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Resolving Nanoscale Processes during Carbon Mineralization Using Identical Location Transmission Electron Microscopy

Basalt reservoirs offer the potential for carbon mineralization, aiding in achieving net-zero emissions. However, debates persist about microscopic crystallization mechanisms due to limited characterization techniques under high-temperature and pressure conditions. By using Identical Location Transmission Electron Microscopy (IL-TEM) and cryo-TEM, this study reveals nanoscale interfacial carbonation processes of forsterite and diopside nanoparticles in water-saturated supercritical carbon dioxide under realistic reservoir conditions. Further, both minerals undergo preferential metal cation dissolution into a thin water film, forming porous Si-rich amorphous layers, supporting the leached layer mechanism as the dominant mineral reactivity process. Diopside’s amorphous layer has lower porosity and growth rate relative to forsterite, likely related to the connectivity of silicate tetrahedra. Kinetically favorable nesquehonite and aragonite nanocrystals form on the amorphous layers. These findings support the development of accurate reservoir simulations and help enable commercial-scale carbon storage deployment.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

An extended trajectory-mechanics approach for calculating two-phase flow paths

A technique originating in quantum dynamics is used to derive a trajectory-based, semi-analytical solution for two-phase flow. The partial differential equation governing the evolution of the aqueous phase is equivalent to a family of ordinary differential equations defined along a path through the porous medium. The trajectories may be found by solving the differential equations directly or by post-processing the output of a numerical solution to the full set of governing equations. The trajectories, which differ from conventional streamlines, are found to bend downward in response to gravitational forces. The curvature is more pronounced as the dip of the porous layer containing the flow increases. Subtle changes in the relative permeability curve can lead to significant variations in the trajectories. The ordinary differential equation for the trajectory provides an expression for the travel time along the path. The expression produces a semi-analytical approximation to the model parameter sensitivities, the partial derivatives of the travel times with respect to changes in the permeability model. The semi-analytical trajectory-based sensitivities generally agree with those computed using a numerical reservoir simulator and a perturbation approach. The sensitivities are useful in tomographic imaging algorithms designed to estimate the spatial variation in permeability within a porous medium using multiphase observations.

58 GEOSCIENCES↗

Supplementary Data for "Evaluation of the Economic Implications of Varied Pressure Drawdown Strategies Generated Using a Real-time, Rapid Predictive, Multi-fidelity Model for Unconventional Oil and Gas Wells" by Bello, K., Vikara, D., Sheriff, A., Viswanathan, H., Carr, T., Sweeney, M., O'Malley, D., Marquis, M., Vactor, R.T., and Cunha, L.

The Bello et al. study evaluates the impact of contrasting pressure drawdown on gas productivity and the resulting economics of a well in the Marcellus Shale of the Appalachian Basin. This research applies a techno-economic analysis approach to help identify potential ways pressure management strategies can be used to improve cumulative recovery of hydraulically fractured horizontal wells while maintaining project profitability. Gas production forecast outlook scenarios of the Marcellus Shale Energy and Environment Laboratory Laboratory's MIP-3H well were generated under varying pressure drawdowns using two approaches: 1) a novel physics-informed machine learning (PIML) workflow and 2) via traditional reservoir simulation in Computer Modeling Group’s (CMG) GEM Compositional & Unconventional Simulator. Cash flow and other economic metrics of interest were compiled on the production outlook using the U.S. Department of Energy's (DOE) National Energy Technology Laboratory (NETL) Unconventional Shale Well Economic Model (UShWEM).The sheets within this Microsoft ExcelTM workbook provide the economic metric outputs for the baseline condition and the one-at-a-time (OAT) sensitivity analysis of UShWEM's input parameters for each of the production scenarios evaluated.

Fracture Network Model↗

SHASTA-HELP

This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

Hydrogen↗

NRAP Toolkit Screening for CarbonSAFE Illinois - Macon County

In this report we take stratigraphic data from the ISGS-led Macon County Phase 2 CarbonSAFE’s proposed site in Christian County, Illinois, and conduct reservoir simulations to generate pressure and CO 2 saturation plume data as a function of time. We then use this plume data along with the stratigraphic data as inputs to the NRAP Open-source Integrated Assessment Model (NRAP-Open-IAM) to evaluate project risks. For this report we focus on the probabilistic risk associated with hypothetical leakage of CO 2 and brine along the injection well and one monitoring well. We also study the resulting impact to two overlying aquifers, which could be used to inform monitoring technology selection.

54 ENVIRONMENTAL SCIENCES↗

Parametric Study to Assess Technical Prospect Feasibility for Offshore CO 2 Storage

This report is a white paper on the parametric study to assess technical prospect feasibility for CO 2 storage with and without CO 2 -EOR. The SECARB Offshore GOM team reviewed key parameters that previous modeling experience suggests have the largest impact on CO 2 plume size and CO 2 -EOR performance (SSEB, 2019) These parameters include tectonic impacts (reservoir dip and fault block size), reservoir properties (permeability) and development strategies (well field payout, waterflood, and CO 2 flooding strategies). These parameters are further evaluated in this study in order to identify upper and lower boundary conditions for the parametric values. The boundary conditions are needed to set constraints for key parameters when performing modeling assessments. Understanding the key parametric values for the GOM will facilitate locating successful offshore carbon capture utilization and storage (CCUS) projects in terms of plume size, CO 2 stored and, in the case of EOR, oil recovery. Importantly, this white paper focuses on both technical factors (geologic and engineering), but does not address economic, commercial, or stakeholder considerations. The report is organized into four sections and includes a review of the datasets used to define the parameter ranges, the results of a full-physics reservoir simulation, a summary of a reduced order modeling approach to evaluate the impact of the study parameters, and, finally, a discussion of the work that will occur during the next phase of the project.

02 PETROLEUM↗

Fracture Adjacent Matrix Permeability: Insights from a Direct Experimental Approach

Description of a measurement technique, using a triple-pressure tap Hassler Style Core holder, that facilitates pressure measurement perpendicular to a fracture. Through the measurement of permeability changes at multiple distances from the fracture, this system enables an understanding of how end effects and localized ‘skin effects’ can impact the ability of fluids to move to and from the bulk matrix. Measurements of this type may lead to improved input values for reservoir simulations involving discrete fractures and/or dual-permeability.

47 OTHER INSTRUMENTATION↗

Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (Final Report)

This document presents final technical findings for the project Using Natural Gas Liquids to Recover Unconventional Oil and Gas Resources (FE0031782). The project is part of the U.S. Department of Energy Oil and Gas Program to develop and advance technologies that can significantly improve the recovery efficiencies of unconventional oil and gas resources. The overall objective of this project is to improve the ultimate recovery from unconventional oil and gas (UOG) resources in the United States by developing a method for using unrefined natural gas liquids (NGLs) as treatment fluids to improve hydrocarbon production. Horizontal extended-lateral drilling coupled with high volume hydraulic fracturing has significantly increased production from UOG resources in the U.S. However, the recovery efficiency is low compared to the estimated oil and gas in place. Recent data indicate that less than 10% of the oil in the liquid-rich UOG reservoirs is produced. Alternative completion methods using NGLs could increase production (Battelle, 2016; Wan et al., 2013; Wan, 2013; Downey et al, 2021); however, field validation tests are needed to develop an approach that is economical, efficient, and compatible in the UOG setting to advance towards commercial deployment. This project aims to develop and field test a method to improve recovery of oil resources in UOG shale plays by using Y-Grade NGLs, or a similar combination of NGLs, as treatment fluids. Refined NGLs have been used as a hydraulic treatment fluid in UOG plays for decades and are shown to be particularly effective because their miscibility with oil allows oil to flow more freely; however, the use of Y-Grade (unrefined) NGLs has not been studied. The use of Y-Grade NGLs would be advantageous over refined NGLs because Y-Grade NGLs do not require infrastructure or investment in refining and are already being produced from many UOG reservoirs. The concept was tested and monitored in the field at a commercial well site owned by project partner Hopco, Ltd. The project team, which consists of multiple oil and gas operators, Linde Gas North America LLC (Linde) and the Ohio Division of Geological Survey (ODGS), has extensive experience with oil and gas production in the Appalachian basin and the ability to work together quickly to solve technical issues and research needs. A key part of the proposed work was the use of existing wells for field testing and monitoring. A total of four wells (three vertical and one horizontal) were available for this project. One of the vertical wells was utilized as the test well for the NGL treatment test. A nearby vertical well was used for microseismic monitoring. The remaining vertical well and the horizontal well provided a baseline for typical UOG production in the oil window of the Utica/Point Pleasant (UPP). Major technical tasks of the project include characterization of the geotechnical properties of the UPP with an emphasis on the field site; design and planning for the NGLs testing; field testing and monitoring; analysis and integration of field data; and economic and resource/reserve assessment. The Shoman monitoring well and Doughty NGL treatment well were successfully plugged back during September-October 2020 in preparation for treatment and monitoring. A nitrogen diagnostic fracture injection test (DFIT) was completed on the Doughty well on July 22, 2021, consisting of 133,000 scf (91 Bbl.) of nitrogen. A nitrogen foam frac was completed in the Utica-Point Pleasant interval on August 17, 2021 with funding from outside sources. A microseismic monitoring array was installed in the Shoman well and monitored microseismic activity during the Doughty well frac job. Y-Grade NGL injection commenced on August 26, 2021. A total of 215 Bbl. was injected but the job was shut down due to a small leak on the suction hose on the pump truck. The Y-Grade treatment resumed on August 27, 2021 and an additional 726 Bbl. of Y-Grade NGL was injected at a well head pressure of 3850 psi. Total volume of injected Y-Grade over the two days of injection was 941 Bbl. The well was shut-in for 17 days following injection to allow the Y-Grade NGLs to soak on the formation. Y-Grade treatment flow back commenced on 9/13/2021 on a weekly basis. Production data, including surface pressures, oil, nitrogen, natural gas, and flow times was measured and recorded. Periodic gas samples were collected and analyzed to determine composition of flowback gas. As of July 2022, the treatment well had produced 726 Bbl of oil and 2,888 mcf gas. In August 2022, tubing and packer in the well were removed and a pump was installed to enhance oil recovery. Currently, the operator is producing the well about 2 days a week for a few hours. The performance of the NGL treatment test was evaluated based on reservoir simulations of the treatment process, processing of well testing data, analysis of micro seismic monitoring data, and production data analysis. This analysis suggested that oil production in the small test would continue through 2025. Upscaling the treatment to a horizontal Utica Point-Pleasant well would allow more oil recovery, but the process would involve more investment, services, and operational support. An economic analysis was conducted for scenarios aimed at upscaling the NGL treatment process for more typical horizontal UPP wells in the Appalachian Basin.

02 PETROLEUM↗

Improving Subsurface Stress Characterization for Carbon Dioxide Storage Projects by Incorporating Machine Learning Techniques

The overall objective of this project is to develop a framework for reliable characterization and prediction of the state of stress in the overburden and underburden (including the basement) in CO 2 storage reservoirs using machine learning and integrated geomechanics and geophysical methods. Specifically, we propose to develop workflow encompassing of technologies and/or methods to predict stress and pressure changes due to CO 2 injection in an active tertiary recovery site and their impacts on subtle fault activation, fractures and occurrence of microseismic events and compare responses to field observations. In this project, we anticipate using dataset from the Farnsworth field Unit (FWU) which is operated by Purdure Petroleum. A novel elastic-waveform VSP inversion technique will be used to estimate high-resolution spatial and temporal changes of elastic moduli in CO 2 storage reservoirs, which will be combined with velocity-stress relationship derived from laboratory tests to obtain subsurface pressure and stress. Clustered microseismic data will be jointly inverted for improved focal mechanisms. Least-squares reverse-time migration of microseismic waveform data will be performed to directly image fracture/fault zones. Additionally, a deep neural network machine learning technique with convolutional and recurrent layers will be used for learning the spectro-temporal structures in microseismic waveforms. The results of this geotechnical data analysis will be integrated to develop a high-resolution 3D mechanical earth model extending from the overburden sealing formations to the underburden including the basement. Mechanical properties will be derived through integration of mechanical logs, tests, available results from chemo-mechanical laboratory tests, and elastic inversion of seismic data using a combination of Bayesian and stochastic methods as well as machine learning technique. Failure features (faults/fractures) will be represented and/or modeled based on seismic and core data analysis. A transient hydrodynamic-geomechanical model will be developed through coupling with the calibrated FWU reservoir simulation model. The full physics coupled model will be used to train a reduced order proxy model using machine learning algorithm for estimating stress which will then be used with appropriate constitutive relationships and forward seismological models to simulate pressure changes and induced microseismicity. An advanced optimization framework will be developed to perform a history match to minimize error between field observations and simulated. The history matched proxy model will be verified against the full-physics equivalent. The field observations that will be used in the coupled model calibration process include pressure/stress inverted from VSP, moment magnitude from microseismic analysis, real time downhole pressure measurements, production and injection data. Parameter sensitivity and uncertainty analysis will be performed to characterize the impact of model parameter uncertainty on stress estimates. The proposed project will have significant impact on future field implementation of the proposed technology. Because the project field site is an ongoing CO 2 EOR development, the value of the new technology will be demonstrated in an operational context and evaluated as a viable risk mitigation strategy. Cost/benefit will be evaluated together with the various commercial incentives for CO 2 sequestration available to oil and gas operators. The extensive available dataset and ongoing data acquisition under the SWP Phase III work plan provides flexibility for investigation of multiple approaches and reduces technical risk.

58 GEOSCIENCES↗

Integration of seismic-pressure-petrophysics inversion of continuous active-seismic monitoring data for monitoring and quantifying CO 2 plume (Final Report)

The overall objective of this project is to develop and validate an integrated package of joint seismic-pressure-petrophysics inversion (jSPPI) of continuous active-source seismic monitoring dataset capable of providing real-time monitoring of CO 2 plume during geologic carbon sequestration (GCS). The three specific developments include: (a) the methodologies for fast seismic full waveform inversion of continuous active source seismic monitoring, (CASSM) datasets for simultaneously estimating velocity and attenuation, and with data assimilation; (b) joint Bayesian petrophysical inversion of seismic models and pressure data for providing and updating CO 2 saturation models; (c) the methods using multiple datasets including (Crainfield and Frio-II borehole) synthetic, laboratory, and field CASSM datasets. The outcomes of jSPPI include (a) a workflow for processing CASSM data, (b) Bayesian inversion algorithms using CASSM data and pressure response data, and (c) integration with data assimilation algorithms for continuously updating site-specific models used for prediction and reservoir management. The validation of joint FWI will be conducted using synthetic models based on the Cranfield and Frio experiments as well as field CASSM datasets collected as part of the Frio-II pilot injection. To quantify and map the mass and distribution of CO 2 (saturation), we will jointly invert velocity and attenuation measurements from the FWI with a Bayesian approach using a rock physics model for attenuation (e.g., White’s attenuation model with two selected patch sizes (White, 1976; Dutta and Seriff, 1979)). The Bayesian inversion will be applied to each time step in the CASSM survey in an updating scheme, which integrates with an ensemble of reservoir simulations at each step. A more complete experimental validation dataset will be collected as part of a mesoscale (2-3 m) gas-CO 2 injection experiment utilizing a higher frequency version of the CASSM system developed for laboratory studies; the integrated inversion will be demonstrated using this dataset which will provide both a dense geometry as well as more precise secondary confirmation measurements (e.g. saturation) typically not available in the field. The resulting real-time map of CO 2 saturation is able to provide a deeper scientific understanding of the complex, time-varying dynamics of subsurface fluid flow migration path as well as the rapid detection of CO 2 leakage hazards.

25 ENERGY STORAGE↗

Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP) User’s Manual

This user’s manual describes version 1.0 of the SHASTA-HELP (Subsurface Hydrogen Assessment, Storage, and Technology Acceleration (SHASTA) - Hydrogen Estimator for Logistical Planning (HELP)) tool and provides instructions for use. The purpose of the SHASTA-HELP tool is to integrate the suite of tools developed by the SHASTA research team in a web-based framework for ease of access and more advanced, integrated analysis. This tool contains functionality for estimating the storage potential of pure and blended natural gas-hydrogen mixtures in various subsurface formations and is intended to be used for pre-characterization or site screening purposes. Detailed storage analysis should be conducted by full reservoir simulation models.

08 HYDROGEN↗

Milestone Report for MS8: Extend Quantitative Brine and CO 2 Leakage Calculations

This report summarizes results of the risk analysis and characterization of CO 2 and brine leakage potential of Farnsworth Unit (FWU) wells. U.S. DOE’s National Risk Assessment Partnership (NRAP) program works on quantitatively assess long-term environmental risks amidst significant geologic uncertainty and variability. NRAP risk assessment and computational tools are developed to quantify uncertainties and calculate risk associated with geologic sequestration of carbon dioxide (CO 2 ). For this study, we have developed a workflow from University of Utah’s physics-based reservoir simulators to performing leakage calculations using NRAP Tools. NRAP tools (NRAP-IAM-CS, RROM-Gen) are used to conduct leakage risk analysis based on Eclipse simulation results, and characterize wellbore leakage at the Farnworth Site. This report summarizes results of the risk analysis and characterization of CO 2 and brine leakage potential of Farnsworth Unit (FWU) wells.

54 ENVIRONMENTAL SCIENCES↗

ML-based Dimension Reduction Strategies

Deep learning (DL)--based surrogate models have achieved success in various applications in carbon capture and storage (CCS). However, the model training on high-dimensional spaces is computationally expensive and impractical for large-scale and complex geological models, because the models usually contain hundreds of thousands to millions of grid cells, each with a set of parameters. Furthermore, the high cost of generating training data with sufficient variation is another limitation of model training on high-dimensional spaces, which may result in overfitting and reduce the model efficiency and prediction performance. We proposed the workflow incorporating dimension reduction methods and deep learning models, which aim to extract the latent variables of input parameters and output state variables, and then build the mapping function at the latent spaces. The proposed workflow can significantly reduce the computational complexity in solving both forward and inverse problems compared to models trained on high-dimensional spaces. Dimensionality reduction models showed great potential in workflows for fast reservoir simulation, history matching, prior model generation, visualization, and more, ultimately enhancing DL model performance in related SMART Work Packages.

Hosseini, Seyyed↗

MRCI Subtask 2.4/2.5: Regional/Subregional Analysis and Risk Assessment Final Technical Summary Report

The objective of the Midwest Regional Carbon Initiative (MRCI) project is to implement a collaborative Regional Initiative (RI) to accelerate the deployment of carbon capture, and storage (CCS) in the Midwest-Northeastern quadrant of the United States. This report is a Technical Summary report describing work performed on Tasks 2.4 (Conducting Regional/Subregional Analysis) and 2.5 (Assessing and Managing Risk) during the MRCI project. In Task 2.4, detailed numerical reservoir simulation models were developed for selected carbon storage (CS) systems identified under Task 2.1 (Battelle, 2021a) in the MRCI study area. The objective of Task 2.4 is to demonstrate a dynamic modeling methodology for evaluating the suitability of the (selected) CS systems in the MRCI region for hosting a commercial-scale storage project. In this study, CO2 injectivity was evaluated for different CS systems with an annual injection rate of 1 million metric tonnes (MMT) of CO2 considered as the minimum requirement for a commercial scale project. The objective of Task 2.5 is to assess key risks associated with storing CO2 in the different CS systems across the MRCI region and to demonstrate a method(s) for assessing these risks that may be used by developers of future CO2 storage projects in the region. The risk analysis was limited to evaluating two types of leakage risks (i.e., wellbore leakage, flow across unfractured caprock) at three modeled sites considered in Task 2.4.

MRCI,Report,Summary,Technical Challenges,dynamic m↗

One Earth Energy Static and Dynamic Reservoir Modeling

This report presents the static and dynamic reservoir modeling conducted for the CarbonSAFE Phase III Illinois Storage Corridor project to assess the feasibility of commercial-scale CO 2 storage in the Mt. Simon Sandstone at the One Earth Energy (OEE) site in McLean County, Illinois. Three-dimensional geocellular models of the Mt. Simon storage complex were developed in Petrel ® by integrating petrophysical log data, core analyses, and seismic surveys from the OEE #1 stratigraphic test well and two nearby wells, with multiple model versions created as new data became available. Dynamic reservoir simulations, performed using Landmark's Nexus software, progressed through three phases (preliminary, sensitivity, and UIC Class VI permit studies) evaluating injection scenarios across varying rates, well orientations, permeability models, and multi-well configurations. Results demonstrate that commercial-scale storage is feasible: three injection wells spaced approximately one mile apart can store a total of 90 million tonnes of CO 2 over 20 years, producing a combined plume with an equivalent radius of 3.2 miles and a maximum pressure-front-defined Area of Review of 178 mi 2 at the end of injection that diminishes to 34 mi 2 after 50 years of post-injection monitoring. Sensitivity analyses indicate that a 20% change in porosity or permeability yields approximately a 7% change in AoR radius, and that perforating the high-permeability arkosic zone minimizes the pressure front compared to injection in the upper Mt. Simon Sandstone.

09 BIOMASS FUELS↗

The Importance of Modeling Carbon Dioxide Transportation and Geologic Storage in Energy System Planning Tools

Energy system planning tools suggest that the cost and feasibility of climate-stabilizing energy transitions are sensitive to the cost of CO 2 capture and storage processes (CCS), but the representation of CO 2 transportation and geologic storage in these tools is often simple or non-existent. We develop the capability of producing dynamic-reservoir-simulation-based geologic CO 2 storage supply curves with the Sequestration of CO 2 Tool (SCO 2 T) and use it with the ReEDS electric sector planning model to investigate the effects of CO 2 transportation and geologic storage representation on energy system planning tool results. We use a locational case study of the Electric Reliability Council of Texas (ERCOT) region. Our results suggest that the cost of geologic CO 2 storage may be as low as $3/tCO 2 and that site-level assumptions may affect this cost by several dollars per tonne. At the grid level, the cost of geologic CO 2 storage has generally smaller effects compared to other assumptions (e.g., natural gas price), but small variations in this cost can change results (e.g., capacity deployment decisions) when policy renders CCS marginally competitive. The cost of CO 2 transportation generally affects the location of geologic CO 2 storage investment more than the quantity of CO 2 captured or the location of electricity generation investment. We conclude with a few recommendations for future energy system researchers when modeling CCS. For example, assuming a cost for geologic CO 2 storage (e.g., $5/tCO 2 ) may be less consequential compared to assuming free storage by excluding it from the model.

20 FOSSIL-FUELED POWER PLANTS↗

Time-Lapse Integration at FWU: Fluids, Rock Physics, Numerical Model Integration, and Field Data Comparison

We present the current status of time-lapse seismic integration at the Farnsworth (FWU) CO2 WAG (water-alternating-gas) EOR (Enhanced Oil Recovery) project at Ochiltree County, northwest Texas. As a potential carbon sequestration mechanism, CO2 WAG projects will be subject to some degree of monitoring and verification, either as a regulatory requirement or to qualify for economic incentives. In order to evaluate the viability of time-lapse seismic as a monitoring method the Southwest Partnership (SWP) has conducted time-lapse seismic monitoring at FWU using the 3D Vertical Seismic Profiling (VSP) method. The efficacy of seismic time-lapse depends on a number of key factors, which vary widely from one application to another. Most important among these are the thermophysical properties of the original fluid in place and the displacing fluid, followed by the petrophysical properties of the rock matrix, which together determine the effective elastic properties of the rock fluid system. We present systematic analysis of fluid thermodynamics and resulting thermophysical properties, petrophysics and rock frame elastic properties, and elastic property modeling through fluid substitution using data collected at FWU. These analyses will be framed in realistic scenarios presented by the FWU CO2 WAG development. The resulting fluid/rock physics models will be applied to output from the calibrated FWU compositional reservoir simulation model to forward model the time-lapse seismic response. Modeled results are compared with field time-lapse seismic measurements and strategies for numerical model feedback/update are discussed. While mechanical effects are neglected in the work presented here, complementary parallel studies are underway in which laboratory measurements are introduced to introduce stress dependence of matrix elastic moduli.

4D↗