Laboratory Investigation of Effective Stresses' Influence on Petrophysical Properties of Sandstone Reservoirs During Depletion

2009 ◽  
Vol 48 (07) ◽  
pp. 47-53 ◽  
Author(s):  
H.A. Belhaj ◽  
H.H. Vaziri ◽  
M.R. Islam
2021 ◽  
Vol 11 (17) ◽  
pp. 8027
Author(s):  
Yan Lu ◽  
Keyu Liu ◽  
Ya Wang

The Eocene low-permeability sandstone reservoirs in the Dongying Depression, Bohai Bay Basin, China host a significant amount of oil reserves. The development of the reservoirs has been hampered by our inability to understand the complex and heterogeneous pore structures of the reservoirs. In this study, the pore systems, pore sizes, pore connectivity, and movable fluid distribution of the Eocene Shahejie Formation (Es4) sandstone reservoirs were investigated using an integrated analysis of optical and scanning electron microscopy (SEM), mercury injection capillary pressure (MICP), and nuclear magnetic resonance (NMR). The full-range pore structures of the Es4 sandstone reservoirs were evaluated by using NMR experiments. Various NMR T2 spectral parameters suitable for describing the pore structures and movable fluid distribution were extracted through morphological and statistical analysis of NMR T2 spectra. In combination with corresponding MICP data and petrophysical properties, we have demonstrated the reliability and robustness of the T2 spectral parameters for pore structure characterization. Four types of pore structures (I, II, III, and IV) were distinguished from the NMR T2 spectral parameters in association with other petrophysical properties and macroscopic behaviors. We have demonstrated the effectiveness of using the NMR T2 spectral parameters to characterize and classify micropore structures, which may be applied to effectively evaluate and predict low-permeability reservoir quality.


Geophysics ◽  
2020 ◽  
Vol 85 (2) ◽  
pp. B35-B47 ◽  
Author(s):  
Pu Wang ◽  
Xiaohong Chen ◽  
Jingye Li ◽  
Benfeng Wang

Tight sandstone reservoirs have complex petrophysical properties, which introduce difficulties to rock-physics modeling. Besides, weak reflection events appear with a high probability in the seismic profile for tight sandstones. By combining the soft-porosity model and Gassmann’s relation, weak reflection events are analyzed in detail, which can be contaminated by remaining internal multiples and the amplitudes may be lowered by the transmission loss. These pose challenges for the porosity prediction. To obtain the porosity estimate accurately of tight sandstone reservoirs, porosity prediction is performed in two steps. First, within the framework of Bayesian inversion, the elastic parameters are obtained with high accuracy by using the reflectivity method, which can effectively describe transmission loss and internal multiples. Second, the Bayes discriminant method is applied to predict porosity from the estimated elastic parameters. It avoids using deterministic rock-physics modeling because the difficulties in rock-physics modeling of tight sandstones make it hard to predict their petrophysical properties. To ensure the prediction accuracy, detailed lithology identification and sensitivity parameters analysis are performed. Different examples of well-logging data and seismic data demonstrate that our approach can well predict the porosity.


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