... joint 4D FWI method using ETM and adaptive model regularization can invert for accurate baseline and monitor velocity models simultaneously and FDRs derived from these inverted models can be directly used to assess the 4D differences. geologist africa government full-waveform inversion etm-fwi...

... isotropic (VTI) media. We implement the method with layer stripping, frequency continuation, and total-variation regularization. We demonstrate the efficacy of our workflow with the successful reconstruction of the Valhall model from longoffset data using surface multiples, crude starting models...

... Advancements in geophysical inverse problem-solving are crucial for extracting reliable information and quantifying uncertainties. Traditional regularization techniques are instrumental in stabilizing these ill-posed problems, imposing additional constraints to control solution non-uniqueness...

... Presence of gas causes anomalous anelastic attenuation in porous rocks. Instantaneous frequency seismic attribute could detect the frequency anomaly, but its sensitivity to noise makes the attribute near useless. Tikhonov regularization can be used to stabilize the attribute, making it a useful...

... Seismic deconvolution encounters problems of multiplicity and instability. The regularization technique based on various prior knowledge is used to constrain the range of solutions and improve the stability of deconvolution results. We use dictionary learning as a technical means to consider...

... of the inversion. One effective approach is to introduce model regularization such as mathematical constraints (Total-Variation regularization) or structure-oriented constraints. Nonetheless, the effectiveness of the structure-oriented method heavily relies on the accuracy of the reflection angle and is limited...

... geology applied geoscience energy 10 geologist united states government exploration geophysicist regularization upstream oil & gas reservoir characterization consideration etienne marc duncan bate figure 3 society crossline david brooke regulation variability seet li yong simon dean...

... that, compared with AWI, the application of LAWI seems to require a higher signal-to- noise ratio (SNR) of observed data. To make LAWI work for low-SNR data, a delta-type regularization is developed to deal with the noise problems inherent in the Gabor deconvolution. Despite a slight resolution loss and a “layer...

... method of simultaneous Vz noise attenuation and P/Z calibration in the 3D curvelet domain. Furthermore, we will demonstrate that our new 3D method outperforms a 2-pass 2D curvelet approach. We will also assess the effect and necessity of Vz attenuation prior to shot carpet regularization. Both...

... reservoir characterization inversion applied geoscience energy 10 seismic model international american association acoustic impedance qingrong zhu baishali roy upstream oil & gas resolution impedance reflection coefficient regularization society artificial intelligence...

... Supervised deep learning methods have been applied for seismic reflectivity inversion. It has been noticed that supervised deep learning for seismic inversion and imaging needs a considerable amount of labeled data that is often only obtainable via synthetic simulations. A regularized Deep Image...

... angle/azimuth-dependent least-squares RTM (LSRTM) with an Lp-norm regularization between the ADCIGs and an angle/azimuth-dependent reflectivity model and with a total-variation regularization of the reflectivity model. The Hessian in the LSRTM is approximated by point spread functions, which...

... learning reservoir characterization inversion exploration geophysicist regularization thin-bed reflectivity inversion kristian torre estimation energy 10 We investigate deep decomposition learning for solving illposed seismic inverse problems. We pay particular attention to the solution of one...

... Seismic data reconstruction (SDR) is a highly ill-posed inverse problem that requires the introduction of suitable priors by regularization methods to obtain unique and accurate reconstruction results. Recently, denoising by regularization (RED) has provided new ideas for solving ill-posed...

... problem: the band-limited nature of seismic data, alongside inaccuracies in the repeatability of consecutive acquisition surveys make it challenging to obtain high-resolution, clean estimates of 4D effects. Adding prior information to the inversion process in the form of properly crafted regularization...

... with nonstationary regularization to (like borehole rugosity, bed boundaries). Finally, this new approach is applied to evaluate hydraulic fracturing performance for a shale oil case. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2022 in Houston, Texas. hydraulic...

... regularization for more accurate and stable results. Such objective function involving non- differentiable terms is then conveniently solved by an extended version of the alternating direction method of multipliers (ADMM). ADMM treats each term in the objective function as an independent subproblem that can...

... association international applied geoscience energy 10 upstream oil & gas artificial intelligence generative modeling optimization algorithm layered media implementation regularization Generative modeling for inverse problems Rami Nammour, TotalEnergies Research and Technology SUMMARY...

... that the neural network can capture spatial correlations at different scales and thus can introduce regularization in our inverse problem. The regularization is enough to mitigate the cross-talk problem in elastic FWI and also produce good results in areas with low illumination. deep learning reservoir...

... but was not presented at IMAGE 2022 in Houston, Texas. resource in place estimate regularization tv regularization reserves evaluation artificial intelligence conductivity estimates of resource in place inversion geophysics american association international equation ir-wri aghamiry upstream oil...