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基于时变理论的优势通道演化规律研究 被引量:3

RESEARCH ON THE EVOLUTION OF HIGH CONDUCTIVE CHANNELS BASED ON FORMATION PARAMETERS VARIATION
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摘要 目前针对优势通道演化规律的研究多是基于实验或矿场统计的宏观分析,缺少微观与宏观结合的定量化机理研究。为此,基于网络模拟方法和时变数模理论开展疏松砂岩油藏优势通道演化规律的研究。首先根据水动力学及化学原理,定量表达优势通道演化过程中的微粒脱落、微粒捕集变化机理;然后,基于孔喉尺度下的物质平衡方程建立微粒运移的网络模型,从而形成储层时变的微观网络模拟方法,并得到微观尺度下储层参数变化的定量表达式;最后与黑油模型进行耦合形成储层参数时变条件下的数值模拟方法。以海上S油田典型井组为原型进行了优势通道演化规律的研究,分析不同级差、不同产液强度条件下,优势通道的演化规律及其对剩余油的控制作用,将研究成果应用于矿场实际,调剖后累增油1.6×10~4m^3,具有良好的效果。 The present research on the evolution of high conductive channels is mainly based on the experiment analysis or field statistics,but lack of quantitative research of combining microcosmic and macroscopic mechanism. Therefore,based on network modelling and numerical simulation of formation parameters variation,the evolution of high conductive channels in unconsolidated sandstone reservoir is studied. According to the hydrodynamic and chemical principles,the mechanism of particle detachment and capture during the evolution of conductive channels is quantitatively described. Based on the material balance equation under the pore scale,the network model of particle migration is established,and the microscopic network simulation of formation parameters variation is formed,and the quantitative expression of formation parameters variation under the micro scale is obtained. Combined with the black oil model,the numerical simulation of formation parameters variation is built.Based on a typical well group in S oilfield,the evolution of high conductive channels and remaining oil distribution under different permeability ratio and liquid production strength are analyzed. Field application indicates that the cumulative incremental oil reaches 1.6×10~4 m^3,which shows a favorable performance.
作者 张伟 刘斌 王欣然 刘喜林 朱志强 ZHANG Wei;Liu Bin;WANG Xinran(Tianjin Branch of CNOOC(China)Co.,Ltd.,Tianjin 300459,China)
出处 《新疆石油天然气》 CAS 2019年第4期61-66,I0004,共7页 Xinjiang Oil & Gas
基金 “十三五”国家科技重大专项(2016ZX05058-001)
关键词 优势通道 剩余油 储层参数时变 网络模拟 数值模拟 High conductive channels Remaining oil formation parameters variation Network modelling Numerical simulation
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