... sufficiently prior to the FWI process. A well sonic velocity function with large smoothing was used to build the starting velocity model for FWI. The process aims to minimize the least-squared difference between predicted and observed seismic responses by means of updating the model on which the prediction...

... and repeatability of FWI results at field-data quality, including the presence of actual noise using time-lapse VSP data. VSP data was acquired at the very early stage of EOR and there was no CO2 injection in the time between the two time-lapse VSP surveys. As a result, a high-resolution P-wave velocity model...

... Successful imaging requires a precise velocity model that includes not only target levels but also overburden levels. In this study area, complex overburden geologies such as high velocity channels, low velocity karst, strongly anisotropic shale and lateral velocity heterogeneity exist...

... volume reveals more confidence in geological features that are not so clear in a pre-stack time migrated (PSTM) volume. The preliminary results indicate how shallow hydrocarbon presence can interfere with the PSDM velocity model and how it can be solved to reveal possible exploration potential in deeper...

... surveys in Abu Dhabi and Saudi Arabia. This directly affects all the geophysical factors responsible for data quality and structural definition of a seismic section, such as noise contamination, frequency content, near surface and velocity model. Abstract This study summarizes the efforts taken...

... analysis is presented over a complex structure where the raw data are characterized by strong Rayleigh waves dominated by a fundamental mode. Dispersion curves were inverted using nonlinear conjugate gradients to generate a shear wave velocity model with high vertical resolution for the first 50 m depth...

... (PreSTM), we regularized and interpolated the data through a five dimensional Fourier transformation, which significantly improved the SNR, as shown in Figure 3 . Velocity model building and imaging It is often difficult to capture the move out of the primary energy in the presence of strong noise...

... created directly from the velocity model. The trained classification neural network shows a very high > 97% accuracy on segregation of valid and invalid NMO velocity picks based on a 5% input data set. Further reduction of the training data set to 1% of velocity picks reduces test accuracy only...

... as well as a tomographic velocity model building approach with iterative inputs from interpreters has been a key to converge to a solid velocity model that allows for a reliable structural imaging. If the near surface is poorly imaged, the deeper sections also will be. Resolving the structural...

...-tomography in order to correct push-down effects in broadband anisotropic Pre-stack Depth migration. The dataset also helps to obtain high accuracy velocity model, de-multiple and quantitative interpretation. This acquisition and processing approach significantly improved the ability to image thin reservoirs...

... Abstract Near-surface characterization is an important part of seismic data processing, especially with land seismic data. The conventional approaches rely on refracted waves and estimate the compressional velocity models from the tomography of the first-break traveltimes ( Glushchenko et al...

..., it is essential to preserve the wavefield while imaging. Artificial Intelligence Imaging Upstream Oil & Gas information diffraction imaging diffraction local angle domain decomposition velocity model diffraction energy amplitude azimuth Reservoir Characterization CRAM adnoc onshore...

... and the basement. Robust seismic velocity model building in salt geology is a challenge and, at the same time, a mandatory requirement for obtaining accurate seismic depth images of the subsurface. Electromagnetic (EM) methods provide the additional independent structural and rock-physics constraints needed...

... depth structure image with higher resolution. Mitigate & address the observed depth uncertainties at the existing wells. Enhance the faults architecture & imaging. Analyze anisotropic velocity & build a reliable velocity model for depth imaging. Interpret azimuth volumes in depth...

... properties, with inconsistencies on variogram model parameters. Also, the validation of the velocity modelling and time-depth conversion used for the structural framework was validated by comparing FWLs depths against spill points. Furthermore, the quality of the facies model could be verified against...

... and interference noise. Poor signal to noise ratio (S/N) affects velocity estimation, wavelet stability and overall image quality. This paper demonstrates the successful implementation of different processing and interpretation tools to deal with these challenges. The initial velocity model was built...

... parameters. It is important to establish key parameters to be investigated for the better understanding of the model. Most important parameters influencing structural uncertainty using 3D seismic data are Horizon Picking, Velocity Modeling, Well Correlation / Marker Picking & Seismic Data Processing...

... is then applied to convert the spatially irregular frequency-dependent picks into a regularized (x, y, frequency) Rayleigh wave’s velocity volume. Lastly a laterally constrained depth inversion is performed, delivering a 3D shear wave’s near-surface depth velocity model. The second step of this workflow uses...

... of deposition was achieved by means of restorative velocity models to translate input mapped surfaces to their approximate original morphologies; results validation was achieved by subjecting study outputs to conformance tests with independent data from well logs, pressure tests, production performance...

... resulting in complex heterogeneous petrophysical and elastic properties. Velocity models development In addition to the petrographic analysis, petrophysical properties - porosity, permeability and grain density, were measured in all plug samples at ambient conditions as well as four confining...