东北石油大学学报2024，Vol.48Issue(1)：51-60,10.DOI:10.3969/j.issn.2095-4107.2024.01.005
基于粒子群优化算法的地震数据品质因子及混合相位子波同时估计
Mixed-phase wavelet and quality factor estimation for seismic data based on particle swarm optimization
摘要
Abstract
With starting wavelet and quality factor(Q),high resolution processing and inversion for non-stationary seismic data can be deployed via solving the related equation that contains the seismic wavelet-and attenuated-filtering.In order to obtain an accurate reflectivity or elastic parameters(velocity and density)model.We proposed a new estimation method for starting wavelet and Q model by combining the encoder-decoder of wavelet root distribution and binary-to-decimal conversion of Q model.In virtue of global optimization algorithm and seismic-to-well tie as criterion function,this method can output the rational mixed-phase wavelet and Q value simultaneously and avoid the drawback of the conventional Q extraction.Synthetic and real data test can illustrate the superb performance of proposed method.In contrast with the calculated zero-phase or constant phase wavelet,mixed-phase of wavelet is updated by fitting nearby well seismic trace with well-log data,which corresponds with the propagated wavelet in reality.The attenuation factors can be evaluated in complex noise case.Compared with conventional in-vert Q filter and constant phase scanning method,the accurate wavelet and Q model provided by the ap-proach are used to calculate deconvolution results,which possess higher quality.For nonstationary seis-mic data,the outputted results can reveal more details in subsurface.The results provide basic parame-ters for the processing of high-resolution seismic data.关键词
混合相位/地震子波/品质因子/粒子群优化算法/非稳态地震数据Key words
mixed-phase/seismic wavelet/quality factor(Q)/particle swarm optimization/nonstation-ary seismic data分类
天文与地球科学引用本文复制引用
杨从涛,陈鹏,刘乐..基于粒子群优化算法的地震数据品质因子及混合相位子波同时估计[J].东北石油大学学报,2024,48(1):51-60,10.基金项目
陕西省自然科学基础研究计划重点项目(2022JZ-16) （2022JZ-16）
天地科技股份有限公司科技创新创业资金专项项目(2020-TD-ZD003) （2020-TD-ZD003）
