Comparative porosity and pore structure assessment in shales: Measurement techniques, influencing factors and implications for reservoir characterization
dc.contributor.author | Yuan, Yujie | |
dc.contributor.author | Rezaee, Reza | |
dc.date.accessioned | 2022-11-02T05:56:46Z | |
dc.date.available | 2022-11-02T05:56:46Z | |
dc.date.issued | 2019 | |
dc.identifier.citation | Yuan, Y. and Rezaee, R. 2019. Comparative porosity and pore structure assessment in shales: Measurement techniques, influencing factors and implications for reservoir characterization. Energies. 12 (11): ARTN 2094. | |
dc.identifier.uri | http://hdl.handle.net/20.500.11937/89583 | |
dc.identifier.doi | 10.3390/en12112094 | |
dc.description.abstract |
Porosity and pore size distribution (PSD) are essential petrophysical parameters controlling permeability and storage capacity in shale gas reservoirs. Various techniques to assess pore structure have been introduced; nevertheless, discrepancies and inconsistencies exist between each of them. This study compares the porosity and PSD in two different shale formations, i.e., the clay-rich Permian Carynginia Formation in the Perth Basin, Western Australia, and the clay-poor Monterey Formation in San Joaquin Basin, USA. Porosity and PSD have been interpreted based on nuclear magnetic resonance (NMR), low-pressure N2 gas adsorption (LP-N2-GA), mercury intrusion capillary pressure (MICP) and helium expansion porosimetry. The results highlight NMR with the advantage of detecting the full-scaled size of pores that are not accessible by MICP, and the ineffective/closed pores occupied by clay bound water (CBW) that are not approachable by other penetration techniques (e.g., helium expansion, low-pressure gas adsorption and MICP). The NMR porosity is largely discrepant with the helium porosity and the MICP porosity in clay-rich Carynginia shales, but a high consistency is displayed in clay-poor Monterey shales, implying the impact of clay contents on the distinction of shale pore structure interpretations between different measurements. Further, the CBW, which is calculated by subtracting the measured effective porosity from total porosity, presents a good linear correlation with the clay content (R2 = 0.76), implying that our correlated equation is adaptable to estimate the CBW in shale formations with the dominant clay type of illite. | |
dc.language | English | |
dc.publisher | MDPI | |
dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
dc.subject | Science & Technology | |
dc.subject | Technology | |
dc.subject | Energy & Fuels | |
dc.subject | gas shale | |
dc.subject | NMR | |
dc.subject | helium porosimetry | |
dc.subject | clay bound water | |
dc.subject | porosity | |
dc.subject | pore size distribution | |
dc.subject | low-pressure gas adsorption | |
dc.subject | MICP | |
dc.subject | ANGLE NEUTRON-SCATTERING | |
dc.subject | CLAY BOUND WATER | |
dc.subject | GAS-ADSORPTION | |
dc.subject | SIZE DISTRIBUTION | |
dc.subject | SURFACE-AREA | |
dc.subject | LOW-PRESSURE | |
dc.subject | POROSIMETRY | |
dc.subject | DISTRIBUTIONS | |
dc.subject | COAL | |
dc.title | Comparative porosity and pore structure assessment in shales: Measurement techniques, influencing factors and implications for reservoir characterization | |
dc.type | Journal Article | |
dcterms.source.volume | 12 | |
dcterms.source.number | 11 | |
dcterms.source.issn | 1996-1073 | |
dcterms.source.title | Energies | |
dc.date.updated | 2022-11-02T05:56:46Z | |
curtin.department | WASM: Minerals, Energy and Chemical Engineering | |
curtin.accessStatus | Open access | |
curtin.faculty | Faculty of Science and Engineering | |
curtin.contributor.orcid | Rezaee, Reza [0000-0001-9342-8214] | |
curtin.contributor.researcherid | Rezaee, Reza [A-5965-2008] | |
curtin.identifier.article-number | ARTN 2094 | |
dcterms.source.eissn | 1996-1073 | |
curtin.contributor.scopusauthorid | Rezaee, Reza [39062014600] |