DUG’s Post

Register for #ASA186 so that you don't miss the Munk Award Lecture by Ross Chapman - Inference of geoacoustic model parameters from acoustic field data: Perspectives on Geoacoustic Inversion https://lnkd.in/gwA2vg2U

I am pleased to announce that our paper "Random noise attenuation in seismic data using an adaptive thresholding and the second‑order variant time‑reassigned synchrosqueezing transform" has been published in the journal of Acta Geophysica. You can download it using this link: https://lnkd.in/diygy6ss This work focuses on efficiently suppressing random noise in the temporal and frequency domains by precisely predicting instantaneous frequency with seismic signals' single-valued group delay. The time-reassigned synchrosqueezing transform (TSST) and its second-order variation (TSST2) provide fine-grained time-frequency representations (TFRs) for noise reduction. Building on these advances, we offer an effective noise suppression strategy that incorporates the adaptive thresholding model into the TSST2 framework and leverages sparse representation of the TFR via low-rank estimation. This approach successfully reduces noise while retaining important signal information. The suggested technique works trace by trace on recorded data, first converting it into a sparse subspace with TSST2.  

"Tools for the efficient analysis of surface waves from active and passive seismic data: exploring an NE-Italy perilagoon area with significant lateral variations" how to identify (and then solve) lateral variations? You can download and read the following paper: https://lnkd.in/g5ymhprf

“How Riedel shears express themselves in outcrop and seismic data” This is the second article in the series in which Molly Turko, PhD shares her great knowledge about Riedel shears. Read more here: https://lnkd.in/gKxZtxMf

PAGravf4.5 is always free and open. www.zcyphygeodesy.com/en/ PAGravf4.5 sets up the scientific gravity field approach system with the spatial domain integration algorithms based on boundary value theory and the spectral domain radial basis function approach algorithms to realize the all-element analytical modelling on gravity field in whole space on or outside the geoid from various heterogeneous observations in the different altitudes, cross-distribution and land-sea coexisting cases.

In First Break, September 2024, Goodway et al published a Special Topic paper on the theory of wavefield sampling. The authors claim that the Shannon/Nyquist sampling theorem is incorrect and should be replaced with the Fresnel zone theory developed in their paper. They state: “Consequently, the correct Fresnel Zone theory for the seismic wavefield sampling comb … replaces the non-applicable, incorrect signal theory Nyquist aliasing equation, which is commonly used to establish the limits to interpolation.” Hence, after 75 years of general acceptance that at least two samples per period/wavelength of the highest frequency/wavenumber are required for alias-free recording, this is now overruled by the authors. If true, such a drastic correction to common knowledge of signal theory would merit a peer-reviewed paper. However, Special Topic papers in First Break are not peer-reviewed.

Join Andrew Long as he kicks off a four-part webinar series on the fundamentals necessary to achieve high-resolution seismic imaging with towed streamer data. ‘Resolution Limits of Conventional Towed Streamer Acquisition’ is the first in this 4-part series. Find out the key factors during towed-streamer acquisition that influence the temporal frequency content available for seismic imaging. After identifying the best-practice spatial sampling limits of wide-tow multi-source shooting with long #GeoStreamer spreads, Andrew shows how even shorter spatial sampling intervals can exploit kilohertz frequencies produced by boomer and sparker source concepts used for 3D UHR (ultra-high-resolution) towed streamer surveys. This webinar series is suitable for anyone with a basic knowledge of reflection seismic principles, and it is a great chance to hear Andrew's expert commentary on this topic and discover the wide range of PGS solutions that are available. Watch the series now👇 #energysecurity #energytransition

Another interesting land seismic data example! Note how the wavelet from a 50-feet depth source is very different from that at 100 feet and 5 feet. This shows how the thin near surface has a big impact on the data. A vibrator will have a bigger effect from the near surface. Understanding this helps acquisition and processing. More information is in my free SEG Distinguished Lecture, May 23: https://lnkd.in/gZU5zkXz

In this paper, the authors propose a random subspace sampling method, RSS, by sampling missing items from the corresponding feature histogram distributions in random subspaces, which is effective and efficient at different levels of missing data. https://lnkd.in/gypE8rNr Jianxin Wu

In recent years, the leaps in artificial intelligence have revolutionized our ability to analyze vast datasets and identify underlying patterns. This evolution holds significant promise for earthquake engineering, particularly through the lens of structural health monitoring. Traditionally, our approach to understanding earthquake engineering has been rooted in experimental and numerical studies of structural elements and systems. While invaluable, these methods face notable challenges, including the complexities of soil-structure interactions, the unique characteristics of 3D ground motions, and the impact of non-structural components. Not to mention the financial burden of such comprehensive studies. Imagine, for a moment, if a substantial number of buildings in Christchurch had been equipped with structural health monitoring systems prior to the earthquake in February 2011. The data collected could have dramatically transformed our comprehension of earthquake engineering. Viewing each instrumented building as a live experiment offers an unparalleled opportunity to extract valuable insights, enabling us to refine, and possibly revamp our current models. In my opinion, the intersection of AI and structural health monitoring represents a frontier of knowledge and innovation in earthquake engineering. The necessity for both engineers and academics to engage deeply with structural health monitoring has never been more critical. Looking forward for the presentation and the discussions it will ignite. #structuralengineering #civilengineering #earthquakeengineering