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TitleCharacterization of shale pore size distribution by NMR considering the influence of shale skeleton signals
AuthorLi, J; Lu, S; Jiang, CORCID logo; Wang, M; Chen, ZORCID logo; Chen, G; Li, J; Lu, S
SourceEnergy & Fuels vol. 33, issue 7, 2019 p. 6361-6372,
Alt SeriesNatural Resources Canada, Contribution Series 20190109
PublisherAmerican Chemical Society (ACS)
Mediapaper; on-line; digital
File formatpdf; html
AreaBeijing; China
Lat/Long WENS 115.0000 119.5000 38.0000 36.0000
Subjectsfossil fuels; sedimentology; geochemistry; mineralogy; Science and Technology; petroleum resources; hydrocarbons; oil; oil saturation; bedrock geology; lithology; sedimentary rocks; shales; porosity; pore size; pore structure; organic geochemistry; organic carbon; temperature; mineralogical analyses; microfractures; laminations; hydrogen; kerogen; Paleogene; Jiyang Depression; Bohai Bay Basin; Zhanhua Sag; Dongying Sag; Shahejie Formation; Methodology; Phanerozoic; Cenozoic; Tertiary
Illustrationslocation maps; geoscientific sketch maps; plots; tables; spectra
ProgramGeoscience for New Energy Supply (GNES) Canadian Energy Geoscience Innovation Cluster (CEGIC)
Released2019 06 11
AbstractAs a non-destructive method, the proton nuclear magnetic resonance (1H NMR) technique with low echo time (TE, e.g., 0.07 ms) has been increasingly used for characterizing full pore size distribution (PSD) of shales. However, hydrogen contained in some components of the shale skeleton (e.g., kerogen and structural water) also can be detected by NMR in the case of low TE, resulting in a questionable PSD derived directly from the T2 spectra of oil-saturated shale. In this study, eight shale samples with different organic and mineralogical components from the Jiyang Depression, China were investigated with regular NMR, low-temperature nitrogen adsorption (LTNA), NMR cryoporometry (NMRC), and mercury injection capillary pressure (MICP) techniques to propose a corrected NMR approach for characterizing shale PSD by considering the influence of the shale skeleton signals. The NMR relaxation characteristics (e.g., T2 spectra and T1-T2 map) of as-received shale, solvent-extracted and dried shale (EX), and oil-saturated shale (OS) were discussed to reveal the NMR response from the shale skeleton itself at T2 below 1 ms on the T2 spectra. With the new approach, the NMR T2 spectra of oil occurring in the OS shale were first obtained through inversion of the differentiated T2 decay curves between the T2 decay curves of the EX shale and OS shale and were then converted to PSD by combination of LTNA, NMRC, and MICP results. For pores with T2 less than 1 ms, the PSD obtained from NMR T2 spectra of the oil signals only compared well with the results of LTNA and NMRC, with a relative error of less than 15% in pore volume. In contrast, the relative errors of PSD obtained directly from the NMR T2 spectra of oil-saturated shales were up to 134%. It was found that the higher total organic carbon shale contained, the larger errors in the PSD profiles, pore volume, and porosity that were calculated directly from the oil-saturated shale's NMR T2 spectra. Compared with the traditional NMR methods, the corrected approach can provide a more accurate PSD for shales, especially for those organic-rich ones.
Summary(Plain Language Summary, not published)
Proton nuclear magnetic resonance (H NMR) technique has been used in this study to characterize the pore size distribution of shale samples. It was found that hydrogen contained in the solid components of shale such as kerogen (i.e., insoluble solid organic matter) and water bound to the clay minerals can produce significant NMR signals on the T2 spectra, and thus significantly affect the pore characters derived directly from the T2 spectra of a shale sample. A new approach was proposed here to estimate a shale pore size distribution by using the differential T2 spectra between the T2 spectra of solvent extracted shale and the T2 spectra of the then oil-saturated shale. Compared with the traditional NMR methods, the corrected approach provides a more accurate PSD for shales, especially for those organic-rich ones.

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