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Recent exploration activities within Paleocene and Eocene remobilized sands have proven the injectite play in the Northern Viking Graben (NVG). Wells targeting these sands have led to new discoveries such as Kveikje (2022) and Heisenberg (2023). This study proposes a robust methodology for detailed mapping of sand injectites by leveraging seismic attributes and integrating machine learning techniques, with a particular focus on the Eocene interval. By analyzing the responses from the seismic attributes at the location of the initial discoveries, we successfully identified other areas exhibiting similar characteristics, indicating the potential presence of prospective sand injectites.

We present a means to estimate porosity and permeability at cm-scale resolution using whole-core computed tomography (CT) scans. We focus on carbonate reservoir intervals of the Buah Formation and Khufai Formation, both part of the Precambrian Nafun Group, from two wells located onshore Oman. We segmented the CT volumes and measured a range of vug properties such as size and shape descriptors, followed by multiple linear regression for all possible permutations of terms for the prediction of CCA porosity and permeability.

We demonstrate how the use of multiples in imaging may provide improved shallow illumination and potentially reduce the requirement for extensive site-survey acquisition in some areas.

Multiple contamination in seismic data from the south of the Sultanate of Oman is challenging due to the combined presence of short-period surface and internal multiples generated in the upper section. We present an innovative workflow to attenuate multiples in the pre-migration pre-stack domain based on a dataset from the south of the Sultanate of Oman. The workflow involved least-squares multiple imaging to obtain a reliable reflectivity of multiple generators in the near surface.

The shallow water region of the Gulf of Mexico is known to present significant petroleum prospects due to dynamic tectonic activities during the late Cretaceous to early Tertiary. Previous imaging in this region using sparse ocean bottom cable (OBC) surveys was poor, mainly due to unresolved overburden velocity in the Mesozoic section. We implemented a velocity model building (VMB) approach driven by Time-lag full-waveform inversion (TLFWI) to resolve the complex velocity features in this area.

Land FWI has been applied to seismic data in the Sultanate of Oman in the past years, but its usage has been limited to low frequency updates and input for migration purpose only. With proper input data conditioning, initial model preparation and velocity inversion, we have managed to run acoustic FWI to 35 Hz. An FWI Image was then derived from the velocity, producing a superior image of the complex fault system compared to the conventional methods due to the utilization of the full wavefield and the least square fitting from low to high frequencies.

We present the use of elastic full waveform inversion (FWI) of surface waves to create a detailed shear velocity model of the near surface in the Middle East, where the shallow geology features strong velocity contrasts, making traditional velocity model building techniques challenging. The approach uses low-frequency virtual data from 3D interferometry and active surface waves to update the shear velocity model, providing valuable information for velocity model building and imaging. The study demonstrates the effectiveness of elastic FWI by comparing the results with the legacy velocity model and migrated images, showing improved resolution of the subsurface and simplified geological structures.

Full-waveform inversion (FWI) uses the full wavefield as input but, in general, diving waves are the key driver of the method. How to maximize the contribution of reflected waves is an important factor for success of FWI, especially on seismic data with a short offset coverage. We propose Dynamic Resolution Time-Lag FWI (DR-TLFWI) to better utilize the reflections, especially for low-wavenumber velocity updates for better kinematics.

In the Barents Sea, bright amplitudes on seismic data below the Base Quaternary indicate the presence of hydrocarbon reservoirs. To allow characterization and quantitative interpretation of these potential reservoirs, analysis of amplitude versus reflection angle (AVA) information is crucial. Even with the availability of high-quality Q-Kirchhoff pre-stack depth migration (Q-KPSDM) products, transmission-absorption relating to shallow gas pockets along with residual surface-related and interbed multiples may compromise the imaging of these shallow reservoirs. By using the full wavefield, imaging from full-waveform inversion (FWI Imaging) provides a reflectivity image without the need to perform the usual pre-processing and migration steps, offering the potential for improved handling of multiples and transmission issues. While FWI Imaging has delivered superior results in terms of imaging compared to more conventional migration methods, it has so far only provided a structural image without access to common image gathers used to derive AVA information. In this study, we extract elastic information from acoustic FWI Images generated from impedance updates using angle-restricted raw seismic data. The results of the angle-restricted FWI flow provide comparable AVA products to those obtained from a conventional Q-KPSDM approach, but with an improved signal-to-noise ratio in areas with complex near-surface geology.