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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]

We present an integrated algorithm for high‐resolution crustal‐scale imaging utilizing long‐offset wide‐angle ocean‐bottom seismometer (OBS) data and short‐offset multichannel streamer (MCS) data. The algorithm adopts a two‐step imaging strategy, initially using the OBS data to enhance deep structure imaging and capture long‐wavelength features of the migration velocity. Subsequently, the MCS data are migrated to recover detailed short‐wavelength components and shallow structures using the migration velocity model modified by the OBS result. Both steps employ the least‐squares reverse time migration (LSRTM) method with appropriate regularization techniques. The algorithm is implemented using the Bregmanized operator splitting (BOS) approach, known for its efficiency and adaptability in handling non‐smooth regularization, such as total‐variation (TV) constraints. To improve computational efficiency, compressed sensing is employed to store incident wavefields at half their actual size and reconstruct them accurately when required. Convergence is expedited through the use of preconditioners and the Anderson acceleration method. The proposed algorithm is validated through large‐scale numerical examples, demonstrating its robustness even with an initially imprecise velocity model. Results showcase improved resolution and accuracy achieved through the integration of OBS and MCS data. This study offers a comprehensive framework for crustal‐scale imaging, addresses computational complexities, and provides enhanced imaging capabilities. Plain Language Summary: We present a method for high‐resolution crustal‐scale imaging using a combination of long‐offset wide‐angle data from stationary receivers deployed on the seafloor with short‐offset data from floating receivers. Our method is structured as a two‐step imaging algorithm that exploits the unique strengths of each data set. In the first step, the stationary recorded data is used to recover the long‐wavelength features. Subsequently, we integrate the floating receiver data with the preceding image to recover the short‐wavelength components, adding details. The efficacy of our method relies on the utilization of least‐squares reverse time migration, which is enhanced by incorporating appropriate regularization techniques. This enables us to address critical challenges such as memory overhead, convergence speed, and image stability. These key challenges are addressed by incorporating three advanced strategies: compressed sensing theory, Anderson acceleration, and total variation regularization. Accordingly, we enhance computational efficiency, expedite convergence, and elevate imaging quality, which helps provide accurate, high‐resolution images of the subsurface that facilitate better geological interpretation of deep structures and therefore improve our understanding of the target's regional geodynamic context. Moreover, this algorithm allows imaging with less initial knowledge about the image and more robustness to the frequency range. Key Points: Enhanced crustal‐scale seismic imaging from academic dataOcean bottom seismometer and multi‐channel streamer data integrationHigh‐resolution least‐squares reverse time migration [ABSTRACT FROM AUTHOR]

A sparse 3D seismic survey was acquired over the Blötberget iron oxide deposits of the Ludvika Mines in south-central Sweden. The main aim of the survey was to delineate the deeper extension of the mineralisation and to better understand its 3D nature and associated fault systems for mine planning purposes. To obtain a high-quality seismic image in depth, we applied time-domain 3D acoustic full-waveform inversion (FWI) to build a high-resolution P-wave velocity model. This model was subsequently used for pre-stack depth imaging with reverse time migration (RTM) to produce the complementary reflectivity section. We developed a data preprocessing workflow and inversion strategy for the successful implementation of FWI in the hardrock environment. We obtained a high-fidelity velocity model using FWI and assessed its robustness. We extensively tested and optimised the parameters associated with the RTM method for subsequent depth imaging using different velocity models: a constant velocity model, a model built using first-arrival travel-time tomography and a velocity model derived by FWI. We compare our RTM results with a priori data available in the area. We conclude that, from all tested velocity models, the FWI velocity model in combination with the subsequent RTM step provided the most focussed image of the mineralisation and we successfully mapped its 3D geometrical nature. In particular, a major reflector interpreted as a cross-cutting fault, which is restricting the deeper extension of the mineralisation with depth, and several other fault structures which were earlier not imaged were also delineated. We believe that a thorough analysis of the depth images derived with the combined FWI–RTM approach that we present here can provide more details which will help with better estimation of areas with high mineralisation, better mine planning and safety measures. [ABSTRACT FROM AUTHOR]

The article discusses a study which applied a graph-space optimal transport (GSOT)-based time-domain acoustic full-waveform inversion (FWI) workflow to a two-dimensional (2D) wide-angle ocean-bottom seismometers (OBS) dataset from the geologically challenging environment of the eastern Nankai Trough. Topics covered include the key features of the GSOT strategy, and the difference in amplitude between short- and far-offset data.

A sparse 3D seismic survey was acquired over the Blötberget iron-oxide deposits of the Ludvika Mines in south-central Sweden. The main aim of the survey was to delineate the deeper extension of the mineralisation and to better understand its 3D nature and associated fault systems for mine planning purposes. To obtain a high-quality seismic image in depth, we applied time-domain 3D acoustic full-waveform inversion (FWI) to build a high-resolution P-wave velocity model. This model was subsequently used for pre-stack depth imaging with reverse time migration (RTM) to produce the complementary reflectivity section. We developed a data preprocessing workflow and inversion strategy for the successful implementation of FWI in the hardrock environment. We obtained a high-fidelity velocity model using FWI and assessed its robustness. We extensively tested and optimised the parameters associated with the RTM method for subsequent depth imaging using different velocity models: a constant velocity model, a model built using first-arrival traveltime tomography and a velocity model derived by FWI. We compare our RTM results with a priori data available in the area. We conclude that, from all tested velocity models, the FWI velocity model in combination with the subsequent RTM step, provided the most focussed image of the mineralisation and we successfully mapped its 3D geometrical nature. In particular, a major reflector interpreted as a cross-cutting fault, which is restricting the deeper extension of the mineralisation with depth, and several other fault structures which were earlier not imaged were also delineated. We believe that a thorough analysis of the depth images derived with the combined FWIRTM approach that we presented here can provide more details which will help with better estimation of areas with high mineralization, better mine planning and safety measures. [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]