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At least 289 records · Page 16

Explosion Discrimination Using Seismic Gradiometry and Spectral Filtering of Data

Here, we present a new method to discriminate between earthquakes and buried explosions using observed seismic data. The method is different from previous seismic discrimination algorithms in two main ways. First, we use seismic spatial gradients, as well as the wave attributes estimated from them (referred to as gradiometric attributes), rather than the conventional three-component seismograms recorded on a distributed array. The primary advantage of this is that a gradiometer is only a fraction of a wavelength in aperture compared with a conventional seismic array or network. Second, we use the gradiometric attributes as input data into a machine learning algorithm. The resulting discrimination algorithm uses the norms of truncated principal components obtained from the gradiometric data to distinguish the two classes of seismic events. Using high-fidelity synthetic data, we show that the data and gradiometric attributes recorded by a single seismic gradiometer performs as well as a conventional distributed array at the event type discrimination task.

58 GEOSCIENCES↗

Relocation of the Seismicity of the Caucasus Region

Our objective is to improve the view of the seismicity in the Caucasus region using instrumental data between 1951 and 2019. To create a comprehensive catalog, we combine the bulletins of local agencies and the International Seismological Centre, and use an advanced single-event location algorithm, iLoc, to obtain better locations. We show that relocations with iLoc, using travel-time predictions from the 3D upper mantle velocity model, Regional Seismic Travel Time, improve the locations. Then, using the iLoc results as initial locations and the ground-truth events identified in the iLoc results as fix points, we apply Bayesloc, a multiple-event location algorithm, to simultaneously relocate the entire seismicity of the Caucasus region. Here we demonstrate that the simultaneous relocation of the seismicity with Bayesloc clarifies the location and geometry of major active structures accommodating ongoing convergence between the Arabian and Eurasian continents between the Black and Caspian Seas. Among our major findings is the confirmation of widespread seismicity in the mantle beneath the northern flank of the Greater Caucasus and central Caspian, resulting from north-dipping subduction of the Kura and South Caspian basins and the identification of a discrete band of crustal seismicity beneath the southern flank of the Greater Caucasus.

58 GEOSCIENCES↗

Multiwell Fiber Optic Sensing Reveals Effects of CO2 Flow on Triggered Seismicity

Induced seismicity is one of the main risks for gigaton-scale geological storage of carbon dioxide (⁠CO 2 ⁠). Thus, passive seismic monitoring is often recommended as a necessary component of the monitoring systems for CO 2 storage projects, with a particular forcus on risk mitigation. We present the first field study, CO2CRC Otway Project Stage 3 (Victoria, Australia), where distributed acoustic sensing (DAS) enabled high-precision tracking of the induced seismicity triggered by a small CO 2 injection and also informed the reservoir models. In 610 days of passive seismic monitoring of the Stage 3 injection, we detected 17 microseismic events (maximum moment magnitude Mw 0.1) using five deep boreholes equipped with enhanced-sensitivity optical fiber. The DAS array has sensitivity sufficient for detection and location of induced events with M w ~ ₋2 in a monitoring borehole located up to 1500 m away. Thanks to the dense spatial sampling by the DAS, we were able to estimate the focal mechanisms for events with M w > ₋1.5; although the monitoring boreholes provided very limited angular coverage. The main cluster of the events has the same location and source mechanism as the one triggered by the previous CO 2 injection at the Otway Project site, Stage 2C. Surprizingly, the Stage 2C and Stage 3 events closely followed the actual movement of the CO 2 saturation plume front (not the pressure front), as observed using controlled-source reflection seismic images. The nature of the plume-fault interaction remains unclear, but some alteration of the fault gouge by CO 2 might be responsible for the faults’ reactivation by the pressure perturbation. Importantly, the seismogenic fault could not be identified in the seismic images and was only revealed by DAS observations, which also demonstrated the signature of fluid–rock interaction, that may control the CO 2 flow.

58 GEOSCIENCES↗

Seafloor Seismic Noise Patterns Across the Pacific Basin

Seismic hazard monitoring and global tomography efforts are improved by recording signals at a variety of distances and azimuths to maximize subsurface sampling. Although seismic networks provide good to excellent coverage on land, seafloor stations are still sparse. Inclusion of ocean-based data would greatly improve the global coverage of seismic networks, but the use of seafloor seismic data to complement land-based detection and characterization of events is complicated by the generally much higher ambient noise level in the ocean compared to that observed on land. This noise is driven primarily by sea surface waves and tides, but how seismic noise levels vary with location in the oceans is not well described. Here, in this work, we analyze the relationship between ocean surface wave height and seismic noise in the 0.4–4 Hz frequency band at ocean-bottom seismometer deployments across the Pacific basin. We find that a noise-to-responsiveness ratio (NRR)—the median noise level at a station divided by its sea surface wave height responsiveness—correlates negatively with detection success for large teleseismic earthquakes. Stations that are close to land, with relatively shallow ocean and low wind speed, often have lower NRR than open-ocean stations, but the connection between geographic location and earthquake detection success is imperfect.

58 GEOSCIENCES↗

Self-Assembling Sup-porosity: The Effect On Fluid Flow And Seismic Wave Propagation

Fractures and joints in the field often contain debris within the void spaces. Debris originates from many different mechanisms: organic and/or inorganic chemical reactions/mineralization, sediment transport, formation of a fracture, mechanical weathering or combinations of these processes. In many cases, the presence of debris forms a sub-porosity within the fracture void space. This sub-porosity often is composed of material that differs from the fracture walls in mineralogy and morphology. The sub-porosity may partially fill voids that are on the order of hundreds of microns and thereby reduce the local porosity to lengths scales on the order of sub-microns to tens of microns. It is quite clear that a sub-porosity affects fracture porosity, permeability and storativity. What is not known is how the existence/formation of a sub-porosity affects seismic wave propagation and consequently our ability to probe changes in the subsurface caused by the formation or alteration of a sub-porosity. If seismic techniques are to be developed to monitor the injection and containment of phases in sequestration reservoirs or the propping of hydraulically induced fracture to enhance oil & gas production, it is important to understand how a sub-porosity within a fracture affects macroscopic seismic and hydraulic measurements. A sub-porosity will directly affect the interrelationship between the seismic and hydraulic properties of a fracture. This reports contains the results of the three main topics of research that were performed (1) to determine the effect of a sub-porosity composed of spherical grains on seismic wave propagation across fractures, (2) to determine the effect of biofilm growth in pores and between grains on seismic wave propagation in sediment, and (3) to determine the effect of the scale of observation (field-of-view) on monitoring alteration the pore space within a fracture caused by reactive flow. A brief summary of the results for each topic is contained in the report and the full details of the research and approach are contained in the publications found in the Attachment section of this report. A list of presentation and publications of all work associated with this grant is also provided.

58 GEOSCIENCES↗

Final report of a scalable, automated, semipermanent seismic array (SASSA) method for detecting CO 2 extent during geologic CO 2 injection

The scalable, automated, semipermanent seismic array (SASSA) project led and managed by the Energy & Environmental Research Center (EERC) was designed as a 3-year proof-of-concept study to evaluate and demonstrate an innovative application of the seismic method. The concept was to use a sparse surface array of 96 nodal seismic sensors paired with a single, remotely operated active seismic source at a fixed location to monitor for CO 2 saturation changes in a subsurface reservoir by processing the data for time-lapse changes at individual, strategically chosen reservoir reflection points. The combination of autonomous equipment and modern processing algorithms was used to apply the seismic method in a manner different from the normal paradigm of collecting a spatially dense data set to produce an image. It was used instead to monitor individual, strategically chosen reservoir reflection points for detectable signal character changes that could be attributed to the passing of a CO 2 saturation front or, possibly, changes in reservoir pressure. Data collection occurred over the course of 1 year at an oil field undergoing CO 2 injection for enhanced oil recovery (EOR) and focused on four overlapping “five-spot” EOR injector–producer patterns. Selection, procurement, configuration, installation, and testing of project equipment and collection of five baseline data sets were completed in advance of CO 2 injection within the study area. Weekly remote data collection produced 41 incremental time-lapse records for each of the 96 nodes. Validation was provided by two methods: 1) a conventional 2-D seismic line acquired through the center of the study area before injection started and again after the project ended and processed in a time-lapse manner and 2) by CO 2 saturation maps created from reservoir simulations based on injection and production history matching. Interpreted results were encouraging but mixed, with indications of changes likely due to the presence of CO 2 on some node reflection points where and when effects would be expected and noneffects where no CO 2 was expected, while results at some locations where simulation outputs suggested CO 2 should be present were ambiguous. Acquisition noise impacted interpretation of data at several locations. Many lessons learned were generated by the study to inform and improve results on a follow-up study. The ultimate aim of the project was to evaluate whether deployment of a SASSA technology can provide a useful and cost-effective monitoring solution for future CO 2 injection projects. The answer appears to be affirmative, with the expectation that lessons learned applied to future iterations, together with technology advances, will likely result in significant improvements.

58 GEOSCIENCES↗

Seismic Phase Identification with Speech Recognition Algorithms

Seismic signals are composed of the seismic waves (phases) that reach a sensor, similar to the way speech signals are composed of phonemes that reach a listener's ear. Large/small seismic events near/far from a sensor are similar to loud/quiet speakers with high/low-pitched voices. We leverage ideas from speech recognition for the classification of seismic phases at a seismic sensor. Seismic Phase ID is challenging due to the varying paths and distances an event takes to reach a sensor, but there is consistent structure of the makeup (e.g. ordering) of the different phases arriving at the sensor.

58 GEOSCIENCES↗

Imaging Fracture Networks Using Joint Seismic and Electrical Change Detection Techniques (Final Report)

During the initial phase of this SubTER project, we conducted a series of high resolution seismic imaging campaigns designed to characterize induced fractures. Fractures were emplaced using a novel explosive source, designed at Sandia National Laboratories, that limits damage to the borehole. This work provided evidence that fracture locations could be imaged at inch scales using high-frequency seismic tomography but left many fracture properties (i.e. permeability) unresolved. We present here the results of the second phase of the project, where we developed and demonstrated emerging seismic and electrical geophysical imaging technologies that characterize 1) the 3D extent and distribution of fractures stimulated from the explosive source, 2) 3D fluid transport within the stimulated fracture network through use of a contrasting tracer, and 3) fracture attributes through advanced data analysis. Focus was placed upon advancing these technologies toward near real-time acquisition and processing in order to help provide the feedback mechanism necessary to understand and control fracture stimulation and fluid flow. Results from this study include a comprehensive set of 4D cross-hole seismic and electrical data that take advantage of change detection methodologies allowing for perturbations associated with the fracture emplacement and particulate tracer to be isolated. During the testing the team also demonstrated near real-time 4D electrical resistivity tomography imaging and 4D seismic tomography using the CASSM approach with a temporal resolution approaching 1 minute. All of the data collected were used to develop methods of estimating fracture attributes from seismic data, develop methods of assimilating disparate and transient data sets to improve fracture network imaging resolution, and advance capabilities for near real-time inversion of cross-hole tomographic data. These results are illustrated here. Advancements in these areas are relevant to all situations where fracture emplacement is used for reservoir stimulation (e.g. Enhanced Geothermal Systems (EGS) and tight shale gases).

42 ENGINEERING↗

Seismic Spatial Gradients and Machine Learning-Based Classifiers for Explosion Monitoring (LDRD 218327)

This final report summarizes the work completed under the Laboratory Directed Research and Development (LDRD) project “Seismic Spatial Gradients as a Machine Learning-Based Classifier for Explosion Monitoring.” The overarching goal of the project was to explore the efficacy of using machine learning-based classification algorithms where the input data are the spatial gradient of the seismic wavefield collected at a single point on the Earth’s surface. The methods that I describe here are in direct contrast to conventional methods of seismic discrimination which typically rely on a spatially extended network of instruments and physics-based wavefield attributes such as, for example, the ratio between $\textit{P}$ and $\textit{S}$ waves. Rather, we use the spatial gradient of the seismic wavefield observed at a single point on the Earth’s surface and data processing approaches inspired by the machine learning community. We tested two algorithms, a neural network and a modified version of principal component analysis termed Spectrally Filtered Principal Component Analysis (SFPCA). To test these algorithms, we first conducted a series of numerical tests using synthetic data and then conducted a small-scale controlled field experiment. The tests using synthetic data showed that both algorithms had high success rates on gradiometric data, even when simulated noise was added to the signal. Furthermore, we found that using seismic spatial gradients increased the performance of our discrimination algorithms when compared to using just the traditional translational motion seismic data. The tests with field data also showed a high degree of discriminative success.

58 GEOSCIENCES↗

A Novel Approach to Map Permeability Using Passive Seismic Emission Tomography

Newly acquired magnetotelluric data and passive seismic data collected with tightly spaced geophone arrays are combined with historic drilling, active seismic, and potential fields data to generate 3-D permeability maps. A cooperative inversion methodology has been developed using active seismic, magnetotelluric, and gravity data in order to produce more robust velocity models for passive seismic data processing without requiring expensive 3-D active seismic surveys. The cooperative inversion estimates velocities from other geophysical data where no prior seismic velocity information is available at two geothermal sites in Nevada: San Emidio and Crescent Valley.

15 GEOTHERMAL ENERGY↗

How far can it go?: Determining the reach of induced seismicity

Induced seismicity is a unique societal and intellectual challenge in the solid Earth sciences. Societally, induced seismicity provides an opportunity to harness the advances of earthquake science to directly reduce hazard. Intellectually, induced seismicity provides a partially controlled, field-scale experiment that allows us to investigate otherwise inaccessible processes. The dramatic increase in induced earthquakes in the 21st century requires rising to both aspects of the challenge. A key issue is establishing general trends of induced seismicity. Fluid injection activity has led to several recent moderate magnitude earthquakes and many detailed studies are available (Bao and Eaton, 2016; Ellsworth, 2013; Kim et al., 2018; Weingarten et al., 2015; Yeck et al., 2017). However, a generalized understanding has been difficult to reach in part because of the variety of potential observables and variables. Some efforts at generalizing behavior have focused on magnitudes or seismicity rate (Bachmann et al., 2011; Galis et al., 2017; Gischig and Wiemer, 2013; McGarr, 1976, 2014; Shapiro et al., 2010). Others have examined migratory behavior (Bourouis and Bernard, 2007; Shapiro and Dinske, 2009; Shapiro et al., 2002). We expand on these results and focus on the spatial distribution of induced events, which has rarely been examined quantitatively. We find that the spatial decay of earthquakes from injection wells is a particularly powerful tool for accessing physics and comparing the factors that exert the most significant control on the resulting seismicity (Goebel and Brodsky, 2018).

15 GEOTHERMAL ENERGY↗

Assessing the Value of Seismic Amplitude Versus Offset (AVO) Attributes for CO2 Storage Project Using a Bayesian Network Model for Decision Support

Attributes versus offset (AVO) are a set of measurements to analyze how the characteristics of reflected seismic waves change as a function of the offset. It can be useful for monitoring CO2 storage sites because the presence of leaked CO2 into the overlying aquifer can change the properties of the rocks and pore fluids composition that can alter the way seismic waves reflect and their amplitudes. The time-lapse changes in AVO attributes derived from repeat seismic surveys can help identify anomalies or shifts in the subsurface that could potentially be used as an indicator for CO2 leak detection. Our study leverages multiple seismic attributes derived from synthetic seismic data and Bayesian network model to quantify the probability of leak detection in the overlying aquifer above the storage reservoir. It helps to quantify the value of individual seismic attributes at multiple monitoring periods based upon their sensitivities.

Kumar, Abhash↗

Shallow Marine High-Resolution 3D Seismics for Above-Zone CO2 Monitoring: A Case Study in Offshore Japan

Shallow marine high-resolution 3D (HR3D) seismic utilizes a novel seismic acquisition technology for imaging fine geological features not revealed by conventional 3D surveys. HR3D technology has been previously used for shallow subsurface studies, however is rarely implemented for monitoring injected fluids, and has not previously been used to monitor an active CO2 storage project. In this study, we for the first time demonstrate the acquisition, processing and initial interpretation of a HR3D seismic survey in Tomakomai, offshore Japan, where a large-scale CO2 storage project is being undertaken. As a seismic monitoring tool, the HR3D survey images the geologic overburden (< 1000 ms), aiming to detect potential CO2 leakage pathways above the injection reservoir. The HR3D acquisition system comprises a 210 in3 GI air gun and 4 streamers that are 25 m in length with 10 m inline separation. Each streamer has 8 channels with a 3.125 m group interval, yielding a very small final bin size of 3 x 3 m. The short offset and low-fold coverage of the HR3D data creates new challenges in seismic data processing, which demands a different data processing workflow tailored to the HR3D acquisition. We present a data processing workflow involving multiple software processing packages, which tackled high-resolution related static issues and significantly reduced various noise elements. Dip-steering and structural filtering were employed on the stacked volume to further enhance the lateral coherence and to remove random noise and suppress acquisition footprints. The final volume shows flat and coherent above-zone stratigraphy, suggesting a good seal quality above the CO2 reservoir. The successful implementation of HR3D acquisition and the customized processing workflow verify the feasibility of HR3D seismics for the above- zone monitoring of offshore CO2 injection and storage projects.

Feng, Ye Erickson↗

SHALLOW MARINE HIGH-RESOLUTION 3D SEISMICS FOR ABOVE- ZONE CO2MONITORING: A CASE STUDY IN OFFSHORE JAPAN

Shallow marine high-resolution 3D (HR3D) seismic utilizes a novel seismic acquisition technology for imaging fine geological features not revealed by conventional 3D surveys. HR3D technology has been previously used for shallow subsurface studies, however is rarely implemented for monitoring injected fluids, and has not previously been used to monitor an active CO2 storage project. In this study, we for the first time demonstrate the acquisition, processing and initial interpretation of a HR3D seismic survey in Tomakomai, offshore Japan, where a large-scale CO2 storage project is being undertaken. As a seismic monitoring tool, the HR3D survey images the geologic overburden (< 1000 ms), aiming to detect potential CO2 leakage pathways above the injection reservoir. The HR3D acquisition system comprises a 210 in3 GI air gun and 4 streamers that are 25 m in length with 10 m inline separation. Each streamer has 8 channels with a 3.125 m group interval, yielding a very small final bin size of 3 x 3 m. The short offset and low-fold coverage of the HR3D data creates new challenges in seismic data processing, which demands a different data processing workflow tailored to the HR3D acquisition. We present a data processing workflow involving multiple software processing packages, which tackled high-resolution related static issues and significantly reduced various noise elements. Dip-steering and structural filtering were employed on the stacked volume to further enhance the lateral coherence and to remove random noise and suppress acquisition footprints. The final volume shows flat and coherent above-zone stratigraphy, suggesting a good seal quality above the CO2 reservoir. The successful implementation of HR3D acquisition and the customized processing workflow verify the feasibility of HR3D seismics for the above-zone monitoring of offshore CO2 injection and storage projects.

Feng, Ye E.↗

Identification of Faults Susceptible to Induced Seismicity (Final Report)

Central to the work documented in this report is the capability of geocellular models to represent the geologic conceptual model updated with fault identification from machine learning and joint inversion modeling of microseismic data measured and recorded as a consequence of CO 2 injection at a field demonstration site: the Illinois Basin - Decatur Project (IBDP). This work required seven unique geocellular models with 100s of simulated variations to gain a very high degree of confidence in the identification of geologic features present that contributed to induced microseismicity at IBDP. All forward modeling: pressure modeling, stress modeling, and seismic modeling used the same geologic conceptual model and representations of that model at different scales. The pressure modeling and poroelastic modeling created “snapshots” of pore pressure and stress field changes at different times during CO 2 injection, in which microseismic events were clustered (in time). These pressure and stress snapshots, within the framework and architecture of the geologic conceptual model via the geocellular model, informed the single fault and fault network models to ascertain the likelihood of fault movement (seismic or aseismic). The outcomes of the pressure, stress, and fault/fault network (seismic) modeling confirmed that the faults in the geologic conceptual model in Task 2 were likely the source of microseismic events measured at IBDP and acted as conduits for pressure to be transmitted from the injection interval into the Precambrian crystalline basement rock. This closely coordinated and integrated unique modeling approach was conducted to prove the viability of our proposed workflow 1) to better resolve crystalline basement faults, 2) detect subseismic faults that could be activated by injection, 3) increase the certainty in fault detection and their susceptibility to release seismic energy, and 4) understand transmission of pressure vertically from the well to the underlying fractured crystalline basement. The proposed methodology was effective in guiding an iterative process of calibrating forward modeling results based on similar geocellular models while honoring the geologic conceptual model (i.e., characterization data and knowledge of regional geology); this led to higher level of certainty in the identification of fault/faults zones to control seismicity and transmission of pressure to the regions of recorded and located injection induced seismicity.

58 GEOSCIENCES↗

Low-Environmental-Impact Monitoring of CO 2 Using Seismic Methods in North Dakota

Conference poster presented at American Association of Petroleum Geologists (AAPG) Carbon Capture, Utilization, and Storage (CCUS) Conference, Houston, Texas, March 28–30, 2022. In 2021, the Energy & Environmental Research Center initiated a multiyear research project associated with Red Trail Energy’s Carbon Capture and Storage Project. The research is based on the scalable automated sparse seismic array (SASSA), a lower-cost, less invasive seismic method that could replace the large-scale 3D seismic surveys by using four stationary seismic sources called surface orbital vibrators (SOVs) and a small number of seismic sensors deployed sparsely within the same 8-square-mile area investigated with a 3D seismic survey conducted in 2019.

01 COAL, LIGNITE, AND PEAT↗

Induced seismicity in geologic carbon storage

Geologic carbon storage, as well as other geo-energy applications, such as geothermal energy, seasonal natural gas storage and subsurface energy storage imply fluid injection and/or extraction that causes changes in rock stress field and may induce (micro)seismicity. If felt, seismicity has a negative effect on public perception and may jeopardize wellbore stability and damage infrastructure. Thus, induced earthquakes should be minimized to successfully deploy geo-energies. However, numerous processes may trigger induced seismicity, which contribute to making it complex and translates into a limited forecast ability of current predictive models. We review the triggering mechanisms of induced seismicity. Specifically, we analyze (1) the impact of pore pressure evolution and the effect that properties of the injected fluid have on fracture and/or fault stability; (2) non-isothermal effects caused by the fact that the injected fluid usually reaches the injection formation at a lower temperature than that of the rock, inducing rock contraction, thermal stress reduction and stress redistribution around the cooled region; (3) local stress changes induced when low-permeability faults cross the injection formation, which may reduce their stability and eventually cause fault reactivation; (4) stress transfer caused by seismic or aseismic slip; and (5) geochemical effects, which may be especially relevant in carbonate-containing formations. We also review characterization techniques developed by the authors to reduce the uncertainty in rock properties and subsurface heterogeneity both for the screening of injection sites and for the operation of projects. Based on the review, we propose a methodology based on proper site characterization, monitoring and pressure management to minimize induced seismicity.

58 GEOSCIENCES↗

Air-coupled seismic waves at long range from Apollo launchings.

Microphones and seismographs were co-located in arrays on Skidaway Island, Georgia, for the launchings of Apollo 13 and 14, 374 km to the south. Simultaneous acoustic and seismic waves were recorded for both events at times appropriate to the arrival of the acoustic waves from the source. The acoustic signal is relatively broadband compared to the nearly monochromatic seismic signal; the seismic signal is much more continuous than the more pulse-like acoustic signal; ground loading from the pressure variations of the acoustic waves is shown to be too small to account for the seismic waves; and the measured phase velocities of both acoustic and seismic waves across the local instrument arrays differ by less than 6 per cent and possibly 3 per cent if experimental error is included. It is concluded that the seismic waves are generated by resonant coupling to the acoustic waves along some 10 km of path on Skidaway Island.

Donn, W. L.↗