Pore-by-Pore Modelling, Validation and Prediction of Waterflooding in Oil-Wet Rocks Using Dynamic Synchrotron Data

We predict waterflood displacement on a pore-by-pore basis using pore network modelling. The pore structure is captured by a high-resolution image. We then use an energy balance applied to images of the displacement to assign an average contact angle, and then modify the local pore-scale contact angles in the model about this mean to match the observed displacement sequence. Two waterflooding experiments on oil-wet rocks are analysed where the displacement sequence was imaged using time-resolved synchrotron imaging. In both cases the capillary pressure in the model matches the experimentally obtained values derived from the measured interfacial curvature. We then predict relative permeability for the full saturation range. Using the optimised contact angles distributed randomly in space has little effect on the predicted capillary pressures and relative permeabilities, indicating that spatial correlation in wettability is not significant in these oil-wet samples. The calibrated model can be used to predict properties outside the range of conditions considered in the experiment.

The Pore-network Modelling of the Infiltration Experiments Performed on Unsaturated Coarse Sands

<p>The research focused on the simulation of the previous experiment described by Princ et al. (2020). The relationship between entrapped air content (<em>ω</em>) and the corresponding satiated hydraulic conductivity (<em>K</em>) was investigated for two coarse sands, in the experiment. Additionally the amount and distribution of air bubbles were quantified by X-ray computed tomography.</p><p>The pore-network model based on OpenPNM platform (Gostick et al. 2016) was used to attempt simulation of a redistribution of the air bubbles after infiltration. Satiated hydraulic conductivity was determined to obtain the <em>K</em>(<em>ω</em>) relationship. The results from pore-network model were compared with the results from experiments.</p><p>Gostick et al. (2016). Computing in Science & Engineering. 18(4), p60-74.</p><p>Princ et al. (2020). Water. 12(2), p1-19.</p>

Petrophysical Correlations for the Permeability of Coquinas (Carbonate Rocks)

The pore structure of many carbonate formations is known to be very complex and heterogeneous. Heterogeneity is manifested by the presence of different types, sizes, and shapes of pores resulting from sedimentation and diagenetic actions. These complexities greatly increase uncertainties in estimated rock hydraulic properties in that different permeability values may occur for samples having similar porosities. In order to understand the effects of pore structure and heterogeneity, petrophysical analyses were performed on coquina samples from the Morro do Chaves Formation (Barremian, Sergipe-Alagoas Basin), which is an analogue of Brazilian Pre-salt oil reservoirs of Itapema Formation in the Santos Basin. Routine core analyses, and NMR and MICP measurements were carried out to obtain pore body and pore throat distributions. Obtained T2 relaxation times were converted to pore size radii by matching the NMR and MICP curves. Pore-scale imaging and pore network modelling were performed using microCT scans and the PoreFlow software, respectively. Calculated permeabilities using PoreFlow showed excellent agreement with the routine laboratory measurements. Samples having pore bodies with a higher coordination number showed much larger permeabilities at similar porosities. This study includes a statistical analysis of various features that caused the observed differences in permeability of the coquinas, including the role of connectivity of the entire porous system. Limitations and challenges of the various techniques, and the imaging and pore-scale flow simulations, are discussed.