Analysis of the Influence of Coal Petrography on the Proper Application of the Unipore and Bidisperse Models of Methane Diffusion

The analysis of phenomena related to gas transport in hard coal is important with regard to the energetic use of coal bed methane (CBM), the reduction of greenhouse gas emissions to the atmosphere (CO2) and the prevention of natural hazards such as methane hazards and gas and rock outbursts. This article presents issues concerning the feasibility and scope of applying the unipore and bidisperse diffusion models to obtain knowledge concerning the kinetics of methane sorption and its diffusion in the carbon structure, depending on its petrography. Laboratory tests were carried out on coal samples which varied in terms of petrography. Quantitative point analyses were carried out, based on which content of groups of macerals was determined. The degree of coalification of coal samples was also determined based on measurements of vitrinite reflectivity R0 and the volatile matter content Vdaf. Sorption kinetics were also investigated, and attempts were made to adjust the unipore and bidisperse models to the real sorption kinetic courses. This allowed the identification of appropriate coefficients controlling the course of sorption in mathematical models. An attempt was also made to assess the possibility of applying a given model to properly describe the phenomenon of methane sorption on hard coal.

Determination of Methane Diffusion Coefficients in Live Oils for Tight Reservoirs at High Pressures

Molecular diffusion plays a critical role in gas injection in tight reservoirs such as liquid-rich shale. Despite recent efforts on measuring diffusion coefficients at high pressures, there is a general lack of the diffusion coefficients in live oil systems at reservoir conditions relevant to the development of these tight reservoirs. The reported diffusion coefficients often differ in orders of magnitude, and there is no consensus on the reliability of the common correlations for liquid phase diffusion coefficients, such as the extended Sigmund correlation. We employed the constant volume diffusion method to measure the high-pressure diffusion coefficients in a newly designed high-pressure tube. The experimental method was first validated using methane + hexadecane and methane + decane, and then used to measure the methane diffusion coefficients in two live oils at reservoir conditions. The obtained data were processed by compositional simulation to determine the diffusion coefficients. The diffusion coefficients measured for methane + hexadecane and methane + decane are in agreement with the existing literature data. For methane + live oil systems, however, the diffusion coefficients estimated by the extended Sigmund correlation are much lower than the measured results. An over ten times adjustment is needed to best fit the pressure decay curves. A further check reveals that for live oil systems, the reduced densities are often in the extrapolated region of the original Sigmund model. The curve in this region of the extended Sigmund correlation has a weak experimental basis, which may be the reason for its large deviation. The estimates from other correlations like Wilke-Chang and Hayduk-Minhas also give very different results. We compared the diffusion coefficients in high-pressure oils reported in the literature, showing a large variation in the reported values. All these indicate the necessity for further study on accurate determination of high-pressure diffusion coefficients in live oils of relevance to shale and other tight reservoirs.

Application of Smart, Swarm and Small UAV’s for Methane Emission Reduction

In this paper, we present the research challenges and opportunities in methane reduction within the smart, swarm, and small Unmanned Aircraft Vehicles (UAVs). Methane is a kind of greenhouse gas (GHG) that contributes to global temperature warming and climate changes through trapping infrared radiation in the atmosphere. The related literature of the current methane measurements and suppression of methane approaches are reviewed, and they are often limited due to the maintenance, installment, and calibration requirements of these sensing systems. To overcome these limitations, an emerging technology, UAVs, as considered mobile sensors to measure and control methane emissions, would extend detection range and acquired fine-grained information that helps to capture methane emissions in a much effective way. However, many challenges need to be explored: In the sensing field, the improvement of positive methane detection rate, which contradicts the methane diffusion in the atmosphere. The swarm UAVs for optimal coverage control, the substances of suppression methane usage, and reaction time in the control field. Different methane diffusion disturbances types could affect the strategy of swarming UAVs movement, especially under wind field. Besides, we also talk about the impact of methane reduction and related technology development for the future. Finally, we concluded that the Digital Twin would be the next methane reduction revolution to prevent potential global warming.

Multi-Scale Modeling of Aqueous-Phase Methane Diffusion in Silicate Channels

Silica-based materials including zeolites are commonly used for wide ranging applications including separations and catalysis.<br>Substrate transport rates in these materials often significantly influence the efficiency of such applications.<br>Two factors that contribute to transport rates include<br>1) the porosity of the silicate matrix and<br>2) non-bonding interactions between the diffusing species and the silicate surface.<br>Here, we utilize computer simulation to resolve the relative contribution of these factors to effective methane transport rates in a silicate channel.<br>Specifically, we develop a `homogenized' model of methane transport valid at micron and longer length scales that incorporates atomistic-scale kinetic information.<br>The atomistic-scale data are obtained from extensive molecular dynamics simulations that yield local diffusion coefficients and potentials of mean force.<br>With this model, we demonstrate how nuances in silicate hydration and silica/methane interactions impact 'macroscale' methane diffusion rates in bulk silicate materials.<br>This hybrid homogenization/molecular dynamics approach will be of general use for describing small molecule transport in materials with detailed molecular interactions.<br><br>

Multi-Scale Modeling of Aqueous-Phase Methane Diffusion in Silicate Channels

Silica-based materials including zeolites are commonly used for wide ranging applications including separations and catalysis.<br>Substrate transport rates in these materials often significantly influence the efficiency of such applications.<br>Two factors that contribute to transport rates include<br>1) the porosity of the silicate matrix and<br>2) non-bonding interactions between the diffusing species and the silicate surface.<br>Here, we utilize computer simulation to resolve the relative contribution of these factors to effective methane transport rates in a silicate channel.<br>Specifically, we develop a `homogenized' model of methane transport valid at micron and longer length scales that incorporates atomistic-scale kinetic information.<br>The atomistic-scale data are obtained from extensive molecular dynamics simulations that yield local diffusion coefficients and potentials of mean force.<br>With this model, we demonstrate how nuances in silicate hydration and silica/methane interactions impact 'macroscale' methane diffusion rates in bulk silicate materials.<br>This hybrid homogenization/molecular dynamics approach will be of general use for describing small molecule transport in materials with detailed molecular interactions.<br><br>