| 基于量子神经网络的油田水淹层识别方法 |
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| 引用本文： | 李盼池,王海英,杨雨.基于量子神经网络的油田水淹层识别方法[J].计算机应用与软件,2012,29(5):41-43. |
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| 作者姓名： | 李盼池 王海英 杨雨 |
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| 作者单位： | 1. 东北石油大学石油与天然气工程博士后科研流动站 黑龙江 大庆 163318;东北石油大学计算机与信息技术学院 黑龙江 大庆 163318
2. 东北石油大学计算机与信息技术学院 黑龙江 大庆 163318 |
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| 基金项目： | 国家自然科基金项目，黑龙江省教育厅科学基金项目，黑龙江省博士后基金资助项目 |
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| 摘 要： | 针对油藏测井解释中的水淹层识别问题,提出一种量子神经网络模型。该模型用量子旋转门更新量子比特的相位,用受控旋转门实现网络的非线性映射功能。网络可调参数为量子旋转门的旋转角度和受控非门的控制参数。基于梯度下降法设计了学习算法。仿真结果表明,该模型的预测能力优于普通BP网络、模糊神经网络和过程神经网络等其他方法。
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| 关 键 词： | 量子计算 量子神经网络 水淹层识别 算法设计 |
OILFIELD WATER-FLOODED LAYER IDENTIFICATION METHOD BASED ON QUANTUM NEURAL NETWORKS |
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| Li Panchi
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Wang Haiying
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Yang Yu.OILFIELD WATER-FLOODED LAYER IDENTIFICATION METHOD BASED ON QUANTUM NEURAL NETWORKS[J].Computer Applications and Software,2012,29(5):41-43. |
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| Authors: | Li Panchi Wang Haiying Yang Yu |
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| Affiliation: | 1(Post-doctoral Research Center of Oil and Gas Engineering,Northeast Petroleum University,Daqing 163318,Heilongjiang,China) 2(School of Computer and Information Technology,Northeast Petroleum University,Daqing 163318,Heilongjiang,China) |
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| Abstract: | Aiming at the water-flooded layer identify in reservoir logging interpretation,a quantum neural networks model is proposed.In this model,quantum rotating gates are employed in updating phase of quantum bits,and the controlled-rotating gates are employed in realising nonlinear mapping.Adjustable parameters involve the rotation angles of quantum rotating gates and the control parameters of controlled not-gates.The learning algorithm is designed based on gradient descent algorithm.Simulation results show that the proposed model is superior to the common BP networks,the fuzzy neural networks and process neural networks,etc. |
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| Keywords: | Quantum computation Quantum neural networks Water-flooded layer identify Algorithm design |
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