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At least 19 records
All sourcesNASA NTRSDOE OSTI
DOE OSTI2018

Devising a framework to Couple Electromagnetic Geophysical Measurements with Reservoir Simulations to Monitor CO2 Plume Movement

Monitoring CO2 plume movement and extent is critical to any CO2 utilization and storage (CCUS) project but can present significant challenges. Downhole measurements (such as cross-well seismic) can give the resolution needed to track the CO2 plume. That resolution comes at a significant expense in equipment and lost production time, and the resolution is only in the vicinity of that well. Surface seismic is less expensive but has decreasing resolution with depth and may not be sensitive to changes in the CO2 plume. Conversely, electrical conductivity has been shown to be correlated with changes in phase saturation associated with CCUS operations. A novel approach for subsurface monitoring that can be applied with minimal expense and operation disruption is charged wellbore casing controlled-source electromagnetics (CWC-CSEM). This technique injects electrical current into two legacy wells. Surface measurements of the induced electric and magnetic fields are obtained with distributed data loggers. Time-lapse measurements are sensitive to changes in CO2 plume movement, but inversion requires the application of prior knowledge from prior characterization efforts. We propose a methodology where simulations are used to inform CWC-CSEM inversion while simultaneously being validated. As such, uncertainty is reduced, and more robust flow models can be devised. A three-year study is underway at the Bell Creek Field in southeast Montana (DOE-NETL Project DE-FE0028320) to evaluate the effectiveness of CWC-CSEM on an active CO2-EOR operation. Determining the relationship between electrical resistivity and phase saturations, and coupling that to a reservoir model is the thrust of this project. Initially, the relative permeability/capillary pressure relationship and the compositional oil model were identified as model parameters with high uncertainty. To elucidate the impact of these uncertain parameters, simulations were run for ten years with a single five-spot pattern. Final water saturation distributions were converted into resistivity using Archie’s Law and available fluid sampling data to provide an exploration of the time lapse electromagnetic anomaly which can be anticipated using CWC-CSEM methods. This technique has promise as an inexpensive and accurate way to monitor CO2 injection in a CCUS site.

Moodie, Nathan↗
DOE OSTI2022

Basin Management of Geologic CO2 Storage: Effect of Well Spacing on CO2 Plume and Pressure Interference

This is the conference paper accompanying an oral presentation made at the Society of Petroleum Engineers (SPE) Western Regional Meeting (WRM) held in Bakersfield, California, April 26–28, 2022. The paper provides the results of a basin-scale CO2 storage modeling project investigating subsurface pressure interference among CO2 injection wells located in proximity to each other.

Wijaya, Nur↗
DOE OSTI2022

A Geospatial Cost Comparison of CO2 Plume Geothermal (CPG) Power and Geologic CO2 Storage

CO 2 Plume Geothermal (CPG) power plants can use gigatonne-levels of CO 2 sequestration to generate electricity, but it is unknown if the resources that support low-cost CPG power align with the resources that support low-cost CO 2 sequestration. Here, we estimate and compare the geospatially-distributed cost of CPG and CO 2 storage across a portion of North America. We find that the locations with lowest-cost CO 2 storage are different than the locations with lowest-cost CPG. There are also locations with low-cost CO 2 storage (<$5/tCO 2 ) that do not support CPG power generation due to insufficient reservoir transmissivity or temperature. Thus, CPG development may require electricity prices that are greater than the levelized cost of electricity (LCOE) to offset the increased cost of sequestration. We introduce the “Additional Cost of Electricity (ACOE)” metric to account for this cost and add it to the LCOE to calculate breakeven electricity prices that are required for CPG development. We find that breakeven prices are lower when new CO 2 injection wells are drilled specifically for CPG (i.e., “greenfield” CPG development) compared to if only existing CO 2 sequestration injection wells are used (i.e., “brownfield” CPG development). This is because comparatively few wells are needed for sequestration-only, and the increased power capacity from having more CPG wells outweighs the increased costs from more drilling. We also find that sequestered CO 2 could be used to approximately triple the United States geothermal electricity power capacity via a single CPG “sweet spot” in South Dakota, but that breakeven electricity price for this development is on the order of $200/MW e h.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Machine Learning-Driven Quantification of CO2 Plume Dynamics at Illinois Basin Decatur Project Sites Using Microseismic Data

This study utilizes machine learning to quantify CO2 plume extents by analyzing microseismic data from the Illinois Basin Decatur Project (IBDP). Leveraging a unique dataset of well logs, microseismic records, and CO2 injection metrics, this work aims to predict the temporal evolution of subsurface CO2 saturation plumes. The findings illustrate that machine learning can predict plume dynamics, revealing vertical clustering of microseismic events over distinct time periods within certain proximities to the injection well, consistent with an invasion percolation model. The buoyant CO2 plume partially trapped within sandstone intervals periodically breaches localized barriers or baffles, which act as leaky seals and impede vertical migration until buoyancy overcomes gravity and capillary forces, leading to breakthroughs along vertical zones of weakness. Between different unsupervised clustering techniques, K-Means and DBSCAN were applied and analyzed in detail, where K-means outperformed DBSCAN in this specific study by indicating the combination of the highest Silhouette Score and the lowest Davies–Bouldin Index. The predictive capability of machine learning models in quantifying CO2 saturation plume extension is significant for real-time monitoring and management of CO2 sequestration sites. The models exhibit high accuracy, validated against physical models and injection data from the IBDP, reinforcing the viability of CO2 geological sequestration as a climate change mitigation strategy and enhancing advanced tools for safe management of these operations.

Iyegbekedo, Ikponmwosa↗
DOE OSTI2025

CO2 Plume Imaging with Accelerated Deep Learning-based Data Assimilation Considering Multiple Realizations: Application to the Illinois Basin-Decatur Carbon Sequestration Project

We propose a fast and efficient deep learning workflow for near real-time data assimilation, forecasting and visualization of CO2 plume evolution in saline aquifer and demonstrate its application at a field site. Unlike the previous work, this study incorporates the impact of spatial heterogeneity using multiple realizations. In the proposed workflow, a neural network model utilizes available monitoring data such as downhole pressure measurements as input and predicts the propagating pressure ‘front’ using the diffusive time of flight (DTOF) map which is considered as representative reservoir image of the flow field. The DTOF is the arrival time of pressure front propagation, which can be computed by the Fast Marching Method rapidly without flow simulations. Reservoir model calibration can be implemented by selecting the training data samples that describe the predicted DTOF map based on observed data. The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project.

CO2 plume imaging↗
DOE OSTI2022

Numerical Simulation of Commercial-Scale CO2 Storage in a Saline Formation Evaluating Basin-Scale Pressure Interference and CO2 Plume Commingling

Presentation at NETL Carbon Management Project Review Meeting held in Pittsburgh, Pennsylvania, August 15–19, 2022. The presentation provides quantitative evaluation of subsurface pressure interference and emphasizes the importance of interproject coordination among stakeholders associated with multi-project geologic CO2 storage in a shared sedimentary basin.

Wijaya, Nur↗
DOE OSTI2020

Detection Thresholds and Sensitivities of Geophysical Techniques for CO2 Plume Monitoring

This report assesses capabilities and limitations of different geophysical techniques for monitoring geologic sequestration of CO 2 . Seismic, gravity, electrical, and electromagnetic (EM) techniques are considered. Monitoring approaches for site characterization prior to CO 2 injection are different from those used while injecting CO 2 , or those suitable for post-injection monitoring. The focus of this study is on the aspects relevant to long-term monitoring of large areas in the post-injection phase, and specifically on early detection of secondary CO 2 plumes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2018

Assessment of Multiple Monitoring Methods for Detection of Brine and CO2 Leakage

We assess the effectiveness of four surface-based geophysical methods and in situ monitoring of pressure and chemical changes for detecting brine and CO2 leakage from legacy wells into underground sources of drinking water (USDW) overlying a CO2 storage reservoir. This is the first such effort to evaluate and compare six monitoring methods for detection of CO2 leakage. This assessment, conducted in support of the USDOE National Risk Assessment Partnership (NRAP), utilizes 3000 synthetic data sets, generated in an uncertainty quantification (UQ) model framework. This framework combines the results of (1) a CO2 storage reservoir model of a hypothetical storage operation of 5 MT/yr for 50 years into the 1700-m deep Vedder Fm. at a site near Kimberlina, California with (2) wellbore leakage models of a legacy well and (3) multi-phase flow and reactive transport models of brine and CO2 plume migration in aquifer layers overlying the storage reservoir. Leakage drives subsurface changes, quantified by pressure plumes, CO2-saturation plumes, and total dissolved solids (TDS) plumes, the latter being related to changes in pH and species concentrations. Depending on the depth of leakage, aquifer permeability, and regional groundwater gradient, pressure plume volumes can become larger than the CO2 and TDS plumes; however, reaching detectable thresholds may take too long to be useful. For a single monitoring well located 500 m downgradient of a leaky legacy well, a depth of 570 m is found to be optimal for sampling pressure and chemical changes. We assess four surface-based geophysical monitoring methods: electrical resistivity tomography (ERT), magnetotellurics (MT), gravity, and seismic methods. Sensors cover a 4-km × 2-km area. Both ERT and MT methods are sensitive to changes in CO2 saturation and TDS concentration, whereas gravity and seismic methods detect changes in CO2 saturation. The six monitoring methods complement each other in space and time, and we find that a minimum of 20 kT of CO2 leakage is required for the leakage plume to be detected. Of the four surface-based geophysical methods, gravity monitoring appears to be the most sensitive to CO2 leaks, while the usefulness of in situ pressure and chemical monitoring will depend on the level of unfilterable background noise. Geophysical monitoring methods may detect a leak anywhere in a large area and in a large depth range, but the effectiveness of pressure and chemical monitoring depends on the number of monitoring wells, where those wells are located, and the depth of sampling. Surface-based geophysical monitoring methods are cost-effective alternatives to in situ pressure and chemical monitoring methods.

NRAP, CCS, monitoring, geophysical methods, gravit↗
DOE OSTI2024

ML-based Data Assimilation and History Matching: Application to the IBDP CCS Project

It is crucial to monitor the CO2 plume effectively throughout the life cycle of a geologic CO2 sequestration project to ensure safety and storage efficiency. However, the computational cost of existing data assimilation methods can be prohibitively expensive due to the complex physics with multi-component non-isothermal simulation and high dimensionality of large-scale reservoir models. We address this challenge by proposing an accelerated deep learning-based workflow for model calibration and prediction of CO2 plume evolution in the reservoir.The power and efficacy of our workflow is demonstrated by application to the Illinois Basin-Decatur Project (IBDP), a large-scale CO2 storage test in saline aquifer. The data assimilation process is implemented rapidly by the proposed workflow with given field measurements including distributed pressure and temperature sensing (DTS) data at an injection and a monitoring well. CO2 plume evolution is predicted by running the simulations of the calibrated reservoir models.

Nagao, Masahiro↗
DOE OSTI2018

CO2 Injection Effect on Geomechanical and Flow Properties of Calcite-Rich Reservoirs

Geologic carbon storage is considered as a requisite to effectively mitigate climate change, so large amounts of carbon dioxide (CO2) are expected to be injected in sedimentary saline formations. CO2 injection leads to the creation of acidic solution when it dissolves into the resident brine, which can react with reservoir rock, especially carbonates. We numerically investigated the behavior of reservoir-caprock system where CO2 injection-induced changes in the hydraulic and geomechanical properties of Apulian limestone were measured in the laboratory. We found that porosity of the limestone slightly decreases after CO2 treatment, which lead to a permeability reduction by a factor of two. In the treated specimens, calcite dissolution was observed at the inlet, but carbonate precipitation occurred at the outlet, which was closed during the reaction time of three days. Additionally, the relative permeability curves were modified after CO2–rock interaction, especially the one for water, which evolved from a quadratic to a quasi-linear function of the water saturation degree. Geomechanically, the limestone became softer and it was weakened after being altered by CO2. Simulation results showed that the property changes occurring within the CO2 plume caused a stress redistribution because CO2 treated limestone became softer and tended to deform more in response to pressure buildup than the pristine rock. The reduction in strength induced by geochemical reactions may eventually cause shear failure within the CO2 plume affected rock. This combination of laboratory experiments with numerical simulations leads to a better understanding of the implications of coupled chemo-mechanical interactions in geologic carbon storage.

54 ENVIRONMENTAL SCIENCES↗