基于照明预处理的分步多参数时间域声波全波形反演方法研究

2017年 56卷 第No. 1期
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The stepped multi-parameter FWI of acoustic media in time-domain by L-BFGS method with illumination analysis
(1.中国石油大学(华东),山东青岛266580;2.海洋国家实验室海洋矿产资源评价与探测技术功能实验室,山东青岛266235;3.中国天辰工程有限公司,天津300400;4.中国石油化工股份有限公司勘探分公司,四川成都610041)
(1.China University of Petroleum,Qingdao 266580,China;2.Function Laboratory of Marine Geo-Resource Evaluation and Exploration Technology,Qingdao 266235,China;3.China Tianchen Engineering Corporation,Tianjin 300400,China;4.Sinopec Exploration Company,Chengdu 610041,China)

密度是地震勘探中最重要的信息之一,在岩性解释、储层流体预测等多个方面起到不可替代的作用。但在全波形反演(FWI)中,由于密度和速度串扰的影响,很难反演出理想的密度信息。针对该问题,采取分步多参数全波形反演的策略,将反演的高精度速度结果作为初始速度模型,联合初始密度模型进行下一步多参数同时反演,通过提高初始速度模型的精度,得到更为准确的密度结果。同时,为了进一步平衡梯度能量,减小地震波传播过程中几何扩散的影响,采用照明预处理L-BFGS法提高反演精度。模型测试结果表明,分步多参数全波形反演及照明预处理L-BFGS法能很好地提高反演精度。

Density can predict fluid saturation of reservoir and plays an important role in reservoir interpretation and hydrocarbon prediction.Due to the cross-talk effects of velocity and density,density is difficult to reconstruct in multi-parameter full waveform inversion.To solve this problem,the strategy of stepped multi-parameter FWI is chosen which takes more accurate velocity inversion result as the initial velocity model and combines with the initial density model for next step simultaneous multi-parameter inversion.The more accurate the initial velocity model is,the more accuracy the density result is.In the meantime,to further balance the energy of gradient and reduce the influence of geometric diffusion in seismic  wave propagation,the preprocessing L-BFGS method is carried out based on the illumination analysis.The numerical examples testify the feasibility of the stepped multi-parameter FWI and the pretreatment L-BFGS method that they can improve accuracy of result.

多参数全波形反演; 分步反演; L-BFGS法; 照明分析; 声波介质;
multi-parameter FWI,; stepped inversion,; L-BFGS,; illumination analysis,; acoustic media;

国家自然科学基金(41674130)、国家科技重大专项(2016ZX05027004-001,2016ZX05002-005-009)、国家重点基础研究发展计划(973计划)项目(2014CB239201-7HZ)、中央高校基本科研业务费专项资金(15CX08002A)联合资助。

10.3969/j.issn.1000-1441.2017.01.004