基于储层动用程度的块状砂体流动单元划分方法及应用研究:以哈萨克斯坦Akshabulak油田为例

doi:10.13745/j.esf.sf.2022.10.16

摘要/Abstract

摘要：

以南图尔盖盆地Akshabulak油田J-Ⅲ层块状砂体为例,利用油田投产初期生产工作制度相近井的产液剖面资料和单井日产油量划分出“好”“较好”“中等”“差”4类储层动用程度类型。以储层动用程度类型为判别函数,利用岩心分析资料选出与储层动用程度类型响应较好的7类地质参数。以7类地质参数为变量,以测井解释数据为基础,运用神经网络聚类技术将储层划分为“高”“较高”“中等”“低”4类不同级别的流动单元。统计结果表明,4类储层动用程度类型与4种级别流动单元的静态地质参数和动态开发指标界限具有较好的对应性。研究结果表明流动单元的组合样式决定了储层的垂向和平面动用程度:垂向上,流动单元发育种类越多,水体会优先流向高级别流动单元,这导致油藏垂向水驱动用程度不均匀;平面上,高级别流动单元较发育的区域,水体会优先波及,这导致油藏平面水驱前缘推进速度有明显差异。在此基础上提出垂向上高级别流动单元实施调剖堵水、平面上天然水驱协同人工注水开发的开发技术策略,实现了稳产高效开发。

关键词: 南图尔盖盆地, 块状砂体, 流动单元划分方法, 储层动用程度类型, 剩余油特征

Abstract:

Taking an example of the massive sandstone of layer J-Ⅲ, Akshabulak oilfield, southern Turgay Basin, Kazakhstan, we propose a new method to identify flow units based on reservoir performance ratings. First, four performance ratings, “excellent”, “good”, “moderate” and “poor”, are assigned according to reservoir production profile and daily well output under similar working conditions. Then, taking the reservoir performance rating as the discriminant function, based on core analysis results, seven types of reservoir quality indicators are selected for clustering analysis. Finally, based on the quality indicator values and well-log interpretation data, the flow units are delineated into four types, “high-flow”, “relatively high-flow”, “moderate-flow” and “low-flow”, according to water flow levels, by neural network clustering. Statistical analysis results show that the reservoir-quality indicator values correlate positively with reservoir performance ratings, therefore it is reasonable to identify flow units according to performance ratings. Our study indicates that the development pattern of flow units determines the reservoir performance: when flow units of different types are developed, water tends to flow towards units with higher flow levels causing uneven flooding in the vertical direction; horizontally, areas with high-level flow units are flooded preferentially causing significant uneven advancements of waterflooding front. We propose, therefore, to control vertical waterflooding by water plugging at high-level flow units and allow planar natural waterflooding combined with water injection to achieve stable and high-efficiency reservoir development.

Key words: South Turgay Basin, massive sandstone, flow unit identification, reservoir performance rating, residue oil characterization

中图分类号:

王进财, 范子菲, 赵伦, 陈烨菲, 张安刚, 张祥忠, 郭雪晶, 李毅. 基于储层动用程度的块状砂体流动单元划分方法及应用研究:以哈萨克斯坦Akshabulak油田为例[J]. 地学前缘, 2023, 30(4): 88-99.

WANG Jincai, FAN Zifei, ZHAO Lun, CHEN Yefei, ZHANG Angang, ZHANG Xiangzhong, GUO Xuejing, LI Yi. A new method for identification of flow units of sandstone reservoir based on reservoir performance and its application in the Akshabulak oilfield, Kazakhstan[J]. Earth Science Frontiers, 2023, 30(4): 88-99.

图/表 17

图1 Akshabulak油田构造位置及地层特征 a—油田构造位置图;b—地层综合柱状图。

Fig.1 Structural location and stratigraphic features of the Akshabulak oilfield

图2 Akshabulak油田顶面构造图及岩心特征图 a—油田基底顶面构造图;b—岩心特征(458井,1 854.20~1 859.20 m,含砾粗砂岩,岩石粒度3~16 mm,块状构造,砂体内不发育泥质夹层)。

Fig.2 Akshabulak oilfield structural features and drill cores

图3 Akshabulak油田J-Ⅲ层垂向非均质性及产液(吸水)特征 a—316采油井;b—307注水井。

Fig.3 Vertical heterogeneity and liquid production (water absorption) characteristics of layer J-Ⅲ

图4 J-Ⅲ层砂体类型及垂向特征 a—水下分流河道砂,348井;b—河口坝砂,360井;c—滩坝砂,33井。

Fig.4 Sand body types and vertical features of layer J-Ⅲ

图5 J-Ⅲ 层三角洲砂体垂向地震属性及沉积特征图 a—地震剖面图;b—沉积剖面图。

Fig.5 Vertical seismic attributes and sedimentary characteristics of J-Ⅲ delta sand bodies

图6 J-Ⅲ层地震属性及综合沉积特征 a—均方根振幅属性;b—均方根振幅属性值与砂岩厚度关系;c—单井岩心特征(自东向西粒度逐渐变细);d—沉积相平面展布。

Fig.6 Composite diagram showing seismic attributes and depositional features of layer J-Ⅲ

图7 基于储层动用程度类型的流动单元划分方法

Fig.7 Flow chart of flow unit identification based on reservoir performance rating

图8 J-Ⅲ层投产初期生产工作制度相近油井产量分布(28口井325个产量数据)

Fig.8 Single well production distribution plot for layer J-Ⅲ under similar working conditions (325 data from 28 wells)

图9 基于储层动用程度类型的流动单元划分参数优选图 a—渗透率与进汞35%时的孔喉半径;b—储层品质指数与进汞35%时的孔喉半径;c—流动层指数与进汞35%时的孔喉半径;d—流动层指数与泥质含量。

Fig.9 Positive correlation relationship between reservoir-quality indicator values and reservoir performance ratings as the basis for flow-unit identification

表1 不同动用程度储层地质参数统计表(315个样品)

Table 1 Reservoir-quality indicator values under different reservoir performance ratings(315 samples)

储层动用程度类型	K/(10^-3 μm²)	Ф	V_sh	R₃₅/μm	RQI/μm	FZI	Ф_z
好	1 698.0	0.29	0.04	18.22	2.25	5.51	0.40
较好	1 198.8	0.28	0.05	15.05	1.83	4.76	0.38
中等	412.1	0.26	0.05	11.42	1.36	3.83	0.35
差	56.5	0.24	0.06	8.27	0.96	3.03	0.31

图10 基于神经网络聚类技术的流动单元划分结果 a—流动层指数与进汞35%时的孔喉半径;b—储层品质指数与进汞35%时的孔喉半径。

Fig.10 Results of flow-unit delineation by neural network clustering

表2 不同级别流动单元地质参数统计表(238口井数据)

Table 2 Reservoir-quality indicator values under different flow unit types (238 well data)

流动单元	K/(10^-3 μm²)	Ф	V_sh	R₃₅/μm	RQI/μm	FZI	Ф_z
A	2 431.4	0.30	0.05	23.55	2.95	6.68	0.44
B	1 182.2	0.27	0.06	13.91	1.69	4.58	0.37
C	344.5	0.24	0.07	7.89	0.92	2.90	0.31
D	51.5	0.18	0.10	3.69	0.41	1.89	0.22

图11 J-Ⅲ层不同流动单元厚度分布及优势流动单元展布特征

Fig.11 Planar thicknesses of different flow units and dominant flow unit distribution in layer J-Ⅲ

表3 不同级别流动单元的相渗曲线特征值

Table 3 Reservoir performance characteristics of different flow unit types

流动单元	渗透率/m	原始含水饱和度/%	剩余油饱和度/%	水驱油效率/%
A	>6 000	0.07	0.1	0.89
B	>2 500~6 000	0.105	0.1	0.89
C	>1 000~2 500	0.14	0.15	0.83
D	2~1 000	0.17	0.15	0.82

图12 研究区J-Ⅲ层主力含油区不同流动单元水驱动用程度 a—不同流动单元剩余储量丰度图(单位为104 t·km-2,图中空白区域为空值区);b—不同流动单元剩余油饱和度分布图(单位为%,图中空白区域为空值区)。

Fig.12 Distributions of recoverable reserves (a) and residual oil saturation levels (b) in different types of flow units in layer J-Ⅲ in the study area

表4 基于油藏数值模拟的不同流动单元动用程度统计表

Table 4 Reservoir performance data for different flow unit types based on numerical simulation

流动单元	平均厚度/m	储量丰度/(10⁴t·km^-2)		含油饱和度/%		采出程度/%
流动单元	平均厚度/m	原始	剩余	原始	剩余	采出程度/%
J-Ⅲ层	13	75.4	31.7	0.87	0.39	0.58
A	8	50.6	20.1	0.87	0.38	0.60
B	11	51.8	22.3	0.87	0.41	0.57
C	11	51.9	23.2	0.87	0.46	0.55
D	8	37.1	17.7	0.87	0.49	0.52

图13 研究区J-Ⅲ 层主力含油区水驱前缘推进速度变化特征 a—调整前剩余油饱和度平面分布图;b—调整后剩余油饱和度平面分布图。图中空白区域为非储层发育区。

Fig.13 Variation of waterflooding-front advancing speed in layer J-Ⅲ in the study area

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