On the basis of the complexity of the pore structure characteristics of a coal reservoir, coal samples with different ranks were selected to study the difference in pore structures and permeability using nuclear magnetic resonance (NMR), scanning electron microscopy (SEM), mercury intrusion porosimetry (MIP), and permeability measurement. Porosity and pore size distribution (PSD) above 20 nm can be analyzed by the improved NMR equation, and the results were basically consistent with that of SEM and MIP. The NMR spectra of the coal samples from the same location were close, but the difference between the coal samples from different locations was quite large, which indicated that the heterogeneity of a coal reservoir was strong. An empirical equation of movable fluid porosity was proposed, which can be used to evaluate the fluid migration characteristics of the coal reservoir, and the porosity of movable fluid mainly came from the contribution of fissures and micro-fissures. The average movable fluid porosity of the coal samples from the Chengzhuang (CZ) coal mine, Wuyang (WY) coal mine, and Yujialiang (YJL) coal mine was 1.37%, 0.67%, and 4.26%, respectively. Although the permeability is related to the NMR porosity and movable fluid porosity, it was difficult to establish a widely used mathematical equation correlating permeability and porosity based on the experimental data.

Coal matrix deformation is one of the main controlling factors for coal reservoir permeability changes in nitrogen foam fracturing. The characteristics and mechanism of coal matrix deformation during the process of adsorption/desorption were studied by isothermal adsorption/desorption experiments with methane and nitrogen. Based on the free-energy theories, the Langmuir equation, and elastic mechanics, mathematical models of coal matrix deformation were developed and the deformation characteristics in adsorption/desorption processes were examined. From the study, we deduced that the coal matrix swelling, caused by methane adsorption, was a Langmuir-type relationship with the gas pressure, and exponentially increased as the adsorption quantity increased. Then, the deformation rate and amplitude of the coal matrix decreased gradually with the increase of the pressure. At the following stage, where nitrogen replaces methane, the coal matrix swelling continued but the deformation amplitude decreased, which was only 19.60% of the methane adsorption stage. At the mixed gas desorption stage, the coal matrix shrank with the reduction of pressure and the shrinkage amount changed logarithmically with the pressure, which had the hysteresis effect when compared with the swelling in adsorption. The mechanism of coal matrix deformation was discussed through a comparison of the change of micropores, mesopores, and also part macropores in the adsorption process.

The non-deterministic nature of multi-threaded workloads running on multi-core platforms often leads to notable performance variability from run to run. Such variability makes experimental results prone to misinterpretations or misguided claims. To deal with such variability, statistical inference methods are usually used to summarize the experimental results with certain confidence levels by running the experiments or measurements a large number of times. However, such statistical results are often too vague or too simplistic. They are not sufficient to help users understand the causes of such variability, and allow more in-depth analysis on the results or reproduce the results for validation during design space exploration. To allow better analyzability and reproducibility, we propose a framework to tackle such variability, called VarCatcher. The key to VarCatcher is to characterize a parallel execution using Parallel Characteristics Vector (PCV). A clustering-based approach is then used to group runs with similar execution characteristics that can later be used to analyze results in-depth, to customize different evaluation strategies, reproduce the result for variability, to determine the impact of features, or to assist performance diagnosis. We have built a prototype of VarCatcher that includes a user-level toolset for runtime monitoring and measurements using the Intel Processor Trace feature on commodity Intel processors as well as an architecture extension with very low runtime overheads (around 3 and 0.01 percent accordingly). Several case studies confirm that VarCatcher enables several appealing features such as in-depth result analysis, customized evaluation strategies, and reproducibility.

In order to research on the law of methane released through the pore in coal particles, the methane desorption experiments were conducted, respectively, on four types of particle size of coal samples under three different initial adsorption pressures. The cumulative methane desorption quantity (CMDQ) with time increasing was obtained to show that the reciprocal of CMDQ was in linear relation with the reciprocal of the square root of time, and the correlation coefficients were all above 0.99, on basis of which an empirical formula of CMDQ was established. Then, according to Fick diffusion law and Darcy percolation law, the mathematical models of methane emission from the spherical coal particles were created, respectively, and the corresponding calculating software was programmed by the finite difference method to obtain the simulated CMDQ of each sample under different conditions. The methane emission rate functions (MERF) of the simulation and the experiment were also calculated, respectively. Comparative analysis between the numerically simulated outcomes and the assay results reveals that the simulation outcomes as per Darcys law match the experimental data better, while the simulated results by Ficks law deviate greatly, which indicates that the methane flowing through coal particles is more in accordance with Darcys law.