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Based on the theories of mass conservation and coalbed methane (CBM) adsorption/desorption, this paper first establishes a novel reservoir pressure model for CBM production, following which, the CBM concentration and production models are also proposed. Then, these models are programmed and solved by means of the finite element method. Taking the Hunchun CBM field in Jilin province, China, as an example, the reservoir pressure, gas concentration, and production characteristics under different hydraulic fracture forms are simulated and investigated. In conclusion, the reservoir pressure decreases very rapidly in a small region near the fracture tip, which we called the "reservoir pressure singularity". The existence of a hydraulic fracture greatly reduces the reservoir pressure in the process of CBM exploitation. The permeability sensitivity coefficient of reservoir pressure, Rpk, is defined to quantitatively describe the influence of coal seam permeability on the evolution of reservoir pressure. Rpk decreases logarithmically as the distance from the CBM extraction well increases. The reservoir pressure and CBM recovery rate characteristics in the presence of multiple hydraulic fractures are also investigated. We believe these results could contribute to the design of hydraulic fracturing wells and the evaluation of gas production in a CBM reservoir. [ABSTRACT FROM AUTHOR]

Mastering the lodging risk of planting environment is of great significance to the optimal layout of maize varieties and the breeding of lodging resistant varieties. However, the existing lodging risk models are still at the stage of single or multi-factors independent analysis, and lack of assessment for different lodging types. To address this issue, based on the mechanism of different lodging types, the Archimedean copula function was used to describe the joint probability distribution of wind speed and precipitation, and the lodging risk assessment model of maize was established. By comparing the goodness of fit, when the rank correlation coefficient of these two is positive and negative, the corresponding optimal joint probability distribution functions are the Gumbel copula and Frank copula. According to the spatial distribution of lodging risk, the area from Liaodong Bay northward to Tongyu, Jilin province in the Northeast and the North China Plain has a high frequency of lodging, in which the probability of stalk lodging is two to four times that of root lodging. Finally, we discussed how to apply the lodging risk distribution results to optimize the maize variety test sites to improve the efficiency and reliability of the existing test system. The method proposed in this paper comprehensively considers the synergistic effect of multiple factors and can provide technical support for other risk assessment. [ABSTRACT FROM AUTHOR]