We have developed a lateral constraint to the inversion of 1D seismic impedance models to
suppress the effect of data noise and improve the fidelity of formation boundaries in 2D …

Seismic high-resolution reconstruction is a key step in retrieving high-resolution components
to characterize subsurface geological structures. Recently, deep learning (DL) has emerged …

Sparse deconvolution methods frequently invert for subsurface reflection impulses and
adopt a trace-by-trace processing pattern. However, following this approach causes …

Bayesian statistical inversion can integrate diverse data sets to infer the posterior probability
distributions of subsurface elastic properties. However, certain existing methods may suffer …

In complex geology, the presence of highly dipping structures can complicate impedance
inversion. We have developed a structurally constrained inversion in which a …

Classical prestack impedance inversion methods are based on performing a common-depth
point (CDP) by CDP inversion using Tikhonov-type regularization. We refer to it as lateral …

We have evaluated a two-step Bayesian algorithm for seismic-reservoir characterization,
which, thanks to some simplifying assumptions, is computationally very efficient. The …

Waldo Tobler frequently reminded us that the law named after him was nothing more than
calling for exceptions. This article discusses one of these exceptions. Spatial relations …

In this letter, we show how a seismic inversion method based on a Bayesian framework can
be applied on poststack seismic data to estimate the wavelet, the seismic noise level, and …

Structurally constrained inversion (SCI) is a multitrace processing technology that can
effectively reduce the complexity of prestack seismic inversion caused by complex geology …