Prediction of Sludge Growth Haracteristics during Gravity Sedimentation Separation of Polymer Flooding Produced Water
As a fundamental process in wastewater treatment,gravity sedimentation uses common facilities like gravity sedimentation tanks,where suspended solids in the incoming water continuously settle to the tank bottom,forming sludge.To prevent secondary pollution of water quality and ensure the efficient operation of the facilities,sludge removal plans must be formulated based on the amount of sludge.This article,based on the actual operation of a sewage treatment plant in the Daqing Oilfield,starts from characteristics such as daily treatment volume,polymer concentration,suspended solids content,oil content,and suspended solids removal rate.By constructing a dataset for gravity sedimentation tank sludge removal,the relationships between various characteristic quantities are analyzed,and the dominant factors affecting sludge growth are determined.Subsequently,a sludge growth rate prediction model is established based on the BP(Backpropagation)neural network architecture.The research results indicate that the polymer concentration in the wastewater affects the oil content and suspended solids content to some extent.As the daily processing volume of the sedimentation tank increases,the removal rates of oil droplets and suspended solids decrease.The sludge growth rate is positively correlated with the content of suspended solids,the suspended solids removal rate,and the polymer concentration in the wastewater.The prediction model,trained on production data,has a fitting degree distribution above 0.9,meeting the accuracy requirements and providing a basis and method for selecting the timing of sludge removal operations in sewage sedimentation tanks.
gravity settlingsettling tank dredgingsludge growth rateBP neural networkpolymer flooding produced water
万方数据
维普
