量子衍生布谷鸟算法及在地层对比中的应用

为提高布谷鸟搜索算法的寻优能力，通过在经典布谷鸟搜索算法中引入量子计算机制，提出一种量子衍生布谷鸟搜索算法。该算法采用量子比特编码个体，采用泡利矩阵确定旋转轴，采用Levy飞行原理确定旋转角度，采用量子比特在Bloch球面上的绕轴旋转实现个体更新。针对钻井剖面地层对比的具体特点及需要满足的约束条件，提出应用量子衍生布谷鸟算法进行地层对比优化的实施方案，该方法既能对比不同地层之间的相似性，也能处理对比井地层因断层或尖灭等因素造成的缺失。实验结果表明，在复杂地质情况下，该算法是有效的和可行的。 

Quantum-inspired Cuckoo Search Algorithm with Application to Stratigraphic Correlation

In order to improve the search ability of cuckoo search algorithm, by introducing the quantum computing mechanism into the classical cuckoo search algorithm, a quantum-inspired cuckoo search algorithm is proposed. In the proposed algorithm, the qubits are used to encode individuals, the Pauli matrixes are employed to determine rotation axis, the Levy flight principle is applied to obtain rotation angle, and the rotation of the qubits on the Bloch sphere is used to update the individuals. Aiming at the specific features of stratigraphic correlation of logging section and the constraint conditions that need to be satisfied, a scheme of applying quantum-inspired cuckoo algorithm to stratigraphic correlation is proposed. This method can not only compare the similarity between different strata, but also deal with the faults caused by faults or sharp extinction. The experimental results show that the algorithm is effective and feasible in complex geological conditions.