Characterization and 3D modeling of multiscale natural fractures in shale gas reservoir: A case study in the Pingqiao structural belt, Sichuan Basin

doi:10.13745/j.esf.sf.2023.6.13

Abstract

Abstract:

Natural fractures in shale reservoirs are important reservoir spaces and seepage channels. Identifying the types and spatial distribution of natural fractures is essential for shale gas exploration and development. This paper, based on seismic/outcrop data, core observation, well logging and micro-test analysis, mainly considering the effect of fractures on shale gas enrichment and high production, divides natural fractures of shale reservoirs into three scale levels: large, medium-small and micro, and clarifies the methodologies for fracture characterization and modeling at each scale level and application results. In summary: (1) large fractures were mainly characterized using stacked 3D seismic data; medium-small fractures using a combination of core, image log and seismic attributes data; and microfractures using microanalysis such as core description, high-resolution scanning electron microscope and maps analysis. Through fracture characterization, the fracture density, crack opening, dip, orientation and filling status at each scale level were determined. (2) The DFN model of large fractures was established via deterministic modeling, using the characterization parameters of post-stack seismic attributes as the input. For medium-small fractures, single-well image logs were used as prior information; a fracture probability model of multi-information fusion was established as the spatial trend; and the DFN model was established via stochastic modelling. Microfracture modeling was based on microfracture parameters obtained from micro-test analysis; microfracture density model was established by combining well data with TOC and other main control factors; and the DFN model was established via stochastic modeling. (3) Taking the shale gas reservoir in the Pingqiao tectonic zone, Sichuan Basin as an example, fracture characterization and fracture 3D geological modeling for different fracture types were carried out. The fracture initiation site, scale, orientation and occurrence characteristics were defined, and fracture attributes such as fracture location, dip angle, azimuth angle, geometric size, development density, porosity and permeability were described. The methodologies for the multiscale natural fracture characterization and modeling provide a basis for numerical modeling of shale gas reservoirs. The 3D geological model of shale reservoir in the Pingqiao tectonic belt and the simulation results are in good agreement with geological knowledge and production data, thus providing a reference for the devlopment of shale gas fields.

Key words: shale gas, multiscale fracture characterization, fracture modeling, Sichuan Basin

CLC Number:

P618.130.2

QIAO Hui, ZHANG Yonggui, NIE Haikuan, PENG Yongmin, ZHANG Ke, SU Haikun. Characterization and 3D modeling of multiscale natural fractures in shale gas reservoir: A case study in the Pingqiao structural belt, Sichuan Basin[J]. Earth Science Frontiers, 2024, 31(5): 89-102.

Figures/Tables 14

Fig.1 Location of the Pingqiao structural belt (a) and structural map of the bottom of Wufeng Formation (b)

Fig.2 Fracture types in shale reservoir

Fig.3 Characterization of large fractures in the 3rd member by ant tracking. (a) Fracture distribution. (b) Strike directions. (c) Propogation length distribution.

Fig.4 Medium-small fractures identified by core and imaging logging in the study area

Fig.5 Distribution of main parameters for medium-small fractures

Fig.6 Cross-well fracture correlation in wells C, A and B

Fig.7 Macrofractures identified by SEM

Fig.8 Distribution of main parameters for shale bedding fractures

Fig.9 Relationship between density of interlayer bedding fractures and total organic carbon (TOC) content

Fig.10 Planar distribution of total organic carbon (TOC) content

Fig.11 Fracture model for large-scale fractures

Fig.12 Modelling of medium-small fractures in the 3rd member. (a) Fracture density model. (b) Fracture density distribution. (c) DFN model.

Fig.13 Modelling of bedding-parallel fractures in shale of the 3rd member. (a) Planar distribution of fracture density. (b) DFN model.

Table 1 Model testing results on wells A and B

井名	物质基础			裂缝发育		产能状况
	TOC含量/	总含气量/	脆性矿物含量/	中小尺度裂缝密度/	页理缝发育密度/	试气产量/	产气量/	累产气量/
	%	(m³·t^-1)	%	(条·m^-1)	(条·m^-1)	(10⁴m³·d^-1)	(10⁴m³·d^-1)	(10⁸m³)
A井	3.5	6.4	68.5	3.63	380	19.65	1.99	0.325 7
B井	3.7	6.3	71.2	1.03	424	9.01	8.25	0.339 9

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