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 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.

Machine learning-based fracture-hit detection algorithm using LFDAS signal

2019 ◽  
Vol 38 (7) ◽  
pp. 520-524 ◽  
Author(s):  
Ge Jin ◽  
Kevin Mendoza ◽  
Baishali Roy ◽  
Darryl G. Buswell
Keyword(s):  
Machine Learning ◽  
Low Frequency ◽  
Detection Algorithm ◽  
Data Sets ◽  
Fracture Zones ◽  
Learning Techniques ◽  
Distributed Acoustic Sensing ◽  
Probability Of Fracture ◽  
Simple Neural Network

Low-frequency distributed acoustic sensing (LFDAS) signal has been used to detect fracture hits at offset monitor wells during hydraulic fracturing operations. Typically, fracture hits are manually identified, which can be subjective and inefficient. We implemented machine learning-based models using supervised learning techniques in order to identify fracture zones, which demonstrate a high probability of fracture hits automatically. Several features are designed and calculated from LFDAS data to highlight fracture-hit characterizations. A simple neural network model is trained to fit the manually picked fracture hits. The fracture-hit probability, as predicted by the model, agrees well with the manual picks in training, validation, and test data sets. The algorithm was used in a case study of an unconventional reservoir. The results indicate that smaller cluster spacing design creates denser fractures.

scholarly journals Dynamic calibration uncertainty of three-axis low frequency accelerometers

ACTA IMEKO ◽  
2015 ◽  
Vol 4 (4) ◽  
pp. 75 ◽  
Author(s):  
Giulio D'Emilia ◽  
Antonella Gaspari ◽  
Emanuela Natale
Keyword(s):  
Low Cost ◽  
Low Frequency ◽  
Bias Error ◽  
Dynamic Calibration ◽  
Data Sets ◽  
Calibration Data ◽  
Civil Infrastructures ◽  
Calibration Uncertainty ◽  
The Matrix ◽  
Rotary Device

In this paper a methodology concerning the static and dynamic calibration of three-axis low-cost accelerometers in the (0 to 10) Hz frequency range is described, to be used for evaluation of existing civil infrastructures. <br /> Main and cross sensitivities of the accelerometers have been experimentally estimated by means of the matrix sensitivity concept. <br />The standard deviation of accelerations obtained along all three axes using different calibration data sets in repeatability conditions has been calculated and intended as dynamic calibration uncertainty. <br />The method has been validated by using reference accelerations accurately realized, in order to evaluate the residual bias error. <br />Static and dynamic calibration test benches have been used to realize reference accelerations. In order to create a three-axis acceleration field, a mechanical arm is used in static calibration; a rotary device is used in order to test the accelerometers in dynamic conditions. <br />According to the procedure described in this paper, a great improvement of the low cost accelerometers' metrological characterization could be achieved, especially in dynamic working conditions.

scholarly journals Multisource Seismic Full Waveform Inversion of Metal Ore Bodies

Minerals ◽  
2021 ◽  
Vol 12 (1) ◽  
pp. 4
Author(s):  
Fengjiao Zhang ◽  
Pan Zhang ◽  
Zhuo Xu ◽  
Xiangbo Gong ◽  
Liguo Han
Keyword(s):  
Seismic Data ◽  
Waveform Inversion ◽  
Low Frequency ◽  
Mining Area ◽  
Seismic Exploration ◽  
Full Waveform Inversion ◽  
Metal Mining ◽  
Full Waveform ◽  
Metal Mine ◽  
Ore Bodies

The seismic exploration method could explore deep metal ore bodies (depth > 1000 m). However, it is difficult to describe the geometry of the complex metal ore body accurately. Seismic full waveform inversion is a relatively new method to achieve accurate imaging of subsurface structures, but its success requires better initial models and low-frequency data. The seismic data acquired in the metal mine area is usually difficult to meet the requirements of full waveform inversion. The passive seismic data usually contains good low frequency information. In this paper, we use both passive and active seismic datasets to improve the full waveform inversion results in the metal mining area. The results show that the multisource seismic full waveform inversion could obtain a suitable result for high-resolution seismic imaging of metal ore bodies.

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

&lt;p&gt;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.&amp;#160;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.&lt;/p&gt;&lt;p&gt;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&amp;#160;Hz. This is based on a series of experiments in Switzerland, including (1) active controlled-source experiments with co-located seismometers and geophones, (2)&amp;#160;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 &amp;#160;co-located broadband stations.&lt;/p&gt;&lt;p&gt;Initial results show a site-unspecific, approximately flat instrument response for all experiments.&lt;/p&gt;&lt;p&gt;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.&lt;/p&gt;

Multiparameter waveform inversion of a large wide-azimuth low-frequency land data set in Oman

Geophysics ◽  
2014 ◽  
Vol 79 (3) ◽  
pp. WA69-WA77 ◽  
Author(s):  
Alexandre Stopin ◽  
René-Édouard Plessix ◽  
Said Al Abri
Keyword(s):  
Waveform Inversion ◽  
Low Frequency ◽  
Large Data ◽  
Earth Model ◽  
Data Sets ◽  
Anisotropic Parameter ◽  
Data Set ◽  
Low Frequencies ◽  
Reflected Waves ◽  
Simultaneous Inversion

Several 3D seismic acoustic full-waveform inversions (FWIs) of offshore data sets have been reported over the last five years. A successful updating of the long-to-intermediate wavelengths of the earth model by FWI requires good-quality wide-angle, long-offset, low-frequency data. Recent improvements in acquisition make such data sets available on land, too. We evaluated a 3D application on a data set recorded in North Oman. The data contain low frequencies down to 1.5 Hz, long-offsets, and wide azimuths. The application of acoustic FWI on land remains complicated because of the elastic effects, notably the strong ground-roll and many acquisition and human-activity-related noises. The presence of fast carbonate layers in this region induces velocity inversions, difficult to recover from diving or postcritical waves. We accounted for anisotropic effects as we include FWI in a classical structural imaging workflow. With a dedicated processing of the data and a simultaneous inversion of the NMO velocity and the anelliptic-anisotropic parameter, we succeeded to interpret the kinematics of transmitted and reflected waves, although in the waveform inversion we included only the diving and postcritical waves. This approach has some limitations because of the acoustic assumption. We could not obtain a high-resolution image, especially at the shale-carbonate interfaces. There is also a trade-off between the NMO velocity and the anelliptic anisotropic parameter. However, the image improvements after acoustic FWI and the ability to handle the large data volume make this technique attractive in an imaging workflow.

scholarly journals Low-Frequency Expansion Approach for Seismic Data Based on Compressed Sensing in Low SNR

2021 ◽  
Vol 11 (11) ◽  
pp. 5028
Author(s):  
Miaomiao Sun ◽  
Zhenchun Li ◽  
Yanli Liu ◽  
Jiao Wang ◽  
Yufei Su
Keyword(s):  
Reflection Coefficient ◽  
Compressed Sensing ◽  
Objective Function ◽  
Low Frequency ◽  
Original Data ◽  
Seismic Exploration ◽  
High Signal ◽  
Inversion Process ◽  
Frequency Information ◽  
Low Snr

Low-frequency information can reflect the basic trend of a formation, enhance the accuracy of velocity analysis and improve the imaging accuracy of deep structures in seismic exploration. However, the low-frequency information obtained by the conventional seismic acquisition method is seriously polluted by noise, which will be further lost in processing. Compressed sensing (CS) theory is used to exploit the sparsity of the reflection coefficient in the frequency domain to expand the low-frequency components reasonably, thus improving the data quality. However, the conventional CS method is greatly affected by noise, and the effective expansion of low-frequency information can only be realized in the case of a high signal-to-noise ratio (SNR). In this paper, well information is introduced into the objective function to constrain the inversion process of the estimated reflection coefficient, and then, the low-frequency component of the original data is expanded by extracting the low-frequency information of the reflection coefficient. It has been proved by model tests and actual data processing results that the objective function of estimating the reflection coefficient constrained by well logging data based on CS theory can improve the anti-noise interference ability of the inversion process and expand the low-frequency information well in the case of a low SNR.

scholarly journals On Time Scales of Intrinsic Oscillations in the Climate System

Entropy ◽  
2021 ◽  
Vol 23 (4) ◽  
pp. 459
Author(s):  
Anastasios A. Tsonis ◽  
Geli Wang ◽  
Wenxu Lu ◽  
Sergey Kravtsov ◽  
Christopher Essex ◽  
...  
Keyword(s):  
Low Frequency ◽  
Milankovitch Cycles ◽  
Data Sets ◽  
External Forcing ◽  
Natural Oscillations ◽  
Climatic Oscillations ◽  
Slow Feature Analysis ◽  
Limited Length ◽  
Past Data ◽  
Cumulative Evidence

Proxy temperature data records featuring local time series, regional averages from areas all around the globe, as well as global averages, are analyzed using the Slow Feature Analysis (SFA) method. As explained in the paper, SFA is much more effective than the traditional Fourier analysis in identifying slow-varying (low-frequency) signals in data sets of a limited length. We find the existence of a striking gap from ~1000 to about ~20,000 years, which separates intrinsic climatic oscillations with periods ranging from ~ 60 years to ~1000 years, from the longer time-scale periodicities (20,000 yr +) involving external forcing associated with Milankovitch cycles. The absence of natural oscillations with periods within the gap is consistent with cumulative evidence based on past data analyses, as well as with earlier theoretical and modeling studies.

scholarly journals The Sampling Distribution of Disease-Associated Alleles

Genetics ◽  
1997 ◽  
Vol 147 (4) ◽  
pp. 1855-1861 ◽  
Author(s):  
Montgomery Slatkin ◽  
Bruce Rannala
Keyword(s):  
Low Frequency ◽  
Null Model ◽  
Sampling Distribution ◽  
Death Process ◽  
Published Data ◽  
Data Sets ◽  
Likelihood Functions ◽  
Alternative Hypotheses ◽  
Size Standard ◽  
Birth Death

Abstract A theory is developed that provides the sampling distribution of low frequency alleles at a single locus under the assumption that each allele is the result of a unique mutation. The numbers of copies of each allele is assumed to follow a linear birth-death process with sampling. If the population is of constant size, standard results from theory of birth-death processes show that the distribution of numbers of copies of each allele is logarithmic and that the joint distribution of numbers of copies of k alleles found in a sample of size n follows the Ewens sampling distribution. If the population from which the sample was obtained was increasing in size, if there are different selective classes of alleles, or if there are differences in penetrance among alleles, the Ewens distribution no longer applies. Likelihood functions for a given set of observations are obtained under different alternative hypotheses. These results are applied to published data from the BRCA1 locus (associated with early onset breast cancer) and the factor VIII locus (associated with hemophilia A) in humans. In both cases, the sampling distribution of alleles allows rejection of the null hypothesis, but relatively small deviations from the null model can account for the data. In particular, roughly the same population growth rate appears consistent with both data sets.

A waveform inversion technique for measuring elastic wave attenuation in cylindrical bars

Geophysics ◽  
1992 ◽  
Vol 57 (6) ◽  
pp. 854-859 ◽  
Author(s):  
Xiao Ming Tang
Keyword(s):  
Elastic Wave ◽  
Wave Attenuation ◽  
Waveform Inversion ◽  
Finite Size ◽  
Low Frequency ◽  
Frequency Range ◽  
Multiple Reflections ◽  
Low Frequencies ◽  
The Time Domain ◽  
Attenuation Values

A new technique for measuring elastic wave attenuation in the frequency range of 10–150 kHz consists of measuring low‐frequency waveforms using two cylindrical bars of the same material but of different lengths. The attenuation is obtained through two steps. In the first, the waveform measured within the shorter bar is propagated to the length of the longer bar, and the distortion of the waveform due to the dispersion effect of the cylindrical waveguide is compensated. The second step is the inversion for the attenuation or Q of the bar material by minimizing the difference between the waveform propagated from the shorter bar and the waveform measured within the longer bar. The waveform inversion is performed in the time domain, and the waveforms can be appropriately truncated to avoid multiple reflections due to the finite size of the (shorter) sample, allowing attenuation to be measured at long wavelengths or low frequencies. The frequency range in which this technique operates fills the gap between the resonant bar measurement (∼10 kHz) and ultrasonic measurement (∼100–1000 kHz). By using the technique, attenuation values in a PVC (a highly attenuative) material and in Sierra White granite were measured in the frequency range of 40–140 kHz. The obtained attenuation values for the two materials are found to be reliable and consistent.

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