Many oil and gas fields, especially non-conventional shale and compacted sand reservoirs, have formation anisotropy. The acoustic anisotropy measurement of cores in these reservoirs can guide drilling, well logging, and exploitation. However, almost all core holders are designed for cylinder cores, which are not suitable for all-directional measurements. A three-dimensional measurement device was designed on the basis of the cross-hole sonic logging method. This device mainly consisted of two pairs of transducers, a signal generator, an oscillograph, an omnidirectional positioning system, and a computer control system. By adjusting the measurement latitude and longitude circle automatically, this device scanned spherical sample rocks and obtained full-wave waveforms in all directions. Experiments were performed taking granite from the Jiaodong Peninsula, China, as an example, and the arrival times and velocities of the longitudinal and shear waves were calculated based on the full-wave waveforms. Thereafter, anisotropic physical characterizations were carried out on the basis of these velocities. These data play an important role in guiding formation fracturing and analyzing the stability of borehole walls.
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http://dx.doi.org/10.3390/s22239473 | DOI Listing |
Nano Lett
December 2024
University of Stuttgart, Institute for Functional Matter and Quantum Technologies, Stuttgart 70569, Germany.
Coupling subcycle THz pulses to a scanning tunneling microscope (STM) enables ultrafast spectroscopy at the atomic scale. This technique critically depends on the shape of the THz near-field waveform in the tunnel junction. We characterize the THz electric field waveform in the STM junction by electro-optic sampling of tip-scattered THz light (-EOS) and pulse correlation using the THz-induced current.
View Article and Find Full Text PDFPLoS One
July 2023
Department of Clinical Sciences, Faculty of Veterinary Medicine, Utrecht University, Utrecht, The Netherlands.
The reliability of surface electromyography (sEMG) has not been adequately demonstrated in the equine literature and is an essential consideration as a methodology for application in clinical gait analysis. This observational study investigated within-session, intra-subject (stride-to-stride) and inter-subject reliability, and between-session reliability of normalised sEMG activity profiles, from triceps brachii (triceps), latissimus dorsi (latissimus), longissimus dorsi (longissimus), biceps femoris (biceps), superficial gluteal (gluteal) and semitendinosus muscles in n = 8 clinically non-lame horses during in-hand trot. sEMG sensors were bilaterally located on muscles to collect data during two test sessions (session 1 and 2) with a minimum 24-hour interval.
View Article and Find Full Text PDFSci Rep
May 2023
Department of Engineering, Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, 466-8555, Japan.
In this study, we numerically demonstrate how the response of recently reported circuit-based metasurfaces is characterized by their circuit parameters. These metasurfaces, which include a set of four diodes as a full wave rectifier, are capable of sensing different waves even at the same frequency in response to the incident waveform, or more specifically the pulse width. This study reveals the relationship between the electromagnetic response of such waveform-selective metasurfaces and the SPICE parameters of the diodes used.
View Article and Find Full Text PDFPhys Med Biol
May 2023
North Carolina State University, Raleigh, NC, United States of America.
. With the ultimate goal of reconstructing 3D elasticity maps from ultrasound particle velocity measurements in a plane, we present in this paper a methodology of inverting for 2D elasticity maps from measurements on a single line..
View Article and Find Full Text PDFJ Imaging
November 2022
Department of Information Sciences and Technology, George Mason University, Fairfax, VA 22030, USA.
Seismic full wave inversion (FWI) is a widely used non-linear seismic imaging method used to reconstruct subsurface velocity images, however it is time consuming, has high computational cost and depend heavily on human interaction. Recently, deep learning has accelerated it's use in several data-driven techniques, however most deep learning techniques suffer from overfitting and stability issues. In this work, we propose an edge computing-based data-driven inversion technique based on supervised deep convolutional neural network to accurately reconstruct the subsurface velocities.
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