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Most past studies on coal shrinkage/swelling due to gas adsorption/ desorption were based on experiments under no constraint conditions. In this paper, the changes of stress and strain measured on one coal specimen under uniaxial compression in a vacuum and under axial constraint conditions during CO2 adsorption are presented and numerically simulated. The simulation results show that a linear elastic deformation model, suitable to isotropic continuum media but widely assumed in analytical permeability models, cannot adequately simulate the deformation behaviour of coal mass even under uniaxial compression in a vacuum. The equivalent continuum medium (ECC) model considering the discontinuities of coal mass is successfully applied to simulate the deformation behaviour of the specimen for the uniaxial compression case and the axial constraint case before the occurrence of shear failure in the specimen. A detailed review of the analytical permeability models is presented and their limitations in application are discussed in this paper. The permeability, in situ stress, and production simulated with two representative analytical permeability models are compared with those calculated using the discontinuum medium coupled (DMC) permeability model and the coupled simulation. The results indicate that the DMC model provides better estimates of permeability and production than the analytical permeability models because it considers the influence of many factors such as the discontinuities and anisotropies that are ignored in analytical permeability models. Introduction A comprehensive review made by Gu and Chalaturnyk(1) indicated that the permeability of a coalbed (i.e., the permeability of cleat (fracture) since matrix is almost impermeable) is the most important parameter for pressure depletion coalbed methane production (CBM) and enhanced coalbed methane recovery (ECBM). However, the permeability of a coalbed is not constant but varies drastically during production due to the changes of stress and/ or strain which result from the alternations of in situ conditions such as pressures, gas desorption or absorption, and temperature. In general, a decrease in pressure causes an increase of effective stresses, a cleat compression or closure, and a decrease of permeability. Concurrently, the decrease in pressure initiates gas desorption from coal resulting in shrinkage of the coal matrix, the widening or expansion of cleat apertures, and an increase of permeability. Field results have shown that the permeability of a coalbed decreases with an increase of minimum effective stresses (corresponding to increasing depth)(2). Mavor and Vaughn(3) illustrated that the permeability of three wells increased 2.7 to 7 times after producing for 3 to 4 years, according to field well tests. The results of work by van der Meer and Fokker(4) indicated that the permeability of a coalbed decreased from 3.65 mD to 0.985 mD due to the injection of CO2. Due to its significant influence on production, the dynamic change of permeability must be considered in the simulations predicting and evaluating CBM and ECBM processes. There are two types of permeability models that can be used to consider the influence of permeability changes during production in simulations.

Sodium lignosulfonate is a polymer with extensive sources and abundant functional groups. Therefore, it has potential value for research and wide utilization. In this study, the adsorption material was prepared by blending sodium lignosulfonate and chitosan, which could adsorb anionic and cationic dyes and metal ions. The composite was characterized by Fourier transform infrared spectroscopy (FT-IR), scanning electron microscopy (SEM), and thermogravimetry (TG). The results showed that the composite was cross-linked mainly by the strong electrostatic interaction between the protonated amino group in chitosan and the sulfonate group in sodium lignosulfonate. Moreover, the effects of initial concentration, adsorption time, initial pH, and mass ratio of chitosan to sodium lignosulfonate on the adsorption performance of the composite were investigated. Meanwhile, the adsorption processes were agreed well with the pseudo-second-order kinetic model and Langmuir isotherm model. The adsorption mechanism was that the electrostatic interaction between the protonated amino and hydroxyl groups of the composite with anionic (SO3–) and HCrO4– groups of Congo red and Cr(VI), respectively. In addition, the electrostatic interaction between SO3– of the composite and positively charged group of Rhodamine B played an important role in the adsorption of Rhodamine B.

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An overview of coalbed methane (CBM) reservoir characteristics, its unique production mechanisms, and the influence of geomechanical processes on these production mechanisms are discussed from a reservoir engineering point of view. Models have been developed to predict changes in cleat porosity and permeability with in situ conditions (stress, pressure, gas sorption, and temperature). Explicit-sequential coupling simulations are conducted for conventional CBM depletion production. The study shows that during production, coal matrix shrinkage due to methane desorption results in an increase of permeability within coal seams in most regions close to the producer even though the mean effective stresses increase. The predicted production rate and cumulative production from explicit-sequential coupling simulations are higher than that from conventional simulations. The developed models also allow coalbed permeability anisotropy to be considered. Introduction Worldwide coalbed methane (CBM) reserves have been estimated at 84 ~ 262 trillion m3 (2,980 ~ 9,260 trillion ft3)(1). The majority of these CBM reserves are mainly located in Russia (17 ~ 113 trillion m3), Canada (6 ~ 76 trillion m3), China (30 ~ 35 trillion M3), Australia (8 ~ 14 trillion m3), and USA (11 trillion m3)(1). In the United States, CBM accounted for 10% of dry gas reserves and 8% of dry gas production in 2003(2). In other countries, such as China, Canada, and Australia, CBM projects are attracting more and more attention by resource companies. The production methods of CBM include conventional pressure depletion production and enhanced coalbed methane (ECBM) recovery. At present, CBM is mainly recovered by the former method. In ECBM, gases such as N2, CO2, or flue gas are injected to displace methane and maintain coalbed pressure. This recovery method is still in its infancy with only two field-scale ECBM projects (one injected N2 and the other injected CO2)(3), and one singlewell pilot project(4) worldwide. Productivity evaluation and prediction are important steps in the development of CBM reservoirs. Because gas storage mechanisms in coal seams (mainly adsorbing on the walls of pores) are different from that in conventional gas reservoirs (compressed in pores), conventional reservoir simulators generally do a poor job in predicting CBM production. Over the past decade, many models have been developed to characterize CBM production processes (5–7). Commercial simulators for CBM production can be categorized into two types: modified conventional black oil simulators and modified compositional simulators. With the recognition of the stress dependency of coal permeability and porosity and shrinkage/swelling of the coal matrix due to desorption/adsorption, some simulators have been modified to accommodate these characteristics(3). However, in these simulators the influence of in situ stresses is simplified with an analytic model or a monotonic relation between the permeability ratio and pressure changes. Durucan et al. developed a finite element model to simulate the in situ stress changes near wellbores and coupled the stress changes with fluid flow simulation by characterizing dynamic changes in permeability(8).

This paper provides a novel and effective compensation method by improving the hardware design and software algorithm to achieve optimization of piezoresistive pressure sensors and corresponding measurement systems in order to measure pressure more accurately and stably, as well as to meet the application requirements of the meteorological industry. Specifically, GE NovaSensor MEMS piezoresistive pressure sensors within a thousandth of accuracy are selected to constitute an array. In the versatile compensation method, the hardware utilizes the array of MEMS pressure sensors to reduce random error caused by sensor creep, and the software adopts the data fusion technique based on the wavelet neural network (WNN) which is improved by genetic algorithm (GA) to analyze the data of sensors for the sake of obtaining accurate and complete information over the wide temperature and pressure ranges. The GA-WNN model is implemented in OPEN ACCESSMicromachines 2015, 6 555 hardware by using the 32-bit STMicroelectronics (STM32) microcontroller combined with an embedded real-time operating system µC/OS-II to make the output of the array of MEMS sensors be a direct digital readout. The results of calibration and test experiments clearly show that the GA-WNN technique can be effectively applied to minimize the sensor errors due to the temperature drift, the hysteresis effect and the long-term drift because of aging and environmental changes. The maximum error of the low cost piezoresistive MEMS-array pressure transmitter proposed by us is within 0.04% of its full-scale value, and it can satisfy the meteorological pressure measurement.

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