Non-invasive subsurface imaging using full waveform inversion (FWI) has the potential to fundamentally change engineering site characterization by enabling recovery of high resolution 2D/3D maps stiffness. Yet, accuracy FWI remains quite sensitive choice initial starting model due complexity and non-uniqueness inverse problem. In response, we present novel application convolutional neural netwo...

SUMMARY Wavelet estimation plays an important role in many seismic processes like impedance inversion, amplitude versus offset (AVO) and full waveform inversion (FWI). Statistical methods of wavelet estimation away from well control are a desirable tool to support seismic signal processing. One of these methods based on Homomorphic analysis has long intrigued as a potentially elegant solution t...

SUMMARY In the context of seismic imaging, full waveform inversion (FWI) is increasingly popular. Because its lower numerical cost, acoustic approximation often used, especially at exploration geophysics scale, both for tests and real data. Moreover, some research domains such as helioseismology face true media which FWI can be useful. this work, an argument that combines particle relabelling h...

Full-waveform inversion (FWI), a popular technique that promises high-resolution models, has helped in improving the salt definition inverted velocity models. The success of relies heavily on having prior knowledge salt, and using advanced acquisition technology with long offsets low frequencies. Salt bodies are often constructed by recursively picking top bottom from seismic images correspondi...

SUMMARY Full waveform inversion (FWI) is a highly non-linear optimization problem that aims to reconstruct high-resolution subsurface structures. The success of FWI in reflection seismology relies on appropriate updates low-wavenumber background velocity structures, which are generally driven by the diving waves conventional FWI. On other hand, reflected mainly contribute updating high-wavenumb...

To exploit Hessian information in full-waveform inversion (FWI), the matrix-free truncated Newton method can be used. In such a method, Hessian-vector product computation is one of major concerns due to huge memory requirements and demanding computational cost. Using adjoint-state estimated by zero-lag crosscorrelation first-/second-order incident wavefields second-/first-order adjoint wavefiel...

The multi-parameter full waveform inversion (FWI) that integrates velocity and density can make use of the kinematic dynamic information measured data to reconstruct underground model. However, it faces problems crosstalk between multiple parameters strong nonlinearity. This research proposes a multi-constrained, FWI framework based on projected quasi-Newton algorithm. introduce types prior geo...

For the safe and efficient operation of dams, frequent monitoring maintenance are required. These usually expensive, time consuming, cumbersome. To alleviate these issues, we propose applying a wave-based scheme for location quantification damages in dams. obtain high-resolution “interpretable” images damaged regions, drew inspiration from non-linear full-multigrid methods inverse problems appl...

Recently, the Wasserstein loss function has been proven to be effective when applied deterministic full-waveform inversion (FWI) problems. We consider application of this in Ba...

Abstract Wildfire is an integral part of the Earth system, but at same time it can pose serious threats to human society and certain types terrestrial ecosystems. Meteorological conditions are a key driver wildfire activity extent, which led emergence use fire danger indices that depend solely on weather conditions. The Canadian Fire Weather Index (FWI) widely used index this kind. Here, we eva...