The sparsity of permanent seismic instrumentation in marine environments often limits the availability of subsea information on geohazards, including active fault systems, in both time and space. One sensing resource that provides observational access to the seafloor environment are existing networks of ocean bottom fiber optic cables; these cables, coupled to modern distributed acoustic sensing (DAS) systems, can provide dense arrays of broadband seismic observations capable of recording both seismic events and the ambient noise wavefield. Here, we report a marine DAS application which demonstrates the strength and limitation of this new technique on submarine structural characterization. Based on ambient noise DAS records on a 20 km section of a fiber optic cable offshore of Moss Landing, CA, in Monterey Bay, we extract Scholte waves from DAS ambient noise records using interferometry techniques and invert the resulting multimodal dispersion curves to recover a high resolution 2D shear-wave velocity image of the near seafloor sediments. We show for the first time that the migration of coherently scattered Scholte waves observed on DAS records can provide an approach for resolving sharp lateral contrasts in subsurface properties, particularly shallow faults and depositional features near the seafloor. Our results provide improved constraints on shallow submarine features in Monterey Bay, including fault zones and paleo-channel deposits, thus highlighting one of many possible geophysical uses of the marine cable network.
Passive seismic methods in highly populated urban areas have gained much attention from geophysics and civil engineering communities because traditional seismic surveys, especially in complex urbanized environments, might be improperly applied. In passive seismic methods, directional noise sources will inevitably bring azimuthal effects and spatial aliasing to dispersion measurements due to the fact that true randomness of ambient noise cannot be achieved in reality. To solve these problems, multichannel analysis of passive surface (MAPS) waves based on long noise sequence crosscorrelations is proposed. We have introduced a hybrid method of seismic interferometry and the roadside passive multichannel analysis of surface waves (MASW) using crosscorrelation to produce common virtual source gathers from 1 h multichannel noise records. Common virtual source gathers are then used to do dispersion analysis with an active scheme based on phase-shift measurement. Synthetic tests demonstrated the advantages of this method with azimuthal adjustment and dispersion imaging for directional noise source distribution. Two field applications were conducted, and results from the roadside passive MASW, MAPS, and spatial autocorrelation method were compared. Our study indicated the superiority of MAPS over the roadside passive MASW on the validity of azimuth detection, feasibility of combining the active MASW and MAPS, and accuracy in determining dispersion energy trends, especially at a relative low-frequency range ([Formula: see text]) in urban areas.
Geothermal energy is one of the most promising renewable energy sources, particularly within the context of China's energy structure optimization, environmental protection measures, energy conservation, and rising pressure on emission reduction. By the end of 2020, renewable energy facilities, including solar, wind, geothermal and other types of energy, in China will supply 27% of total power generation, according to the government's 2016-2020 plan for renewable energy. However, geothermal resources accounted for only 0.6
In the recent decades, passive surface wave methods have gained much attention in the near-surface community due to their ability to retrieve low-frequency surface wave information. Temporal averaging over a sufficiently long period of time is a crucial step in the workflow to fulfill the randomization requirement of the stationary source distribution. Because of logistical constraints, passive seismic acquisition in urban areas is mostly limited to short recording periods. Due to insufficient temporal averaging, contributions from non-stationary sources can smear the stacked dispersion measurements, especially for the low-frequency band. We formulate a criterion in the tau-p domain for selective stacking of dispersion measurements from passive surface waves and apply it to high-frequency (> 1 Hz) traffic noise. The criterion is based on the automated detection of input data with a high signal-to-noise ratio in a desired velocity range. Modeling tests demonstrate the ability of the proposed criterion to capture the contributions from the non-stationary sources and classify the passive surface wave data. A real-world application shows that the proposed data selection approach improves the dispersion measurements by extending the frequency band below 5 Hz and attenuating the distortion between 6 and 13 Hz. Our results indicate that significant improvements can be obtained by considering tau-p-based data selection in the workflow of passive surface wave processing and interpretation.
The Imperial Valley, CA, is a tectonically active transtensional basin located south of the Salton Sea; the area hosts numerous geothermal fields, including significant hidden hydrothermal resources without surface manifestations. Development of inexpensive, rugged, and highly sensitive exploration techniques for undiscovered geothermal systems is critical for accelerating geothermal power deployment as well as unlocking a low‐carbon energy future. We present a case study utilizing distributed acoustic sensing (DAS) and ambient noise interferometry for geothermal reservoir imaging, utilizing unlit fiber‐optic telecommunication infrastructure (dark fiber). The study exploits two days of passive DAS data acquired in early November 2020 over a ∼28‐km section of fiber from Calipatria, CA to Imperial, CA. We apply ambient noise interferometry to retrieve coherent signals from DAS records and develop a bin stacking technique to attenuate the effects from persistent localized noise sources and to enhance retrieval of coherent surface waves. As a result, we are able to obtain high‐resolution two‐dimensional (2D) S wave velocity (Vs) structure to 3 km depth, based on joint inversion of both the fundamental and higher overtones. We observe a previously unmapped high Vs and low Vp/Vs ratio feature beneath the Brawley geothermal system, which we interpret to be a zone of hydrothermal mineralization and lower porosity. This interpretation is consistent with a host of other measurements including surface heat flow, gravity anomalies, and available borehole wireline data. These results demonstrate the potential utility of DAS deployed on dark fiber for geothermal system exploration and characterization in the appropriate geological settings.
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