Dynamic Variation Characteristics of Phosphorus in Paddy Field Runoff in Saline Land and Its Potential Environmental Effect

[Objective] The aim was to study the dynamic variation characteristics of phosphorus in paddy field runoff in saline land and its potential environmental effect. [Method] Taking Qianguo irrigation district in soda-saline land in Songnen Plain as study object, the dynamic variation law of phosphorus in paddy field runoff under different irrigation conditions and its potential environmental effect were discussed. [Result] Surface water in paddy field was alkaline, and scattered soil had poor fertilizer conservation capacity. Phosphorus accumulated in soil surface, which could increase the risk of phosphorus loss. Phosphorus loss in paddy field mainly occurred in irrigation period and runoff period caused by rainstorm. The concentration of total phosphorus (TP), particulate phosphorus (PP), total dissolved phosphorus (TDP) and dissolved reactive phosphorus (DRP) in paddy field runoff decreased with time, especially PP. Phosphorus concentration exceeded critical value and resulted to eutrophication, which threatened the water quality security of Chagan Lake. Phosphorus concentration in water recession canal increased with time, and eutrophication with different degrees appeared under high temperature. TP concentration in surface water of paddy field was highly negatively correlated with that in water recession canal, and the correlation coefficients R2(α=0.05)in three paddy fields were 0.850 9, 0.896 4 and 0.915 3, respectively. The pollution load of phosphorus in paddy field with the best irrigation condition was higher, and its pollution risk was the highest. Thus, such fields should be monitored and controlled mainly as the critical source area of phosphorus loss. [Conclusion] The study could provide theoretical foundations for developing saline land rationally, establishing optimal management measure of phosphorus in saline land and controlling phosphorus loss from farmland to protect local water resources.

Experimental Simulation on Dynamic Variation of the Permeability of High-Rank Coal Reservoirs

In terms of the coal reservoir permeability of effective stress, coal matrix shrinkage and gas slippage,we conduct the tests of gas permeability under constant confining pressure and effective stress, as well as illustrate the cumulating method of permeability increment caused by the effects of gas slippage and coal matrix shrinkage.The results show that under the constant confining pressure, gas slippage affecting coal permeability changes to effective stress affecting it mainly. The change point increases with the increase of the confining pressure. The gas slippage effect leads to high permeability under low confining pressure, but coal matrix expansion results in the low value as confining and gas pressures increase. Combined with the drainage process of coalbed methane(CBM)well, the permeability is divided into four change stages based on the above analysis about the three effects, which can improve the change regulation understanding. Four stages are the downward phase under effective stress,the conversion phase of effective stress-coal matrix contraction effect(mainly based on effective stress), the rising stage of the effective stress-coal matrix contraction effect(mainly based on coal matrix contraction effect) and the rising phase of coal matrix contraction-slippage effect(mainly based on slippage effect). Permeability of coal reservoir during the process of drainage and production goes through four stages.

Evaluation of infill well pattern based on the dynamic change of reservoirs during coalbed methane development

With the deepening of coalbed methane(CBM)exploration and development,the problem of low gas production has gradually become one of the main factors restricting the development of the CBM industry in China.Reasonable well pattern deployment can improve the productivity of CBM wells and reduce the cost of production,while the reservoir changes of CBM wells play a important role for well pattern infilling.In this study,the dynamic characteristics of the average reservoir pressure(ARP),permeability,and drainage radius during the development process of CBM wells are systematically analyzed,and predicted the production changes of well groups before and after infilling wells in combination with the characteristics of reservoir changes.The results show that the high gas production wells have a larger pressure drop,long drainage radius,and a large increase in permeability.On the contrary,low gas production wells are characterized by small drainage radius,damaged permeability and difficult to recover.The productivity of infilled horizontal wells is predicted for two well groups with different productivity and reservoir dynamic characteristics.After infilling wells,the production of current wells has increased at different degrees.It is predicted that the average gas production of low gas production well group H1 and middle gas production well group H2 will increase 1.64 and 2.09 times respectively after 3000 days production simulation.In addition,the pressure interference between wells has increased significantly,and the overall gas production of the well group has greatly increased.Infill wells can achieve better development results in areas with superior CBM resources,recoverable reservoir permeability,and small drainage radius during the early production process.The research results provide a reference for the later infill adjustment of CBM well patterns in the study area.

Genetic Programming Using Dynamic Population Variation for Computational Efforts Reduction in System Modeling

In this paper,we propose genetic programming(GP) using dynamic population variation(DPV) with four innovations for reducing computational efforts.A new stagnation phase definition and characteristic measure are defined for our DPV.The exponential pivot function is proposed to our DPV method in conjunction with the new stagnation phase definition.An appropriate population variation formula is suggested to accelerate convergence.The efficacy of these innovations in our DPV is examined using six benchmark problems.Comparison among the difierent characteristic measures has been conducted for regression problems and the new proposed measure outperformed other measures.It is proved that our DPV has the capacity to provide solutions at a lower computational effort compared with previously proposed DPV methods and standard genetic programming in most cases.Meanwhile,our DPV approach introduced in GP could also rapidly find an excellent solution as well as standard GP in system modeling problems.