... to avoid the NMO stretch effect, which are required by conventional residual statics correction. Numerical results on simulated and field data suggest that the method has the potential of replacing existing residual statics correction techniques. applied geoscience georgia institute exploration...

... synthetic and field examples are provided to demonstrate the current performance of our proposed framework. neural network ground truth primary artificial intelligence training data data distribution reservoir characterization upstream oil & gas field data primary label machine learning...

... artificial intelligence applied geoscience multiple elimination exploration geophysicist 10 reservoir characterization decoder field data workflow machine learning upstream oil & gas autoencoder input data surface-related multiple elimination separation latent space...

... of zerooffset DAS VSP. The resolution of the final algorithm is defined by DAS channel spacing and gauge length rather than by the frequencies of the seismic wavelet. We validate the algorithm in a synthetic example, inspired by a complex near-surface model from the desert environment, and a field data test...

... in field data might be addressed in a data-driven framework. In particular, deep learning models trained on synthetic data could be used for inference on the field data. Such an implementation of switching application domains remains challenging. We, therefore, propose the concept of generative dual-band...

... machine learning applied geoscience waveform inversion warner artificial intelligence awi exploration geophysicist 10 reflection waveform inversion formulation reservoir characterization field data velocity model inversion rwi dataset umpleby synthetic dataset upstream oil...

... applied geoscience category artificial intelligence cost value surface wave geophysics automatic dispersion curve non-deterministic factor inversion loss function exploration geophysicist 10 williamson machine learning neural network field data noisy data dispersion curve transfer...

... function, allows automatic transition from a pure time-shift problem to a conventional FWI. We apply the new FWI method to both synthetic and field data to demonstrate its effectiveness starting from inaccurate initial models. Results show that the new FWI approach is able to build high-resolution models...

... Traditionally, geophysics has been playing a major and crucial role in oil and gas and mining exploration. Mainly seismic and potential fields data are contributing in a big way to the discovery of hydrocarbon fields and mining deposits. With the Energy Transition taking place we see new...

... compare the proposed scheme with the POCS interpolation method through synthetic and field data. The numerical results demonstrate that the inadequately sampled synthetic and field data are effectively reconstructed by the proposed scheme. artificial intelligence interpolation prediction...

... applied geoscience incident-angle stretch exploration geophysicist 10 depth-domain ps compensation ps data reservoir characterization north sea ps depth-migrated data p-and s-wave velocity match-filter approach upstream oil & gas field data fletcher schlumberger depth-migrated data...

... better acquisition geometry coupled with processing to address these challenges. applied geoscience heterogeneity raw data velocity model oristaglio migration exploration geophysicist 10 seam arid model reservoir characterization field data density contrast arid model processing...

... parameters in denoising methods is a difficult task, especially for filtering field data. To address the above issues, We propose a multichannel denoising scheme, termed as multi-channel variational mode decomposition (MVMD) based multi-channel singular spectrum analysis (MSSA). The proposed method first...

... Supervised learning-based seismic data processing has difficulty transferring synthetic data learning to real data applications. We report a distribution analysis method to build training datasets for the target field data, without modifying the network, and only a small volume of data is needed...

... neural network field data exploration geophysicist 10 demultiple alexander breuer unified approach machine learning deep learning stencil application input gather seismic processing synthetic data reservoir characterization upstream oil & gas trim static cdp gather seg international...

... produce the output almost in real-time. Therefore, it can be used by grid-search type approaches to focus the grid search over the smaller volume provided by the ConvNet. In this study we train ConvNets with synthetic data and apply them to field data. To our knowledge this is the first attempt...

.... artificial intelligence seismic data prediction result reservoir characterization porosity log frequency band neural network highest correlation coefficient prediction exploration geophysicist 10 geophysics sd seismic machine learning upstream oil & gas field data porosity prediction...

... and real data admitted reasonably accurate models representing mostly the low wavenumber features of the true models. Presentation Date: Wednesday, October 14, 2020 Session Start Time: 1:50 PM Presentation Time: 2:15 PM Location: 351F Presentation Type: Oral artificial intelligence field data...

... workflow upstream oil & gas field data tot resistivity university inversion geophysical survey interaction software myanmar seg international exposition interpretation notebook The Role of Open Source Resources and Practices in Capacity Building Douglas W. Oldenburg1, Lindsey J. Heagy2...

..., 2020 Session Start Time: 8:30 AM Presentation Time: 10:10 AM Location: 360D Presentation Type: Oral conventional rtm vertical seismic profile upstream oil & gas reflection geophysics rss-rtm image reservoir characterization fractured-basement imaging field data seg international...