龙马溪组为例[J].石油实验地质,2017,39(1):71-78.GENG Yikai,JIN Zhenkui,ZHAO Jianhua,et al.Controlling fac⁃ tors of pore types in shale reservoirs:A case study from the Long⁃ maxi Formation in Jiaoshiba area,eastern Sichuan Basin[J].Pe⁃ troleum Geology & Experiment,2017,39(1):71-78.

    • [5] 尉鹏飞,张金川,隆帅,等.四川盆地及周缘地区龙马溪组页岩微观孔隙结构及其发育主控因素[J].中国石油勘探,2016,21(5):42-51.WEI Pengfei,ZHANG Jinchuan,LONG Shuai,et al.Characteris⁃ tics and controlling factors of microscopic pore structure of Long⁃ maxi Formation in Sichuan Basin and its periphery[J].China Pe⁃ troleum Exploration,2016,21(5):42-51.

    • [6] 李武广,杨胜来,殷丹丹,等.页岩气开发技术与策略综述[J].天然气与石油,2011,29(1):34-37.LI Wuguang,YANG Shenglai,YIN Dandan,et al.Development technology and strategy of shale gas[J].Natural Gas and Oil,2011,29(1):34-37.

    • [7] 葛岩,万欢,黄志龙,等.页岩气储层微观孔隙结构影响因素及 “三元”耦合控制作用[J].油气地质与采收率,2018,25(5):17-23.GE Yan,WAN Huan,HUANG Zhilong,et al.Influencing factors and three-element coupled control on microscopic pore structure in shale gas reservoir[J].Petroleum Geology and Recovery Effi⁃ ciency,2018,25(5):17-23.

    • [8] JAVADPOUR F.Nanopores and apparent permeability of gas flow in mudrocks(shales and siltstone)[J].Journal of Canadian Petro⁃ leum Technology,2009,48(8):16-21.

    • [9] XIONG X,DEVEGOWDA D,VILLAZON M,et al.A fully-cou⁃ pled free and adsorptive phase transport model for shale gas reser⁃ voirs including non-Darcy flow effects[C].Texas:SPE Annual Technical Conference and Exhibition,2012.

    • [10] WANG J,LIU H,WANG L,et al.Apparent permeability for gas transport in nanopores of organic shale reservoirs including multi⁃ ple effects[J].International Journal of Coal Geology,2015,152(3):50-62.

    • [11] 吴克柳,李相方,陈掌星.页岩纳米孔吸附气表面扩散机理和数学模型[J].中国科学:技术科学,2015,45(5):525-540.WU Keliu,LI Xiangfang,CHEN Zhangxing.The mechanism and mathematical model for the adsorbed gas surface diffusion innanopores of shale gas reservoirs[J].Scientia Sinica:Technologi⁃ ca,2015,45(5):525-540.

    • [12] 吴明录,丁明才,姚军,等.考虑表面扩散的页岩气藏多级压裂水平井数值模拟[J].西安石油大学学报:自然科学版,2018,33(3):29-36.WU Minglu,DING Mingcai,YAO Jun,et al.Numerical simulation of multi-stage fracturing horizontal well in shale gas reservoir con⁃ sidering surface diffusion[J].Journal of Xi’an Shiyou University:Natural Science Edition,2018,33(3):29-36.

    • [13] 赵谦平,王博涛,姜磊,等.页岩气多场耦合渗透率计算模型 [J].特种油气藏,2017,24(2):125-130.ZHAO Qianping,WANG Botao,JIANG Lei,et al.Computational model for multi-field coupling permeability of shale gas[J].Spe⁃ cial Oil & Gas Reservoirs,2017,24(2):125-130.

    • [14] JIANG Jiamin,YANG Jie.Coupled fluid flow and geomechanics modeling of stress-sensitive production behavior in fractured shale gas reservoirs[J].International Journal of Rock Mechanics and Mining Sciences,2018,101:1-12.

    • [15] XU Chunyuan,LI Peichao,LU Zhiwei,et al.Discrete fracture mod⁃ eling of shale gas flow considering rock deformation[J].Journal of Natural Gas Science & Engineering,2018,52:507-514.

    • [16] 李凯,张浩,冉超,等.考虑应力敏感的页岩气产能预测模型研究——以川东南龙马溪组页岩气储层为例[J].西安石油大学学报:自然科学版,2016,31(3):57-61.LI Kai,ZHANG Hao,RAN Chao,et al.Productivity model of shale gas well with consideration of stress sensitivity:taking Long⁃ maxi Formation shale reservoir in southeastern Sichuan Basin as an example[J].Journal of Xi’an Shiyou University:Natural Sci⁃ ence Edition,2016,31(3):57-61.

    • [17] 朱维耀,马东旭,朱华银,等.页岩储层应力敏感性及其对产能影响[J].天然气地球科学,2016,27(5):892-897.ZHU Weiyao,MA Dongxu,ZHU Huayin,et al.Stress sensitivity of shale gas reservoir and its influence on productivity[J].Natural Gas Geoscience,2016,27(5):892-897.

    • [18] 糜利栋,姜汉桥,胡向阳,等.页岩气藏数值模拟方法评价及选择[J].中国科学:技术科学,2018,48(6):680-690.MI Lidong,JIANG Hanqiao,HU Xiangyang,et al.Evaluation and selection of numerical simulation methods for shale gas reservoirs [J].Scientia Sinica:Technologica,2018,48(6):680-690.

    • [19] 徐春元.裂缝性油气藏离散裂缝数值模拟[D].合肥:中国科学技术大学,2017.XU Chunyuan.Discrete fracture modeling of fractured reservoirs [D].Hefei:University of Science and Technology of China,2017.

    • [20] LEE A L,GONZALEZ M H,EAKIN B E.The viscosity of natural gases[J].Journal of Petroleum Technology,1966,18(8):997-1 000.

    • [21] ZHU Guangpu,YAO J,SUN Hai,et al.The numerical simulation of thermal recovery based on hydraulic fracture heating technolo⁃ gy in shale gas reservoir[J].Journal of Natural Gas Science and Engineering,2016,28:305-316.

    • [22] 姜瑞忠,原建伟,崔永正,等.基于TPHM的页岩气藏多级压裂水平井产能分析[J].天然气地球科学,2019,30(1):95-101.JIANG Ruizhong,YUAN Jianwei,CUI Yongzheng,et al.Produc⁃ tivity analysis of multifractured horizontal wells in shale gas reser⁃ voirs based on TPHM[J].Natural Gas Geoscience,2019,30(1):95-101.

    • [23] ZHAO Yulong,TANG Xuchuan,ZHANG Liehui,et al.Numerical solution of fractured horizontal wells in shale gas reservoirs con⁃ sidering multiple transport mechanisms[J].Journal of Geophysics and Engineering,2018,15(3):739-750.

    • [24] GENG Lidong,LI Gensheng,WANG Minsheng,et al.A fractal pro⁃ duction prediction model for shale gas reservoirs[J].Journal of Natural Gas Science and Engineering,2018,55:354-367.

    • [25] CAO Peng,LIU Jishan,LEONG Yee-Kwong.A fully coupled mul⁃ tiscale shale deformation-gas transport model for the evaluation of shale gas extraction[J].Fuel,2016,178:103-117.