First EAGE Offshore Workshop “Seismic to Simulation”

In recent decades, Carbon Capture, Utilization, and Storage (CCUS) has revolutionized the way numerous technologies, such as the oil and gas industries, have transitioned to provide sustainable solutions to reduce carbon emissions. This issue is of importance in relation to the United Nations Sustainable Development Goals (SDGs). In this study, we propose a multi-criteria decision-making (MCDM) framework to assess and compare the key criteria for selecting CCUS technologies. We proposed the technique of order of preference by similarity to ideal solution (TOPSIS) and the analytic hierarchy process (AHP) to rank CCUS technologies based on different criteria. Therefore, it was concluded that Cryogenic technology can be an essential technique among others, while in the TOPSIS method, Adsorption and Absorption technology ranked first.

Production monitoring with time-lapse seismic has been a key practice in the oil and gas industry, aiding in extending field life, identifying bypassed reserves, and preventing water breakthrough. Advances in seismic acquisition and processing now enable more detailed monitoring, even in geologically complex reservoirs.

For a deep-water gas field in the Romanian Black Sea, currently under development, maintaining a high production plateau is key to economic viability. Seismic interpretation indicates reservoir compartmentalization, making it crucial to identify untapped zones. Time-lapse seismic enables timely detection of these compartments, guiding infill drilling to sustain production. A detailed assessment of the field-specific expected time-lapse signal signature and magnitude, the associated noise levels and the optimum seismic acquisition configuration to evaluate the signal acquisition over the noise is required.

Using a calibrated rock physics and simulation-to-seismic modelling, the feasibility of future 4D seismic monitoring was assessed and monitor surveys designed considering conventional image-domain reflectivity techniques and advanced data domain methods using time-lapse full waveform inversion (4D FWI). The study characterized pressure depletion and saturation change signals. It was determined the pressure depletion signal is likely below the noise floor for conventional imaging, but with 4D FWI offering an alternative time-lapse seismic data processing strategy.

Recurring karst-related subsidence in the Wafra Joint Operation (WJO) oil fields has caused well abandonment, drilling fluid loss, and significant financial impacts for over 14 years. This study introduces a multidisciplinary approach to identify and mitigate these hazards in the Partitioned Zone (PZ).

The methodology combines geomorphological mapping, InSAR analysis for ground movement, hydrogeological assessments, and advanced geophysical surveys—including 3D passive seismic imaging (SWANS) and seismic reflection—to detect subsurface voids and fractures. Groundwater monitoring will clarify aquifer dynamics influencing karst processes. All data will be integrated into conceptual and numerical models to produce karst hazard risk maps and subsurface characterizations.

Expected deliverables include geological and hydrogeological models, anomaly maps, and actionable recommendations for sinkhole risk mitigation, infrastructure planning, and groundwater management. This integrated approach enhances operational safety, reduces financial losses, and supports sustainable development in a geologically sensitive region.

Over the past decade, our research has revealed that permeability in carbonate reservoirs is fundamentally controlled by tectonic-related secondary features—such as fractures, sheared bedding, and karstification—rather than by matrix properties as in clastic systems. Despite this, most subsurface modeling technologies still rely on matrix porosity-permeability trends, which are inadequate for predicting flow in carbonates. Our studies in Abu Dhabi and the wider region demonstrate that these secondary features, formed and modified by tectonic processes, create the primary pathways for fluid movement and reservoir connectivity.

To accurately represent these features in dynamic models, an integrated workflow is essential. This includes advanced borehole imaging, multi-attribute seismic analysis, and machine learning to extract and model fractures, bedding corridors, and karst systems in three dimensions. Geomechanical modeling is also critical to assess the kinematic activity and connectivity of these features, determining their contribution to effective permeability. By incorporating tectonic-driven heterogeneities into geocellular models, we achieve more realistic simulations of reservoir behavior, improved well placement, and optimized production strategies. This approach marks a paradigm shift in carbonate reservoir characterization, emphasizing the need to routinely include tectonic features as primary permeability drivers in offshore field development.

A multi-stage seismic attribute workflow was implemented to enhance the detection and mapping of faults, fractures, and karst corridors. Seismic data conditioning was performed to improve signal-to-noise ratio and highlight structural discontinuities.

The integration of seismic attribute-derived faults and fractures into the reservoir model resulted in significant improvements in history matching of oil rates and water cuts. The refined structural framework enabled the simulation to capture preferential flow paths, early water breakthrough, and compartmentalization effects observed in the field. The approach also improved well placement strategies by avoiding karstified and highly fractured zones, reducing drilling hazards, and maximizing reservoir exposure.

The use of advanced geosteering technologies and real-time inversion of deep azimuthal resistivity data further enhanced well placement accuracy and reservoir contact.

Kuwait Bay represents a largely untapped segment of the prolific Kuwait Arch in the state of Kuwait, offering potential for hydrocarbon exploration and development. The Cretaceous clastic reservoirs in the Kuwait Bay area, particularly Burgan, have been acknowledged for their substantial hydrocarbon production capabilities. Effective pay zones within the Burgan sandstone reservoir unit are highly correlated to the occurrence of relatively thin sand and shale interbeds, rather than thick single sand interval. This intraformational reservoir-seal pair delineation was critical for reducing uncertainty and mitigating risk for exploration success.

The present study aims to assess the prospectivity of these reservoirs through a custom-devised risk map approach that integrating geological, petrophysical, geophysical, and reservoir quality data to delineate potential hydrocarbon-bearing interbedded zones of relatively thin sand and shale. The risk map approach offers a structured framework for identifying prospective zones while minimizing risk by assessing factors such as reservoir-seal pairs, trap integrity and reservoir quality. The study results brought out promising zones with significant hydrocarbon potential, while identifying areas with higher geological risk, enabling a more targeted exploration strategy in Kuwait Bay.

Seismic surveys are critical for the investigation of subsurface geological formations, and the process of acquiring new surveys involves considerable planning, resources and huge costs. This study reuses legacy seismic surveys collected in the state of Kuwait, which includes thirteen vintages of 3D surveys, as well as three vintage 2D surveys from 1997, 1998, and 2005 where 3D data is not available. These surveys encompass both onshore and offshore areas and were conducted by various companies to provide geological insights of the subsurface. In a previous study, all the interpretation was done on individual surveys and when we merge interpretation and create maps of various properties then we always see the survey boundaries. In the case of 2D data the interpretation becomes very cumbersome, and interpretation of regional faults and acoustic properties cannot be determined efficiently. So, in this study we have created 3D data from 2D data combining geostatistical and machine Learning to get more accurate picture of the subsurface. Then in this study we merge the 3D data generated from 2D with the existing 3D surveys to create a Mega-Merge 3D dataset for the whole of Kuwait including both onshore and offshore.

Securing geological storage of carbon dioxide (CO2) requires a robust understanding of the subsurface, from large-scale geology to fine-scale fluid dynamics. For potential storage sites in mature hydrocarbon provinces, a comprehensive “seismic-to-simulation” workflow is essential to de-risk the storage complex and ensure long-term containment.

This study presents the application of an integrated workflow to characterize and evaluate the CO2 storage potential of the Cretaceous Burgan Formation in West Kuwait (“ Figure 1 ”), a major elastic reservoir, with a focus on geological characterization, dynamic performance, and containment assurance.