We report observations and analysis of 30 kHz radio emissions (sferics) from lightning discharges associated with 26 terrestrial gamma ray flashes (TGFs) recorded by the RHESSI satellite over Caribbean Americas, between 1500 4000 km away magnetic field sensors located at Duke University. Thirteen TGFs are found to occur within −3/+1 ms positive polarity direction subsatellite point, strongly indicating that linked these discharges. The event timing sferic finding reveals a ∼300 radius circle...

We have developed a frequency-domain joint electromagnetic (EM) and seismic inversion algorithm for reservoir evaluation exploration applications. EM data are jointly inverted using cross-gradient constraint that enforces structural similarity between the conductivity image compressional wave (P-wave) velocity image. The is based on Gauss-Newton optimization approach. Because of ill-posed nature inverse problem, regularization used to constrain solution. multiplicative technique selects...

We present a simultaneous multifrequency inversion approach for seismic data interpretation. This algorithm inverts all frequency components simultaneously. A data-weighting scheme balances the contributions from different so process does not become dominated by high-frequency components, which produce velocity image with many artifacts. Gauss-Newton minimization achieves high convergence rate and an accurate reconstructed image. By introducing modified adjoint formulation, we can calculate...

The transient ELF(∼50–5000 Hz) magnetic field radiated by lightning discharges across North America was continuously measured at Duke University during the summer of 2000. In total, 881 sprite‐associated over 17 days were analyzed. We report in detail on 76 sprites for which we could reliably determine charge moment change from ELF data time sprite onset. initiation a is found to be as low 120 C km. By folding together distributions sprite‐producing and all positive lightning, find that...

We present a contrast source inversion (CSI) technique which is based on finite-difference (FD) solver for use in microwave biomedical imaging. The algorithm capable of inverting complex-permittivity data sets without the explicit forward at each iteration. FD frequency domain, utilizes perfectly matched layer (PML) boundary conditions, and stiffness matrix solved via an LU decomposition Gaussian elimination. An important feature FD-CSI that associated with depends only upon background...

We present a contrast source inversion (CSI) algorithm using finite-difference (FD) approach as its backbone for reconstructing the unknown material properties of inhomogeneous objects embedded in known background medium. Unlike CSI method integral equation (IE) approach, FD-CSI can readily employ an arbitrary medium background. The ability to use has made this very suitable be used through-wall imaging and time-lapse applications. Similar IE-CSI sources function are updated alternately...

PreviousNext No AccessSEG Technical Program Expanded Abstracts 2014FWI without low frequency data - beat tone inversionAuthors: Wenyi Hu*Wenyi Hu*Advanced Geophysical Technology, Inc.Search for more papers by this authorhttps://doi.org/10.1190/segam2014-0978.1 SectionsAboutPDF/ePub ToolsAdd to favoritesDownload CitationsTrack CitationsPermissions ShareFacebookTwitterLinked InRedditEmail Abstract Inspired interference tone, a phenomenon commonly used musicians tuning check, we developed novel...

In current times, reconstruction of remote sensing images using super-resolution is a prominent topic study. Remote data have complex spatial distribution. Compared with natural pictures, pictures often contain subtler and more complicated information. Most algorithms cannot restore all the information contained in when reconstructing them. The content some areas reconstructed may be too smooth, even color changes, resulting lower quality images. response to problems presenting about...

Previous research has shown that the statistical measurements of charge moment changes in sprite‐producing lightning are general agreement with predictions based on conventional breakdown theory for sprite initiation mesosphere. Measurements have progressed to point where a detailed, event‐level quantitative comparison between and could more rigorously test existing theories by estimating electric fields above thunderstorm clouds responsible initiation. We selected this analysis set events...

We have applied the finite-difference contrast-source inversion (FDCSI) method to seismic full-waveform problems. The FDCSI is an iterative nonlinear algorithm. However, unlike conjugate gradient and Gauss-Newton method, does not solve any full forward problem explicitly in each step of process. This feature makes very efficient solving large-scale computational It shown that FDCSI, with a significant lower computation cost, can produce results comparable quality those produced by better...

We present preconditioned non-linear conjugate gradient algorithms as alternatives to the Gauss-Newton method for frequency domain full-waveform seismic inversion. designed two preconditioning operators. For first preconditioner, we introduce inverse of an approximate sparse Hessian matrix. The matrix, which is highly sparse, constructed by judiciously truncating matrix based on examining auto-correlation and cross-correlation Jacobian As second employ approximation This preconditioner...

Full waveform inversion (FWI) is an advanced seismic processing method for high-resolution subsurface geophysical property reconstruction through a data-fitting procedure. When low-frequency data are not available, conventional FWI often suffers from the cycle-skipping issue caused by severe nonlinearity nature of standard L2 norm objective function, inducing strong artifacts in reconstructed models.

A deep-learning-based workflow is proposed in this paper to solve the first-arrival picking problem for near-surface velocity model building. Traditional methods, such as short-term average/long-term average method, perform poorly when signal-to-noise ratio low or geologic structures are complex. This challenging task formulated a segmentation accompanied by novel postprocessing approach identify pickings along boundary. The includes three parts: deep U-net segmentation, recurrent neural...

To effectively overcome the cycle-skipping issue in full-waveform inversion (FWI), we have developed a deep neural network (DNN) approach to predict absent low-frequency (LF) components by exploiting hidden physical relation connecting LF and high-frequency (HF) data. efficiently solve this challenging nonlinear regression problem, two novel strategies are proposed design DNN architecture optimize learning process: (1) dual data feed structure (2) progressive transfer learning. With...

In this work, we successfully applied an alternative formulation of the perfectly matched layer (PML), so-called nearly PML (NPML), to acoustic wave propagation modeling. The NPML shows great advantages over standard complex stretched coordinate PML. deviates from through inexact variable change, but fact only affects behavior in layer, which is outside region interest. equivalence wave-absorbing performance between these two formulations (the and formulation) 3D Cartesian coordinates for...

In this paper, we will explore the possibility of synthesizing low-frequency data from high-frequency data. The synthesized are used to improve full-waveform inversion (FWI). Unlike all previously methods, best our knowledge, is first attempt utilize a driven approach solve problem. We propose learn low wavenumber information in FWI via Deep Inception based Convolutional Networks. Once deep learning network sufficiently trained, can be predicted with high accuracy on completely different...

First break picking is an inevitable process in land seismic data processing, which involves a huge amount of human labor to perform. Even after decades investigation on the first process, there are still enormous challenges developing robust automatic approach. Although many experts proposed techniques solve problems automatically, no solid solutions avoid labors during process. In late 20th century, rise artificial intelligence and advancement computer hardware have overcome some but level...

The simultaneous-source technology for high-density seismic acquisition is a key solution to efficient surveying. It cost-effective method when blended subsurface responses are recorded within short time interval using multiple sources. A following deblending process, however, needed separate signals contributed by individual Recent advances in deep learning and its data-driven approach toward feature engineering have led many new applications variety of processing problems. still challenge,...

Although seismic industry has been investigating decades on solving the first break picking problems automatically, there are still enormous challenges during investigation. Even till today, not solid solutions to avoid human labors manually pick data by geophysicists. With raise of deep learning and powerful hardware, many those can be overcome. In this work, we propose a semi-supervised neural network achieve automatic for in data. The is designed perform with both unlabeled limited amount...

In recent years, with the rapid development of artificial intelligence technology, computer vision-based pest detection technology has been widely used in agricultural production. Tomato diseases and pests are serious problems affecting tomato yield quality, so it is important to detect them quickly accurately. this paper, we propose a disease model based on an improved YOLOv5n overcome low accuracy large size traditional methods. Firstly, use Efficient Vision Transformer as feature...

We developed a seismic‐attenuation‐tomography algorithm for improving image amplitude fidelity and other geophysical applications. This is based upon the centroid‐frequency‐shift method. However, compared with conventional method, our has been significantly improved through introduction of several novel techniques. First, specially designed source‐amplitude frequency spectrum function enables this Q tomography to handle more realistic source spectra. Second, multi‐index active‐set method...