CO2 plume evolution in a depleted natural gas reservoir: Modeling of conformance uncertainty reduction over time

Abstract

Uncertainty in the long-term fate of CO2 injected for geologic carbon sequestration (GCS) is a significant barrier to the adoption of GCS as a greenhouse-gas emission-mitigation for industry and regulatory agencies alike. We present a modeling study that demonstrates that the uncertainty in forecasts of GCS site performance decreases over time as monitoring data are used to update operational models. We consider a case study of GCS in a depleted natural gas reservoir, with CO2 injection occurring over 20 years, with a 50-year post-injection site care period. We constructed a detailed model to generate the actual model output, which is considered synthetic observation data. A series of simpler operational models based on limited data and assumptions about how an operator would model such a site are then run and compared against actual model output at specific monitoring points after one year, two years, etc. The operational model is updated and improved using the synthetic observation data from the actual model at the same time intervals. Model parameter values and model features needed to be updated over time to improve matches to the actual model. These kinds of model adjustments would be a normal part of reservoir engineering and site management at GCS sites. Uncertainty in two key measures related to site performance decreases with time: extent of the CO2 plume up-dip migration, and radial extent of the pressure pulse. This conclusion should help allay the concerns of industry and regulators about uncertainty in long-term fate of CO2 at GCS sites.

Improved geophysical monitoring of carbon sequestration through parameter linkage to reservoir modeling

“…Reservoirs of this kind are prospective candidates for long-term storage. Extensive CO2 plume evolution simulations by Doughty and Oldenburg (2020) assessed long-term forecasting uncertainties associated with pressure and saturation evolution. Their simulated scenario involves 8 Mt/year of CO2 injection over 20 years.…”

“…Reservoir models are expected to be a standard part of GCS site management. Doughty and Oldenburg (2020) use the term operational reservoir model for a hydrogeologic model that is expected to be initially crude at the pre-injection stage due to a limited data base. Operational reservoir modeling then involves the assimilation of the monitoring data stream for an ongoing model improvement.…”

Accurate and Rapid Forecasts for Geologic Carbon Storage via Learning-Based Inversion-Free Prediction

“…The conventional numerical method for predicting CO 2 distribution in a reservoir relies heavily on inverse modeling (history matching, calibration) to constrain uncertain parameters in complex reservoir simulation models (Bianco et al, 2007;Oliver and Chen, 2011;Doughty and Oldenburg, 2020). This inversion-based prediction approach has limitations for rapid integration of observation data and providing timely decision support due to the following reasons: 1) Model inversion is computationally expensive and can require tens of thousands of expensive reservoir model simulations.…”

Geomechanical effects of co2 storage in geological structures: two case studies

“…However, there is no direct or clear evaluation tool to explain induced seismicity during production and injection. Also several researchers have studied the mechanisms of ground surface movement due to production [7][8][9][10], the prediction of movement in the ground surface remains difficult [11]. Moreover, there are several evidence of well failure due to horizontal ground movement and faults sliding as a result of production [12].…”