Porosity and permeability determination of organic-rich Posidonia shales based on 3-D analyses by FIB-SEM microscopy

Abstract

Abstract. The goal of this study is to better understand the porosity and permeability in shales to improve modelling fluid and gas flow related to shale diagenesis. Two samples (WIC and HAD) were investigated, both mid-Jurassic organic-rich Posidonia shales from Hils area, central Germany of different maturity (WIC R 0 0.53 % and HAD R 0 1.45 %). The method for image collection was focused ion beam (FIB) microscopy coupled with scanning electron microscopy (SEM). For image and data analysis Avizo and GeoDict was used. Porosity was calculated from segmented 3-D FIB based images and permeability was simulated by a Navier Stokes-Brinkman solver in the segmented images.Results show that the quantity and distribution of pore clusters and pores (≥ 40 nm) are similar. The largest pores are located within carbonates and clay minerals, whereas the smallest pores are within the matured organic matter. Orientation of the pores calculated as pore paths showed minor directional differences between the samples. Both samples have no continuous connectivity of pore clusters along the axes in the x, y, and z direction on the scale of 10 to 20 of micrometer, but do show connectivity on the micrometer scale. The volume of organic matter in the studied volume is representative of the total organic carbon (TOC) in the samples. Organic matter does show axis connectivity in the x, y, and z directions. With increasing maturity the porosity in organic matter increases from close to 0 to more than 5 %. These pores are small and in the large organic particles have little connection to the mineral matrix. Continuous pore size distributions are compared with mercury intrusion porosimetry (MIP) data. Differences between both methods are caused by resolution limits of the FIB-SEM and by the development of small pores during the maturation of the organic matter. Calculations show no permeability when only considering visible pores due to the lack of axis connectivity. Adding the organic matter with a background permeability of 1×10 −21 m 2 to the calculations, the total permeability increased by up to 1 order of magnitude for the low mature and decreases slightly for the overmature sample from the gas window. Anisotropy of permeability was observed. Permeability coefficients increase by 1 order of magnitude if simulations are performed parallel to the bedding. Our results compare well with experimental data from the literature suggesting that upscaling may be possible in the future as soon as maturity dependent organic matter permeability coefficients can be determined.

Integrating SANS and fluid-invasion methods to characterize pore structure of typical American shale oil reservoirs

“…Based on FIB-SEM observations, the organic particles in Posidonia shales (at R o of 1.45%) from Hils area only contain small pore networks, which are not well connected with the surrounding mineral matrix 77 . The four samples in this study are all in the oil window with a similar maturity level (R o ranging from 0.67% to 1.05%), indicating that organic matter pores should only just be developing 60 , 78 – 80 . We suggest that the lack of abundant pores in the organic matter results in low connectivity of organic pores.…”

Comparison of Three Key Marine Shale Reservoirs in the Southeastern Margin of the Sichuan Basin, SW China

“…As higher total pore volume is more advantageous for shale gas extraction [17,28], the results of the PSD analysis show that the LSL and the UOW shales are more competitive than the LCN shale. Figure 6.…”

Nanoscale Pore Structure Characterization and Permeability of Mudrocks and Fine-Grained Sandstones in Coal Reservoirs by Scanning Electron Microscopy, Mercury Intrusion Porosimetry, and Low-Field Nuclear Magnetic Resonance

“…At present, there are a series of experimental methods such as scanning electron microscopy (SEM) [19][20][21][22][23][24][25][26][27][28][29][30][31], mercury intrusion porosimetry (MIP) [5,[32][33][34][35][36], and low-field nuclear magnetic resonance (NMR) [35][36][37][38][39][40] which have been widely applied for qualitative and quantitative determination of pore structure characteristics of different types of reservoir rocks. Among them, high resolution SEM-based imaging techniques, for example, field emission SEM (FE-SEM) [19,20,[22][23][24][25], broad ion beam SEM (BIB-SEM) [21,27,29], and focused ion beam SEM (FIB-SEM) [26][27][28][29][30][31]41], are commonly used in the field of visualized characterization of nanoscale pore systems of tight reservoir rocks such as gas shales and fine-grained sandstones due to their high resolution imaging advantages.…”

“…Among them, high resolution SEM-based imaging techniques, for example, field emission SEM (FE-SEM) [19,20,[22][23][24][25], broad ion beam SEM (BIB-SEM) [21,27,29], and focused ion beam SEM (FIB-SEM) [26][27][28][29][30][31]41], are commonly used in the field of visualized characterization of nanoscale pore systems of tight reservoir rocks such as gas shales and fine-grained sandstones due to their high resolution imaging advantages. For example, nanoscale pore structure characteristics of the organic-rich Wufeng-Longmaxi shale and the Lower Cambrian Niutitang shale were investigated by Yang et al [19] and Sun et al [24] using FE-SEM.…”