Abstract

The conventional techniques cannot accurately predict the multiphase flow behaviour in clay rich low permeability rocks. This is particularly important in applications such as hydraulic fracturing where fluid uptake into low permeability rocks is of interest. This inability has given rise to the use of fractal-based estimation of petrophysical properties of such rocks. The concept of fractal theory revolves around the fractal dimension (Df) representing the entire pore structure which is often estimated using the mercury-intrusion capillary pressure (MICP) data among other techniques. However, rocks containing high clay content often exhibit higher capillary pressures than those based on MICP. This is due to interaction of clay minerals with external fluids such as hydraulic fracturing fluid and subsequent transient change in pore structure. This also in turn causes the Df value to vary thus leading to errors and uncertainties in fractal-estimated petrophysical properties of clay rich rocks. This transient aspect of clay rich rocks’ pore network is not yet fully understood nor systematically investigated or incorporated in current fractal methods. We have therefore conducted a comprehensive study to narrate a cautionary tale on the use of MICP-based fractal methods in clay rich tight rocks analyses. We first highlighted the uncertainty in the MICP-based Df value by comparing experimental and simulated oil recoveries from three clay-rich low permeability sandstone samples. We then developed, for the first time, a new set of physical equations to describe the transient pore network based on MICP-based fractal theory in order to partially overcome these uncertainties. We next compared the new theoretical model with experimental oil-water capillary pressure data. Through such rigorous analyses, it was concluded that MICP-based fractal theory relying on an unchanging pore structure is not accurate in its current form. Although our new approach can address the issue with the transient nature of clay rich pore network, there is yet immense space for improvement to overcome the limitations associated with fractal based petrophysical property estimation.

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