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WANG WenKai, LIU ShiQi, SANG ShuXun, DU RuiBin, LIU YingHai. Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou[J]. Acta Sedimentologica Sinica, 2023, 41(6): 1890-1902. doi: 10.14027/j.issn.1000-0550.2023.105
Citation: WANG WenKai, LIU ShiQi, SANG ShuXun, DU RuiBin, LIU YingHai. Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou[J]. Acta Sedimentologica Sinica, 2023, 41(6): 1890-1902. doi: 10.14027/j.issn.1000-0550.2023.105

Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou

doi: 10.14027/j.issn.1000-0550.2023.105
Funds:

National Natural Science Foundation of China 42030810

National Natural Science Foundation of China 41972168

Fundamental Research Funds for the Central Universities 2023KYJD1001

  • Received Date: 2023-08-13
  • Accepted Date: 2023-10-23
  • Rev Recd Date: 2023-10-12
  • Available Online: 2023-10-23
  • Publish Date: 2023-12-10
  • In coal measure superimposed reservoir development, the reservoir combination affects the gas production effect of coal measure gas wells. Objective Owing to the large differences in rock mechanics and physical properties between coal measure superimposed reservoirs, the fluid migration law is more complicated than that of a single reservoir development. Numerical simulation is an effective method for solving this problem. Methods Taking the typical coal-sandstone-shale interbedded reservoir of the Longtan Formation in western Guizhou as the research object, considering the matrix contraction effect, effective stress effect, and the influence of interlayer fluid flow on reservoir fluid migration, as well as permeability and other physical parameters, a fluid-solid coupling mathematical model of the coal measure gas reservoir is established to conduct numerical simulations of coal measure gas production. The evolution of reservoir characteristic parameters such as pore pressure, matrix gas content, and permeability, as well as the impact of interlayer flow variation on gas production under different reservoir combination drainage scenarios, are analyzed. Results Compared with single-layer drainage, cumulative gas production is increased by 1.26, 1.42, and 1.62 times, respectively, under (coal + shale), (coal + sandstone), and entire reservoir drainage. There is interlayer energy and material transfer under the four types of reservoir combination drainage. There are clear differences in pore pressure, conductivity direction, matrix gas content, and permeability ratio of coal, sandstone, and shale reservoirs under different reservoir combination drainage. Conclusions The gas production effect is the best in the reservoir combination drainage of the entire reservoir, and the free methane in the sandstone reservoir is easier to produce, which effectively weakens the influence of vertical pore pressure difference between reservoirs, and is more conducive to the radial conduction of pore pressure in the superimposed reservoir, promoting the methane desorption in the coal and shale matrix, enhancing the matrix shrinkage, promoting the permeability rebound of the coal and shale reservoir, and thereby increasing overall gas production.
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  • Received:  2023-08-13
  • Revised:  2023-10-12
  • Accepted:  2023-10-23
  • Published:  2023-12-10

Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou

doi: 10.14027/j.issn.1000-0550.2023.105
Funds:

National Natural Science Foundation of China 42030810

National Natural Science Foundation of China 41972168

Fundamental Research Funds for the Central Universities 2023KYJD1001

Abstract: In coal measure superimposed reservoir development, the reservoir combination affects the gas production effect of coal measure gas wells. Objective Owing to the large differences in rock mechanics and physical properties between coal measure superimposed reservoirs, the fluid migration law is more complicated than that of a single reservoir development. Numerical simulation is an effective method for solving this problem. Methods Taking the typical coal-sandstone-shale interbedded reservoir of the Longtan Formation in western Guizhou as the research object, considering the matrix contraction effect, effective stress effect, and the influence of interlayer fluid flow on reservoir fluid migration, as well as permeability and other physical parameters, a fluid-solid coupling mathematical model of the coal measure gas reservoir is established to conduct numerical simulations of coal measure gas production. The evolution of reservoir characteristic parameters such as pore pressure, matrix gas content, and permeability, as well as the impact of interlayer flow variation on gas production under different reservoir combination drainage scenarios, are analyzed. Results Compared with single-layer drainage, cumulative gas production is increased by 1.26, 1.42, and 1.62 times, respectively, under (coal + shale), (coal + sandstone), and entire reservoir drainage. There is interlayer energy and material transfer under the four types of reservoir combination drainage. There are clear differences in pore pressure, conductivity direction, matrix gas content, and permeability ratio of coal, sandstone, and shale reservoirs under different reservoir combination drainage. Conclusions The gas production effect is the best in the reservoir combination drainage of the entire reservoir, and the free methane in the sandstone reservoir is easier to produce, which effectively weakens the influence of vertical pore pressure difference between reservoirs, and is more conducive to the radial conduction of pore pressure in the superimposed reservoir, promoting the methane desorption in the coal and shale matrix, enhancing the matrix shrinkage, promoting the permeability rebound of the coal and shale reservoir, and thereby increasing overall gas production.

WANG WenKai, LIU ShiQi, SANG ShuXun, DU RuiBin, LIU YingHai. Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou[J]. Acta Sedimentologica Sinica, 2023, 41(6): 1890-1902. doi: 10.14027/j.issn.1000-0550.2023.105
Citation: WANG WenKai, LIU ShiQi, SANG ShuXun, DU RuiBin, LIU YingHai. Production Simulation of Typical Types of the Coal Measure Superimposed Reservoir: A case study on the Longtan Formation, western Guizhou[J]. Acta Sedimentologica Sinica, 2023, 41(6): 1890-1902. doi: 10.14027/j.issn.1000-0550.2023.105
  • 中国煤系气资源丰富,占全国天然气地质资源量的60%以上[1]。煤系气的高效勘探开发对我国能源结构调整和国家能源安全保障具有重要意义[23]。在煤系气开发过程中,叠合型储层层间流体能量差异、储层力学性质与物性差异共同影响共采兼容性。目前的勘探开发地质理论与地质适配性开发技术尚处于探索起步阶段[47]。为支持煤系气开发示范工程,国内开展了许多相关研究。桑树勋等[8]针对华南地区龙潭组,提出了“层段优选、小层射孔、分段压裂、投球分压”的关键技术,实现了煤系叠合型气藏煤层气与致密砂岩气共采,并获得了工业气流。秦勇等[9]认为煤系气勘探开发效果取决于有机储层气与无机储层气之间合采兼容性及其地质控因,主要受合采产层能量状态、产层物性之间的差异影响。易同生等[10]基于煤系气示范工程,发现了松河井田煤系气主要赋存于龙潭煤系多个煤层及临近细砂岩、粉砂岩。中煤组煤层间细砂岩、粉砂岩厚度大且含气性好,是煤系气共探共采的主要目标层段。

    关于煤系气开采的数值模拟研究,申建等[11]建立了煤层与砂岩储层叠合的双层无窜流均质模型,探讨了两气共采效果的影响因素,但并未考虑储层间的物质传递;李勇等[12]建立了煤层气和致密气同井筒合采模型,实现了气井产能劈分,明确不同层位的气、水产出贡献,研究表明煤层与砂岩之间压力系统越相近,合采效果越好;李立功[13]建立了煤—页岩、煤—砂岩及煤—页岩—砂岩复合储层煤系气合采渗流模型,研究了层内动态滑脱流、层间窜流及其耦合作用对煤系气合采储层压力分布的影响,揭示了其随抽采时间、初始渗透率、层间渗透率比的变化规律,但忽略了水对煤系气排采的影响。Pan et al.[14]采用三重孔隙模型和伪混合气体方法,通过修改现有的煤层气模拟方法,实现了定量区分吸附气和游离气体的产量贡献,并通过应用于Barnett页岩的一个气体生产实例进行了测试。Liu et al.[15]通过对页岩气储层中气水运移以及持水行为的系统研究,将临界含水饱和度作为划分两个产气阶段的转折点。在第一阶段,气—水两相流主导着页岩气的生产。在第二阶段,产气速率则主要受到吸附相水流动的影响。综上所述,对于不同储层组合排采下煤系气渗流规律的对比研究相对较少,尚处于起步阶段,仍需进一步探索。

    在前人研究基础上,以黔西地区大河边区块煤系气开发示范工程的地质、排采等资料为基础,通过建立煤系叠合型气藏流固耦合数学模型并求解,探讨不同储层组合排采下储层孔隙压力,基质含气量、渗透率等叠合型储层特征参数动态变化规律及层间流动差异。研究成果为典型煤系叠合型气藏开发提供理论基础和技术支持。

  • 大河边区块位于贵州省六盘水市城区北部,构造上位于大河边向斜西翼中段,总体构造形态为一宽缓向斜,地层走向为南北向,构造复杂程度简单—中等,褶皱相对不发育,但整体断层较为发育(图1)。区内出露的地层由老至新有上二叠统峨眉山玄武岩组(P3 β)、龙潭组(P3l)、三叠系下统飞仙关组(T1 f)和永宁镇组(T1yn)、三叠系中统关岭组(T2 g)及上覆于上述地层之上的第四系(Q)。上二叠统龙潭组为大河边区块主要煤系,为一套海陆交互相含煤沉积。研究区先后经历了海西—燕山—喜马拉雅运动,形成了当今的构造组合,控制了含煤地层的保存程度与赋存状态[1617]

    Figure 1.  Structural outline map of the research area

  • 受构造活动与沉积作用影响,黔西地区多发育薄—中厚煤层群和煤层、泥岩、砂岩交互储层[8]。根据测井资料显示,该区域主要为单煤层—泥页岩—砂岩互层气藏、多煤层—泥页岩互层气藏、泥页岩砂岩互层气藏(图2)。煤层作为煤系气藏的主要气源,使得以煤层为核心的互层型气藏含气量远高于泥页岩—砂岩互层的气藏[18]

    Figure 2.  Gas reservoir distribution map of the production well in the Dahebian block

    以大河边区块生产井为例,龙潭组埋深839 m,厚度159 m,含煤12层,煤层总厚约33 m,单层厚度0.5~13.5 m,平均2.75 m,煤层含气量7.69~25.27 m3/t,平均17.46 m3/t。如图2所示,龙潭组埋深839~890 m层段煤层间距较大,煤层含气量13.08~19.99 m3/t,煤层间气测显示较为平缓,仅靠近煤层的砂岩、泥页岩气测显示较高,因此该层段气藏类型为单煤层—泥页岩—砂岩互层气藏;埋深915~960 m层段煤层间距较小,煤层含气量7.69~25.27 m3/t,煤层间气测峰值连续性较好,且煤层间泥页岩、砂岩均显示出较好的含气性,因此该层段气藏类型为多煤层—泥页岩—砂岩互层气藏。虽然煤层间泥页岩、砂岩相较煤层含气性较低,但作为补充性气藏,整体资源量可观,是具有较高的开发研究价值的气藏。

  • 贵州省拥有丰富的煤田地质资料,以及大量煤层气参数井和试采井,勘探程度较高,其中龙潭组已经获得较好含气发现、具有较大煤系气成藏潜力[19]。主采层段为C601、C409、C407、C406层段。

    大河边区块煤系井投产前首先进行加砂水力压裂改造,以Z1井为例,通过Fracpro PT压裂软件进行裂缝模拟,裂缝模拟结果表明,裂缝总高与支撑裂缝总高远超C601、C409、C406煤层厚度,裂缝已延伸至煤层顶底板(表1)。

    煤层编号煤层厚度/m射孔层段/m裂缝总高/m支撑裂缝总高/m裂缝半长/m支撑裂缝半长/m
    C6012.2934.5~936.711.611.4143.2140.2
    C40911.5992.3~994.6998.8~1 001.320.9/24.920.1/22.9168/158161.7/145.2
    C4061.5/1.41 009.0~1 011.31 013.2~1 014.69.7/9.18.6/7.9151.5/149.8148.1/145
  • 由于煤系气地质条件和各储层属性差异大,不同类型煤系气开采地质条件和产出特点各不相同。为了方便研究,根据煤系气在不同储层中赋存状态与运移机理的差异作如下假设[20]:(1)储层为“双孔”介质,且各向均质;(2)叠合型储层中CH4与水的渗流均遵循Darcy定律,且储层裂隙中水和CH4饱和;(3)CH4的吸附、解吸主要发生在煤与泥页岩基质孔隙中,基质中CH4扩散过程遵循Fick扩散定律,砂岩内CH4以游离态为主,不考虑吸附解吸;(5)CH4解吸收缩、有效应力会使煤与泥页岩基质体积发生变化,砂岩则不考虑基质解吸收缩效应;(6)忽略温度对开采的影响。

  • 考虑煤与泥页岩的基质收缩效应以及有效应力作用引起的应变,而砂岩中以有效应力为主,不考虑基质解吸收缩效应,因此煤、泥页岩与砂岩的应力场方程表示为[2122]

    G(1,2)ui, jj+G(1,2)1-2v(1,2)uj, ji+Fj=am(1,2)Pm(1,2),i+af(1,2)Pf(1,2),i+K(1,2)εa(1,2),i (1)
    G3ui, jj+G31-2v3uj, ji+Fj=am3Pm3,i+af 3Pf 3,i (2)

    式中:下标1、2、3分别表示煤、泥页岩、砂岩;其中i,j=x,y,z,表示三维坐标系中方向;G为剪切模量;αmαf 分别为基质与裂隙的Biot有效压力系数;PmPf 分别为煤基质与裂隙内CH4压力,Pa;Pf =SwPfw +SgPfgPfwPfg 分别为裂隙内水相与CH4压力,MPa;SwSg 分别为水相饱和度与CH4饱和度,且Sw +Sg =1;εa 为CH4吸附/解吸所引起的煤基质收缩应变。

  • 1) 基质内CH4流动方程

    在未开采前,叠合型储层中CH4处于动态平衡状态,基质中CH4压力等于裂隙中CH4压力。排采开始后,基质内CH4开始解吸。根据Fick扩散定律及煤与泥页岩基质内的CH4质量守恒方程,煤与泥页岩储层基质内的CH4运移方程可表示为[2324]

    tVL1Pm1PL1+Pm1ρs1MgRTsPs+Φm1MgRTPm1=- MgτRT(Pm1-Pf g1)tVL2Pm2PL2+Pm2ρs2MgRTsPs+Φm2MgRTPm2=- MgτRT(Pm2-Pf g2) (3)

    式中:下标1、2分别表示煤、泥页岩;VL 为Langmuir体积,m3/kg;PL 为Langmuir压力,ρs 为岩石骨架密度,kg/m3Mg 为CH4的摩尔质量,kg/mol;R为气体摩尔常数,R=8.314 J/(mol·K);Ts 为标准状况(标况)下温度,Ts =273.5 K;Ps 为标准大气压,Ps =0.1 MPa;Φm 为基质孔隙率,%;τ为CH4脱附时间,s。

    2) 裂隙内流体运移方程

    排采过程中,煤与泥页岩基质不断向裂隙提供CH4,煤与页岩基质可认为是裂隙内CH4的质量源,而砂岩中不考虑基质解吸扩散,则煤、泥页岩与砂岩裂隙内的CH4质量守恒方程可表示为[2326]

    tSg(1,2)Φf (1,2)MgPf g(1,2)RT+- Mg(Pf g(1,2)+b1)RTkrgk(1,2)μgPf g(1,2)=(1-Φf (1,2))MgτRT(Pm(1,2)-Pf g(1,2))tSw(1,2)Φf (1,2)ρw+- ρwkrwk(1,2)μwPf w(1,2)=0 (4)
    tSg3Φf 3MgPfg3RT+- Mg(Pf g3+b3)RTkrgk3μgPf g3=0tSw3Φf 3ρw+- ρwkrwk3μwPf w3=0 (5)

    式中:下标1、2、3分别表示煤、泥页岩、砂岩;Φf 为裂隙孔隙率,%;ρfg 为裂隙内气体密度,kg/m3ρw 为水相密度,kg/m3k为裂隙渗透率,10-3 μm2krgkrw 分别为气体与水相的相对渗透率;μwμg 分别为水相与气体的动力黏度,MPa·s;b1为克林肯伯格(Klinkenberg)因子,MPa。

    其中,气水相对渗透率表示为[2728]

    krg=1-Sw-Swr1-Swr-Sgr21-Sw-Swr1-Swr2krw=Sw-Swr1-Swr4 (6)

    式中:Swr 为束缚水饱和度;Sgr 为残余气饱和度。

  • 排采过程中受储层间力学性质与物性差异影响,不同储层间形成垂向压差,在垂向压差的作用下,流体通过层间流动向渗透性好的储层运移。根据Darcy定律,煤系气发生层间流动时流速uz 可表示为[13]

    uz=kc(Pf)μgdiv(Pz) (7)

    式中:kc 为层间渗透率;div(Pz )为压力梯度。

    因此层间流体流动方程可表示为:

    tρgΦcPf+zρgkcμgPz=0 (8)

    式中:Φc为层间孔隙度。

  • 考虑煤与泥页岩储层有效应力与吸附应变对孔隙度的影响,砂岩储层仅考虑有效应力,则煤、泥页岩与砂岩储层的孔隙度分别表示为[29]

                                                      Φ(1,2,3)=(1+s0(1,2,3))Φ0(1,2,3)+a(s(1,2,3)-s0(1,2,3))(1+s(1,2,3))Φ0(1,2,3)s(1,2)=εv(1,2)+PfKs(1,2)+εa(1,2)s3=εv3+PfKs3 (9)

    式中:下标1、2、3分别表示煤、泥页岩、砂岩;s0 为变量初始值,εa 为气体吸附引起的煤与泥页岩基质变形;εv 为体积应变;Ks 为体积模量。

    利用渗透率与孔隙度之间的立方定理,可推导出储层渗透率方程[30]

    k=k0ΦΦ03 (10)

    综上,式(1)—式(10)共同构成典型煤系叠合型气藏流固耦合数学模型。

  • 使用多物理场仿真模拟软件COMSOL Multiphy⁃ sics求解数学模型。通过COMSOL Multiphysics中的固体力学模块与PDE模块进行流固耦合模拟,其高效的计算性能和杰出的多场耦合分析能力为求解复杂的偏微分方程提供保障。

  • 以大河边区块Z1井的煤系储层为对象开展数值模拟。根据实际开发储层(C601、C409、C406)构建几何模型a(图3a),进行产气量历史拟合。为优化模拟方案,同时考虑到计算机运算效率,选取实际开发储层中代表性层段(煤—泥页岩—砂岩交互储层)作为方案二研究对象,构建几何模型b(图3b),依据对称性仅模拟四分之一区域。在COMSOL Multiphysics软件内通过自由四边形和扫掠定义功能对其进行网格划分。定义几何模型a自由四边形最小单元为尺寸0.02 m、最大单元尺寸为30 m,最大单元增长率为1.50,曲率因子0.60;几何模型b自由四边形最小单元为尺寸0.01 m、最大单元尺寸为20 m,最大单元增长率为1.50,曲率因子0.60。其中几何模型b,储层埋深为932 m,C601号煤层厚度2.2 m,顶板泥页岩厚度2.36 m;底板砂岩厚2.11 m。长宽为200 m×200 m,高为实际储层厚度6.67 m,气井半径0.12 m(图3c)。为便于观察煤系气排采模拟效果,选取XZ平面以及距离井口2 m处纵向截面分别为观测面a、观测面b,A(1,1,1)、B(1,1,3)、C(1,1,5)为观测点。

    Figure 3.  Numerical simulation geometric model schematic

  • 数值模拟所使用的关键参数主要来源于该井工程数据及相关参考文献(表2[3132]

    参数数值参数数值
    煤裂隙孔隙率/%2.200煤层密度/kg·m-31 470
    泥页岩裂隙孔隙率/%1.050泥页岩密度/kg·m-32 660
    砂岩裂隙孔隙率/%3.500砂岩密度/kg·m-32 950
    煤裂隙渗透率/(10-3 μm2)0.514水黏度系数Pa·s1×10-3
    泥页岩裂隙渗透率/(10-3 μm2)0.197甲烷黏度系数Pa·s1.84×10-5
    砂岩裂隙渗透率/(10-3 μm2)0.230煤Langmuir压力pL/MPa2.95
    煤的弹性模量/GPa3.000煤Langmuir体积VL/m3·kg-10.027 6
    泥页岩的弹性模量/GPa6.550泥页岩Langmuir压力pL/MPa1.01
    砂岩的弹性模量/GPa11.480泥页岩Langmuir体积VL/m3·kg-10.002 0
    煤泊松比/无量纲0.350克林肯伯格因子/MPa0.76
    泥页岩泊松比/无量纲0.280煤基质弹性模量/GPa7.340
    砂岩泊松比/无量纲0.120
  • 为研究不同储层组合排采对煤系气井产气效果的影响,结合实际气井生产特征,以原始煤系储层压力为初始条件(煤层及其顶底板在初始条件下,处于同一压力系统),P0=9.31 MPa;以实际气井井底流压为内边界条件;上边界为垂直向下的边界载荷,大小为10 MPa;左右边界为水平方向的边界载荷,大小为11 MPa;下边界为固定约束;储层初始水饱和度煤层为0.6。通过方案一对实际煤层气井开展生产历史拟合,验证数学模型的准确性。基于前述设定,方案二将模拟分为单煤层排采、(煤+砂岩)排采、(煤+泥页岩)排采以及全层段(煤+砂岩+泥页岩)排采(表3)。

    模拟方案储层组合排采压力/MPa模拟时长/d
    方案一(几何模型a)实际排采实际井底流压1 000
    方案二(几何模型b)单层排采(煤层)0.51 000
    (煤+砂岩)排采0.51 000
    (煤+泥页岩)排采0.51 000
    全层段(煤+砂岩+泥页岩)排采0.51 000
  • 由生产井CH4实测日产气量历史拟合结果可以看出,模拟日产气量与实测日产气量拟合度较高,误差8.68%,验证了数学模型的准确性(图4),为后续方案二的研究提供依据。

    Figure 4.  CH4 production history matching of the simulation well

  • 随时间推移,不同储层组合排采下煤系气的日产气量均是先升高再降低(图5)。在单层排采、(煤+泥页岩)排采、(煤+砂岩)排采、全层段排采的过程中,煤系气的最大日产气量分别为424.5 m3/d、540.6 m3/d、575.2 m3/d和666.1 m3/d(图5a),累积产气量分别为340 793.98 m3、429 668.72 m3、484 029.90 m3、551 116.42 m3。与单层排采相比,(煤+泥页岩)排采、(煤+砂岩)排采、全层段排采下,煤系气最大日产气量分别提高了1.27倍、1.36倍和1.57倍,累计产气量分别提高了1.26倍、1.42倍、1.62倍。

    Figure 5.  Gas production effect of different reservoir combinations

    在单层排采、(煤+泥页岩)排采、(煤+砂岩)排采、全层段排采的过程中,煤层的最大日产气量分别为424.5 m3/d、443.5 m3/d、403.7 m3/d和404.0 m3/d(图5b,c)。与(煤+砂岩)排采、全层段排采相比,单层排采下,煤层日产气量高于两者。这是由于在单层排采下砂岩层中气体在垂向孔隙压差下向煤层运移,并在径向孔隙压差下从煤层段产出。当砂岩层参与排采后,砂岩层中垂向孔隙压差减小,径向孔隙压差增大,因此气体更多地从砂岩层段产出。但煤层的日产气量仍远高于砂岩层与泥页岩层,为产气主要储层。砂岩的日产气量则高于泥页岩层,且在排采前期砂岩层中游离气迅速产出,使得(煤+砂岩)排采、全层段排采在排采前期的总日产气量高于另外两种排采方式。

  • 随着煤系气排采的进行,各储层孔隙压力不断变化。受储层组合及不同储层物性差异影响,煤、泥页岩和砂岩的储层孔隙压力变化与传导方向均存在明显差异。

    在排采第200 d,四种储层组合排采下均出现煤储层孔隙压力下降值大于泥页岩储层孔隙压力下降值的现象(图6),进而导致煤储层与泥页岩、砂岩储层之间形成垂向孔隙压力差,孔隙压力由泥页岩、砂岩储层高孔隙压力区向煤储层低孔隙压力区传导。压力梯度作为煤系气运移的主要动力,在储层间孔隙压差的影响下,煤系气的运移方向也由泥页岩、砂岩储层高孔隙压力区向煤储层低孔隙压力区运移。

    Figure 6.  Pore pressure conduction direction of the 200 d reservoir discharged by different reservoir combinations

    由距离井筒2 m处纵向储层孔隙压力动态分布可以看出,不同储层组合排采下,煤、泥页岩和砂岩储层孔隙压力均随排采时间而出现不同程度的下降(图7)。单层排采下,煤层孔隙压力始终低于泥页岩与砂岩。在排采结束时,储层间最大孔隙压力差为0.41 MPa、最小孔隙压力为3.70 MPa。(煤+泥页岩)排采下,煤层孔隙压力始终低于泥页岩与砂岩。由于泥页岩层参与排采,其储层孔隙压力相较砂岩层更易形成径向传导,因此泥页岩层孔隙压力始终低于砂岩层。在排采结束时,储层间最大孔隙压力差为0.36 MPa、最小孔隙压力为3.81 MPa。(煤+砂岩)排采下,泥页岩储层孔隙压力始终高于煤与砂岩,而砂岩储层孔隙压力则呈现出先低于煤层后高于煤层的现象。产生该现象的主要原因是砂岩层参与排采后游离气迅速产出,孔隙压力传导相较以吸附气为主的煤层更快。在排采结束时,储层间最大孔隙压力差为0.42 MPa、最小孔隙压力为3.55 MPa。全层段排采下,在排采结束时,储层间最大孔隙压力差为0.06 MPa,最小孔隙压力为3.55 MPa。

    Figure 7.  Vertical dynamic distribution of reservoir pore pressure under different reservoir combination drainages

    在垂向孔隙压差的影响下,其孔隙压力传导方向与气体运移方向呈现出由泥页岩层、砂岩层向煤层传递的趋势(图6,7)。相较于单层排采,多储层组合的排采方式能够有效降低层间垂向孔隙压差,减缓储层间的垂向孔隙压力传导,促进整体储层径向孔隙压力下降,进而提升产气量。

  • 在不同储层组合排采下,煤与泥页岩基质含气量均表现出随生产时间延长而逐渐降低的变化趋势(图8)。由于煤储层与泥页岩储层自身含气量以及孔隙度、渗透率等存在差异,导致两种储层含气量的减少量呈现显著差异。

    Figure 8.  Matrix gas content extracted from different reservoir combinations

    在排采结束时,单层排采下,煤储层含气量减少5.77 m3/t、泥页岩储层含气量减少0.20 m3/t;(煤+泥页岩)排采下,煤储层含气量减少5.60 m3/t、泥页岩储层含气量减少0.23 m3/t;(煤+砂岩)排采下,煤储层含气量减少6.10 m3/t、泥页岩储层含气量减少0.22 m3/t;全层段排采下,煤储层含气量减少6.12 m3/t、泥页岩储层含气量减少0.25 m3/t。

    在(煤+砂岩)排采与全层段排采下,煤储层含气量减少量大于单层排采与(煤+泥页岩)排采。其主要原因是在砂岩层参与排采的情况下,在排采初期砂岩层中游离气在径向孔隙压差下迅速产出,形成垂向孔隙压差,进而影响煤层孔隙压力传导,加快煤层中的甲烷解吸扩散。此外,由于泥页岩层没有较好的渗透通道,在泥页岩层参与排采的情况下,储层孔隙压力下降较为缓慢,对煤储层的影响相对较小。

    综上所述,在全层段的储层组合排采下,煤与泥页岩储层孔隙压力传导效率提高,更有利于煤与泥页岩基质内甲烷解吸扩散。与另外三种储层组合排采相比,煤与泥页岩储层含气量减少量均有所增加,更利于产量的提高。

  • 随着排采的进行,煤层渗透率比例呈现先降后升的趋势(图9a)。由于排采初期煤储层孔隙压力快速下降,但基质解吸量较少,有效应力作用大于基质收缩作用,导致初期煤储层渗透下降。随着煤基质解吸量不断增加,基质收缩作用增强,渗透开始回升,排采后期回升幅度逐渐下降。在不同储层组合排采下,煤层渗透率比例出现回升的时间点与回升值存在明显差异。单层排采下,煤层渗透率比例在50 d时达到最小值0.983后开始回升,在1 000 d时回升至1.070;(煤+泥页岩)排采下,煤层渗透率比例在60 d时达到最小值0.984后开始回升,在1 000 d时回升至1.065;(煤+砂岩)排采下,煤层渗透率比例在30 d时达到最小值0.984后开始回升,在1 000 d时回升至1.083;全层段排采下,煤层渗透率变化规律与(煤+砂岩)排采下几乎一致。根据上述变化可以看出,在全层段排采与(煤+砂岩)排采下,有助于煤层渗透率比例更早出现回升且提高回升值。结合不同储层组合排采下煤基质含气量变化可以看出,在(煤+泥页岩)排采下,煤基质解吸量小于单层排采下煤基质解吸量,进而导致(煤+泥页岩)排采下煤层基质收缩作用弱于单层排采下煤层基质收缩效应。

    Figure 9.  Variation of the permeability ratio for different reservoir assemblage drainage monitoring points

    泥页岩储层渗透率比例随排采时间变化趋势与煤层渗透率比例变化趋势相似(图9b)。但受力学性质与物性差异影响,渗透率比例回升时间点晚于煤层,且回升值低于煤层。单层排采下,泥页岩渗透率比例在130 d时达到最小值0.966后开始回升,在1 000 d时回升至0.979;(煤+泥页岩)排采下,泥页岩层渗透率比例在110 d时达到最小值0.966后开始回升,在1 000 d时回升至0.985;(煤+砂岩)排采下,泥页岩层渗透率比例在110 d时达到最小值0.967后开始回升,在1 000 d时回升至0.983;全层段排采下,泥页岩层渗透率比例在60 d时达到最小值0.966后开始回升,在1 000 d时回升至0.992。在有泥页岩参与排采的情况下,泥页岩层孔隙压力更易传导,从而促进泥页岩层中甲烷解吸,增强基质收缩作用。但由于泥页岩层解吸能力较弱,导致基质收缩作用弱于有效应力作用,因此泥页岩层整体渗透率比例仍低于初始值。

    砂岩层排采过程中渗透率比例呈现先快速下降后缓慢下降的现象(图9c)。这主要是由于砂岩层渗透率主要受有效应力作用影响。随排采进行,有效应力作用逐渐增强,导致砂岩层渗透率比例下降。在有砂岩层参与排采的情况下,砂岩层孔隙压力下降更快,有效应力作用更显著,砂岩层渗透率比例下降更快。

    综上所述,全层段的储层组合排采更有利于煤层与泥页岩渗透率回升,但易导致砂岩层渗透率快速降低,因此对于叠合型储层是否采用全层段的储层组合排采,应充分结合储层性质与现场工况选择适宜的储层组合进行排采,避免造成储层伤害。

  • 模拟结果表明,全层段的储层组合排采相较另外三种储层组合排采更有助于产量提高。全层段的储层组合排采下,不仅有利于砂岩层中游离态甲烷产出,而且使泥页岩储层获得更好的渗流通道,从而提高了叠合型储层整体的孔隙压力传递效率,促进基质解吸以及渗透率回弹,达到增产的目的。但该储层组合排采下易导致砂岩层的渗透率快速下降,因此在实际工程中是否采用全层段的储层组合排采方式,应结合实际储层性质,避免造成储层伤害。由于不同岩性储层含气性、渗透率、孔隙度以及力学性质差异较大,在叠合型储层排采过程中射孔层段、射孔方式以及压裂工艺的选择,仍有待进一步深入研究。

  • (1) 以大河边区块龙潭组实际地层条件为约束,建立了典型煤系叠合型气藏流固耦合数学模型。模拟结果显示,数学模型具有较好的准确性,日产气量拟合误差8.68%。

    (2) 与单层排采相比,(煤+泥页岩)排采、(煤+砂岩)排采、全层段排采下,煤系气最大日产气量分别提高了1.27倍、1.36倍和1.57倍,累计产气量分别提高了1.26倍、1.42倍、1.62倍;四种储层组合排采下均存在层间能量与物质传递;煤、砂岩和泥页岩储层在不同储层组合排采下,储层孔隙压力与传导方向、基质含气量以及渗透率比例均存在明显差异;与单层排采相比,另外三种储层组合排采方式,更有利于煤与泥页岩基质中甲烷解吸与渗透率回升,但(煤+砂岩)、全层段的储层组合排采易导致砂岩渗透率出现短期快速下降。

    (3) 全层段的储层组合排采下,更有利于叠合型储层孔隙压力传导,加快砂岩层中游离态甲烷产出,促进煤、泥页岩基质中甲烷解吸,增强基质收缩作用,促使煤、泥页岩储层渗透率回升,从而提高产气量。但砂岩层在甲烷快速产出的同时易出现储层渗透率快速下降,因此在选择排采储层组合时,应充分结合实际地质条件与工况进行选择,避免造成储层伤害。

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