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作者简介:

吴宽宽(1994—),男,河南周口人,在读博士研究生,从事油气田开发及数值模拟研究。E-mail:wukuankuanupc@126.com。

通讯作者:

冯其红(1969—),男,四川西充人,教授,博士。E-mail:fengqihong@126.com。

中图分类号:TE319

文献标识码:A

文章编号:1009-9603(2023)05-0067-09

DOI:10.13673/j.pgre.202304024

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目录contents

    摘要

    由于储层非均质性及开发措施的影响,易造成水驱过程驱替不均衡。基于统计学方法,提出了采用克里斯琴森均匀系数定量评价多层水驱油藏开发过程中均衡驱替程度,以最大化均衡驱替为目标建立了分层注采参数优化数学模型,采用协方差矩阵自适应智能进化算法进行求解,形成了多层水驱油藏注采参数协同优化方法,并通过实例验证了方法的可靠性。将建立的新方法应用于胜利油区胜坨油田坨142油藏典型井组,通过对比智能协同分层注采参数优化前后结果,相比于原始方案克里斯琴森均匀系数提高了3.49%,累积产油量增加1.024×104 m3 ,同时含水率降低1.34%。表明该方法可以精准地控制各层间的配产和配注,有效地改善水驱油藏层间和井间的均衡驱替状况,实现注采参数和剩余油分布的精准匹配。

    Abstract

    Unbalanced water flooding can easily occur due to the influence of reservoir heterogeneity and development measures. Based on the statistical method,the Christiansen uniformity coefficient is used to quantitatively evaluate the balanced water flood‐ ing degree during the development of multi-layer reservoirs. A mathematical model for optimizing multi-layer injection and produc‐ tion parameters is established to maximize balanced water flooding,and the covariance matrix adaptive intelligent evolution algo‐ rithm is used to solve the problem. A collaborative optimization method of injection and production parameters for multi-layer reser‐ voirs based on water flooding is developed,and its reliability is verified by an example. The new method is applied to the typical well group of Shengtuo T142 reservoir in Shengli Oilfield. By comparing the results before and after the optimization of intelligent collaborative stratified injection and production parameter,it is found that the Christiansen uniformity coefficient by the original scheme is improved by 3.49%. The cumulative oil production is increased by 1.024 × 104 m3 ,and the water cut is decreased by 1.34%. The results show that this method can accurately control the production and injection allocation between layers,effectively improve the balanced water flooding between layers and wells,and realize the accurate matching between injection and production parameters and remaining oil distribution.

  • 受储层的非均质性、井网不完善以及注采制度不合理等因素的影响,长期的多层合采导致层间剩余油动用不均衡,从而造成注入水的无效循环,但采用分层注水方式可有效改善水驱均衡程度,因此如何构建水驱油藏目前均衡驱替状况的评价指标,并开展基于均衡驱替的多层水驱油藏注采参数协同优化方法研究,是目前研究的难点[1-3]。传统均衡驱替定义为注入井的驱替液在各个方向的驱替程度相同,并在相同时间内能到达最近的采油井[4]。 SUN等根据Buckley-Leverett方程和水驱油理论,推导了含水率、产液量和注水速率之间的定量关系,定义了均衡驱替的评价系数,用来指导水驱油藏平面均衡注采方案优化[1]。王军等以见水时间相同作为判断是否均衡驱替的标准,并以此标准进行井网和注采措施调整[5-6]。冯其红等基于油藏工程方法和经济性角度对均衡驱替理论进行了推导,当水驱油藏各注采方向上的累积注水量等于注入孔隙体积倍数,即油藏达到了均衡驱替,并以最大化均衡驱替开展了单层油藏注采参数优化研究[47-8]。刘海成等基于油藏工程理论推导了非均质油藏在定液量和定压差2种不同生产方式下的注采参数设计公式,以减小不均衡驱替为目的,形成了非均质油藏均衡注采优化的方法[9]。马奎前等推导采出程度和注水量与注入孔隙体积倍数的关系,以实现油田均衡驱替的目标,形成一种基于均衡驱替的单层油藏配产配注优化方法[10-11]。陈存良等开展了基于最大净现值的多层水驱油藏配注方法研究[12-13]。崔传智等以层间吸水指数级差作为注水层系分段指标,以均衡驱替为目标,利用Buckley-Leverett非活塞式水驱油理论计算各段配注量[14]。孙召勃等分析多层合采油藏长期注水开发特点,提出采用驱替通量定量表征各层驱替程度差异的方法,建立了基于驱替通量均衡化思想的注水井纵向各层配注量确定方法[15]。卜亚辉根据渗流力学原理分析了流场参数间的相互影响关系,建立了适配系数与累积产油量之间的相关性,并提出了一种基于适配系数的流场调控优化方法,从而使流场分布更加均衡[16]。梁文福根据油藏工程基本原理,建立了分类井网产液量分配比例优化数学模型,该方法可以有效减少油层动用不均衡等开发矛盾,取得较好的增油降水效果[17]

  • 近年来,诸多学者开展了基于均衡驱替理念作为评价和指导开发方案设计的研究,但多是基于单井组或单层油藏建立均衡驱替的指标,结合油藏工程方法或者经验公式进行配产配注方案设计,未考虑注水井和生产井之间的协同开发效果影响;其次是基于智能算法对油藏进行笼统注采参数优化,无法实现注采参数和各层剩余油分布的精准匹配。为此,笔者结合统计学理论和智能优化算法,提出基于克里斯琴森均匀系数的水驱油藏均衡驱替定量评价方法,以最大化均衡驱替为目标,建立了多层水驱油藏分层注采参数协同优化数学模型,并结合智能优化算法对注采井的工作制度进行分层智能优化,从而实现储层非均质性和剩余油分布与注采参数的精准匹配。

  • 1 基于克里斯琴森均匀系数的水驱油藏均衡驱替评价方法

  • 1.1 均衡驱替评价指标

  • 已有的研究表明,利用饱和度标准差来反映水驱油藏的均衡驱替程度是一种直观有效的方法[47]。目前现场应用中,多是采用含水饱和度标准差或者方差指标来评价水驱油藏的均衡驱替程度,但该方法只能是针对单层水驱油藏,无法对多层水驱油藏的均衡驱替程度进行评价。计算公式为:

  • SD=1ni=1n xi-x-2
    (1)
  • 从(1)式中可以看出,饱和度标准差虽然能够反映出饱和度数据与平均饱和度数值的离散情况,但并不能体现含油饱和度数值的高低,就会导致更高或更低的平均含油饱和度其饱和度标准差的结果可能相同,因此对于多层的水驱油藏,无法定量准确地表征不同层位饱和度离散状况。引入统计学中克里斯琴森均匀系数(CU)来表征多层水驱油藏的均衡驱替程度,克里斯琴森均匀系数[17] 也称为克里斯琴森一致性系数,是一种常用的统计学方法,通常被视为评估、测量数据内部一致性和可靠性的有效指标,克里斯琴森均匀系数是基于平均偏差的统计量,能够直观反映试验中被测参数与平均值的偏离程度,其计算公式为:

  • CU=1-i=1n xi-x-i=1n xi×100%
    (2)
  • 1.2 均衡驱替评价指标检验

  • 采用经典的egg模型对多层水驱油藏注采参数优化方法的适用性进行评价,egg 模型采用注水开发,作为计算实例被广泛应用于历史拟合和井网注采优化等算法的检验[18-19]。模型[20] 总网格数为 60 × 60 × 7,每个网格尺寸为8 m × 8 m × 4 m。截取部分 egg标准算例模型来验证所提出的均衡驱替评价指标,设置一注四采 5口井,多层 egg模型分别截取第 1,3,5和 7层,其余层设置为隔层,截取模型渗透率场和井位分布如图1所示。

  • 图1 多层egg模型渗透率场及井位分布

  • Fig.1 Permeability field and well location distribution of multi-layer egg model

  • 首先进行多层 egg 模型均衡驱替指标论证,设置注水井的日注液量为140 m3 /d,4口生产井的日产液量变化范围为0~140 m3 /d,保持注采平衡,对生产井日产液量以10 m3 /d为步长单位进行遍历组合,共有 680 种液量分配方案,运行数值模拟计算不同方案下第 10 a 和第 15 a 的 SDCU 与其相对应的累积产油量(图2,图3)。从图2 和图3 中可以看出, SD 和累积产油量不再具有线性关系,证明此时 SD 已无法再用来定量表征油藏的均衡驱替程度。而 CU在不同的时间节点和累积产油量相关程度仍然在99%以上,由此表明,CU可以定量评价多层水驱油藏均衡驱替的程度。

  • 2 多层水驱油藏注采参数协同优化数学模型构建与求解

  • 2.1 优化数学模型构建

  • 根据克里斯琴森均匀系数的意义,即克里斯琴森均匀系数越大,油藏驱替程度越均匀,因此为实现油藏均衡驱替程度的最大化,选择克里斯琴森均匀系数作为目标函数,各层的注水井日产液量和生产井日产液量作为优化变量,同时对油藏总产液量、总注入量和各注采井进行单井液量约束。基于上述考虑,构建注采参数优化数学模型为:

  • (3)
  • 2.2 优化数学模型求解

  • 注采参数优化问题具有多峰值、多约束、高纬度和非线性等特点,在采用优化算法求解优化数学模型时较难,不同类型的优化算法在求解不同特点优化问题时效率不同,因此对于优化算法的选取十分重要。采用协方差矩阵自适应智能进化算法 (CMA-ES)[21] 进行求解优化数学模型,CMA-ES 属于一种随机性、全局性优化算法,是一个应用广泛、性能较好的自适应算法,常用于非线性、非凸函数的优化问题,在中等规模变量的复杂优化问题上具备较好的优化效果,CMA-ES 在优化过程不需要对目标函数进行求导,属于随机性搜索算法。

  • 图2 10 a后不同注采液量下的累积产油量与均衡驱替评价指标相关性

  • Fig.2 Correlation between cumulative oil production and balanced water flooding evaluation index with different injection and production fluid volumes after 10 years

  • 图3 15 a后不同注采液量下的累积产油量与均衡驱替评价指标相关性

  • Fig.3 Correlation between cumulative oil production and balanced water flooding evaluation index with different injection and production fluid volumes after 15 years

  • 基于均衡驱替的水驱油藏分层注采参数优化方法主要表现为:针对目前油藏的开发状况,利用克里斯琴森均匀系数定量评价油藏的均衡驱替程度,以最大化均衡驱替为目标,在此基础上,构建注采参数分层优化数学模型,结合相应的约束条件,采用 CMA-ES对注采参数优化数学模型进行求解,以实现注采参数和剩余油分布的精准匹配,从而改善油藏的水驱开发效果(图4)。

  • 2.3 方法验证

  • 将建立的基于均衡驱替的分层注采参数优化方法应用于 egg 模型,分别开展分层注采参数优化和笼统注采参数优化。在分层注采优化时,每层注入液量同样作为优化变量,设置注水井在每层的日注液量优化范围均为 0~80 m3 /d,日总注液量约束为 160 m3 /d;每口生产井日产液量优化范围为 0~80 m3 /d,然后对生产井日产液量和各层日注液量进行优化;在笼统注采参数优化时,日总注液量为160 m3 /d保持不变,只优化每口生产井日产液量。

  • 为了对比笼统注采优化和分层注采优化的效果,优化中保持注采平衡,评价时间为 10 a,优化算法设置相同的初始化参数,由于数值模拟需要耗费大量的时间,设置 CMA-ES 最大迭代次数为 1 000,种群数为 50,各优化 10 次,取平均优化结果进行对比。不同优化方式的寻优过程如图5 所示,在相同的迭代次数下,分层注采优化可以提高克里斯琴森均匀系数为2.5%,表明分层注采优化后可使水驱程度更加均衡。通过对比不同优化方式的最优生产动态(图6,表1)可知,在相同的注入液量下,相比于笼统注采优化,分层注采优化后油藏采出程度提高 1.45%,同时含水率下降了2.75%,由此表明,分层注采优化可有效改善油藏的开发效果,对注入水实现更充分的利用,验证其方法的有效性。

  • 图4 基于均衡驱替注采参数优化流程

  • Fig.4 Flow chart for optimization of injection and production parameters based on balanced water flooding

  • 3 实例应用

  • 胜利油区胜坨油田坨 142 油藏位于东营凹陷坨-胜-永断裂构造带胜利村构造东翼,是一个倾向东南的单斜构造,地层较陡,地层倾角约为 5°~8°,油层埋深为 2 450~2 880 m,构造高差为 430 m,地层原油密度为0.834 5 g/cm3,油层温度为99.8℃,原始地层压力为27.0 MPa。坨142油藏是三角洲前缘亚相反韵律沉积,纵向上主要划分为6个开发层系,沙二段是坨 142 油藏的主力层,共细分为 4 个小层 (152-1,152-2,152-3 和 152-4),截取沙二段典型井组进行应用分析,典型井组主要位于 152-1,152-2 和 152-3 这 3 个小层,渗透率、剩余油和井位分布如图7 所示,属于高渗透油藏,水驱开发后期剩余油高度分散,生产井和注水井各6口,目前井组日配注量为360 m3 /d,设置注采比为 1∶1,根据现场实际单井最大配产配注能力设置约束范围,注水井的日注液量为0≤Ivwi,k≤300 m3 /d,生产井的日产液量为 0≤Pvlj ≤300 m3 /d,在保持原始总配注的情况下对注采参数开展优化,考虑到实际油藏模拟耗时问题,设置 CMA-ES最大迭代次数为 500,种群数为 25,以 5 a 后克里斯琴森均匀系数为评价目标函数开展优化。

  • 图5 不同优化方式寻优过程

  • Fig.5 Optimization of different optimization methods

  • 图6 不同优化方式生产动态对比

  • Fig.6 Comparison of production dynamics of different optimization methods

  • 表1 不同优化方式优化结果

  • Table1 Comparison of results of different optimization methods

  • 图7 坨142油藏典型井组属性分布

  • Fig.7 Typical well group attribute distribution in T142 reservoir

  • 从沙二段典型井组优化前后的生产动态对比 (图8)和优化结果(表2)可以看出,当优化结束时,分层注采优化的克里斯琴森均匀系数相比原始方案提高了 3.49%,同时累积产油量增加 1.024×104m3,含水率降低1.34%,说明在相同生产时间及注采液量条件下,通过分层注采优化后,油藏驱替更加均衡,可以有效地改善油藏开发效果。

  • 图8 优化前后生产动态对比

  • Fig.8 Comparison of production dynamics before and after optimization

  • 表2 优化前后结果对比

  • Table2 Comparison of results before and after optimization

  • 从优化前后注采液量对比(图9)、优化后各层液量分布(图10)和优化前后剩余油分布(图11,图12)可以看出,通过注采参数智能协同分层优化,在沙二段的 152-1 小层对 INJ1,INJ2 和 INJ4 等 3 口注水井进行精准调配,同时对 INJ3,INJ5 和 INJ6 等 3 口注水井进行降注,可以减少高含水区域注入水的无效循环;对应的生产井 PROD5进行提液,有利于采出油藏边部高度富集的剩余油,对生产井PROD2和 PROD3 进行稍微提液,有利于采出井间局部剩余油;通过对 INJ1,INJ2 和 INJ4 等 3 口注水井在沙二段的 152-3 小层进行精准增注,同时关闭注水井 INJ6,可以使得注水井INJ1更多的水流向角落生产井,以及对生产井PROD5和PROD6的合理提液,可以有效地采出 PROD3,PROD5 和 PROD6 等 3 口生产井之间的连片剩余油。通过矿场实际应用表明,对注采井液量的精准分配,可以有效地实现注采参数和剩余油分布的精准匹配,提高各层间注水利用率,最终实现井间和平面的均衡驱替。

  • 4 结论

  • 提出了基于克里斯琴森均匀系数的水驱油藏均衡驱替的评价指标,该指标可以定量评价单层和多层水驱油藏的均衡驱替程度,相比于传统的含水饱和度标准差具有更广泛的适用意义。基于克里斯琴森均匀系数,构建了以油藏最大化均衡驱替为目标的分层注采参数优化数学模型,并采用协方差矩阵自适应智能进化算法进行求解,形成多层水驱油藏注采参数协同优化方法。将新建立的方法应用于胜利油区胜坨油田坨 142 油藏,通过分层注采优化后克里斯琴森均匀系数相比原始方案提高了 3.49%,累积产油量增加了 1.024×104 m3,同时含水率降低了1.34%。实例应用表明该方法可以精准地控制各层间的配产和配注,有效地改善水驱油藏层间和井间的均衡驱替状况,实现增油降水的开发目标,可以为现场的开发调整提供技术支撑。

  • 图9 优化前后日注采液量对比

  • Fig.9 Comparison of injection and production fluid volumes before and after optimization

  • 图10 分层注采优化后各层液量分布

  • Fig.10 Distribution of liquid volume in each layer after injection and production optimization

  • 图11 沙二段152-1 小层优化前后剩余油分布对比

  • Fig.11 Comparison of remaining oil distribution before and after optimization of Es2152-1

  • 图12 沙二段152-3 小层优化前后剩余油分布对比

  • Fig.12 Comparison of remaining oil distribution before and after optimization of Es2152-3

  • 符号解释

  • CU——克里斯琴森均匀系数,%;

  • CUx)——优化目标函数;

  • i——优化的第i口注水井;

  • Ivwi ——第i口注水井的注水速度,m3 /d;

  • Ivwi,k——第i口注水井在第k层的注水速度,m3 /d;

  • j——优化的第j口生产井;

  • k——第k层;

  • m——生产井总井数,口;

  • M——随机生成的样本个数;

  • n——数值模型网格总数;

  • Pvlj ——第j口生产井的产液速度,m3 /d;

  • SD——含水饱和度标准差;

  • x-——含水饱和度的平均值,小数;

  • xi ——每个网格的含水饱和度,小数;

  • z——注水井总井数,口。

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