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Original Paper | Open Access

Mechanical characteristics and reservoir stimulation mechanisms of the Gulong shale oil reservoirs, the northern Songliao Basin

Si-Wei Menga,b, Jia-Ping Taoa,b, Tian-Jiao Lic, Dong-Xu Lid, Su-Ling Wange, Liu Yangf, Xin Liub,c, Li-Hao Lianga,b, He Liua,b( )
PetroChina Research Institute of Petroleum Exploration Development, Beijing, 100083, China
National Key Laboratory of Continental Shale Oil, Daqing 163002, Heilongjiang, China
Dalian University of Technology, Dalian, 116024, Liaoning, China
PetroChina Daqing Oilfield Co. Ltd., Daqing, 163002, Heilongjiang, China
Northeast Petroleum University, Daqing, 163002, Heilongjiang, China
China University of Mining and Technology (Beijing), Beijing, 100083, China

Edited by Jia-Jia Fei and Min Li

Show Author Information

Abstract

Shale oil of the Qingshankou Formation of the Gulong Sag, the northern Songliao Basin, represents the first attempt at large-scale development of pure-shale-type shale oil in China. By integrating the multi-scale refined reservoir characterization with macro-micro-scale mechanical testing, it is clarified that the Gulong shale is characterized by high clay mineral content, high rock plasticity, highly-developed bedding, and prominent mechanical anisotropy. A three-dimensional (3D) fracture propagation model of hydraulic fracturing was built for the Gulong shale, which fully captures the hydraulic fracture distribution pattern affected by the high bedding density, in-situ stress, and fracturing treatment parameters. Our research showed that due to influences of bedding, hydraulic fracturing in the Gulong shale forms a complex fracture morphology featuring the main fracture with multiple perpendicular branches that have different lengths (like the outdoor directional TV antenna); however, the vertical propagation of fractures is inhibited, and the fracture height is commonly less than 10 m. The limited stimulated reservoir volume (SRV) is the main problem facing the fracturing stimulation of the Gulong shale oil. Bedding density has vital effects on fracture morphology, so case-specific fracturing designs shall be developed for shale intervals with different bedding development degrees. For reservoirs with well-developed bedding, it is suggested to properly increase the perforation cluster spacing and raise the volume and proportions of viscous fluids of the pad, so as to effectively promote vertical fracture propagation and improve reservoir stimulation performance. This study integrates multi-scale fine reservoir characterization and macro-micro-scale mechanical testing, as well as the construction and numerical simulation of hydraulic fracturing models for high-density layered shale reservoirs, providing a new approach and methodological framework for the fracturing research of high-density layered shale reservoirs.

Keywords

Shale oilHydraulic fracturingHigh bedding densityFracture propagation model

References

 

Chang, X., Shan, Y., Zhang, Z., et al., 2015. Behavior of propagating fracture at bedding interface in layered rocks. Eng. Geol. 197, 33-41. https://doi.org/10.1016/j.enggeo.2015.08.010.
Crossref Google Scholar
 

Dong, J., Yuan, G., Wang, X., et al., 2021. Experimental study of multi-timescale crack blunting in hydraulic fracture. Petrol. Sci. 18, 234-244. https://doi.org/10.1007/s12182-020-00479-1.
Crossref Google Scholar
 

Feng, Z., Liu, B., Shao, H., et al., 2020. The diagenesis evolution and accumulating performance of the mud shale in Qingshankou Formation in Gulong area, Songliao Basin. Pet. Geol. Oilfield Dev. Daqing 39, 72-85. https://doi.org/10.19597/J.ISSN.1000-3754.202004057 (in Chinese)
Crossref Google Scholar
 

Heng, S., Liu, X., Li, X., et al., 2019. Experimental and numerical study on the non-planar propagation of hydraulic fractures in shale. J. Petrol. Sci. Eng. 179, 410-426. https://doi.org/10.1016/j.petrol.2019.04.054.
Crossref Google Scholar
 

Jin, X., Li, G., Meng, S., et al., 2021. Microscale comprehensive evaluation of continental shale oil recoverability. Petrol. Explor. Dev. 48, 256-268. https://doi.org/10.1016/S1876-3804(21)60021-6.
Crossref Google Scholar
 

Kuang, L., Hou, L., Wu, S., et al., 2022. Organic matter occurrence and pore-forming mechanisms in lacustrine shales in China. Petrol. Sci. 19 (4), 1460-1472. https://doi.org/10.1016/j.petsci.2022.03.005.
Crossref Google Scholar
 

Labani, M., Rezaee, R., 2015. The importance of geochemical parameters and shale composition on rock mechanical properties of gas shale reservoirs: a case study from the Kockatea Shale and Carynginia Formation from the Perth Basin, Western Australia. Rock Mech. Rock Eng. 48, 1249-1257. https://doi.org/10.1007/s00603-014-0617-6.
Crossref Google Scholar
 

Li, L., Tang, C., Wang, S., et al., 2013. A coupled thermo-hydrologic-mechanical damage model and associated application in a stability analysis on a rock pillar. Tunn. Undergr. Space Technol. 34, 38-53. https://doi.org/10.1016/j.tust.2012.10.003.
Crossref Google Scholar
 

Li, N., Yu, J., Wang, D., et al., 2022. Development status of crosslinking agent in high-temperature and pressure fracturing fluid: a review. J. Nat. Gas Sci. Eng. 107, 104369. https://doi.org/10.1016/j.jngse.2021.104369.
Crossref Google Scholar
 

Li, T., Li, L., Tang, C., et al., 2019. A coupled hydraulic-mechanical-damage geotechnical model for simulation of fracture propagation in geological media during hydraulic fracturing. J. Petrol. Sci. Eng. 173, 1390-1416. https://doi.org/10.1016/j.petrol.2018.10.104.
Crossref Google Scholar
 

Liu, B., Shi, J., Fu, X., et al., 2018. Petrological characteristics and shale oil enrichment of lacustrine fine-grained sedimentary system: a case study of organic-rich shale in first member of Cretaceous Qingshankou Formation in Gulong Sag, Songliao Basin, NE China. Petrol. Explor. Dev. 45, 884-894. https://doi.org/10.1016/S1876-3804(18)30091-0.
Crossref Google Scholar
 

Liu, H., Kuang, L., Li, G., et al., 2020. Considerations and suggestions on optimizing completion methods of continental shale oil in China. Acta Pet. Sin. 41, 489-495. https://doi.org/10.7623/syxb202004011 (in Chinese).
Crossref Google Scholar
 

Liu, X., Meng, S., Liang, Z., et al., 2023. Microscale crack propagation in shale samples using focused ion beam scanning electron microscopy and three-dimensional numerical modeling. Petrol. Sci. 20 (3), 1488-1512. https://doi.org/10.1016/j.petsci.2022.10.004.
Crossref Google Scholar
 

Lu, C., Jiang, H., Yang, J., et al., 2022. Simulation and optimization of hydraulic fracturing in shale reservoirs: a case study in the Permian Lucaogou formation, China. Energy. Rep. 8, 2558-2573. https://doi.org/10.1016/j.egyr.2022.01.189.
Crossref Google Scholar
 

Lu, C., Lu, Y., Guo, J., et al., 2020. Stability of the formation interface under the impact of hydraulic fracture propagation in the vicinity of the formation interface. Petrol. Sci. 17, 1101-1118. https://doi.org/10.1007/s12182-019-00416-x.
Crossref Google Scholar
 

Meng, S., Li, D., Wang, Q., et al., 2021. Nanoindentation-based three-parameter fracability evaluation method for continental shales. Front. Earth. Sc. 9, 797405. https://doi.org/10.3389/feart.2021.797405.
Crossref Google Scholar
 

Nandlal, K., Weijermars, R., 2022. Shale well factory model reviewed: eagle Ford case study. J. Petrol. Sci. Eng. 212, 110158. https://doi.org/10.1016/j.petrol.2022.110158.
Crossref Google Scholar
 

Oliver, W., Pharr, G., 1992. An improved technique for determining hardness and elastic modulus using load and displacement sensing indentation experiments. J. Mater. Res. 7, 1564-1583. https://doi.org/10.1557/JMR.1992.1564.
Crossref Google Scholar
 
Ouchi, H., Agrawal, S., Foster, J., et al., 2017. Effect of small scale heterogeneity on the growth of hydraulic fractures. In: SPE Hydraulic Fracturing Technology Conference and Exhibition. 24-26 January, the Woodlands, Texas. https://doi.org/10.2118/184873-MS.
Crossref
 

Ren, L., Lin, R., Zhao, J., et al., 2018. Stimulated reservoir volume estimation for shale gas fracturing: mechanism and modeling approach. J. Petrol. Sci. Eng. 166, 290-304. https://doi.org/10.1016/j.petrol.2018.03.041.
Crossref Google Scholar
 

Sun, L., He, W., Feng, Z., et al., 2022. Shale oil and gas generation process and pore fracture system evolution mechanisms of the continental Gulong Shale, Songliao Basin, China. Energy. Fuels. 36, 6893-6905. https://doi.org/10.1021/acs.energyfuels.2c01407.
Crossref Google Scholar
 

Sun, L., Liu, H., He, W., et al., 2021. An analysis of major scientific problems and research paths of Gulong shale oil in Daqing Oilfield, NE China. Petrol. Explor. Dev. 48, 527-540. https://doi.org/10.1016/S1876-3804(21)60043-5.
Crossref Google Scholar
 

Veytskin, Y., Tammina, V., Bobko, C., et al., 2017. Micromechanical characterization of shales through nanoindentation and energy dispersive x-ray spectrometry. Geomech. Energy. Envir. 9, 21-35. https://doi.org/10.1016/j.gete.2016.10.004.
Crossref Google Scholar
 

Wang, H., Guo, Y., Wang, L., et al., 2017. An experimental study on mechanical anisotropy of shale reservoirs at different depths. Rock Soil Mech. 38, 2496-2506. https://doi.org/10.16285/j.rsm.2017.09.005.
Crossref Google Scholar
 

Wang, T., Liu, Z., Gao, Y., et al., 2018. Theoretical and numerical models to predict fracking debonding zone and optimize perforation cluster spacing in layered shale. J. Appl. Mech. 85, 011001. https://doi.org/10.1115/1.4038216.
Crossref Google Scholar
 

Wang, Y., Li, X., Zhang, B., et al., 2016. Optimization of multiple hydraulically fractured factors to maximize the stimulated reservoir volume in silty laminated shale formation, Southeastern Ordos Basin, China. J. Pet. Sci. Eng. 145, 370-381. https://doi.org/10.1016/j.petrol.2016.05.033.
Crossref Google Scholar
 

Zhang, Y., Wei, X., Tang, P., et al., 2020. Fracture propagating mechanism and fracturing engineering technology in Gulong shale oil reservoirs of Songliao Basin. Pet. Geol. Oilfield Dev. Daqing 39, 170-175. https://doi.org/10.19597/J.ISSN.1000-3754.202004060 (in Chinese).
Crossref Google Scholar
 

Zhao, P., Xie, L., Fan, Z., et al., 2021. Mutual interference of layer plane and natural fracture in the failure behavior of shale and the mechanism investigation. Petrol. Sci. 18, 618-640. https://doi.org/10.1007/s12182-020-00510-5.
Crossref Google Scholar
 

Zhao, W., Hu, S., Hou, L., et al., 2020. Types and resource potential of continental shale oil in China and its boundary with tight oil. Petrol. Explor. Dev. 47 (1), 1-11. https://doi.org/10.1016/S1876-3804(20)60001-5.
Crossref Google Scholar
 

Zhao, X., Jin, F., Liu, X., et al., 2022. Numerical study of fracture dynamics in different shale fabric facies by integrating machine learning and 3-D lattice method: a case from Cangdong Sag, Bohai Bay basin, China. J. Petrol. Sci. Eng. 218, 110861. https://doi.org/10.1016/j.petrol.2022.110861.
Crossref Google Scholar
 

Zhou, T., Wang, H., Li, F., et al., 2020. Numerical simulation of hydraulic fracture propagation in laminated shale reservoirs. Petrol. Explor. Dev. 47, 1117-1130. https://doi.org/10.1016/S1876-3804(20)60122-7.
Crossref Google Scholar
 

Zou, C., Dong, D., Wang, Y., et al., 2016. Shale gas in China: characteristics, challenges and prospects (Ⅱ). Petrol. Explor. Dev. 43, 182-196. https://doi.org/10.1016/S1876-3804(16)30022-2.
Crossref Google Scholar
Petroleum Science
Volume 21 Issue 3,
June 2024
Pages 2023-2036
DOI: 10.1016/j.petsci.2023.11.002
Cite this article:
Meng S-W, Tao J-P, Li T-J, et al. Mechanical characteristics and reservoir stimulation mechanisms of the Gulong shale oil reservoirs, the northern Songliao Basin. Petroleum Science, 2024, 21(3): 2023-2036. https://doi.org/10.1016/j.petsci.2023.11.002

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Received: 25 November 2022
Revised: 30 August 2023
Accepted: 01 November 2023
Published: 02 November 2023
© 2023 The Authors.

This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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