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Goodman, Angela L.

Publications and source records attributed to Goodman, Angela L..

Numerical Simulations of Carbon Dioxide Storage Efficiency in Heterogeneous Reservoir Models

The U.S. Department of Energy’s National Energy Technology Laboratory (DOE-NETL) has been developing methods and tools (the online Carbon Dioxide Storage prospeCtive Resource Estimation Excel aNalysis (CO2-SCREEN) tool) to estimate carbon dioxide (CO2) storage potential in subsurface reservoirs. The CO2 storage efficiency terms are input in the tool to calculate storage potential in targeted reservoirs. In this effort, two CO2 storage efficiency terms were evaluated: volumetric displacement ( E V ) and microscopic displacement ( E d ). The first term deals with efficiency of CO2 propagation into an accessible reservoir volume, while the second term evaluates effectiveness of native fluid displacement with CO2. The interpreted well logs and core sample measurements were applied to create the heterogeneous reservoir models including geostatistical realizations of porosity and intrinsic permeability fields. Supercritical CO2 was injected over the course of 30 years into brine-saturated reservoir models for clastics, limestone, and dolomite lithologies and deltaic fluvial, aeolian, shallow marine, and reef depositional environments by means of varying reservoir parameters and injection scenarios. The reservoir models providing vertically heterogeneous petrophysical properties and designated as “layered reservoir models” (with homogeneous parameters along each layer of the model) were not determined to be a transition between the homogeneous and heterogeneous models in respect to storage efficiency. Another finding shows that high-efficiency factors do not necessarily mean increased CO2 storage; they rather indicate that the available volume and pore space are more fully utilized. The CO2 storage efficiency factors were evaluated dynamically at the select time points using P 10 ‐ P 50 ‐ P 90 percentiles. The results of this study show that the P 10 ‐ P 90 distribution for volumetric efficiency is wider when compared to the microscopic efficiency. It was found that where dominant buoyancy forces drive the plume to the top of a target formation, the volumetric efficiency is low. Tighter sandstone and carbonate formations show prevalence of capillary forces and better utilization of reservoir volume.

Myshakin, Evgeniy M.↗

Simulated CO 2 storage efficiency factors for saline formations of various lithologies and depositional environments using new experimental relative permeability data

Saline formations are attractive geologic reservoirs for permanent carbon dioxide (CO 2 ) storage. Here, the U.S. Department of Energy's National Energy Technology Laboratory (DOE-NETL) has worked to develop and refine methods and tools for the calculation of CO 2 storage potential in subsurface reservoirs. DOE-NETL's CO 2 -SCREEN provides an online tool for executing these storage methods. CO 2 storage efficiency terms are input parameters in DOE-NETL's methods and equations embedded in the CO 2 -SCREEN, which assesses pore space available for CO 2 storage. In this work, a modeling workflow was initiated to refine two CO 2 storage efficiency terms - volumetric displacement (E V ) and microscopic displacement (E d ). The models are based on new experimental relative permeability data that are specific to homogenous lithology and depositional environments of key subsurface saline formations targeted for CO 2 storage. In future work, heterogenous features will be added to this initial modeling effort to update efficiency factors as described in DOE-NETL's methods and CO 2 -SCREEN tool. E V accounts for the volume utilized in the reservoir under the areal plume, while E d accounts for saturation values in the plume to assess efficiency of CO 2 storage at the pore scale. The results of this work are significant in that prior values were based on a limited geologically non-specific relative permeability data set that were collected prior to 2009. Specifically, we applied numerical simulations using TOUGH3 models to update CO 2 storage efficiency values for supercritical CO 2 injection into brine-saturated reservoirs for three lithologies (clastics, limestone, dolomite) and six depositional environments (Marginal Marine, Strand Plain, Deltaic Complex Fluvial, Aeolian, Shallow Marine, and Reef) that have a high potential for geologic CO 2 storage. Experimental relative permeability data in cores from these environments were utilized in the models with corresponding rock type/sedimentary environment. Results of this study showed that dolomite followed by limestone generated higher ranges of storage efficiency compared to clastics. The updated values provided a tighter efficiency range for clastics, lower P 10 but higher P 90 range for limestone, and higher P 10 and P 90 for dolomite. In general, tighter reservoirs with relatively low permeability and porosity were associated with higher E V and E d , showing efficient reservoir and pore utilization in these scenarios. High reservoir pressure and temperature associated with increasing depth increased the E V , and high CO 2 injection rates resulted in increases in E V and E d , while the impact of permeability anisotropy was minimal after the 30-year injection period.

03 NATURAL GAS↗

Enhanced Guest@MOF Interaction via Stepwise Thermal Annealing: TCNQ@Cu 3 (BTC) 2

Confinement of guest molecules in porous materials such as metal organic frameworks (MOFs) promises to deliver emergent properties separate from those of the individual components. Understanding the confinement mechanism is therefore important for the development of new synthesis routes that adjust MOF properties for specific applications. In this work, we developed a new synthetic method to confine guest molecules into MOF pores through a stepwise thermal annealing process, wherein the confinement of 7,7,8,8-tetracyanoquinodimethane (TCNQ) guest molecules into Cu 3 (BTC) 2 (BTC = benzene-1,3,5-tricarboxylic acid) MOF host is used as an example of how novel materials can be created with new physical properties. The stepwise thermal annealing process includes 1) an activation process of pristine Cu 3 (BTC) 2 MOF to maximizes the TCNQ guest loading in the MOF host by effectively removing the residual solvents and 2) post-annealing of the TCNQ infiltrated MOF to enhances the interaction of the confined guest molecules with the MOF host. Obtained experimental results based on thermogravimetric analysis, N 2 gas adsorption, electron microscopy, X-ray diffraction and infrared absorption, combined with density functional theory calculations provide evidence that the use of a stepwise thermal annealing process yields enhancements in the guest loading, packing and interaction between the TCNQ guest and the MOF host. The new hybrid TCNQ@Cu 3 (BTC) 2 system is stable and shows no significant signs of structural degradation even after submersion in water. This is due to the presence of significantly stronger interactions of TCNQ with the frame-work metal ions compared to those of the water molecules competing for the same framework binding sites. It was also found that TCNQ@Cu 3 (BTC) 2 system maintains a significant CO 2 and CH 4 adsorption potential compared to the pristine MOF. The synthetic route developed in this work yields novel guest@MOF hybrid systems that will be useful for many MOF-based applications such as gas separations and chemical sensors performed under humid conditions.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) User’s Manual

This user’s manual guides the use of the National Energy Technology Laboratory’s (NETL) CO₂ Storage prospeCtive Resource Estimation Excel aNalysis (CO₂-SCREEN) tool, which was developed to aid users screening geologic formations for prospective CO₂ storage resources. This manual is specific to the CO₂-SCREEN 4.0 version which is based in Python. CO₂-SCREEN applies U.S. Department of Energy (DOE) methods and equations for estimating prospective CO₂ storage resources for saline formations, shale formations, and residual oil zones (ROZ). CO₂-SCREEN was developed to be substantive and user-friendly and provide a consistent method for calculating prospective CO₂ storage resources. CO₂-SCREEN uses a Java based graphical user interface for data inputs and uses Python to calculate prospective CO₂ storage resources.

54 ENVIRONMENTAL SCIENCES↗