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作者简介:

姜彬(1984—),男,山东烟台人,高级工程师,在读博士研究生,从事油气田开发及综合调整研究工作。E-mail:jiangbin@cnooc.com.cn。

中图分类号:TE343

文献标识码:A

文章编号:1009-9603(2022)02-0124-07

DOI:10.13673/j.cnki.cn37-1359/te.2022.02.015

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目录contents

    摘要

    多层砂岩油藏开发进入中高含水期,层间矛盾突出,层间干扰加剧,新钻调整井的产能预测难度大、精度低。为进一步分析油田不同含水率对多层砂岩油藏产能的影响,通过回归P油田不同流动能力突进系数下的层间干扰系数随含水率的变化趋势,建立层间干扰动态表征模型,形成层间干扰系数与流动能力突进系数和含水率变化关系图版,实现不同流动能力突进系数下对层间干扰系数随含水率变化的定量表征。通过建立无层间干扰条件下采油指数与地层流动系数的产能回归公式,指导P油田中高含水期调整井的产能评价。研究结果表明,基于层间干扰校正预测的P油田新投产调整井的产能误差为20%,低于层间干扰校正前,预测结果可靠。

    Abstract

    At the middle and high water cut stages of multi-layer sandstone reservoir,the development between layers is un- even,and the interlayer interference is obvious,leading to the great difficulty and low accuracy of productivity prediction for newly drilled adjustment wells. To further analyze the influence of different water cuts on the productivity of multi-layer sandstone reservoirs,this paper constructed the dynamic prediction model of interlayer interference after the variation of in- terlayer interference coefficients with water cuts was analyzed under different breakthrough coefficients of flow capacity in P Oilfield. The relationship chart of interlayer interference coefficients with the breakthrough coefficients and water cuts was drawn to quantitatively characterize the variation of interlayer interference coefficient with water cuts under different breakthrough coefficients of flow capacity. The productivity formula between productivity index and formation flow coeffi- cient without interlayer interference was constructed to guide the well productivity evaluation of P Oilfield at middle and high water cut stages. The results indicate that the productivity error of new adjustment wells in P Oilfield predicted by in- terlayer interference correction is 20%,which is lower than that before the correction,indicating a reliable productivity pre- diction result.

  • 多层砂岩油藏合采过程中的物性差异是导致开发不均衡的主要原因。多层砂岩油藏开发初期常以一套层系合采,开发以主力厚层为主,兼顾薄互层。但随着开发的不断深入,层间矛盾更加突出,进而加剧了层间干扰,增大了油田二次调整的难度,尤其是在中高含水期,新钻调整井的产能预测精度相对较低。

  • 目前产能预测的普遍方法是根据平面径向稳定渗流达西公式,通过统计分析,建立组合参数流度或地层流动系数与产能的回归公式。进入中高含水期后,在调整井的产能预测过程中通常对采油指数只进行含水率校正。但对于多层砂岩油藏来说,不同含水率条件下产能受层间干扰的影响较大,上述方法得到的预测结果并不理想,仍需进一步考虑不同含水率条件下的层间干扰系数校正。黄世军等分别通过物理模拟实验和动态研究方法证明了普通稠油油藏不同含水期层间干扰的变化规律及对开发效果的影响[1-9]。但目前对于油田开发全过程层间干扰的影响程度依然缺乏系统的认识,缺少层间干扰动态预测的手段,无法直接指导油田中高含水期的产能评价。

  • 笔者利用 P 油田多层砂岩油藏的实际生产数据,建立了不同流动能力突进系数下的单井层间干扰系数随含水率变化关系,定量表征流动能力突进系数、含水率等变化对层间干扰系数的影响,用于指导油田中高含水期的产能评价,也为同类型油田层间矛盾的定量评价及配产配注提供借鉴。

  • 1 油田概况

  • P油田为在渤南低凸起基底隆起背景上发育的受北东向和南北向走滑断层控制的断背斜构造,其断裂发育,平面上划分为22个区块。主力含油层系馆陶组为辫状河三角洲沉积,储层埋藏深度为 1 000~1 400 m,纵向跨度大,达 300 m,共划分为 9 个油组40个小层,属于典型的多层砂岩油藏。研究区纵向各层之间的储层物性、流体性质及注采连通状况差异非常明显,非均质性严重。主力含油层系厚度大、连续性好,非主力含油层系层数多、连续性差,其中厚度在5 m以下储层的占比达50%。

  • P油田主体区 2018年已进入高含水期,2020年含水率达 87%。由于前期采用大段合采,纵向各层间储量动用程度差异明显,主力含油层系采出程度为 30%,非主力含油层系采出程度仅为 7%~15%。由于纵向层数多,对层间干扰规律缺乏系统认识,调整井产量预测难度大,实施效果不理想。

  • 2 多层砂岩油藏层间干扰动态表征

  • 2.1 层间干扰动态反演模型

  • 许多学者从不同的应用角度对层间干扰系数进行了定义[10-17],笔者将层间干扰系数定义为油井在相同的工作制度下各层分采时采油指数之和与多层合采时采油指数的差值除以各层分采时的采油指数之和,即合采时产能相比分采时总产能下降的幅度[5]。其表达式为:

  • α=i=1n Jdoi-J0i=1n Jdoi
    (1)
  • 由定向井的产量公式可知:

  • Q=542.87i=1n KroiKihipe-pwfμoBolnRevrwe+Sθ+Sd
    (2)
  • J=Qpe-pwf=542.87i=1n KroiKihiμoBolnRevrwe+Sθ+Sd
    (3)
  • 其中:

  • rwe=L4×0.454sin2πrwvhhL
    (4)
  • 随着开发的进行,不同层间的采出程度差异引起层间含水率的变化,进一步影响各小层中油相的相对流动能力[18-27]。将油相相对渗透率随含水率的变化引入(3)式,并与(1)式联立,即可以得到层间干扰系数的动态表达式为:

  • α=1-0.00184Q'lnRevrwe+Sθ+Sdpe-pwfμoBoi=1n KihiKroifwi
    (5)
  • 由(5)式可知,除绝对渗透率、有效厚度等静态参数差异外,由于层间含水期不同引起的油相相对渗透率的差异也是影响层间干扰系数差异的重要因素之一。

  • 2.2 层间干扰程度的变化规律

  • 文献[5]开展了考虑渗透率单一因素差异下层间干扰系数随含水率变化的物理模拟实验,确定了层间干扰系数与含水率和渗透率突进系数的函数关系。考虑实际生产中储层厚度、流体黏度等差异,笔者进一步引入流动能力突进系数、平均流动能力以及基准流动能力等参数对实际油田生产过程中的层间干扰系数随含水率的变化进行定量表征。

  • 定义 Fi 为各小层的地层流动系数,其表达式为:

  • Fi=KiHiμi
    (6)
  • 定义T f为流动能力突进系数,其表达式为:

  • Tf=FmaxF-
    (7)
  • 将研究区单井各小层的地层流动系数的最小值作为基准流动能力。选取 P油田 3口具有不同流动能力突进系数的典型调整井,利用(5)式计算各井的层间干扰系数随含水率的变化(图1)。3 口典型调整井的初期日产量、初始含水率、基准流动能力及流动能力突进系数见表1。

  • 图1 P油田典型调整井层间干扰系数随含水率变化规律

  • Fig.1 Variation of interlayer interference coefficient with water cuts in typical adjustment wells of P Oilfield

  • 表1 P油田3口典型调整井不同含水率下的产能及流动能力统计

  • Table1 Productivity and flow capacity of three typical adjustment wells at different water cuts in P Oilfield

  • 去除噪点后通过三次样条插值进行简化处理,分别对3口典型调整井不同含水率下的层间干扰系数进行分段多元拟合,确定 P 油田层间干扰系数与流动能力突进系数、基准流动能力以及含水率等变量的相关关系式为:

  • α=κλ+fw3-fw2+fwTfωln1+Fmin γ
    (8)
  • 为进一步确定P油田κλγω这4个相关系数的参数范围,对 P油田 30口生产井按流动能力突进系数分类,进行多元非线性回归,计算结果如表2所示。并绘制P油田不同流动能力突进系数下层间干扰系数随含水率变化的图版(图2)。

  • 表2 P油田层间干扰系数的相关系数取值

  • Table2 Correlation coefficients of interlayer interference coefficients in P Oilfield

  • 图2 P油田不同流动能力突进系数下层间干扰系数随含水率的变化

  • Fig.2 Variation of interference coefficients with water cuts under different breakthrough coefficients of flow capacity in P Oilfield

  • 由图2 可以看出,当 P 油田 2.0<T f ≤5.0,其中低含水期层间干扰程度相对较弱且变化平缓,并随含水率的升高,层间干扰程度加剧。若5.0<T f ≤7.0,层间干扰程度稳步上升,抑制作用持续增强。当7.0< T f ≤16.0,其中低含水期层间干扰程度快速上升,并迅速达到较高水平,对油井整体产能抑制作用较强,进入高含水期后单层突进现象明显,层间干扰程度在较高水平保持稳定。

  • 3 基于层间干扰动态表征的产能评价

  • 3.1 基于层间干扰动态表征的比采油指数校正方法

  • 根据产量计算公式,假设 Q o为不考虑层间干扰的日产量,则考虑层间干扰且层间干扰随含水率动态变化后,(3)式中的采油指数J可以改写为:

  • Jαofw=Qope-pwf1-αfw=Jofw1-αfw
    (9)
  • 根据无因次采油指数的定义,可以得到考虑层间干扰的无因次采油指数为:

  • JαDofw=JαofwJofw=01-αf(w=0)=Jofw1-αfwJofw=01-αfw=0
    (10)
  • 因此,校正后的无水采油期下不考虑层间干扰的采油指数可以表示为:

  • Jofw=JαDofw1-αfw1-αfw=0Jofw=0
    (11)
  • 3.2 实例应用

  • 应用基于层间干扰动态表征的比采油指数校正方法,分别计算 P油田 N区块 20口生产井的采油指数、投产初期含水率及初期含水率条件下的层间干扰系数、无水采油期下的层间干扰系数及无因次采油指数等,生产井采油指数计算参数见表3,绘制考虑层间干扰校正后采油指数与地层流动系数图版,并与层间干扰校正前的采油指数与地层流动系数关系进行对比(图3)可以看出,经过层间干扰系数校正后,P 油田 N 区块无水采油期下的采油指数与地层流动系数的拟合关系更好。

  • 3.3 效果分析

  • 基于P油田N区块考虑层间干扰校正前后采油指数与地层流动系数关系(图3),进一步对 N 区块新投产的3口调整井进行产能预测(表4),发现计算结果与实际产能测试结果基本一致,层间干扰校正前的平均相对误差为40%,校正后为20%,可以满足矿场产能预测要求,表明该方法预测结果可靠,可以用于指导现场配产。

  • 4 结论

  • 开发中后期层间含水率的差异是影响多层砂岩油藏产能的重要因素。基于层间干扰动态反演模型,对 P 油田不同流动能力突进系数下的单井层间干扰系数随含水率变化趋势进行拟合,得到了层间干扰系数与流动能力突进系数、基准流动能力以及含水率的相关关系。据此建立的不同流动能力突进系数下层间干扰系数与含水率的关系图版,可以分类表征不同流动能力突进系数取值范围下层间干扰程度的变化规律。基于层间干扰校正预测的 P 油田新投产调整井产能误差为 20%,低于层间干扰校正前,预测结果可靠,可以为同类型油田制定合理的开发对策提供借鉴。在实际油田开发过程中,需结合研究人员对各小层的岩石类型、储层类型及相渗特征等的分类表征和精细描述成果,进一步提高该方法的预测精度。

  • 表3 P油田N区块生产井采油指数计算参数

  • Table3 Parameters of oil productivity index calculation of production wells in N Block,P Oilfield

  • 图3 P油田N区块考虑层间干扰校正前后采油指数与地层流动系数关系

  • Fig.3 Relationship between productivity index and formation flow coefficient before and after interlayer interference correction in N Block,P Oilfield

  • 表4 考虑层间干扰动态表征的产能评价准确性对比

  • Table4 Comparison of accuracy of productivity evaluation considering dynamic predicted interlayer interference

  • 符号解释

  • B o——原油体积系数;

  • f w——含水率,%;

  • f wi ——第i层的含水率,%;

  • F-—— 单井各小层的平均地层流动系数,mD · m/ (mPa·s);

  • Fi ——单井各小层的地层流动系数,mD·m/(mPa·s);

  • F max——单井各小层的地层流动系数的最大值,mD· m/(mPa·s);

  • F min——单井各小层的地层流动系数的最小值,即基准流动能力,mD·m/(mPa·s);

  • h ——有效厚度,m;

  • hi ——第i层的有效厚度,m;

  • Hi ——单井各小层的有效厚度,m;

  • i ——某一单层;

  • J ——采油指数,m3 /(d·MPa);

  • J doi ——第i层的采油指数,m3 /(d·MPa);

  • J o——合采采油指数,m3 /(d·MPa);

  • Jofw=0——含水率为 0时不考虑层间干扰的采油指数, m3 /(d·MPa);

  • Jofw——含水率为f w时不考虑层间干扰的采油指数,m3 / (d·MPa);

  • Jαofw ——含水率为 f w 时考虑层间干扰的采油指数,m3 /(d·MPa);

  • JαDofw——含水率为f w时考虑层间干扰的无因次采油指数;

  • Ki ——第i层的绝对渗透率,D;

  • K roi ——第i层的油相相对渗透率;

  • Kroi fwi ——第i层含水率为f wi时的油相相对渗透率;

  • L ——定向井的等效长度,m;

  • n ——小层总数;

  • p e——供给压力,MPa;

  • p wf——井底流压,MPa;

  • Q ——不考虑层间干扰的合采日产量,m3 /d;

  • Q’——考虑层间干扰的合采日产量,m3 /d;

  • Q o——不考虑层间干扰的日产量,m3 /d;

  • r we——有效井的井筒半径,m;

  • r wv——定向井的井筒半径,m;

  • R ev——供给半径,m;

  • S d——完井表皮系数;

  • Sθ——井身结构表皮系数;

  • T f ——流动能力突进系数;

  • α——层间干扰系数;

  • αfw——含水率为f w时的层间干扰系数;

  • αfw=0 ——含水率为0时的层间干扰系数;

  • θ——井斜角,rad;

  • μi ——各小层的原油黏度,mPa•s;

  • μo——原油黏度,mPa•s;

  • κλγω——相关系数。

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