Controlling factors of lamellation fractures in marine shales: A case study of the Fuling Area in Eastern Sichuan Basin, China

Xiang, Xu; Zeng, Lianbo; Tian, He; Ling, Kegang; Che, Shiqi; Yu, Xiao; Shu, Zhiguo; Dong, Shaoqun

doi:10.1016/j.petrol.2021.109091

Cited by 17 publications

(15 citation statements)

References 66 publications

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“…The Jinping Anticline Belt simultaneously exhibited apparent D P and D ε anomalies. This supports that hydrocarbon enrichment indicated by a high D P anomaly may positively correlate with the intensity of development of bedding fractures generated by overpressure owing to gas generation in this region (Xu et al 2021), as suggested by a high D ε anomaly. Therefore, the Jinping Anticline Belt is a promising area for future exploration.…”

Section: Seismic Dispersion Attributes and Their Implications Of Shal...supporting

confidence: 78%

“…The closing and opening of aligned fractures at different effective stress fields can cause variations in shale anisotropy. Recent experimental studies have shown that the Longmaxi shale exhibits a substantially variable anisotropy with loading stress fields (Liu et al 2019b), indicating the presence of bedding fractures, which has been further supported by the observations from cores and outcrops (Zhang et al 2020b;Xu et al 2021).…”

Section: Introductionsupporting

confidence: 52%

“…Total organic carbon (TOC) has been used to determine gas generation in the organic shale of the Longmaxi Formation (Zou et al 2015;He et al 2017;Zhang et al 2020a). Horizontal bedding fractures, accounting for most natural fractures in the Longmaxi shale, provide storage spaces and migration channels for gas enrichment (Zhang et al 2020b;Xu et al 2021) and are favorable for hydraulic fracturing (Zhou et al 2020). Using seismic methods to identify hydrocarbon enrichment and predict bedding fractures can provide valuable information for locating promising shale gas reservoirs.…”

Section: Introductionmentioning

confidence: 99%

“…On the other hand, current research is focused on predicting vertical fractures in shale using wide-azimuth seismic inversion as they exhibit particular azimuthal seismic signatures that can be conveniently extracted (Bachrach 2015;Kumar et al 2018;Luo et al 2019). However, because of intense tectonic uplift and overpressure formed by gas generation, massive bedding fractures are observed in the Longmaxi shale that can accumulate and preserve natural gas (Zhang et al 2020b;Xu et al 2021). Thus, it is necessary to develop methods to predict bedding fractures in shales.…”

Section: Introductionmentioning

confidence: 99%

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Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

et al. 2022

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Prediction of hydrocarbon enrichment and natural fractures is significant for sweet spot characterization in shale gas reservoirs. However, it is difficult to estimate reservoir properties using conventional seismic techniques based on elastic and isotropic assumptions. Considering that the viscoelastic anisotropic model better represents organic shale, we propose a new seismic inversion method to improve shale gas characterization by incorporating the anisotropic reflectivity theory in the frequency-dependent inversion scheme. The computed P-wave velocity dispersion attribute DP evaluates the hydrocarbon enrichment by estimating the inelastic properties of shale associated with organic materials. The inverted anisotropic dispersion attribute Dε detects the development intensity of bedding fractures using frequency-dependent anisotropy owing to wave-induced fluid flow in parallel fractures. Synthetic tests indicate that DP can robustly estimate shale attenuation and Dε is sensitive to the frequency-dependent anisotropy of shale. The results are validated by reservoir properties measured in gas-producing boreholes and rock physical modeling analysis, supporting the applicability of the dispersion attributes for hydrocarbon identification and bedding fracture detection. The predicted hydrocarbon enrichment and the development of bedding fractures correlate with the structural characteristics of the shale formation. The depth-related shale properties can be described by improving the geological understanding of the study area. Finally, favorable areas with high hydrocarbon enrichment and extensive development of bedding fractures are identified by simultaneously considering high DP and Dε anomalies, providing essential information for predicting potential shale gas reservoirs. Article Highlights A novel seismic inversion method for anisotropy dispersion attributes is proposed P-wave velocity dispersion attribute is used to identify hydrocarbon enrichment in shale Anisotropic dispersion attribute is used to detect bedding fractures in shale

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Section: Seismic Dispersion Attributes and Their Implications Of Shal...supporting

confidence: 78%

Section: Introductionsupporting

confidence: 52%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

et al. 2022

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“…13 , 14 The controlling factors of the pore structure are different in different thermal maturity stages of shale. 15 − 19 During the evolution of organic matter, a large number of micropores, mesopores, and macropores will be formed. 20 …”

Section: Introductionmentioning

confidence: 99%

Study on Pore Structure and Fractal Characterization during Thermal Evolution of Oil Shale Experiments

Liu

Du³

et al. 2022

ACS Omega

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In order to better study the characteristics of the pore structure and to explore the influence factors of its fractal dimensions during the thermal evolution of oil shale, the immature oil shale ( T max = 433 °C, TOC = 28.00%) of the Ordos Basin Extension Group was selected to simulate the whole thermal evolution process from immature to over mature in a semiopen system. Organic geochemical data show that the thermal simulation hydrocarbon generation threshold is between 300 and 400 °C. According to AIP-SEM observation, the pore types of the samples are different in different thermal simulation stages. The fractal dimensions are calculated by low-temperature N 2 adsorption data using the fractal Frenkel–Halsey–Hill fractal model. The average surface fractal dimension ( D 1 ) is 2.26, indicating that the pore (<4 nm) surface is relatively smooth. The average pore structure fractal dimension ( D 2 ) is 2.49, indicating that the pore (>4 nm) structure is complex. Through the exploration of the relationship between fractal dimensions and organic geochemistry, whole rock X-ray diffraction, and N 2 adsorption data, it is found that fractal dimensions have different degrees of correlation with thermal maturity, mineral composition, TOC content, and pore parameters. Through comprehensive research, it shows that hydrocarbon generation and expulsion, oil and gas cracking, and organic matter carbonization have important effects on the pore structure and fractal characteristics of oil shale.

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Structure- and lithofacies-controlled natural fracture developments in shale: Implications for shale gas accumulation in the Wufeng-Longmaxi Formations, Fuling Field, Sichuan Basin, China

Zhang

Ren

Shi

et al. 2023

Geoenergy Science and Engineering

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Controlling factors of lamellation fractures in marine shales: A case study of the Fuling Area in Eastern Sichuan Basin, China

Cited by 17 publications

References 66 publications

Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

Hydrocarbon Identification and Bedding Fracture Detection in Shale Gas Reservoirs Based on a Novel Seismic Dispersion Attribute Inversion Method

Study on Pore Structure and Fractal Characterization during Thermal Evolution of Oil Shale Experiments

Structure- and lithofacies-controlled natural fracture developments in shale: Implications for shale gas accumulation in the Wufeng-Longmaxi Formations, Fuling Field, Sichuan Basin, China

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