scholarly journals Reciprocity-gap misfit functional for Distributed Acoustic Sensing, combining data from passive and active sources

Geophysics ◽  
2020 ◽  
pp. 1-59 ◽  
Author(s):  
Florian Faucher ◽  
Maarten V. de Hoop ◽  
Otmar Scherzer
Keyword(s):  
Quantitative Imaging ◽  
A Priori ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Inversion Method ◽  
Acoustic Sensing ◽  
Use Of Data ◽  
Combining Data ◽  
Distributed Acoustic Sensing ◽  
Priori Information

Quantitative imaging of sub-surface Earth’s properties in elastic media is performed from Distributed Acoustic Sensing data. A new misfit functional based upon the reciprocity-gap is designed, taking cross-correlations of displacement and strain, and these products further associate an observation with a simulation. In comparison with other misfit functionals, this one has the advantage to only require little a-priori information on the exciting sources. In particular, the misfit criterion enables the use of data from regional earthquakes (teleseismic events can be included as well), followed by exploration data to perform a multi-resolution reconstruction. The data from regional earthquakes contain the low-frequency content which is missing in the exploration ones, allowing for the recovery of the long spatial wavelength, even with very few sources. These data are used to build prior models for the subsequent reconstruction from the higher-frequency exploration data. This gives the elastic Full Reciprocity-gap Waveform Inversion method, and we demonstrate its performance with a pilot experiment for elastic isotropic reconstruction.

Source-independent extended waveform inversion based on space-time source extension: Frequency-domain implementation

Geophysics ◽  
2018 ◽  
Vol 83 (5) ◽  
pp. R449-R461 ◽  
Author(s):  
Guanghui Huang ◽  
Rami Nammour ◽  
William W. Symes
Keyword(s):  
Source Function ◽  
Random Noise ◽  
A Priori ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Inversion Method ◽  
Target Velocity ◽  
Extended Source ◽  
Full Waveform ◽  
Time Variables

Source signature estimation from seismic data is a crucial ingredient for successful application of seismic migration and full-waveform inversion (FWI). If the starting velocity deviates from the target velocity, FWI method with on-the-fly source estimation may fail due to the cycle-skipping problem. We have developed a source-based extended waveform inversion method, by introducing additional parameters in the source function, to solve the FWI problem without the source signature as a priori. Specifically, we allow the point source function to be dependent on spatial and time variables. In this way, we can easily construct an extended source function to fit the recorded data by solving a source matching subproblem; hence, it is less prone to cycle skipping. A novel source focusing annihilator, defined as the distance function from the real source position, is used for penalizing the defocused energy in the extended source function. A close data fit avoiding the cycle-skipping problem effectively makes the new method less likely to suffer from local minima, which does not require extreme low-frequency signals in the data. Numerical experiments confirm that our method can mitigate cycle skipping in FWI and is robust against random noise.

Seismic imaging combining active and passive sources using distributed acoustic sensing

2021 ◽  
Author(s):  
Florian Faucher ◽  
Otmar Scherzer ◽  
Maarten V. de Hoop
Keyword(s):  
Low Cost ◽  
Quantitative Imaging ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Seismic Exploration ◽  
Data Sets ◽  
Elastic Media ◽  
Combine Data ◽  
Exciting Source ◽  
Distributed Acoustic Sensing

<p>DAS finds growing interest in seismic exploration by offering a dense and low-cost coverage of the area investigated. Nonetheless, contrary to the usual geophones that measure the displacement, DAS provides information on the strain. In this work, we perform quantitative imaging of elastic media designing a new misfit functional that is adapted to these data-sets. This misfit criterion is based on the reciprocity-gap, hence defining the full reciprocity-gap waveform inversion. The main feature of our misfit is that it does not require the knowledge of the exciting source positions, and it allows us to combine data from active and passive (of unknown location) sources. In particular, the data from passive sources contain the low-frequency information needed to build initial models, while the exploration data contain the higher frequencies. We consequently follow a multi-resolution framework that we illustrate with two-dimensional elastic experiments.</p>

scholarly journals Distributed Acoustic Sensing from mHz to kHz: Empirical Investigations of DAS Instrument Response

2020 ◽  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Cédric Schmelzbach ◽  
Joesph Doetsch ◽  
Dominik Gräff ◽  
...  
Keyword(s):  
Urban Areas ◽  
Waveform Inversion ◽  
Geophysical Methods ◽  
Low Frequency ◽  
Acoustic Sensing ◽  
Temporal Sampling ◽  
Cable Properties ◽  
Instrument Response ◽  
Distributed Acoustic Sensing ◽  
Initial Results

<p>With the upside of high spatial and temporal sampling even in remote or urban areas using existing fiber-optic infrastructure, Distributed Acoustic Sensing (DAS) is in the process of revolutionising the way we look at seismological data acquisition. However, recent publications show variations of the quality of DAS measurements along a single cable. In addition to site- and orientation effects, data quality is strongly affected by the transfer function between the deforming medium and the fiber, which in turn depends on the fiber-ground coupling and the cable properties. Analyses of the DAS instrument response functions in a limited part of the seismological frequency band are typically based on comparisons with well-coupled conventional seismometers for which the instrument response is sufficiently well known to be removed from the signal.</p><p>In this study, we extend the common narrow-band analyses to DAS response analyses covering a frequency range of five orders of magnitude ranging from ~4000 s period to frequencies up to ~100 Hz. This is based on a series of experiments in Switzerland, including (1) active controlled-source experiments with co-located seismometers and geophones, (2) low-frequency strain induced by hydraulic injection in a borehole with co-located Fiber-Bragg-Grating (FBG) strain-meters, and (3) local to teleseismic ice- and earthquake recordings with  co-located broadband stations.</p><p>Initial results show a site-unspecific, approximately flat instrument response for all experiments.</p><p>The initial results suggest that the amplitude and phase information of DAS recordings are sufficient for conventional geophysical methods such as event localisation, full-waveform inversion, ambient noise tomography and even event magnitude estimation. Despite the promising initial results, further engagement by the DAS community is required to evaluate the DAS performance and repeatability among different interrogation units and study sites.</p>

Combining Distributed Acoustic Sensing and Beamforming in a Volcanic Environment on Mount Meager, British Columbia.

2021 ◽  
Author(s):  
Sara Klaasen ◽  
Patrick Paitz ◽  
Jan Dettmer ◽  
Andreas Fichtner
Keyword(s):  
British Columbia ◽  
Power Distribution ◽  
High Frequency ◽  
Low Frequency ◽  
Volcanic Tremor ◽  
Extreme Environment ◽  
Volcanic Complex ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing ◽  
Volcanic Environment

<p>We present one of the first applications of Distributed Acoustic Sensing (DAS) in a volcanic environment. The goals are twofold: First, we want to examine the feasibility of DAS in such a remote and extreme environment, and second, we search for active volcanic signals of Mount Meager in British Columbia (Canada). </p><p>The Mount Meager massif is an active volcanic complex that is estimated to have the largest geothermal potential in Canada and caused its largest recorded landslide in 2010. We installed a 3-km long fibre-optic cable at 2000 m elevation that crosses the ridge of Mount Meager and traverses the uppermost part of a glacier, yielding continuous measurements from 19 September to 17 October 2019.</p><p>We identify ~30 low-frequency (0.01-1 Hz) and 3000 high-frequency (5-45 Hz) events. The low-frequency events are not correlated with microseismic ocean or atmospheric noise sources and volcanic tremor remains a plausible origin. The frequency-power distribution of the high-frequency events indicates a natural origin, and beamforming on these events reveals distinct event clusters, predominantly in the direction of the main peaks of the volcanic complex. Numerical examples show that we can apply conventional beamforming to the data, and that the results are improved by taking the signal-to-noise ratio of individual channels into account.</p><p>The increased data quantity of DAS can outweigh the limitations due to the lower quality of individual channels in these hazardous and remote environments. We conclude that DAS is a promising tool in this setting that warrants further development.</p>

Empirical Investigations of the Instrument Response for Distributed Acoustic Sensing (DAS) across 17 Octaves

2020 ◽  
Author(s):  
Patrick Paitz ◽  
Pascal Edme ◽  
Dominik Gräff ◽  
Fabian Walter ◽  
Joseph Doetsch ◽  
...  
Keyword(s):  
Ground Motion ◽  
Urban Areas ◽  
Waveform Inversion ◽  
Acoustic Sensing ◽  
Full Waveform ◽  
Environmental Properties ◽  
Instrument Response ◽  
Distributed Acoustic Sensing ◽  
Reference Measurements ◽  
Seismic Networks

ABSTRACT With the potential of high temporal and spatial sampling and the capability of utilizing existing fiber-optic infrastructure, distributed acoustic sensing (DAS) is in the process of revolutionizing geophysical ground-motion measurements, especially in remote and urban areas, where conventional seismic networks may be difficult to deploy. Yet, for DAS to become an established method, we must ensure that accurate amplitude and phase information can be obtained. Furthermore, as DAS is spreading into many different application domains, we need to understand the extent to which the instrument response depends on the local environmental properties. Based on recent DAS response research, we present a general workflow to empirically quantify the quality of DAS measurements based on the transfer function between true ground motion and observed DAS waveforms. With a variety of DAS data and reference measurements, we adapt existing instrument-response workflows typically in the frequency band from 0.01 to 10 Hz to different experiments, with signal frequencies ranging from 1/3000 to 60 Hz. These experiments include earthquake recordings in an underground rock laboratory, hydraulic injection experiments in granite, active seismics in agricultural soil, and icequake recordings in snow on a glacier. The results show that the average standard deviations of both amplitude and phase responses within the analyzed frequency ranges are in the order of 4 dB and 0.167π radians, respectively, among all experiments. Possible explanations for variations in the instrument responses include the violation of the assumption of constant phase velocities within the workflow due to dispersion and incorrect ground-motion observations from reference measurements. The results encourage further integration of DAS-based strain measurements into methods that exploit complete waveforms and not merely travel times, such as full-waveform inversion. Ultimately, our developments are intended to provide a quantitative assessment of site- and frequency-dependent DAS data that may help establish best practices for upcoming DAS surveys.

Three‐dimensional gravity inversion using simulated annealing: Constraints on the diapiric roots of allochthonous salt structures

Geophysics ◽  
2001 ◽  
Vol 66 (5) ◽  
pp. 1438-1449 ◽  
Author(s):  
Seiichi Nagihara ◽  
Stuart A. Hall
Keyword(s):  
Simulated Annealing ◽  
Gulf Of Mexico ◽  
Gravity Data ◽  
A Priori ◽  
Gravity Inversion ◽  
Inversion Method ◽  
A Priori Information ◽  
Final Density ◽  
Smoothing Effects ◽  
Priori Information

In the northern continental slope of the Gulf of Mexico, large oil and gas reservoirs are often found beneath sheetlike, allochthonous salt structures that are laterally extensive. Some of these salt structures retain their diapiric feeders or roots beneath them. These hidden roots are difficult to image seismically. In this study, we develop a method to locate and constrain the geometry of such roots through 3‐D inverse modeling of the gravity anomalies observed over the salt structures. This inversion method utilizes a priori information such as the upper surface topography of the salt, which can be delineated by a limited coverage of 2‐D seismic data; the sediment compaction curve in the region; and the continuity of the salt body. The inversion computation is based on the simulated annealing (SA) global optimization algorithm. The SA‐based gravity inversion has some advantages over the approach based on damped least‐squares inversion. It is computationally efficient, can solve underdetermined inverse problems, can more easily implement complex a priori information, and does not introduce smoothing effects in the final density structure model. We test this inversion method using synthetic gravity data for a type of salt geometry that is common among the allochthonous salt structures in the Gulf of Mexico and show that it is highly effective in constraining the diapiric root. We also show that carrying out multiple inversion runs helps reduce the uncertainty in the final density model.

scholarly journals Retrieval of Canopy component temperatures through Bayesian inversion of directional thermal measurements

2009 ◽  
Vol 6 (2) ◽  
pp. 3007-3040 ◽  
Author(s):  
J. Timmermans ◽  
W. Verhoef ◽  
C. van der Tol ◽  
Z. Su
Keyword(s):  
Sensitivity Analysis ◽  
Surface Temperature ◽  
A Priori ◽  
Inversion Method ◽  
Success Rates ◽  
Brightness Temperatures ◽  
Ill Posed ◽  
Priori Information ◽  
The Individual ◽  
High Level

Abstract. In remote sensing evapotranspiration is estimated using a single surface temperature. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (ℜspectra≈0.3, ℜgonio≈0.3, and ℜAATSR≈0.5), and no improvement using mono-angular sensors (ℜ≈1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K), but for low LAI values the measurement setup provides extra disturbances in the directional brightness temperatures, RMSEyoung maize=2.85 K, RMSEmature maize=2.85 K. As these disturbances, were only present for two crops and can be eliminated using masked thermal images the method is considered successful.

scholarly journals Retrieval of canopy component temperatures through Bayesian inversion of directional thermal measurements

2009 ◽  
Vol 13 (7) ◽  
pp. 1249-1260 ◽  
Author(s):  
J. Timmermans ◽  
W. Verhoef ◽  
C. van der Tol ◽  
Z. Su
Keyword(s):  
Sensitivity Analysis ◽  
A Priori ◽  
Inversion Method ◽  
Success Rates ◽  
Brightness Temperatures ◽  
Single Temperature ◽  
Ill Posed ◽  
Priori Information ◽  
The Individual ◽  
High Level

Abstract. Evapotranspiration is usually estimated in remote sensing from single temperature value representing both soil and vegetation. This surface temperature is an aggregate over multiple canopy components. The temperature of the individual components can differ significantly, introducing errors in the evapotranspiration estimations. The temperature aggregate has a high level of directionality. An inversion method is presented in this paper to retrieve four canopy component temperatures from directional brightness temperatures. The Bayesian method uses both a priori information and sensor characteristics to solve the ill-posed inversion problem. The method is tested using two case studies: 1) a sensitivity analysis, using a large forward simulated dataset, and 2) in a reality study, using two datasets of two field campaigns. The results of the sensitivity analysis show that the Bayesian approach is able to retrieve the four component temperatures from directional brightness temperatures with good success rates using multi-directional sensors (Srspectra≈0.3, Srgonio≈0.3, and SrAATSR≈0.5), and no improvement using mono-angular sensors (Sr≈1). The results of the experimental study show that the approach gives good results for high LAI values (RMSEgrass=0.50 K, RMSEwheat=0.29 K, RMSEsugar beet=0.75 K, RMSEbarley=0.67 K); but for low LAI values the results were unsatisfactory (RMSEyoung maize=2.85 K). This discrepancy was found to originate from the presence of the metallic construction of the setup. As these disturbances, were only present for two crops and were not present in the sensitivity analysis, which had a low LAI, it is concluded that using masked thermal images will eliminate this discrepancy.

scholarly journals Low-Frequency Distributed Acoustic Sensing for Early Gas Detection in a Wellbore

2020 ◽  
pp. 1-1
Author(s):  
Jyotsna Sharma ◽  
Theo Cuny ◽  
Oloruntoba Ogunsanwo ◽  
Otto Santos
Keyword(s):  
Low Frequency ◽  
Gas Detection ◽  
Acoustic Sensing ◽  
Distributed Acoustic Sensing
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