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The petrophysical characterization of tight gas sands can be affected by clay minerals, gas adsorption, microfractures, and the presence of high-density minerals. In this study, we conducted various petrophysical, petrographic, and high-resolution image analyses on Saudi Arabian tight sand in order to understand how a complex pore system responds to measurement tools. About 140 plug samples extracted from six wells were subjected to routine core analyses including cleaning, drying, and porosity–permeability measurements. The porosity–permeability data was used to identify hydraulic flow units (HFU). In order to probe the factors contributing to the heterogeneity of this tight sand, 12 subsamples representing the different HFUs were selected for petrographic study and high-resolution image analysis using SEM, quantitative evaluation of minerals by scanning electron microscope (QEMSCAN), and micro-computed tomography (µCT). Nuclear magnetic resonance (NMR) and electrical resistivity measurements were also conducted on 56 subsamples representing various lithofacies. NMR porosity showed good agreement with other porosity measurements. The agreement was remarkable in specific lithofacies with porosity ranging from 0.1% to 7%. Above this range, significant scatters were seen between the porosity methods. QEMSCAN results revealed that samples with <7% porosity contain a higher proportion of clay than those with porosity >7%, which are either microfractured or contain partially dissolved labile minerals. The NMR T2 profiles also showed that samples with porosity <7% are dominated by micropores while samples with porosity >7% are dominated by macropores. Analysis of the µCT images revealed that pore throat sizes may be responsible for the poor correlation between NMR porosity and other porosity methods. NMR permeability values estimated using the Shlumberger Doll Research (SDR) method are fairly correlated with helium permeability (with an R2 of 0.6). Electrical resistivity measurements showed that the different rock types fall on the same slope of the formation factors versus porosity, with a cementation factor of 1.5.

Clays, hydrous aluminous phyllosilicates, have a significant impact on the interpretation of physical measurements and properties of porous media. In particular, the presence of paramagnetic and/or ferromagnetic ions like iron, nickel, and magnesium in clays can complicate the analysis of nuclear magnetic resonance (NMR) data for porous media characterization. This is due to the internal magnetic field gradient induced by the clay minerals. In this study, we aim to investigate the impact of clay content on spin–spin relaxation time (T 2), which is strongly influenced by the pore surface chemistry. Seven rock core plugs, characterized with variable clay content, were used for this purpose. The clay mineralogy and volume were determined by means of quantitative evaluation of minerals by scanning electron microscopy (QEMSCAN). The T 2 relaxation time was measured using a Carr–Purcell–Meiboom–Gill (CPMG) sequence with variable echo spacing (T E). The maximum percentage difference in dominant T 2 values (MRDT 2) between shortest and longest echo spacing was subsequently correlated with clay content obtained from QEMSCAN. Our results show that the reduction in T 2 distribution with increasing echo time T E is more significant in samples characterized by higher clay contents. The MRDT 2 was found to be strongly correlated with clay content. An analytical equation is presented expressing MRDT 2 as a function of clay content providing a quick and non-destructive approach for clay content estimation. Moreover, the MRDT 2–clay content relationship showed a nonlinear behavior: MRDT 2 increases drastically as the clay content increases up to 15%, beyond which the rate of MRDT 2 change with clay content diminishes. This behavior could be attributed to the clay distribution. At higher clay contents (above 15%), it is more likely for clay to form clusters (structural clays), which will not significantly increase the clay surface in contact with the pore fluid. Further, experimental data suggests that ignoring the impact of clay on internal magnetic gradients and T 2 signal may result in considerable underestimation of the actual pore size distribution.