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At least 415 records · Page 23

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DOE OSTI2022

Computed Tomography Scanning and Geophysical Measurements of State 16-2 Well in the Paradox Basin

58 GEOSCIENCES↗

DOE OSTI2023

Computed Tomography Scanning and Geophysical Measurements of Appalachian Basin Core from the Jones and Laughlin #1 Well, Beaver County, PA

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia, were used to characterize Appalachian Basin core from Beaver County, Pennsylvania. The primary impetus of this work is a collaboration between the U.S. Department of Energy (DOE) and the Pennsylvania Geological Survey to characterize and make publicly available core information from the Onondaga-Huntersville formations of the Appalachian Basin. This stratigraphic well and the core data produced in this report will aid in understanding the structural complexities of the Onondaga-Huntersville formations. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/jonesandlaughlin1well. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. Fractures, discontinuities, and millimeter-scale features were readily detectable with imaging performed with the NETL medical CT scanner over the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for further study. Targeted higher resolution CT scanning of select sections was performed with NETL’s micro-CT scanner. The combination of methods used provides a multiscale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy related examinations traditionally performed at NETL.

58 GEOSCIENCES↗

DOE OSTI2023

New Insights from Legacy Seismic Data regarding Basalt Elevations and Variability on the Hanford Site

Migration of groundwater contaminants in the Gable Gap area of the Hanford Site in southeastern Washington State is strongly influenced by the distribution and permeability of basalts that lie beneath an unconfined aquifer. Locally, folding and faulting of the Columbia River Basalt associated with the Yakima fold and thrust belt followed by erosion due to the Lake Missoula floods resulted in a complex basalt surface that represents either an impermeable lower boundary to the unconfined aquifer system or localized regions of increased permeability that potentially promote communication between the unconfined aquifer system and deeper, confined aquifer systems. Paleo-channels carved into the basalt by floodwaters are thought to provide preferential flow paths for groundwater contaminants. In 2011, a seismic landstreamer campaign was carried out to image the basalt surface and produced pre-stack depth migrated p-wave reflection images. The reflection images identified two large troughs that may represent paleo-channels and several areas of possible faulting. Here, the streamer data are re-analyzed using refraction travel-time and Rayleigh wave dispersion analyses to obtain images of compressional and shear wave velocities within the suprabasalt sediment sections and the upper basalt surface. The combined interpretation of reflection and seismic velocity images shows complexity in the basalt velocity and elevation, which varies by 50 m or more within the study area. These results, along with other ongoing geophysical investigations, will be used to inform the site geologic model and potentially guide placement of future boreholes needed to quantify vertical flow between the confined and unconfined aquifers.

58 GEOSCIENCES↗

DOE OSTI2022

Kinetic and equilibrium reactions on natural and laboratory generation of thermogenic gases from Type II marine shale

The phenomenon that laboratory pyrolysis experiments produce much wetter gases than those in natural reservoirs is a long-recognized and debated problem in the investigation of natural gases in sedimentary basins. In this study, we explore the discrepancy by pyrolyzing a type II kerogen from the Woodford Shale in Oklahoma, compared with the previous results on the produced natural gases from the Arkoma Basin generated from the same source rock (Liu et al., 2019) with the discussion of gas and isotopic compositions at bulk and position-specific (PS) levels. An improved GC-pyrolysis-GC IRMS method is applied for the determination of PS δ 13 C of propane produced in the pyrolysis of the Woodford Shale at Easy %R o from 0.76 to 3.27. Kinetic and thermodynamic considerations of the chemical and isotopic compositions of the natural and laboratory pyrolysis gases suggest that the generation of light hydrocarbons involves uni-directional cracking reactions, exchange reactions with water, and likely reversible reactions among light hydrocarbons and other H-containing volatiles. After the gas generation in the unconventional Woodford Shale reservoirs, the C 1 -C 4 gases might have approached close to chemical equilibrium of C 1 -C 3 and isotope equilibrium of C 2 -C 1 and C 3 -C 1 pairs at their peak temperatures. The capping H for the generation of C 1 -C 4 in the Woodford Shale gases appears to have experienced at least partial exchange with the water, while that in the pyrolysis gases is only originated from organic-bound compounds with large kinetic isotope effects (KIE). Our findings indicate that elevated compound-specific and PS δ 13 C values of propane in the wet-gas cracking stage are significantly influenced by the breakdown of the thermally stable compounds (e.g., remaining kerogen, residues). A first synthesis of PS δ 13 C and δ 2 H isotopic compositions of propane from this study and the literature data suggests relatively similar isotopic structures of propane precursors in kerogens. Finally, this study demonstrates that PS isotope analysis of propane can contribute to identifying various geological (e.g., maturation, wet-gas cracking, H exchange, diffusion) and biodegradation processes.

58 GEOSCIENCES↗

DOE OSTI2023

Association Between Injection and Microseismicity in Geothermal Fields With Multiple Wells: Data-Driven Modeling of Rotokawa, New Zealand, and Húsmúli, Iceland

Understanding injection-induced microseismicity in geothermal systems can provide insight into reservoir connectedness. However, fault and reservoir complexity are difficult to represent in simple analytical models, which makes it difficult to discern clear relationships from incidental associations. Here, we have used data-driven models to study how fluid injection and microseismicity are related in the Rotokawa (New Zealand) and Hellisheiði (Iceland) geothermal fields. We tested two classes of model: (a) lagged linear regression of seismicity rate as a function of well injection rates; and (b) systematic extraction of injection time series features that are then evaluated for associations with the seismicity. These models allowed us to determine which wells had the greatest correlation with microseismicity and to explain this association in a reservoir context. Finally, exploring different data types and transformations, we were unable to establish a link between rapid changes in injection rate and seismicity spikes, as suggested by some theoretical models.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

FLIT: A Generic Fortran Library based on Interfaces and Templates

This Fortran code consists of multiple modules with a focus on simplifying array operations, image processing, and numerical computation especially for computational geophysics applications. We intend to use this code to demonstrate the application and usefulness of Fortran interface and templates for generic programming, especially for computational geophysics and seismology applications. The code has several notable features. Firstly, it is based on a modularized structure, where each module contains multiple functions but with a focus of functionality. Secondly, it heavily uses interfaces and templates for improving the genericness and convenience of the resulting code, where a same function interface can enclose a group of functions that perform the same functionality but with inputs/output variables of different data types. Thirdly, it includes a variety of generic functions with an emphasis on array operations, such as rotation, flipping, cropping, padding, fast Fourier transform, Gaussian blurring, interpolation, and so on. We name this package FLIP – a generic Fortran Library based on Interfaces and Templates.

Gao, Kai↗

DOE OSTI2023

Implementation of MLP-NN on Field data for dipole dipole and Alt3 Wenner configurations

Training data for both dipole dipole and Alt3 wenner configurations included. Field dataset for both dipole dipole and Alt3 wenner configurations included (Test dataset). Python code for implementation of MLP-NN included. Results for inversion of both configurations included.

58 GEOSCIENCES↗

DOE OSTI2022

labquake_future_prediction

The labquake_future_prediction code is a collection of python modules and scripts that serves as supporting information for the article “Predicting future laboratory fault friction through deep learning” for publication in the journal of “Geophysical Research Letters”. It is designed to predict laboratory fault slips in the immediate future by scanning continuous acoustic emission (AE) waveforms recorded in laboratory biaxial shear experiments. The predictions are made with a deep learning model based on convolutional encoder-decoder (CED) models and the Transformer model primarily developed for Natural Language Processing (NLP). The deep learning model is trained with the tensorflow package using publicly available laboratory data sets in standard binary file format in numpy. The utility functions for reading data files, configuring model hyperparameters, constructing the CED and Transformer models, training and testing of the models are defined in python module files. The workflow of training the models for labquake future predictions and the multiple GPU’s rapid model hyperparameter optimization as described in the journal article, are demonstrated in accompanying python script files and Jupyter notebooks.

Wang, Kun↗

DOE OSTI2024

NORTH DAKOTA CARBONSAFE PHASE III: SITE CHARACTERIZATION AND PERMITTING OF GEOLOGIC STORAGE OF CARBON DIOXIDE

The Energy & Environmental Research Center (EERC), in partnership with Minnkota Power Cooperative Inc. (Minnkota), SLB, and Computer Modelling Group Ltd. (CMG), supported wide-scale deployment of carbon capture and storage (CCS) as part of the U.S. Department of Energy (DOE) National Energy Technology Laboratory Carbon Storage Assurance Facility Enterprise (CarbonSAFE) Initiative Phase III. This phase included the acquisition, analysis, and development of information to fully characterize two storage complexes to demonstrate viable storage resources for commercial volumes of CO2 (defined by DOE as a minimum of 50 million tonnes [MMt] of CO2 within a 30-year period) (National Energy Technology Laboratory, 2024). Phase III also involved the preparation, submission, and approval of North Dakota underground injection control (UIC) Class VI storage facility permits (SFPs)—required precursors to applications for Class VI injection well permits. The presumed viability of commercial-scale CCS, situated adjacent to Minnkota’s Milton R. Young Station (MRYS), is validated by Minnkota’s continued pursuit of Project Tundra—an initiative to build the world’s largest lignite-based CCS project in central North Dakota (www.projecttundrand.com). Project Tundra comprises two scopes of work, Tundra Capture (installation of postcombustion CO2 capture at MRYS) and Tundra SGS (secure geologic storage). The efforts of North Dakota CarbonSAFE Phase III, Site Characterization and Permitting, supported Tundra SGS. Extensive site-specific characterization activities included a successful multimeasurement geophysical approach and drilling a stratigraphic test well (J-ROC 1, subsequently renamed Liberty-1) adjacent to MRYS. Core collection and analyses, downhole testing and fluid sampling, and geophysical logging were performed on J-ROC 1 and on a nearby stratigraphic test well (known as J-LOC 1), which was drilled, cored, and tested under a complementary project funded by the North Dakota Lignite Research Program. The injection tests performed on J-LOC 1 positively impacted the CarbonSAFE project, resulting in fewer proposed injection wells and significant construction, operations, and monitoring cost savings. The characterization data collected and analyses performed were integrated into geologic models, and successive numerical simulations were run to determine CO2 plume extent and subsurface pressure buildup associated with the planned CO2 injection rate of nearly 4 MMt per year. The latter doubles the CarbonSAFE Initiative goal with an estimated 100 MMt of CO2 stored in 20 years. Application of the U.S. Environmental Protection Agency’s (EPA’s) method for estimating the Class VI Rule area of review (AOR) to the overpressurized Broom Creek Formation inspired an alternative method of calculation, called risk-based AOR delineation. This peer-reviewed method was applied for the first time during the storage facility-permitting process. The two SFP applications submitted in 2021 successfully resulted in North Dakota Industrial Commission (NDIC) orders in 2022 authorizing the creation of the storage facility areas and amalgamation of pore space as well as establishing financial responsibility requirements. After approval of the SFPs, Minnkota filed in 2022 applications for permits to reenter the J-ROC 1 well and to drill two new wells—all with the intended purpose to become Class VI injection wells. To establish eligibility under the Internal Revenue Code for Section 45Q tax incentives, a monitoring, reporting, and verification (MRV) plan was prepared and submitted by Minnkota to EPA in 2022, resulting in the first such plan approved in North Dakota. Also in 2022, under the National Environmental Policy Act (NEPA), Minnkota prepared and submitted an environmental information volume (EIV) describing the proposed CCS project and associated potential environmental impacts. Based on the EIV, DOE determined that the proposed construction project required an environmental assessment, and Minnkota submitted the first draft in 2023 and a revised draft in 2024. Both submissions were followed by a public comment period. Subsequently, DOE issued a finding of no significant impact (FONSI) on September 13, 2024. A successful outreach program, strongly based in the production, presentation, and dissemination of informational material, fostered an environment to aid stakeholders in making informed decisions regarding the planned project. Opportunities for public input were provided at various steps along the way, including at county planning and zoning meetings, before and during the SFP administrative hearing, and during environmental assessment public comment periods. In addition, land/pore space owners and mineral owners had various points of contact, including granting access rights, securing pore space leasing, and mineral owner notifications. Based upon the successful storage facility permitting issued by NDIC, approval of the MRV plan by EPA, and receipt of a FONSI under the NEPA, Minnkota is continuing its pursuit of Project Tundra. In December 2023, the Office of Clean Energy Demonstrations under its Carbon Capture Demonstrations Projects Program announced funding for the capture system (Office of Clean Energy Demonstrations, 2023) and a proposal for CarbonSAFE Phase IV: Construction funding was submitted in March 2024 for the storage project. A go/no-go decision to proceed with construction and operations in the Broom Creek Formation is anticipated in 2024. References National Energy Technology Laboratory, CarbonSafe Initiative, https://netl.doe.gov/carbon-management/carbon-storage/carbonsafe (accessed August 2024). Office of Clean Energy Demonstrations, 2023, OCED selects three projects in CA, ND, and TX to reduce harmful carbon pollution, create new economic opportunities, and advance carbon reducing technologies, December, www.energy.gov/oced/articles/oced-selects-three-projects-ca-nd-and-tx-reduce-harmful-carbon-pollution-create-new (accessed August 2024).

Peck, Wesley↗

DOE OSTI2022

EGS Collab Experiment 2: Continuous Broadband Seismic Waveform Data

Two broadband seismometers were installed on the 4100 level and recorded for the duration of EGS Collab Experiment #2. Inspired by published data from similar instruments installed in the Aspo Hard Rock Lab, these long-period instruments aimed to measure the tilting of the drift in response to the injection of fluid into the testbed. One instrument was installed underneath the wellheads in Site A (aka the "battery" alcove) and the other was installed along the east wall of the drift, south of Site B. Due to the feet of gravel (ballast) laid along the floor of the drift, we were unable to anchor the sensors directly to the rock. As a result, the coupling of the sensors to the experiment rock volume is likely poor. In addition, there are a number of noise sources that complicate the interpretation of the data. For example, sensor BBB is installed adjacent (within 3 ft) to the rail line that runs towards the Ross shaft. Trains (motors) run along this line almost daily and produce a large signal in these data. Careful extraction of periods of interest, as well as filtering for specific signals, is necessary. The sensors are Nanometrics Trillium Compact Posthole seismometers, sensitive down to 120 seconds period. They were installed as close to the drift wall and as deep as we could manually excavate (only about 1 ft or so). The holes were leveled with sand and the sensors were placed on a paver before backfilling with sand. The hole was then covered by a bucket filled with insulation to improve the sensor's isolation from daily temperature variations, which are minor but present due to drift ventilation from the surface. Data were recorded on Nanometrics Centaur digitizers at 100 Hz. The full response information is available in the StationXML file provided here, or by querying the sensors through the IRIS DMC (see links below). These instruments were provided free of charge through the IRIS PASSCAL instrument center. The network code is XP and the station codes are BBA and BBB. The waveform data can be queried through the IRIS FDSN server using any method the user likes. One convenient option is to use the Obspy python package: https://docs.obspy.org/packages/obspy.clients.fdsn.html

15 GEOTHERMAL ENERGY↗

DOE OSTI2021

Computed Tomography Scanning and Geophysical Measurements of the Wabash No.1 Core

The computed tomography (CT) facilities and the Multi-Sensor Core Logger (MSCL) at the National Energy Technology Laboratory (NETL) in Morgantown, West Virginia were used to characterize Mt. Simon core from the Wabash CarbonSAFE project, Wabash No. 1 well. The primary impetus of the work in this report is a collaboration between NETL Research and Innovation Center and the Illinois State Geological Survey at the Prairie Research Institute, University of Illinois Urbana-Champaign in Champaign, Illinois. The resultant datasets are presented in this report and can be accessed from NETL's Energy Data eXchange (EDX) online system using the following link: https://edx.netl.doe.gov/dataset/wabash-no-1-well. The Wabash No. 1 well was drilled as part of a U.S. Department of Energy (DOE) funded Carbon Storage Assurance Facility Enterprise field project to assess the feasibility of developing a commercial-scale geological storage complex at the Wabash Valley Resources Integrated Gasification Combined Cycle plant near Terre Haute, Indiana. All equipment and techniques used were non-destructive, enabling future examinations and analyses to be performed on these cores. None of the equipment used was suitable for direct visualization of the pore space in fine-grained structures; fractures, discontinuities, and millimeter scale features were readily detectable with the methods tested. Imaging with the NETL medical CT scanner was performed on the entire core. Qualitative analysis of the medical CT images, coupled with X-ray fluorescence (XRF), P-wave, and magnetic susceptibility measurements from the MSCL were useful in identifying zones of interest for more detailed analysis. The ability to quickly identify key areas for more detailed study with higher resolution will save time and resources in future studies. The combination of methods used provides a multi-scale analysis of the core; the resulting macro and micro descriptions are relevant to many subsurface energy-related examinations traditionally performed at NETL.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Probabilistic neural networks for fluid flow surrogate modeling and data recovery

We consider the use of probabilistic neural networks for fluid flow surrogate modeling and data recovery. This framework is constructed by assuming that the target variables are sampled from a Gaussian distribution conditioned on the inputs. Consequently, the overall formulation sets up a procedure to predict the hyperparameters of this distribution which are then used to compute an objective function given training data. We demonstrate that this framework has the ability to provide for prediction confidence intervals based on the assumption of a probabilistic posterior, given an appropriate model architecture and adequate training data. The applicability of the present framework to cases with noisy measurements and limited observations is also assessed. To demonstrate the capabilities of this framework, we consider canonical regression problems of fluid dynamics from the viewpoint of reduced-order modeling and spatial data recovery for four canonical data sets. The examples considered in this study arise from (i) the shallow-water equations, (ii) a two-dimensional cylinder flow, (iii) the wake of a NACA0012 airfoil with a Gurney flap, and (iv) the NOAA sea surface temperature data set. Furthermore, the present results indicate that the probabilistic neural network not only produces a machine-learning-based fluid flow surrogate model but also systematically quantifies the uncertainty therein to assist with model interpretability.

42 ENGINEERING↗

DOE OSTI2025

Long-Term Evaluation of Remedial Technology Performance in the Laboratory: Multi-year Experimental Test Plan

An understanding of the long-term effectiveness of remediation technologies is central to sustainable environmental cleanup. Long-term experiments are valuable for reducing uncertainty and predicting remediation outcomes at scales required for regulatory compliance. However, these types of tests can be costly and challenging to interpret. Therefore, contaminated sites often rely on short-term laboratory experiments that may not account for the potentially significant effects of gradual, time- dependent processes governing contaminant retention, release, and species transformation. For example, short-term lab experiments (from months to a year) conducted with sediments from the unsaturated and saturated zones at the Hanford Site play an important role in initial evaluations of remediation technologies but cannot capture the full extent of time-dependent reactions, leaving uncertainties in field-scale deployment. Here, long-term testing will be conducted on select technologies based on their performance in short-term testing. The overall objective is to directly address the challenges described above by generating and analyzing data on long-term (2–10 years) efficacy of selected remediation technologies, integrating this understanding into models, and providing critical input for remediation planning, monitoring, and 5-year review cycles for field-implemented remedies. Specific objectives include: 1. Evaluating long-term efficiency of promising remedies under site-specific conditions. 2. Generating robust parameters for modeling, reducing uncertainty in predictive simulations. 3. Advancing integrated monitoring by combining geochemical and geophysical observations. 4. Informing field-scale implementation by incrementally advancing technologies, identifying failure mechanisms early, and prioritizing robust, cost-effective remedies. Through systematic evaluation of technologies in laboratory-scale column experiments, integrated monitoring, and modeling support, this project is designed to bolster confidence in the long-term robustness of selected technologies. The ultimate outcome is the identification and deployment of more reliable, cost-effective remedies that safeguard human health and the environment while reducing the uncertainties that have historically hindered cleanup progress at Hanford Site. An experimental approach was developed and initiated for long-term testing potentially up to 10 years. The table below summarizes the experimental approach developed for testing select technologies and presented in this multi-year experimental test plan.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Utah FORGE 3-2417: Fiber-Optic Geophysical Monitoring of Reservoir Evolution - Workshop Presentation

This is a presentation on the Fiber-Optic Geophysical Monitoring of Reservoir Evolution at the Utah FORGE Milford Site project by Rice University, presented by Prof. Jonathan Ajo-Franklin. The project's objective was to develop an end-to-end fiber-optic sensing approach for EGS to track the initial zone of fracture creation, zones of connected mechanically compliant fractures, and zones of flowing fractures linking the injection/production well pair. This approach would also be used to integrate data into an improved thermo-hydro-mechanical model (THM). This presentation was featured in the Utah FORGE R&D Annual Workshop on September 8, 2023. The workshop provided a valuable opportunity to explore the progress made in each of the 17 Research and Development projects funded under Solicitation 2020-1 which aim to enhance our understanding of the crucial factors influencing the development of Enhanced Geothermal Systems (EGS) reservoirs and resources.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

Identifying atmospheric rivers and their poleward latent heat transport with generalizable neural networks: ARCNNv1

Abstract. Atmospheric rivers (ARs) are extreme weather events that can alleviate drought or cause billions of US dollars in flood damage. By transporting significant amounts of latent energy towards the poles, they are crucial to maintaining the climate system's energy balance. Since there is no first-principle definition of an AR grounded in geophysical fluid mechanics, AR identification is currently performed by a multitude of expert-defined, threshold-based algorithms. The variety of AR detection algorithms has introduced uncertainty into the study of ARs, and the thresholds of the algorithms may not generalize to new climate datasets and resolutions. We train convolutional neural networks (CNNs) to detect ARs while representing this uncertainty; we name these models ARCNNs. To detect ARs without requiring new labeled data and labor-intensive AR detection campaigns, we present a semi-supervised learning framework based on image style transfer. This framework generalizes ARCNNs across climate datasets and input fields. Using idealized and realistic numerical models, together with observations, we assess the performance of the ARCNNs. We test the ARCNNs in an idealized simulation of a shallow-water fluid in which nearly all the tracer transport can be attributed to AR-like filamentary structures. In reanalysis and a high-resolution climate model, we use ARCNNs to calculate the contribution of ARs to meridional latent heat transport, and we demonstrate that this quantity varies considerably due to AR detection uncertainty.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Utah FORGE Seismic Stations and Wells GPS Survey Data, 2021

This is a CSV spreadsheet containing UTM and Latitude and Longitude coordinates and elevations for Wells 78-32, 58-32, and 16A(78)-32 and BOR1, BOR2, BOR3, FOR2, FOR5, FORK, FORU, and FORW seismic stations. These are from a GPS survey conducted by the Utah Geological Survey in June, 2021.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Exploratory analysis of machine learning techniques in the Nevada geothermal play fairway analysis

Play fairway analysis (PFA) is commonly used to generate geothermal potential maps and guide exploration studies, with a particular focus on locating and characterizing blind geothermal systems. This study evaluates the application of machine learning techniques to PFA in the Great Basin region of Nevada. Following the evaluation of various techniques, we identified two approaches to PFA that produced promising results, 1) supervised Bayesian probabilistic neural networks to generate geothermal potential maps with confidence intervals, and 2) unsupervised principal component analysis paired with k-means clustering to generate both cluster maps to help identify spatial patterns, as well as new combined feature inputs. We applied these techniques to perform a comparative analysis between two principal sets of geological and geophysical features related to permeability and heat and a set of positive (known geothermal resources) and negative training sites (known drill sites with unsuitable geothermal conditions). We found that these methods constrain previously unrecognized feature controls on geothermal favorability, many of which are spatially organized within the extent of cluster groups and the major structural-hydrologic domains of the study area. Furthermore, we utilized exploratory unsupervised modeling to highlight spatial relationships between input data and predictive output results of our supervised modeling. As a result, we demonstrate how our models compare to the previous Nevada PFA and how the rapid insights these machine learning techniques offer may support future assessments of both known and undiscovered blind geothermal systems in the Great Basin region of Nevada and beyond.

15 GEOTHERMAL ENERGY↗

DOE OSTI2024

An assessment of controlled source EM for monitoring subsurface CO 2 injection at the wyoming carbonSAFE geologic carbon storage site

Here we evaluate if electromagnetic (EM) geophysical methods for monitoring geologic carbon storage (GCS) efforts at the Wyoming CarbonSAFE project adjacent to the Dry Fork Station power plant near Gillette, Wyoming. This first involved acquiring both electric and magnetic fields at eleven different locations ranging in distance from immediately adjacent to 4 km from the plant. Passive EM measurements were made to provide spectral EM noise measurements generated by electricity production at the plant and to determine if useful magnetotelluric (MT) data can be successfully collected in the region. The processed data indicate that useful MT data can be collected as long as the site is located more than 2km away from the power plant as well as active roads and rail lines. Controlled source EM data were collected using three different source configurations, two of which connected to steel casings used to complete the injection wells. Comparing the EM noise measurements to the CSEM data show measurable electric and magnetic field signals at all sites. Next a series of three-dimensional (3D) numerical models were built that simulate resistivity changes caused by the proposed CO2 injection at depths ranging from 2.4 to 3.0km. These models were used to simulate various EM measurement configurations. The modeling shows that casing-source CSEM monitoring can provide sensitivity to the injected CO 2 if source electrodes are connected to the bottom of one or both of the injection wells.

58 GEOSCIENCES↗