Prediction of natural fracture in shale oil reservoir based on <i>R</i>/<i>S</i> analysis and conventional logs

doi:10.1007/s11707-020-0843-z

Front. Earth Sci.

2021, Vol. 15

Issue (3) : 705-718 https://doi.org/10.1007/s11707-020-0843-z

REVIEW ARTICLE

Prediction of natural fracture in shale oil reservoir based on R/S analysis and conventional logs

Haoran XU^1,², Wei JU^1,²(

), Xiaobing NIU^3,⁴, Shengbin FENG⁴, Yuan YOU⁴, Hui YANG^1,², Sijia LIU⁵, Wenbo LUAN²

¹. Key Laboratory of Coalbed Methane Resources and Reservoir Formation Process (Ministry of Education) China University of Mining and Technology, Xuzhou 221008, China
². School of Resources and Geosciences, China University of Mining and Technology, Xuzhou 221116, China
³. School of Geosciences, China University of Petroleum (East China), Qingdao 266580, China
⁴. Institute of Exploration and Development, PetroChina Changqing Oilfield Company, Xi’an 710018, China
⁵. School of Computer Science and Technology, China University of Mining and Technology, Xuzhou 221116, China

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Abstract

Investigation into natural fractures is extremely important for the exploration and development of low-permeability reservoirs. Previous studies have proven that abundant oil resources are present in the Upper Triassic Yanchang Formation Chang 7 oil-bearing layer of the Ordos Basin, which are accumulated in typical low-permeability shale reservoirs. Natural fractures are important storage spaces and flow pathways for shale oil. In this study, characteristics of natural fractures in the Chang 7 oil-bearing layer are first analyzed. The results indicate that most fractures are shear fractures in the Heshui region, which are characterized by high-angle, unfilled, and ENE-WSW-trending strike. Subsequently, natural fracture distributions in the Yanchang Formation Chang 7 oil-bearing layer of the study area are predicted based on the R/S analysis approach. Logs of AC, CAL, ILD, LL8, and DEN are selected and used for fracture prediction in this study, and the R(n)/S(n) curves of each log are calculated. The quadratic derivatives are calculated to identify the concave points in the R(n)/S(n) curve, indicating the location where natural fracture develops. Considering the difference in sensitivity of each log to natural fracture, gray prediction analysis is used to construct a new parameter, fracture prediction indicator K, to quantitatively predict fracture development. In addition, fracture development among different wells is compared. The results show that parameter K responds well to fracture development. Some minor errors may probably be caused by the heterogeneity of the reservoir, limitation of core range and fracture size, dip angle, filling minerals, etc.

Keywords natural fracture prediction shale oil reservoir R/S analysis Chang 7 oil-bearing layer Ordos Basin

Corresponding Author(s): Wei JU

Online First Date: 24 March 2021 Issue Date: 17 January 2022

Cite this article:

Haoran XU,Wei JU,Xiaobing NIU, et al. Prediction of natural fracture in shale oil reservoir based on R/S analysis and conventional logs[J]. Front. Earth Sci., 2021, 15(3): 705-718.

URL:

https://academic.hep.com.cn/fesci/EN/10.1007/s11707-020-0843-z
https://academic.hep.com.cn/fesci/EN/Y2021/V15/I3/705

Fig.1 Regional geological background of the Ordos Basin (Darby and Ritts, 2002; Ritts et al., 2004).

Fig.2 Stratigraphic column of the Yanchang Formation in the Ordos Basin (Zeng and Li, 2009).

Fig.3 Frequency histogram of the types of fractures obtained from the imaging logs date and core date.

Fig.4 Fracture characteristics from the cores, where the red arrows indicate natural fracture.

Fig.5 Fracture characteristics in the imaging logs.

Fig.6 Rose diagram of the strikes of natural fractures in the study area.

Fig.7 Double logarithm curve of R(n)/S(n) and n of AC, CAL, ILD, LL8 and DEN in Well Z200.

Fig.8 The relationship between the concave sections of the R(n)/S(n) curve and their quadratic derivative.

Fig.9 Log curves of the fracture zones in the core data and R/S calculation results of each log in Well Z200. The fracture density is the surface density observed in the core. K is the strength of the fracture response. The gray solid line is the dividing line of the gray correlation analysis.

Tab.1 The basic data of the gray correlation analysis

Tab.2 The standardized data of the gray correlation analysis

Tab.3 The gray relation coefficient and gray relational grade

Tab.4 Weight value of each conventional logs

Fig.10 Comparison of natural fracture zones in the core data and fracture zones recognized by the R/S analysis method in Well Z200.

Fig.11 Comparison of natural fracture zones in the core data and fracture zones recognized by the R/S analysis method in Wells Z15(a), Z87(b), Z186(c) and Z230(d).

Fig.12 The factors that influence the errors found in the rock core. (a) interbedded sandstones and mudstones, Z186,1703.5 m; (b) plant fossils, Z186, 1707.45 m; (c) carbonaceous particles, Z186,1731.5 m; (d) sulfur, Z186, 1732.87 m; (e) flowing structure, Z15, 1988.05 m; (f) sulfur, Z15, 1991.15 m.

Fig.13 Comparison of the average K values among different wells.

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