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一种引入吸收衰减的压缩感知薄储层识别方法
引用本文:张军华,常健强,王喜安,白青林,王福金,刘中伟.一种引入吸收衰减的压缩感知薄储层识别方法[J].科学技术与工程,2023,23(7):2768-2775.
作者姓名:张军华  常健强  王喜安  白青林  王福金  刘中伟
作者单位:中国石油大学华东地球科学与技术学院;中石化石油物探技术研究院有限公司;中国石化胜利油田分公司现河采油厂
基金项目:国家自然科学基金(42072169)
摘    要:常规基于压缩感知稀疏反演方法是基于频域平稳地震褶积模型进行的,而实际地下介质是粘弹性的,这使得该方法的反演反射系数振幅缺失、位置偏移。针对该问题,本文通过引入时频衰减因子,构建改进的感知矩阵,将稀疏反演从常规的频率域拓展至衰减频率域。反演结果在一定程度上可恢复缺失的振幅,增强弱信号的识别能力。由于噪声影响,以上处理结果中仍存在噪声干扰,故在衰减频率域稀疏反演的基础上,引入平滑的高斯函数,对反演目标函数进一步优化,以有效压制残存的噪声干扰;之后将反演结果与褶积宽频子波可生成高分辨率地震剖面,由此形成了一种引入吸收衰减的压缩感知薄储层识别方法。薄层理论模型及含有河道砂储层的实际地震资料的处理结果表明,本文方法较常规方法,有效地增强了薄层弱信号的振幅及横向连续性,可在保证信噪比的情况下,提高地震资料的分辨率及薄储层的识别能力。

关 键 词:压缩感知  稀疏反演  衰减感知矩阵  非平稳褶积  薄层
收稿时间:2022/5/12 0:00:00
修稿时间:2022/12/15 0:00:00

A Thin Reservoir Identification Method Based on Compressed Sensing with Introducing Absorption andAttenuation
Zhang Junhu,Chang Jianqiang,Wang Xian,Bai Qinglin,Wang Fujin,Liu Zhongwei.A Thin Reservoir Identification Method Based on Compressed Sensing with Introducing Absorption andAttenuation[J].Science Technology and Engineering,2023,23(7):2768-2775.
Authors:Zhang Junhu  Chang Jianqiang  Wang Xian  Bai Qinglin  Wang Fujin  Liu Zhongwei
Abstract:The conventional sparse inversion method of reflection coefficient based on compressive sensing is carried out on the frequency domain stationary seismic convolution model, but the actual underground medium is viscoelastic, which distorts the amplitude and position of the inversion reflection coefficient. To solve this problem, this paper constructs an improved "attenuation sensing matrix" by introducing the time-frequency attenuation factor, which expands the sparse inversion from the conventional frequency domain to the attenuated frequency domain. The inversion results can generally recover the missing amplitude and enhance the identification of weak signals. Besides, there are still residual interferences in the inversion results of the above processing method because of noise. Therefore, the inversion objective function is further optimized by introducing a Gaussian function based on the above method, which can effectively suppress the residual noised interferences; then, high-resolution seismic data can be generated by convoluting the inversion results with broadband wavelet, thus, a thin reservoir identification method is formed based on compressed sensing with absorption and attenuation. The processing results of the theoretical model and the actual seismic data containing thin sand reservoirs show that compared with the conventional method, this method effectively enhances the weak signal amplitude and transverse continuity, and which can improve the resolution of seismic data and the identification ability of thin reservoirs while ensuring the signal-to-noise ratio.
Keywords:Compressed sensing  Sparse inversion  Attenuation sensing matrix  Nonstationary convolution  Thin layer
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