论文详情
针对重力勘探中倾斜断层模型密度参数与几何参数的获取, 提出了改进藤壶交配算法. 传统藤壶交配算法的寻优过程与定量模拟藤壶特殊交配繁殖特征密不可分, 但其受制于关键参数(生殖器长度pl)的选取、种群进化方式多样性以及当藤壶位置超出搜索解空间时处理方式的影响. 故提出一种结合变生殖器长度plvar, 新型藤壶子代更新和越界校正策略的改进藤壶交配算法. 通过理论无噪声重力异常研究了藤壶生殖器长度pl对于传统藤壶交配算法的影响, 验证了采用plvar策略的有效性以及改进藤壶交配算法的优越性. 进一步利用合成无噪声重力异常、含不同噪声比例(10%和30%) 重力异常和埃及Gazelle断层实际数据反演对比了藤壶交配算法、改进藤壶交配算法和粒子群算法获取相关参数的可行性、准确性、稳定性和实用性. 处理结果表明, 改进藤壶交配算法相较于藤壶交配算法和粒子群算法而言具有更小的拟合误差、更准确的模型参数以及更高的稳定性, 具有推广至解决其它地球物理反演问题的潜力.
We present a modified barnacles mating optimizer (MBMO) to recuperate model parameters, including density and geometric parameters, from gravity anomalies generated by dipping faults.Barnacles mating optimizer (BMO) is a recently proposed nature-inspired gradient-free global optimizer, which simulates the unique mating and reproduction characteristics of barnacles quantitatively.BMO has been proved to be an effective optimizer strategy in solving various optimization problems.However, its efficiency can be easily affected by the selection of an algorithm-based parameter (the genital length pl), the methods of evolving barnacles to enhance the stochastic feature, and the processing techniques when solutions exceed the searching bounds.Therefore, we propose a modified barnacles mating optimizer combining a variable plvar technique, novel evolving strategy and out-of-bounds correction method.We investigate the influence of genital length plvar on BMO using synthetic noise-free gravity anomalies and certify the effectiveness of the variable pl strategy and the superiority of MBMO.Further comparative study of the accuracy, stability and practicability of BMO, MBMO and particle swarm optimizer (PSO) uses synthetic noise-free gravity anomalies, noise-corrupted gravity anomalies with different noise degrees (10% and 30%), and field data obtained from the Gazelle fault in Egypt.MBMO is demonstrated to have smaller fitting difference, more accurate model parameters, and higher stability than additional two methods.It thus can be applied to a wide range of geophysical inverse problems.