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Active seismic surveys are routinely employed by academia to study geological structure of the crust and upper mantle. Wavefields generated during these surveys are sampled at the receiver locations, but the wave‐paths traveled from a source to a sensor remains unknown. Although seismic acquisition layouts designed to investigate complex crustal‐scale environments are often two‐dimensional, the seismogram recorded at the receiver location represents information gathered along the three‐dimensional wavepaths that might offset from the 2D source/receiver profile along its transverse direction. This so‐called 3D‐effect distorts the results of 2D seismic imaging, which is unable to handle the out‐of‐plane propagation. Despite the numerous 2D seismic imaging case studies, the assessment of this issue is often overlooked. However, the problem exists ‐ especially for crustal‐scale profiles, where seismic energy propagates over distances of hundreds of kilometers and probes different crustal units. In this work we investigate the impact of 3D‐effect on the results of 2D velocity model building from the academic ocean‐bottom seismometer data. We show with polarization analysis how the 3D‐effect can manifest itself in the data domain. Using various scenarios of acquisition we evaluate the imprint of the out‐of‐plane propagation on the data and the results of full‐waveform inversion. We show that 2D velocity model building from the seismic profiles acquired in the complex geological setting can lead to wrong solution. Looking for the remedy to this issue we couple different configurations of acquisition geometries with 3D full‐waveform inversion that allow to handle the 3D effect and provide correct model reconstruction. Plain Language Summary: Subsurface structures can often form complex geological settings. Assumption that 2D seismic surveys and 2D imaging of resulting data is sufficient to reconstruct such complex environment might often be wrong and can lead to false geological interpretation. In this study we demonstrate how the 2D seismic data acquired in a subduction zone environment can be affected with various intensity by the out‐of‐plane wavefield propagation and how this can bias the velocity model reconstruction. We demonstrate how this issue can manifest itself in the data domain and how it can be solved by changing the approach to the crustal‐scale seismic acquisition from 2D to 3D. We show that 3D velocity model building at wavelet resolution from academic seismic data is possible nowadays with available computing power and efficient source codes. Through this work we want to promote this kind of seismic data acquisition and processing for better and less uncertain reconstructions of the key crustal‐scale geological settings that shape our planet. Key Points: 2D seismic data acquired in complex geological settings are affected by the 3D‐effect, which leads to the errors during 2D seismic imagingProcessing of the data from the 2D profiles within the 3D models can provide partial remedy to the 3D effect at the processing stageRobust 3D full‐waveform inversion of academic crustal‐scale data is possible once supported by optimization of the acquisition design [ABSTRACT FROM AUTHOR]

Detailed reconstruction of deep structures with full‐waveform inversion (FWI) of wide‐angle ocean‐bottom seismometer (OBS) data remains challenging and unconventional. The complexity of the long‐offset waveforms increases the nonlinearity of the inverse problem, while the sparsity of the OBS deployments leads to a poorly constrained model reconstruction. Consequently, for such a FWI setting it is difficult to derive an initial model that satisfies the cycle‐skipping criterion. Searching for a remedy to this issue, we investigate the graph‐space optimal transport (GSOT) technique, which can potentially overcome the cycle‐skipping problem at the initial FWI stage. The key feature of the GSOT cost function is the convexity with respect to the patterns in the two seismograms, which allows for correct matching of the arrivals shifted in time for more than half of the wavelet. This in turn shall allow FWI to handle the large kinematic errors of the starting model. We test this hypothesis by applying the time‐domain acoustic FWI to the synthetic and field data from the subduction zone environment. We show that despite the complexity of the geological structure, the GSOT misfit function is able to guide the FWI toward the precise velocity model reconstruction and data fitting starting from a simple 1D model. The improved convexity of the GSOT misfit function allows FWI to converge even when mismatches between the observed and synthetic signals reach a few cycles. This ability reduces the constraint on the kinematic accuracy of the initial model and makes the FWI from the OBS data more feasible. Key Points: Time‐domain full‐waveform inversionAlternative misfit functionHigh‐resolution crustal‐scale imaging [ABSTRACT FROM AUTHOR]

Detailed reconstruction of deep crustal targets by seismic methods remains a long-standing challenge. One key to address this challenge is the joint development of new seismic acquisition systems and leading-edge processing techniques. In marine environments, controlled-source seismic surveys at a regional scale are typically carried out with sparse arrays of ocean bottom seismometers (OBSs), which provide incomplete and down-sampled subsurface illumination. To assess and minimize the acquisition footprint in high-resolution imaging process such as full waveform inversion, realistic crustal-scale benchmark models are clearly required. The deficiency of such models prompts us to build one and release it freely to the geophysical community. Here, we introduce GO_3D_OBS – a 3D high-resolution geomodel representing a subduction zone, inspired by the geology of the Nankai Trough. The 175km×100km×30km model integrates complex geological structures with a viscoelastic isotropic parameterization. It is defined in the form of a uniform Cartesian grid containing ∼ 33.6e9 degrees of freedom for a grid interval of 25 m. The size of the model raises significant high-performance computing challenges to tackle large-scale forward propagation simulations and related inverse problems. We describe the workflow designed to implement all the model ingredients including 2D structural segments, their projection into the third dimension, stochastic components, and physical parameterization. Various wavefield simulations that we present clearly reflect in the seismograms the structural complexity of the model and the footprint of different physical approximations. This benchmark model is intended to help to optimize the design of next-generation 3D academic surveys – in particular, but not only, long-offset OBS experiments – to mitigate the acquisition footprint during high-resolution imaging of the deep crust. [ABSTRACT FROM AUTHOR]

Detailed reconstruction of deep crustal targets by seismic methods remains a long-standing challenge. One key to address this challenge is the joint development of new seismic acquisition systems and leading-edge processing techniques. In marine environments, controlled-source seismic surveys at regional scale are typically carried out with sparse arrays of ocean bottom seismometers (OBSs), which provide incomplete and down-sampled subsurface illumination. To assess and minimize the acquisition footprint in high-resolution imaging process such as full waveform inversion, realistic crustal-scale benchmark models are clearly required. The deficiency of such models prompts us to build one and release it freely to the geophysical community. Here we introduce GO_3D_OBS - a 3D high-resolution geomodel representing a subduction zone, inspired by the geology of the Nankai Trough. The 175 km x 100 km x 30 km model integrates complex geological structures with a visco-elastic isotropic parametrization. It is defined in form of a uniform Cartesian grid containing 33.6e9 degrees of freedom for a grid interval of 25 m. The size of the model raises significant high-performance computing challenges to tackle large-scale forward propagation simulations and related inverse problems. We describe the workflow designed to implement all the model ingredients including 2D structural segments, their projection into the third dimension, stochastic components and physical parametrisation. Various wavefield simulations we present clearly reflect in the seismograms the structural complexity of the model and the footprint of different physical approximations. This benchmark model shall help to optimize the design of next generation 3D academic surveys - in particular but not only long-offset OBS experiments - to mitigate the acquisition footprint during high-resolution imaging of the deep crust. [ABSTRACT FROM AUTHOR]