Characteristic reflection wavefield-based wave equation traveltime inversion

被引:0
|
作者
Wu, Chengliang [1 ,2 ]
Wang, Huazhong [1 ,2 ]
Feng, Bo [1 ,2 ]
Xu, Rongwei [2 ]
机构
[1] Tongji Univ, Sch Ocean & Earth Sci, State Key Lab Marine Geol, Shanghai, Peoples R China
[2] Tongji Univ, Sch Ocean & Earth Sci, Wave Phenomena & Intelligent Invers Imaging Grp WP, Shanghai, Peoples R China
基金
中国博士后科学基金; 中国国家自然科学基金;
关键词
FORM INVERSION; VELOCITY ANALYSIS; FREQUENCY-DOMAIN; MODEL; REGULARIZATION; TOMOGRAPHY; PHASE;
D O I
10.1190/GEO2024-0029.1
中图分类号
P3 [地球物理学]; P59 [地球化学];
学科分类号
0708 ; 070902 ;
摘要
Introducing a high-precision deep-depth velocity model is essential for accurately imaging seismic data in complex areas such as deepwater and deep depth in oil and gas exploration. Conventional methods, such as reflection full-waveform inversion (RFWI), face challenges, notably the cycle-skipping issue, especially when the initial velocity model is far away from the true model. To address this, we develop a novel wave equation traveltime inversion (WETI) using the characteristic reflection wave- field (CRW) to update the low-wavenumber components of the velocity model. The CRWs are primary reflections in seismic data that contribute significantly to velocity model updates. We implement a multistep approach, including migration, characteristic reflector structure (CRS) picking, and demigration to extract the CRW. This extraction, constrained by CRS, ensures accurate matching between the observed and the simulated CRWs, even with an inaccurate initial velocity model, thus enabling an accurate traveltime shift estimation during inversion. Unlike conventional methods that use all reflection data simultaneously, CRW-WETI strategically selects fewer CRWs, enhancing inversion convexity and avoiding local minima from the cycle-skipping problem. This selective inversion begins with a limited number of CRWs to ensure stability and progressively incorporates more as the WETI process advances, eventually transitioning into conventional RFWI. Moreover, with the CRS constraint, CRW can be selected based on the target region. The target-oriented velocity inversion can also be implemented easily to update a local anomalous velocity model. Numerical examples of synthetic and field data demonstrate the effectiveness and validity of our method.
引用
收藏
页码:R457 / R477
页数:21
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