This presentation highlights two complementary studies that use advanced seismic techniques to improve understanding of how injected carbon dioxide (CO₂) moves and behaves in the subsurface at the Farnsworth CO₂-Enhanced Oil Recovery (EOR) Field in Texas. We used time-lapse three-dimensional (3D) vertical seismic profiling (VSP) to monitor how CO₂ distribution evolved within the reservoir over several years, revealing its gradual migration from injection wells toward production wells. We also deployed a borehole geophone array to record microseismic events triggered by CO₂ injection and migration, showing that the process created small fractures and altered the local stress field as reservoir pressure increased. Together, these studies demonstrate that integrating seismic imaging with microseismic monitoring provides a robust and reliable approach to tracking CO₂ migration in deep geological formations, improving the safety and effectiveness of both geologic carbon storage and oil recovery.

This panel will give attendees a comprehensive understanding of the technical, financial, and policy considerations that are crucial for successful carbon storage initiatives. It explores the multifaceted landscape of carbon capture, utilization, and storage (CCUS) risk management. This expert panel brings together diverse perspectives from academia, industry, and regulatory domains to dissect the critical challenges and strategies for mitigating risks across the CCUS project lifecycle. From subsurface geological complexities to financial assurance mechanisms and regulatory frameworks, our speakers will provide insights into how the industry can effectively de-risk CCUS projects, enhance public confidence, and drive sustainable carbon management solutions.

Perhaps the most important problem that we are facing is the Energy Problem which is coupled with the CO2 emissions. Anthropogenic greenhouse gas emissions (GHG), mainly CO2 have reached very high levels, causing long-term climate changes and visible in many ways such as rising sea levels, warmer and more acidic oceans, diminished ice coverage, increased global surface temperatures, and multi-dimensional chemical changes that can alter the global equilibrium of the earth systems. CO2, the key gas in these systems, should be reduced and parallel to that tremendous amount CO2 (~ 50 Gt) needs to be handled: stored/sequestered. Gas injection at large scale has been practiced in petroleum/subsurface engineering area for more than 50 years. Many technologies developed during this period.  Initially, most of the technologies for various gas injection processes, such as hydrocarbon gases and/or CO2, developed are centralized around the recovery improvement and gas storage. Later on, these technologies are applied for CO2 sequestration successfully at different settings in various countries. When the objective of CO2 injection is not limited to oil recovery processes, the application envelope for CO2 injection includes wider spectrum of options, such as deep saline aquifers and as well as basaltic rocks in addition to depleted hydrocarbon reservoirs and coal seams. Each option/case will have its own complexities, from data requirements to monitoring, especially in the context of reducing the uncertainty for screening, project execution and surveillance. In this talk, we will stress some of the key points and challenges of this global problem, how and how much progress has been made for various subsurface options.

Geologic CO2 storage (GCS) offers a viable technology for reducing CO2 emissions into the atmosphere and mitigating its climate change impact. The newly formed NSF Center for geologic CO2 Storage Modeling, Analytics, and Risk Reduction Technologies (CO2-SMART) aims to create a multidisciplinary synergistic program to accelerate safe and cost-effective deployment of the GCS technology at scale through industry-driven research and workforce development. A partnership between the University of Southern California (USC) and the Pennsylvania State University (PSU), the CO2-SMART Center has been established to address industry research needs in deploying GCS technology by advancing the understanding of complex processes that are triggered during and after CO2 injection into geologic formations. The focus is to develop advanced technologies to improve the safety, efficiency, and economics of GCS operations, and by providing scientific results to support the development of a pragmatic policy framework for large-scale deployment of GCS projects. In the first part of the talk, I will provide some details about the operational structure of the center and the research being performed. Point bars are channel sediments that accumulate when sinuous or meandering rivers or channels migrate laterally over a geologic period. Point bars can serve as high storage capacity reservoirs such as the Athabasca Oil Sands deposit in the Lower Cretaceous McMurray Formation in Canada. The Cranfield, Mississippi reservoir which is considered by several studies as a viable candidate for CO2 sequestration experiments is also characterized as a point bar reservoir. In this talk I will present a stochastic process-based approach to model the architecture of point bar systems and their associated heterogeneities. To account for uncertainties, the modeling was done by generating several realizations of point bar reservoir models. A model calibration workflow was implemented to reduce the uncertainties in the ensemble of point bar reservoir models using the injection rate data from the Cranfield CO2 sequestration study. The implemented hierarchical, two-step ensemble-based data assimilation technique addresses two important considerations: (1) account for uncertainties in reservoir geometry (2) handle the non-Gaussian relationship between the primary state variables and secondary variables for reservoirs with complex heterogeneities such as point bars. Finally, the updated models (i.e., calibrated models) were further refined in a Bayesian model selection workflow. The model selection algorithm is used to create a posterior set of models that reflect time-lapse seismic information, based on observed dynamic response. The applicability of the entire integrated workflow to a real field scenario is demonstrated, using the CO2 injection and timelapse seismic dataset for the Cranfield in Mississippi. The final ensemble of the refined selected models can be used to assess the uncertainty in predicting CO2 storage capacity and the future displacement of CO2 plume.