Forecast on Water Locking Damage of Low Permeable Reservoir with Quantum Neural Network

2017 3rd International Conference on Environmental Science and Material Application

生态环境科学;材料科学

Zhao, Jingyuan^1 ; Sun, Yuxue^1 ; Feng, Fuping^1 ; Zhao, Fulei^1 ; Sui, Dianjie^1 ; Xu, Jianjun^1

Department of Petroleum Engineering, Northeast Petroleum University, 163318, China^1

关键词: Biological neuron;    Evaluation matrices;    Grey correlation analysis;    Longxi Area;    Low permeable reservoirs;    Production mechanisms;    Protection techniques;    Quantum neural networks;   

Others  :  https://iopscience.iop.org/article/10.1088/1755-1315/108/3/032008/pdf
DOI  :  10.1088/1755-1315/108/3/032008

来源: IOP

【 摘 要 】

It is of great importance in oil-gas reservoir protection to timely and correctly forecast the water locking damage, the greatest damage for low permeable reservoir. An analysis is conducted on the production mechanism and various influence factors of water locking damage, based on which a quantum neuron is constructed based on the information processing manner of a biological neuron and the principle of quantum neural algorithm, besides, the quantum neural network model forecasting the water locking of the reservoir is established and related software is also made to forecast the water locking damage of the gas reservoir. This method has overcome the defects of grey correlation analysis that requires evaluation matrix analysis and complicated operation. According to the practice in Longxi Area of Daqing Oilfield, this method is characterized by fast operation, few system parameters and high accuracy rate (the general incidence rate may reach 90%), which can provide reliable support for the protection technique of low permeable reservoir.