Analysis of Physical Properties and Influencing Factors of Longmaxi Shale in Sichuan Basin
Publication: Journal of Energy Engineering
Volume 148, Issue 6
Abstract
The physical properties of shale reservoirs directly affect the form of shale gas and its preservation conditions, and an evaluation of these properties has great significance on the storage and exploitation of shale gas. In this study, the Longmaxi Formation shale in the Sichuan Basin was considered as the research object. The parameters of porosity, permeability, mineral composition, total organic carbon content, density, in-situ stress, brittleness index, and fluid saturation of the samples were obtained through a series of tests. The influence of each parameter on the porosity and permeability was analyzed, and a weight analysis was conducted using an analytic hierarchy process (AHP). The results show that: clay mineral content in the mineral composition has a positive correlation with porosity, and the content of brittle minerals can affect the fracture development density and improve the permeability of samples; the total organic carbon content has a positive correlation with porosity and permeability; increases in density and in-situ stress will significantly reduce the porosity and permeability of samples; the brittleness index has a negative correlation with porosity and a positive correlation with permeability; water saturation has a positive correlation with porosity, gas saturation has a negative correlation with porosity, and the movable oil saturation has an obvious logarithmic relationship with porosity and a negative correlation with permeability. Furthermore, the AHP was used to analyze the specific effects of various parameters on porosity and permeability, with the weight of total organic carbon content > mineral composition > brittleness index > density > in-situ stress > fluid saturation. In this study, we evaluated the physical properties of shale reservoirs, which provides an important basis for shale reservoir evaluation and mining area selection.
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Data Availability Statement
All data, models, and code generated or used throughout the study appear in the published article.
Acknowledgments
This research was funded by the Natural Science Foundation of China (41941018) and National Key Research and Development Program (Grant Nos. 2018YFC0603705 and 2016YFC0600901).
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Published In
Journal of Energy Engineering
Volume 148 • Issue 6 • December 2022
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© 2022 American Society of Civil Engineers.
History
Received: Oct 14, 2021
Accepted: Jun 1, 2022
Published online: Sep 14, 2022
Published in print: Dec 1, 2022
Discussion open until: Feb 14, 2023
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