Seismic Advances in Process Geomorphology

One of the pillars of geomorphology is the study of geomorphic processes and their drivers, dynamics, and impacts. Like all activity that transfers energy to Earth's surface, a wide range of geomorphic process types create seismic waves that can be measured with standard seismic instruments. Seismic signals provide continuous high-resolution coverage with a spatial footprint that can vary from local to global, and in recent years, efforts to exploit these signals for information about surface processes have increased dramatically, coalescing into the emerging field of environmental seismology. The application of seismic methods has the potential to drive advances in our understanding of the occurrence, timing, and triggering of geomorphic events, the dynamics of geomorphic processes, fluvial bedload transport, and integrative geomorphic system monitoring. As new seismic applications move from development to proof of concept to routine application, integration between geomorphologists and seismologists is key for continued progress. ▪ Geomorphic activity on Earth's surface produces seismic signals that can be measured with standard seismic instruments. ▪ Seismic methods are driving advances in our understanding of the occurrence, triggering, and internal dynamics of a range of geomorphic processes. ▪ Dedicated seismic-based observatories offer the potential to comprehensively characterize geomorphic activity and its impacts across a landscape. ▪ Collaboration between seismologists and geomorphologists is fostering the development of new applications, models, and analysis techniques for geomorphic seismology. Expected final online publication date for the Annual Review of Earth and Planetary Sciences, Volume 50 is May 2022. Please see http://www.annualreviews.org/page/journal/pubdates for revised estimates.

Evaluation of Lake Sediment Thickness from Water-Borne Electrical Resistivity Tomography Data

Lakes are integrators of past climate and ecological change. This information is stored in the sediment record at the lake bottom, and to make it available for paleoclimate research, potential target sites with undisturbed and continuous sediment sequences need to be identified. Different geophysical methods are suitable to identify, explore, and characterize sediment layers prior to sediment core recovery. Due to the high resolution, reflection seismic methods have become standard for this purpose. However, seismic measurements cannot always provide a comprehensive image of lake-bottom sediments, e.g., due to lacking seismic contrasts between geological units or high attenuation of seismic waves. Here, we developed and tested a complementary method based on water-borne electrical-resistivity tomography (ERT) measurements. Our setup consisted of 13 floating electrodes (at 5 m spacing) used to collect ERT data with a dipole–dipole configuration. We used a 1D inversion to adjust a layered-earth model, which facilitates the implementation of constraints on water depth, water resistivity, and sediment resistivity as a priori information. The first two parameters were readily obtained from the echo-sounder and conductivity-probe measurements. The resistivity of sediment samples can also be determined in the laboratory. We applied this approach to process ERT data collected on a lake in southern Mexico. The direct comparison of ERT data with reflection seismic data collected with a sub-bottom profiler (SBP) showed that we can significantly improve the sediment-thickness estimates compared to unconstrained 2D inversions. Down to water depths of 20 m, our sediment thickness estimates were close to the sediment thickness derived from collocated SBP seismograms. Our approach represents an implementation of ERT measurements on lakes and complements the standard lake-bottom exploration by reflection seismic methods.

Road sinkhole detection with 2D ambient noise tomography

Seismic methods are often used for detection of pre-collapsed sinkholes (voids) under roadway for remediation to minimize the risk to the safety of the traveling public. While the active-source seismic methods can provide accurate subsurface profiles, they require closing the traffic flow for hours during testing and potentially cause sinkhole collapse due to ground perturbation by source excitation. To address these issues, we present a new 2D ambient noise tomography (2D ANT) method for imaging voids under roadway. Instead of using the approximated Green’s function, whose required assumption of energy balance at both sides of each receiver pair is rarely satisfied, the cross-correlation function of traffic noise recordings is inverted directly to obtain velocity structures. To adopt the concepts of seismic interferometry and derive the model structural kernel, passing-by vehicles are assumed as moving sources along the receiver array. The source power-spectrum density is determined via the reverse-time imaging approach to approximate the source distribution. The 2D ANT method is first demonstrated on a realistic synthetic model with the accurate recovery of the model variable layers and a buried void. To demonstrate its effectiveness to the real-world problems, we successfully applied it to field data for assessment of a repaired sinkhole under the US441 highway, Florida, USA. The field experimental result shows that the method is capable of resolving the subsurface S-wave velocity ( VS) structure and detecting a low-velocity anomaly. The inverted VS profile from the 2D ANT generally agrees with that of 2D active-source full-waveform inversion, including the VS value and depth of the anomaly. To our best knowledge, this is the first study to directly invert the waveform cross-correlation of traffic noise recordings to extract material property at the engineering meter scale (<30 m depth).

Reverse time migration (RTM) imaging of iron oxide deposits in the Ludvika mining area, Sweden

To discover or delineate mineral deposits and other geological features such as faults and lithological boundaries in their host rocks, seismic methods are preferred for imaging the targets at great depth. One major goal for seismic methods is to produce a reliable image of the reflectors underground given the typical discontinuous geology in crystalline environments with low signal-to-noise ratios. In this study, we investigate the usefulness of the reverse time migration (RTM) imaging algorithm in hardrock environments by applying it to a 2D dataset, which was acquired in the Ludvika mining area of central Sweden. We provide a how-to solution for applications of RTM in future and similar datasets. When using the RTM imaging technique properly, it is possible to obtain high-fidelity seismic images of the subsurface. Due to good amplitude preservation in the RTM image, the imaged reflectors provide indications to infer their geological origin. In order to obtain a reliable RTM image, we performed a detailed data pre-processing flow to deal with random noise, near-surface effects, and irregular receiver and source spacing, which can downgrade the final image if ignored. Exemplified with the Ludvika data, the resultant RTM image not only delineates the iron oxide deposits down to 1200 m depth as shown from previous studies, but also provides a better inferred ending of sheet-like mineralization. Additionally, the RTM image provides much-improved reflection of the dike and crosscutting features relative to the mineralized sheets when compared to the images produced by Kirchhoff migration in the previous studies. Two of the imaged crosscutting features are considered to be crucial when interpreting large-scale geological structures at the site and the likely disappearance of mineralization at depth. Using a field dataset acquired in hardrock environment, we demonstrate the usefulness of RTM imaging workflows for deep targeting mineral deposits.

Void Hunting

Karst environments are characterized by voids, i.e. sinkholes and conduits of varying size that arise from the active dissolution of carbonate rock by acidic groundwater. These voids, whether air-, water-, or soil-filled, can be difficult to image using near-surface geophysical methods due to the limited investigation depths of most active-source methods. In addition, due to the significant effort it takes to collect active-source data, investigators are often unable to monitor spatio-temporal variations in the subsurface. The ability to detect, image, and monitor subsurface voids improves the understanding of processes that create and transform voids, a vitally important insight across a variety of scientifc disciplines and engineering applications, including hydrogeology, geotechnical engineering, planetary science and even issues of national security. Using a 54-element nodal array (1C and 3C sensors), I image the subsurface of the USF GeoPark with ambient noise surface wave tomography. I also use complementary active-source geophysical datasets (e.g. 2D ERT) collected at the GeoPark to constrain and/or validate the tomography results. I address two research questions with this study: (1) How do ambient seismic methods complement active-source near-surface methods? (2) Can ambient noise tomography resolve voids in the karst environment? In this thesis, I discuss my answers to these questions and present the current state of surface wave methods in the karst environment, including the feasibility for utilizing ambient noise methods to monitor spatio-temporal changes in sinkhole and conduit formation. In addition to the ability to use seismic methods for temporal monitoring, ambient noise provides lower frequencies than what are achievable with active-source seismic methods. Using frequencies from 5-28 Hz, ambient noise tomography is able to image deeper into the subsurface (up to 100 m at 5 Hz) than previous active-source seismic studies at the GeoPark field site. This study yields a more robust and simple method to image voids in covered karst environments and a long-term installation of ambient seismic nodes enables future investigations of spatio-temporal variations in void structures.

Borehole seismic methods for geologic CO2 storage monitoring

Borehole geophysical methods are a key component of subsurface monitoring of geologic CO2 storage sites because boreholes form a locus where geophysical measurements can be compared directly with the controlling geology. Borehole seismic methods, including intrawell, crosswell, and surface-to-borehole acquisition, are useful for site characterization, surface seismic calibration, 2D/3D time-lapse imaging, and microseismic monitoring. Here, we review the most common applications of borehole seismic methods in the context of storage monitoring and consider the role that detailed geophysical simulations can play in answering questions that arise when designing monitoring plans. Case study examples are included from the multitude of CO2 monitoring projects that have demonstrated the utility of borehole seismic methods for this purpose over the last 20 years.