基于核磁共振测井的页岩油产能分析及甜点评价

doi:10.7657/XJPG20240308

摘要/Abstract

摘要：

吉木萨尔凹陷芦草沟组页岩油水平井产能差异大，各井产水率区别明显，其主控因素尚不清楚，现有甜点分类标准无法满足该区页岩油精细开发的需要，基于核磁共振测井截止值的含油性及可动性解释难以精细识别页岩油甜点。以核磁共振测井和实验室核磁共振测试为基础，基于分频处理、分流体核磁共振测井孔隙结构表征、弹性能排油模拟等技术，精细表征页岩油层中不同类型流体分布；分别刻画油水赋存孔径，建立可动油量评价模型，对流体赋存、孔径分布、可动油量等进行定量表征；结合单井试油和生产数据，明确水平井产能控制因素。研究表明：大孔轻质组分占比、可动油孔隙度与水平井产能的相关性明显优于孔隙度、含油饱和度和核磁可动油孔隙度；水影响指数则反映地层水对页岩油流动的影响程度，该值越小，相同可动油孔隙度下水平井产能越高、含水率越低。以大孔轻质组分占比、水影响指数和可动油孔隙度为指标，将页岩油油层划分为3类，由Ⅰ类至Ⅲ类油层，日产油量快速减小，含水率明显升高，可作为芦草沟组页岩油甜点精细评价的依据。

关键词: 吉木萨尔凹陷, 芦草沟组, 页岩油, 核磁共振, 产能, 甜点评价

Abstract:

Shale oil horizontal wells in the Lucaogou formation within the Jimsar sag vary greatly in productivity, with notable differences in water production rate. Main factors controlling this phenomenon remain unclear. Moreover, the existing sweet spot classification criteria fail to meet the requirements for fine development of shale oil in this area, and the interpretation of oil saturation and mobility based on the cutoff values from nuclear magnetic resonance (NMR) logging cannot realize precise identification of shale oil sweet spots. In this paper, based on the results of NMR logging and laboratory NMR testing, and through frequency division processing, NMR logging-based pore structure characterization by fluids, and elastic oil displacement simulation, the distribution of different types of fluids in shale oil reservoirs was characterized detailedly. The pore sizes for oil/water occurrence were delineated, and a model for evaluating movable oil amount was established to quantitatively characterize the fluid occurrence, pore size distribution, movable oil quantity, and other parameters. By integrating single-well testing and production data, the factors controlling horizontal well productivity were elucidated. The results show that horizontal well productivity is much more correlated to the large-pore light oil proportion (LOP) and movable oil porosity (MOP) than to porosity, oil saturation, NMR MOP and other parameters. The water influence index reflects the extent of formation water’s impact on shale oil flow, and given the same MOP, a smaller water influence index corresponds to a higher productivity and a lower water cut of a horizontal well. Based on large-pore LOP, water influence index and MOP, the shale oil sweet spots are classified into Class Ⅰ, Class Ⅱ and Class Ⅲ, with rapid decline in daily oil production and significant rise in water cut, which can serve as the basis for finely evaluating shale oil sweet spots in the Lucaogou formation.

Key words: Jimsar sag, Lucaogou formation, shale oil, NMR, productivity, sweet spot evaluation

中图分类号:

TE122

覃建华, 李映艳, 杜戈峰, 周阳, 邓远, 彭寿昌, 肖佃师. 基于核磁共振测井的页岩油产能分析及甜点评价[J]. 新疆石油地质, 2024, 45(3): 317-326.

QIN Jianhua, LI Yingyan, DU Gefeng, ZHOU Yang, DENG Yuan, PENG Shouchang, XIAO Dianshi. NMR Logging-Based Productivity Analysis and Sweet Spot Evaluation for Shale Oil[J]. Xinjiang Petroleum Geology, 2024, 45(3): 317-326.

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油层分类	可动性指标		含油性指标	产能指标
油层分类	可动油孔隙度/%	水影响指数	大孔轻质组分占比/%	含水率/%	米产油强度/（t·d^-1）
Ⅰ类油层	>2.5	<0.18	>35	<45	>1.7
Ⅱ类油层	1.5~2.5	<0.18	25~35	45~70	0.5~1.7
Ⅱ类油层	>3.0	>0.18	25~35	45~70	0.5~1.7
Ⅲ类油层	0.5~1.5	<0.18	15~25	70~90	0.2~0.5
Ⅲ类油层	2.5~3.0	>0.18	15~25	70~90	0.2~0.5
无效油层	<0.5		<15	>90	<0.2