scholarly journals Interference suppression by adaptive cancellation in a high Arctic seismic experiment

Geophysics ◽  
2017 ◽  
Vol 82 (4) ◽  
pp. V201-V209 ◽  
Author(s):  
David Harris ◽  
Julie Albaric ◽  
Bettina Goertz-Allmann ◽  
Daniela Kuehn ◽  
Sebastian Sikora ◽  
...  
Keyword(s):  
Seismic Data ◽  
Electromagnetic Interference ◽  
Low Cost ◽  
Interference Suppression ◽  
High Arctic ◽  
Microseismic Monitoring ◽  
Process Noise ◽  
Seismic Experiment ◽  
Passive Seismic ◽  
Adaptive Cancellation

Mechanical and electromagnetic interference (process noise) is common in seismic data recorded to monitor and characterize induced microseismicity during industrial injection and production operations. We have developed a case study of adaptive cancellation to reduce observed process noise in passive seismic data recorded during the 2014 injection test at the [Formula: see text] Lab research site in Spitsbergen. Our results suggest that adaptive cancellation is effective when major sources of interference are readily identifiable. Adaptive cancellation requires these sources to be instrumented separately but conceivably with low-cost sensors. We suggest that adaptive cancellation should be considered routinely when planning microseismic monitoring operations when strong industrial or anthropogenic noise is anticipated. Interference suppression algorithms are sufficiently simple that they could be implemented in acquisition systems to avoid archival of noise reference data.

Passive Seismic Marchenko Imaging

2020 ◽  
Author(s):  
Zhongyuan Jin
Keyword(s):  
Free Surface ◽  
Seismic Data ◽  
Low Cost ◽  
Body Waves ◽  
Seismic Survey ◽  
Significant Difference ◽  
Passive Seismic ◽  
Seismic Acquisition ◽  
Imaging Property ◽  
Internal Multiples

<p>In recent years, seismic interferometry (SI) has been widely used in passive seismic data, it allows to retrieve new seismic responses among physical receivers by cross-correlation or multidimensional deconvolution (MDD). Retrieval of reflected body waves from passive seismic data has been proved to be feasible. Marchenko method, as a new technique, retrieves Green’s functions directly inside the medium without any physical receiver there. Marchenko method retrieves precise Green’s functions and the up-going and down-going Green’s functions can be used in target-oriented Marchenko imaging, and internal multiples related artifacts in Marchenko image can be suppressed. </p><p>Conventional Marchenko imaging uses active seismic data, in this abstract, we propose the method of passive seismic Marchenko imaging (PSMI) which retrieves Green’s functions from ambient noise signal. PSMI employs MDD method to obtain the reflection response without free-surface interaction as an input for Marchenko algorithm, such that free-surface multiples in the retrieved shot gathers can be eliminated, besides, internal multiples don’t contribute to final Marchenko image, which means both free-surface multiples and internal multiples have been taken into account. Although the retrieved shot gathers are contaminated by noises, the up-going and down-going Green’s functions can be still retrieved. Results of numerical tests validate PSMI’s feasibility and robustness. PSMI provides a new way to image the subsurface structure, it combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging, as well as the advantage that there are no artifacts caused by internal multiples and free-surface multiples.</p><p>Overall, the significant difference between PSMI and conventional Marchenko imaging is that passive seismic data is used into Marchenko scheme, which extends the Marchenko imaging to passive seismic field. Passive seismic Marchenko imaging avoids the effects of free-surface multiples and internal multiples in the retrieved shot gathers. PSMI combines the low-cost property of passive seismic acquisition and target-oriented imaging property of Marchenko imaging which is promising in future field seismic survey.</p><p>This work is supported by the Fundamental Research Funds for the Central Universities (JKY201901-03). </p>

scholarly journals Characterizing the complexity of seismic signals at slow-moving clay-rich debris slides: The Super-Sauze (Southeastern France) and Pechgraben (Upper Austria) case studies

2017 ◽  
Author(s):  
Naomi Vouillamoz ◽  
Sabrina Rothmund ◽  
Manfred Joswig
Keyword(s):  
Case Studies ◽  
Seismic Data ◽  
Early Warning Systems ◽  
Microseismic Monitoring ◽  
Seismic Signals ◽  
Warning Systems ◽  
Detection Systems ◽  
Upper Austria ◽  
Passive Seismic ◽  
Slow Moving

Abstract. Soil and debris slides are prone to rapid and dramatic reactivation. Deformation within the instability is accommodated by sliding, whereby weak seismic energies are released through material deformation. Thus, passive microseismic monitoring provides information that relate to the slope dynamics. In this study, passive seismic data acquired at Super-Sauze (Southeastern France) and Pechgraben (Upper Austria) slow-moving clay-rich debris slides (“clayey landslides”) are investigated. Observations are benchmarked to previous similar case studies to provide a comprehensive and homogenized typology of seismic signals at clayey landslides. A well knowledge of the various seismic signals potentially triggered by the slope deformation is crucial for the future development of automatic detection systems to be implemented in early-warning systems. Detected seismic events range from short duration (

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