Abstract:In most cases,far-field wavelets are notional,and they are quite different from acquired wavelets.Therefore,data after debubbling based on far-field wavelets have obvious residual bubbles.This paper proposes a data-driven debubbling method.It extracts wavelets by the cross-correlation of data,calculates the debubbling operator based on extracted wavelets and expected wavelets (without bubbles),and then debubbles data.In addition,the paper analyzes two main factors affecting the debubbling results of the method:①The length of the debubbling operator.It has an impact on debubbling effect,and it is decided by bubble oscillations; ② White noise.It has a bad influence on the notch of ghosts; and as the white noise increases,it will artificially enhance the notch and reduce the deghosting effect.Therefore,during debubbling,it is better to apply a less white noise.The new method based on extracted wavelets solves the problem of the method based on far-field wavelets.The latter doesn't consider the influence of acquisition conditions on wavelets.The new method can remove bubble oscillations more effectively,increase signal to noise ratio (SNR) and resolution,and maintain the fidelity of data.All of these have been proven by the processing results of field data.
马光凯, 周铮铮, 李建锋, 李培明, 张红英, 蔡东地. 利用提取的子波压制气泡效应及影响因素分析[J]. 石油地球物理勘探, 2020, 55(6): 1237-1244.
MA Guangkai, ZHOU Zhengzheng, LI Jianfeng, LI Peiming, ZHANG Hong-ying, CAI Dongdi. A debubbling method based on extracted wavelet and its controlling factors. Oil Geophysical Prospecting, 2020, 55(6): 1237-1244.
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