... artificial intelligence estimation exploration geophysicist upstream oil & gas machine learning regression reservoir characterization application applied geoscience society toc assessment linear regression algorithm prediction evaluation international american association...

... upstream oil & gas artificial intelligence exploration geophysicist deep learning reservoir characterization algorithm neural network machine learning international china university segmentation american association dianyong ruan institute discontinuity energy 10 society...

... sparse stft united states government artificial intelligence upstream oil & gas neural network deep learning reservoir characterization time-frequency representation exploration geophysicist machine learning figure 8 algorithm applied geoscience representation denote stft...

... energy 10 fillippone formula algorithm application accuracy mudstone gypsum mudstone Application of formation pressure prediction technique based on high-density threedimensional seismic constraints in complex structural zones Yu Baoli, Liu Keyu, China University of Petroleum (East China); Li...

..., and is therefore suitable to study the quality factor Q. In radiative transfer one models scattering in terms of average intensities instead of wavefields. To solve the coupled system of equations that arises in radiative transfer we develop a time-stepping algorithm, and show numerical simulations for three...

...-solution of fracture interpretation, this study explores a set of methods for multi-scale characterization based on seismic data. In the process of methods implementation, the neural network fusion algorithm, the improved multi-layer weighted U-net 3D deep learning method and the dip-enhanced eigenvalue...

.... We compare the coupled and uncoupled cases, including and neglecting viscosity. The algorithms may become useful for a better understanding of the behavior of seismic waves in hydrocarbon reservoirs and crustal rocks, because the assumption of isothermal wave propagation is now removed...

... on understanding the intrinsic correlation of different measurements on the given geo-body, a combination of machine learning algorithms was established for multi-scale geological-geophysical intelligent reservoir characterization, which was named “Data-Feature-Policy” solution. (1) Data-level fusion: The dataset...

... upstream oil & gas machine learning refraction interferometry artificial intelligence interferometry algorithm dbscan traveltime accuracy enhancing amplitude correction reservoir characterization svi picking geophysics application supervirtual refraction interferometry snr...

... increase of computational cost for KDMIG. An accelerated KDMIG algorithm has been developed based on the CPU-GPU heterogeneous parallel computing system. To fully utilize the power of the supercomputer, we have developed four strategies, including cross-spread sorting, texture interpolation, multi-stream...

... methods and maintain comparable results to that by state-of-the-art inversion algorithms. The computational time of the deblending via neural networks can be significantly faster than that of the conventional deblending methods, qualifying neural network as a promising way for the separation...

... of surfaces available to better define the distinctive frequencies. In this paper, the Matching Pursuit algorithm is compared with both the Short Time Fourier Transform and the Continuous Wavelet Transform methods. A case study is presented on the Maui field, offshore New Zealand, in the Taranaki basin...

... and no need for editing. deep learning reservoir characterization applied geoscience artificial intelligence rmo neural network machine learning cig algorithm expanded abstract american association probability upstream oil & gas international exploration geophysicist workflow...

.... Then the challenge of performing the optimization shifts to adjusting the penalty weight to balance the reduction of data misfit with driving the penalty term towards physically-meaningful solutions. The source extended objective function minimized using the discrepancy algorithm requires an estimate of the noise...

... from recorded seismic signals. In this study, we introduce a novel deep learning algorithm to establish the nonlinear mapping between the depth domain property contrast and the time domain seismic response to CO2 injection and plume body migration using a fully processed baseline data and a monitoring...

... for matching filter and two for each CG iteration. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2022 in Houston, Texas. artificial intelligence iteration reconstruction inversion hessian algorithm formulation upstream oil & gas implementation depth...

... of the construction of broadband wavelet, low frequency constraint and prior geological information constraint, the inversion objective function under Bayesian framework is constructed, and the combined algorithm of simulated annealing and least square optimization is used to realize the high precision inversion...

... Marchenko algorithms enable the Green’s function retrieval for arbitrary subsurface locations from recorded reflected waves and smooth velocity model, and the retrieved Green’s function includes the primary and multiple reflected waves. The initial Marchenko algorithms in geophysics depend...

... designs. artificial intelligence exploration geophysicist algorithm complex reservoir machine learning applied geoscience upstream oil & gas optimization american association energy 10 shale gas prediction international society contribution shale reservoir sichuan basin china...

... in field operation, how to optimize the operation sequence and production mode of vibrators will affect the production efficiency. This paper analyzes that the conventional queue sequencing and sweep algorithm mode has certain advantages of optimization calculation, which can qualify optimization...