A new method for predicting capillary pressure curves based on NMR echo data: Sandstone as an example

被引:9
作者
Wu, Bohan [1 ,2 ]
Xie, Ranhong [1 ,2 ]
Xu, Chenyu [1 ,2 ]
Wei, Hongyuan [1 ,2 ]
Wang, Shuai [1 ,2 ]
Liu, Jilong [1 ,2 ]
机构
[1] China Univ Petr, State Key Lab Petr Resources & Prospecting, Beijing 102249, Peoples R China
[2] China Univ Petr, Key Lab Earth Prospecting & Informat Technol, Beijing 102249, Peoples R China
基金
中国国家自然科学基金;
关键词
Pore structure; MICP cures; NMR echo Data; Sandstone reservoir classification; P-C CURVES; RESERVOIRS; FIELD; LOGS;
D O I
10.1016/j.petrol.2021.108581
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
The mercury injection capillary pressure (MICP) curves have been widely used for the evaluation of the pore structure. In practical application, the MICP curves are usually obtained by the mercury injection experiment, but the experimental measurement can not obtain the MICP curves of the reservoir continuously. Since the pore size distribution obtained from the nuclear magnetic resonance (NMR) transverse relaxation time (T2) distribution is related to the pore-throat size distribution obtained from the MICP curve, so in previous studies, the MICP curves were predicted based on the NMR T2 distribution. However, the NMR T2 distribution obtained by the inversion of the NMR echo data has uncertainty, which affects the prediction accuracy of the MICP curves. In this paper, a new method for predicting the MICP curves of sandstone based on NMR echo data is proposed for the first time. Multiple characteristic parameters of the NMR echo data are calculated. The relationship between the parameters and the mercury saturation (Shg) is established at each capillary pressure point to predict the MICP curves. And the parameters of the MICP curves and the physical parameters are selected to create a reservoir classification index. The results show that the method for predicting the MICP curves of sandstone based on NMR echo data has high prediction accuracy and strong stability, and the reservoir classification index provides an accurate classification of sandstone reservoirs.
引用
收藏
页数:12
相关论文
共 22 条
[1]  
[Anonymous], 2010, Nuclear Magnetic Resonance Petrophysical and Logging Applications
[2]  
Dastidar R, 2007, PETROPHYSICS, V48, P186
[3]   Construction of synthetic capillary pressure curves from the joint use of NMR log data and conventional well logs [J].
Eslami, Maede ;
Kadkhodaie-Ilkhchi, Ali ;
Sharghi, Yousef ;
Golsanami, Naser .
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2013, 111 :50-58
[4]  
Jin G., 2019, IEEE GEOSCI REMOTE S, P1
[5]   Dimensional-model studies of oil-field behavior [J].
Leverett, MC ;
Lewis, WB ;
True, ME .
TRANSACTIONS OF THE AMERICAN INSTITUTE OF MINING AND METALLURGICAL ENGINEERS, 1942, 146 :175-192
[6]   Analytical derivation of Brooks-Corey type capillary pressure models using fractal geometry and evaluation of rock heterogeneity [J].
Li, Kewen .
JOURNAL OF PETROLEUM SCIENCE AND ENGINEERING, 2010, 73 (1-2) :20-26
[7]   Characterization of Pore Structures of Tight Sandstone Reservoirs by Multifractal Analysis of the NMR T2 Distribution [J].
Liu, Mi ;
Xie, Ranhong ;
Guo, Jiangfeng ;
Jin, Guowen .
ENERGY & FUELS, 2018, 32 (12) :12218-12230
[8]   A New Method for Predicting Capillary Pressure Curves Based on NMR Logging in Tight Sandstone Reservoirs [J].
Liu, Mi ;
Xie, Ranhong ;
Xu, Hongjun ;
Wu, Songtao ;
Zhu, Rukai ;
Mao, Zhiguo .
APPLIED MAGNETIC RESONANCE, 2018, 49 (10) :1043-1058
[9]   Determining the segmentation point for calculating the fractal dimension from mercury injection capillary pressure curves in tight sandstone [J].
Liu, Mi ;
Xie, Ranhong ;
Li, Changxi ;
Li, Xia ;
Jin, Guowen ;
Guo, Jiangfeng .
JOURNAL OF GEOPHYSICS AND ENGINEERING, 2018, 15 (04) :1350-1362
[10]   RELATIONS BETWEEN PORE SIZE FLUID AND MATRIX PROPERTIES, AND NML MEASUREMENTS [J].
LOREN, JD ;
ROBINSON, JD .
SOCIETY OF PETROLEUM ENGINEERS JOURNAL, 1970, 10 (03) :268-&