NMR Logging-Based Productivity Analysis and Sweet Spot Evaluation for Shale Oil

doi:10.7657/XJPG20240308

Abstract

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

CLC Number:

TE122

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.

Figures/Tables 10

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Table 1.

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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