KS油田高含水后期调剖堵水选井

doi:10.7657/XJPG20220118

摘要/Abstract

摘要：

KS油田开发进入高含水期后,注水井调剖是常用的稳油控水措施,但是在选井决策方面,存在指标界限不易选择、权重数值不易量化等问题。针对上述问题,筛选出能够较准确反映水窜特征的单井指标、井间指标和静态指标,构建基于多项式核函数、径向基核函数和Sigmoid核函数的新型核函数,并基于函数形式优化模糊聚类方法,提高拟合精度和预测精度。提出适合KS油田高含水后期调剖选井模糊聚类决策方法,提高调剖选井样本集和检测集的识别率。将新型注水井调剖选井决策方法应用于KS油田,从22口注水井中优选出3口进行调剖,增油降水效果显著。

关键词: KS油田, 砂岩油藏, 高含水期, 注水井调剖, 模糊聚类方法, 选井决策, 窜流通道, 稳油控水, 核函数

Abstract:

In the late high-water cut stage in KS oilfield, profile control in water injection wells is a common measure to stabilize oil production while controlling water production. However, it is difficult to decide index limits and quantify weight values when selecting water wells. This study screened single-well, interwell and static indicators that can accurately reflect the characteristics of water channeling, developed a new kernel function based on polynomial kernel function, radial basis kernel function and Sigmoid kernel function, and optimized the fuzzy clustering method to improve the accuracy of fitting and prediction. Then a special fuzzy clustering method was proposed for selecting wells for profile control in the late high water-cut stage in KS oilfield. It can improve the recognition rates of sample set and detected set for selected wells. The new decision-making method for selecting wells for profile control has been applied to KS oilfield, and 3 wells were selected from 22 water wells for profile control. Significant oil increasing and water reducing effects have been achieved.

Key words: KS oilfield, sandstone reservoir, high water cut stage, profile control in water injection well, fuzzy clustering method, decision making for well selection, channeling pathway, stabilizing oil production and controlling water, kernel function

中图分类号:

TE357

王桂芳, 王硕亮, 许学健, 雷燕, 康波. KS油田高含水后期调剖堵水选井[J]. 新疆石油地质, 2022, 43(1): 122-126.

WANG Guifang, WANG Shuoliang, XU Xuejian, LEI Yan, KANG Bo. Selection of Wells for Profile Control and Water Plugging in Late High-Water Cut Stage in KS Oilfield[J]. Xinjiang Petroleum Geology, 2022, 43(1): 122-126.

图/表 6

表1

模糊聚类类间最优距离计算方法"

距离类型	表达式
明科夫斯基距离	$d q (x i, x j) = x i - x j q = ∑ k = 1 p x ik - x jk q 1 q$	（3）式
曼哈坦距离	$d 1 (x i, x j) = x 1 - x j 1 = ∑ k = 1 q x ik - x jk$	（4）式
欧几里德距离	$d 2 (x i, x j) = x i - x j 2 = ∑ k = 1 p x ik - x jk 2 12$	（5）式
切比雪夫距离	$d ∞ (x i, x j) = x i - x j ∞ = max k ∈ 1,2, ?, p x ik - x jk$	（6）式
马哈拉诺比斯距离	$d a (x i - x j) = (x i - x j) T A (x i - x j)$	（7）式

表1

表2

常用核函数的表达式和特征"

常用核函数	表达式		特征
多项式核函数	$K (x i, x j) = (x i x j + 1) q$	（8）式	全局性强,外推能力较强,内推能力较弱
径向基核函数	$K (x i, x j) = exp - x i - x j σ 2 2$	（9）式	内推能力较强,外推能力弱于多项式核函数
Sigmoid核函数	$K (x i, x j) = tanh [v (x i x j) + c]$	（10）式	对初值较敏感

表2

表3

表4

表5

图1

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