The Effect of Rank and Lithotype on Coal Wettability and its Application to Coal Relative Permeability Models

Abstract

We report the effect of rank and lithotype on the wettability of artificial cleat channels in five coals from the Bowen Basin with ranks in the R max% range 0.98-1.91%. Wettability was assessed by measuring contact angles of air and water in the artificial cleats using a microfluidic Cleat Flow Cell (CFC) instrument. The artificial cleats were produced by reactive ion etching and had widths in the range 20 -40 m that replicate the width and shape of some natural coal cleats under sub-surface reservoir conditions. These model cleats were developed to allow systematic laboratory investigations of water and gas relative permeability behaviour.Imbibition and drainage experiments were performed in the artificial channels using air and 0.1 %wt. fluorescein in fresh tap water to observe contact angles, the entry pressure of the air-water and water-air interface to the channel, and the pressure at which the channel was filled by the displacing fluid. Relative contact angles on the coal surface of 110 -140°were determined from images collected in the imbibition experiments. A trend of increasing contact angle with coal rank was observed. The low rank coal exhibited smaller contact angles and lower breakthrough pressures than the higher rank coal samples. In the drainage experiments the injection air displaced the water but left a residual liquid film on cleat walls across dull, inertinite rich bands. This residual film was not observed in the bright, vitrinite rich bands. The results of this study may provide the basis to consider an improved relative permeability model that explicitly accounts for wettability and the effect of coal rank. Figure 7-A) Reactive Ion Etched vitrinite rich wall. B) RIE inertinite rich wall. Both samples were titled 45°to capture the images.

Pore-scale simulation of effects of coal wettability on bubble-water flow in coal cleats using lattice Boltzmann method

“…The impact of contact angle on the gas displacement dynamics in a regular pore-network has been reported by Liu et al (2013). Since the contact angle varies across different coal rank (Mahoney et al, 2015), even within the same rank, this behaviour is likely to have a significant impact on drainage rates and relative permeability in different coal seams. …”

“…Saghafi et al (2014) measured the contact angles of CO 2 and CH 4 bubbles in water with coal from the Sydney Basin at different pressures. Later, Mahoney et al (2015) used a microfluidic Cleat Flow Cell (CFC) instrument to investigate the effect of rank and lithotype on coal wettability. However, difficulties still exist to provide an in-depth understanding of the influences of coal wettability on gas/water flow at pore scale.…”

Coal seam gas associated water production in Queensland: Actual vs predicted

“…The nature of fluid migration along the cleat system to the production bore is a multiphase flow process that is highly dependent on the relative permeability of the cleat to water and methane. The relative permeability can be a function of the fluid saturation, coal mineralogy, rank, and organic and clay content (Mahoney et al, 2015). While most of these factors are fixed, the relative water and gas saturation changes with production.…”

Insights, Trends and Challenges Associated with Measuring Coal Relative Permeability

“…This is a common technique for analysing the permeability properties of coals (Niu et al, 2018) and is used in our work to understand how effective stress influences coal relative permeability without the influence of matrix shrinkage. Once decoupled, the main controlling factor influencing relative permeability will likely be the rank of the coal since rank is known to be correlated with fracture network development and matrix compressibility (Mahoney et al, 2015;Guo et al, 2014;Close and Mavor, 1991), which is known to influence coal permeability. Literature data on coal that measures relative permeability at different effective stress states are sparse leading to a lack in understanding of the fundamental trends (Zhang et al, 2015).…”