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All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Mechanisms for Microseismicity Occurrence Due to CO 2 Injection at Decatur, Illinois: A Coupled Multiphase Flow and Geomechanics Perspective

Here, we numerically investigate the mechanisms that resulted in induced seismicity occurrence associated with CO 2 injection at the Illinois Basin–Decatur Project (IBDP). We build a geologically consistent model that honors key stratigraphic horizons and 3D fault surfaces interpreted using surface seismic data and microseismicity locations. We populate our model with reservoir and geomechanical properties estimated using well-log and core data. We then performed coupled multiphase flow and geomechanics modeling to investigate the impact of CO 2 injection on fault stability using the Coulomb failure criteria. We calibrate our flow model using measured reservoir pressure during the CO 2 injection phase. Our model results show that pore-pressure diffusion along faults connecting the injection interval to the basement is essential to explain the destabilization of the regions where microseismicity occurred, and that poroelastic stresses alone would result in stabilization of those regions. Slip tendency analysis indicates that, due to their orientations with respect to the maximum horizontal stress direction, the faults where the microseismicity occurred were very close to failure prior to injection. These model results highlight the importance of accurate subsurface fault characterization for CO 2 sequestration operations.

58 GEOSCIENCES↗
DOE OSTI2020

Microseismic Event Denoising: Removal of Borehole Waves

The vertical borehole array at Farnsworth Unit, TX is used to monitor microseismic activity in the subsurface around the Carbon Capture and Sequestration (CCS) reservoir. The array consists of 16 3-component seismometers spaced vertically in a single borehole. Tube or borehole waves traveling up or down the borehole can corrupt signals of interest, such as microseismic events. A denoising convolutional neural network (DCNN) was trained to remove borehole waves from seismic waveforms of microseismic events for the purpose of reducing unwanted signal detections and better characterizing events of interest. This R&D leverages the work of Sandia colleague Rigo Tibi, who used a DCNN developed by Greg Beroza at Stanford University to improve the signal-to-noise ratio (SNR) of teleseismic events detected by the International Monitoring System.

58 GEOSCIENCES↗
DOE OSTI2023

A case study of denoising microseismic data in the Farnsworth, TX CO 2 EOR site

As geologic carbon sequestration projects begin to be funded with a higher degree of frequency, microseismic monitoring will become more necessary to establish caprock integrity and induced seismicity risk. The Farnsworth, TX site, which hosts enhanced oil recovery operations, provides an ideal laboratory to test essential components of microseismic monitoring such as surface station placement, denoising, and different autopicker methods. We find that despite careful optimization, the surface station placement at the Farnsworth site was insufficient given the high level of background noise from the industrial operations at the oil field. Thus, we use only borehole geophone data in our processing. Two denoising techniques were examined: the DeepDenoiser and the continuous wavelet transform. The continuous wavelet transform was shown to be a valuable tool in converting between raw waveforms to processed denoised waveforms for microseismic monitoring. In the case of the noisy waveforms, only ten detections are found, compared with 90 in the denoised data for a two-hour window. The DeepDenoiser suffered from the fact that the training data was regional earthquake data. In addition, the PhaseNet machine-learning autopicker was applied to both the noisy and the denoised data, and this algorithm detected thousands of more arrivals in the data denoised with the continuous wavelet transform technique.

58 GEOSCIENCES↗
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 OSTI2021

A Frequency-Domain-Based Algorithm for Detecting Microseismicity Using Dense Surface Seismic Arrays

We propose a new frequency-domain-based algorithm for detecting small-magnitude seismic events using dense surface seismic arrays. Our proposed method takes advantage of the high energy carried by S waves, and approximate known source locations, which are used to rotate the horizontal components to obtain the maximum amplitude. By surrounding the known source area with surface geophones, we achieve a favorable geometry for locating the detected seismic events with the backprojection method. To test our new detection method, we used a dense circular array, consisting of 151 5 Hz three-component geophones, over a 5 km aperture that was in operation at the Utah Frontier Observatory for Research in Geothermal Energy (FORGE) in southcentral Utah. We apply the new detection method during a small-scale test injection phase at FORGE, and during an aftershock sequence of an Mw 4.1 earthquake located ~30 km north of the geophone array, within the Black Rock volcanic field. We are able to detect and locate microseismic events (Mw<0) during injections, despite the high level of anthropogenic activity, and several aftershocks that are missing from the regional catalog. By comparing our method with known algorithms that operate both in the time and frequency domain, we show that our proposed method performs better in the case of the FORGE injection monitoring, and equally well for the off-array aftershock sequence. Our new method has the potential to improve microseismic event detections even in extremely noisy environments, and the proposed location scheme serves as a direct discriminant between true and false detections.

Geochemistry & Geophysics↗
DOE OSTI2024

Seismic Monitoring near Ithaca, New York, Reveals Nonuniform Distribution of Microseismicity in an Intraplate Region

Abstract Cornell University intends to use a deep direct-use geothermal system to heat its Ithaca, New York, campus. In preparation for this project, the Cornell Seismic Network has been monitoring the background seismicity in this intraplate region since 2019. From January 2020 to June 2023, 95 events were detected within 20 km of the proposed geothermal well site, with local magnitudes ranging from −1.02 to 0.56. None of these events appear in regional or national catalogs. Events locate in a narrow geographic band, with one-fourth exhibiting multimodal hypocentral probability peaks both near the surface and at 1–4 km depth. We relocate events with a joint hypocenter and 1D velocity model inversion, in addition to a fully nonlinear method, and then compare observations with synthetic waveforms. Together, these approaches provide strong evidence for >95% of events locating at the surface or within the 3-km-thick sedimentary sequence. We explore how anthropogenic activity and regional topographic stress may contribute to frequent surficial events. This information is critical for characterizing the background microseismicity for comparison during future geothermal operations. Ithaca’s geology of Paleozoic sediments overlying Precambrian crystalline basement is typical of many continental interiors, so these results also provide insight into intraplate microseismicity patterns.

Geochemistry & Geophysics↗
DOE OSTI2020

Interpretation of Hydraulic Fractures Based on Microseismic Response in the Marcellus Shale, Monongalia County, West Virginia, USA: Implications for Shale Gas Production

Summary Hydraulic fracturing is critical for extracting shale gas in the subsurface. The treatment technique of multistage hydraulic fracturing is widely used to maximize production. In multistage hydraulic fracturing, not all pumping stages make the same contribution for production, although the designed stimulation process is almost same in every pumping stage. In this study, we characterize the microseismic responses of hydraulic fracturing. Significant variations of microseismic characteristics are observed among the different pumping stages. Pre-existing natural fractures are examined along the horizontal well in selected stages. Combined with the Mohr’s circle analysis, results of the fracture study show that induced hydraulic fractures can be captured by pre-existing natural fractures. Induced hydraulic fractures are simulated by the unconventional fracture model (UFM), and the result reveals that the stress-shadow effect diverts the direction of hydraulic fractures. The diverted hydraulic fracture affects the development of the hydraulic fracture network, which has influence on production. The treatment of two-step pumping is investigated by application of hydraulic diffusivity. Hydraulic fracturing performance and production could be optimized by the treatment of two-step pumping in a single stage. The second pumping creates new fractures and fills the fractures with additional proppants to maintain production for a long duration.

Energy & Fuels↗
DOE OSTI2025

Quantitative Assessment of Parent Well Effect on Hydraulic Fracture Propagation at HFTS2: Insights from Cross-Well Strain Measurements and Microseismic Data

Understanding fracture propagation behavior is essential for optimizing hydraulic fracturing in unconventional reservoirs. This study demonstrates the value of integrating Low-Frequency Distributed Acoustic Sensing (LF-DAS) and microseismic data, which together provide a more complete picture of fracture growth. Using data from Hydraulic Fracturing Test Site 2 (HFTS2), we identify stress changes in depletion zones induced by parent wells as a key factor influencing fracture propagation. This result is shown by new measurements of in-situ fracture propagation velocity and fracture-hit volume (fluid volume at fracture hit?) from LF-DAS and event density from microseismic. These findings highlight the importance of considering parent well effects, well spacing, and stimulation sequencing in completion design to improve reservoir development and production efficiency.

depletion zones↗
DOE OSTI2021

Close Observation of Hydraulic Fracturing at EGS Collab Experiment 1: Fracture Trajectory, Microseismic Interpretations, and the Role of Natural Fractures

Abstract Despite the wide application of hydraulic fracturing in enhanced geothermal system (EGS) development and unconventional hydrocarbon production, our understanding of the many factors affecting the propagation of hydraulic fractures has relied on circumstantial evidence. This is partly due to the scarcity of direct observations in the subsurface. The EGS Collab project attempts to address these issues in the context of EGS research by performing intermediate‐scale (∼10 m) hydraulic stimulation experiments in a thoroughly characterized and heavily instrumented underground testbed. This paper analyzes the data collected from the first suite of hydraulic fracturing tests in this testbed, consisting of seven stimulation episodes. High‐quality microseismic data delineate five planar features very clearly. Combining fracture‐wellbore intersection observations from distributed temperature sensing (DTS) and visual observations from an open‐hole well, as well as prior in‐situ stress measurements, we conclude with high certainty that the four larger planes were hydraulic fractures. The growth of the hydraulic fractures was temporarily halted by a prominent, open natural fracture in the testbed but they eventually crossed and slightly reoriented under continued stimulation. Mineral‐filled (i.e., healed) natural fractures, though prevalent in the testbed, did not have perceivable effects on hydraulic fracture propagation. The high‐quality, mutually corroborating data sets allowed conclusions to be drawn with high confidence and attests to the advantage of intermediate‐scale experiments in subsurface research.

58 GEOSCIENCES↗
DOE OSTI2024

EGS Collab Experiment 2: Microseismic Monitoring

This dataset contains continuous seismic waveform data recorded during stimulation and thermal circulation tests for the Enhanced Geothermal Systems (EGS) Collab Experiment #2, conducted from February to September 2022 at the Sanford Underground Research Facility in Lead, South Dakota. This experiment aimed to study and validate models of geothermal systems by injecting high-pressure fluids into rock formations 1200-1500 meters below the surface, inducing microseismic events. The seismic monitoring system included 16 three-component accelerometers and a 24-channel hydrophone array, installed in boreholes surrounding the test area. Data were recorded at high sampling rates using a continuous waveform recording system to monitor seismic activity in real time. The dataset contains the raw data stored in binary format, with files named based on timestamps, and includes calibration certificates for some sensors to facilitate corrections to real units. Users are strongly advised to consult the accompanying detailed report, which outlines the experimental setup, sensor specifications, installation procedures, and data processing methods. The report also describes important nuances, such as the hardware filters on hydrophones, sensor calibration details, and the naming conventions for the recorded data. Proper use of this dataset may require familiarity with seismic data analysis tools, such as the Obspy Python package, and an understanding of the SEED naming conventions used for channel identification.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Enhanced Microseismicity During Production Pumping Cessation at the San Emidio Geothermal Field (Nevada, USA) in December 2016

Abstract Tectonic activity, geothermal fluids, and microseismic events (MSEs) tend to occur in similar locations as a result of spatiotemporal changes in the subsurface stress state. To quantify this association, we analyze data from a dense seismic array deployed at the San Emidio geothermal field, Nevada for 1 week in December 2016 to coincide with a 19.45‐hr shutdown of all injection and production pumping operations. 123 MSEs were detected, of which 101 occurred during the shutdown. The spatial association of the MSEs with the production wells suggests a causal relationship between the production cessation and the MSEs. Here we performed a detailed analysis to investigate reservoir material properties, distribution of seismically activated faults, and local stress state. We determined the hypocenters, magnitudes, and focal mechanisms for the MSEs, P‐wave tomographic velocity model, and local stress tensor. The results show that most MSEs occurred near the production wells. Magnitudes fall between −2.2 and 0.0 with larger events located closer to the production wells. Most MSEs occurred within a westward‐dipping normal fault zone in the reservoir associated with anomalously low P‐wave velocity values. The focal mechanism and stress inversion results show predominantly normal faulting with the maximum horizontal stress oriented north‐south. We suggest that the MSEs during shutdown were triggered on pre‐existing, small‐scale, critically stressed fault patches in the reservoir as the pore pressure increased around the production wells when the production pumping ceased. We interpret the larger MSE magnitudes closer to the production wells as a result of higher pore pressure increase.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE Project 3-2417: DAS Microseismic Event Catalog from the 16A/16B Circulation Test, 2023

This preliminary data archive includes the relocated microseismic event catalog, 1D velocity model, and methods report from DAS acquisition conducted during the Well 16A and 16B circulation test (July 19th and 20th, 2023) at Utah FORGE. The methods report describes all processing steps, including real-time event detection, hierarchical clustering, joint velocity/hypocenter inversion, and relocation. The resulting work is accepted and will be presented at IMAGE 2024. This dataset was acquired by the FOGMORE R&D project (Fiber Optic MOnitoring for Reservoir Evolution), Utah FORGE R&D Project 3-2417.

15 GEOTHERMAL ENERGY↗
DOE OSTI2024

Utah FORGE: Well 16A(78)-32 Hydraulic Fracturing Stage 8 Crosswell Strain FDI and Microseismic Presentations - April 2024

This is a pair of PowerPoint presentations from Neubrex Energy Services (US), LLC. The presentations review work done in April 2024 on crosswell strain fracture driven interactions (FDI) and microseismic event monitoring during hydraulic fracturing in stage 8 of Utah FORGE well 16A(78)-32. Well 16B(78)-32 was the monitoring well and was where the data for these presentations were collected.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Microseismic Monitoring of Laboratory Hydraulic Fracturing Experiments in Granitic Rocks for Different Fracture Propagation Regimes

While hydraulic fracturing (HF) is a widely employed process, the underlying fracturing processes are still heavily contested. The attributes of the HF generated fracture network can exhibit substantial variation when dealing with specific HF propagation regimes encountered in the field. In this study, HF experiments were performed on true-triaxially loaded Barre granite cubes, with microseismic monitoring, to identify and characterize the fracturing mechanisms associated with different viscosity injection fluids. Utilizing fluids with high (oil/1450 cP) and low (water/1 cP) viscosity represented two key HF propagation regimes: viscosity- and toughness-dominated. The experiments conducted with oil involved higher breakdown pressures, larger fluid volumes, and slower fracture propagation speeds. Furthermore, the frequency–magnitude distribution (b value) for all experiments (1.9–2.3) was similar to those encountered for large-scale operations. Slightly larger b values were encountered during the initiation phase (2.4–2.7) relative to the fracture propagation and post-fracturing phases (1.9–2.2). Techniques such as polarity and moment-tensor inversion were utilized to characterize the source mechanisms. For the HF experiments with oil, tensile fractures were most dominant (92%) in the initiation phase compared to fracture propagation and post-fracturing phases (70–75%). Similar tensile fracturing dominancy was not observed with water, attributable to fluid permeation and leak-off. Regardless of the injection fluid or classification criteria employed, tensile fractures were the dominant type consistently, with fewer occurring in water experiments but the specific ratio of crack types varied with different source mechanism criteria employed.

58 GEOSCIENCES↗
DOE OSTI2024

DASEventNet: AI‐Based Microseismic Detection on Distributed Acoustic Sensing Data From the Utah FORGE Well 16A (78)‐32 Hydraulic Stimulation

Abstract Distributed acoustic sensing (DAS) has emerged as a promising seismic technology for monitoring microearthquakes (MEQs) with high spatial resolution. Efficient algorithms are needed for processing large DAS data volumes. This study introduces a deep learning (DL) model based on a Residual Convolutional Neural Network (ResNet) for detecting MEQs using DAS data, named as DASEventNet. The test data were collected from the Utah FORGE 16A (78)‐32 hydraulic stimulation experiments conducted in April 2022. The DASEventNet model achieves a remarkable accuracy of 100% when discriminating MEQs from noise in the raw test set of 260 examples. Surprisingly, the model identified weak MEQ signatures that have been manually categorized as noise. The decision‐making process with the model is decoded by the classic activation map, which illuminates learning features of the DASEventNet model. These features provide clear illustrations of weak MEQs and varied noise types. Finally, we apply the trained model to the entire period (∼7 days) of continuous DAS recordings and find that it discovers >5,700 new MEQs, previously unregistered in the public Silixa DAS catalog. The DASEventNet model significantly outperforms the traditional seismic method Short‐Term Average/Long‐Term Average (STA/LTA), which detected only 1,307 MEQs. The DASEventNet detection threshold is M w −1.80 compared to the minimum magnitude of M w −1.14 detected by STA/LTA. The spatiotemporal distribution of the newly identified MEQs defines an extensive stimulation zone and more accurately characterizes fracture geometry. Our results highlight the potential of DL for long‐term, real‐time microseismic monitoring that can improve enhanced geothermal systems and other activities that include subsurface hydraulic fracturing.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Stratigraphy‐Induced Localization of Microseismicity During CO 2 Injection in Illinois Basin

Abstract Subsurface fluid injection stimulates complex hydromechanical interaction, necessitating the integration of geomechanical data across spatial and temporal scales to consider the sophisticated behavior. Induced seismic response is usually associated with the complex reservoir architecture and pre‐existing features that are three‐dimensional, such as local stratigraphy, fractures, faults, and other discontinuities. This study encompasses laboratory characterization of the coupled hydromechanical response of cores extracted from rock formations in Illinois Basin: reservoir ‐ Mt. Simon sandstone, basal seal ‐ Argenta sandstone, and crystalline basement ‐ Precambrian rhyolite. High‐resolution numerical modeling allows considering the three‐dimensional complexity of the Illinois Basin Decatur Project with spatial resolution comparable to one of the active seismic surveys. A detailed reconstruction of the evolving state of stress in formations lacking direct stress measurements is achieved by numerical modeling that integrated laboratory‐derived hydromechanical properties, a porosity‐permeability relationship, active seismic data, and an inverted three‐dimensional porosity distribution. It appears that the microseismic clusters, mainly observed in the crystalline basement during the injection, are linked to zones experiencing more critically stressed conditions prior to injection. These zones have a potential for reactivation during the injection and are attributed to the specific local stratigraphy of the injection site, as well as transfer of triggering perturbations during the injection.

Bondarenko, N. [University of Illinois Urbana‐Cham↗