Design and implementation of forward modeling algorithm for anisotropic seismic waves

2020 ◽  
Author(s):  
Wei Wei ◽  
Fan Gao ◽  
BeiBei Zhang ◽  
Rafal Scherer ◽  
Mingwei Hui ◽  
...  
Keyword(s):  
Seismic Waves ◽  
Forward Modeling ◽  
Design And Implementation ◽  
Modeling Algorithm

scholarly journals TESLA GPUs versus MPI with OpenMP for the Forward Modeling of Gravity and Gravity Gradient of Large Prisms Ensemble

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
Carlos Couder-Castañeda ◽  
Carlos Ortiz-Alemán ◽  
Mauricio Gabriel Orozco-del-Castillo ◽  
Mauricio Nava-Flores
Keyword(s):  
Parallel Computing ◽  
Graphics Processing Units ◽  
Forward Modeling ◽  
Gravity Gradient ◽  
Constant Density ◽  
Gravitational Fields ◽  
Design And Implementation ◽  
Cuda Technology ◽  
Performance Results ◽  
Graphics Processing

An implementation with the CUDA technology in a single and in several graphics processing units (GPUs) is presented for the calculation of the forward modeling of gravitational fields from a tridimensional volumetric ensemble composed by unitary prisms of constant density. We compared the performance results obtained with the GPUs against a previous version coded in OpenMP with MPI, and we analyzed the results on both platforms. Today, the use of GPUs represents a breakthrough in parallel computing, which has led to the development of several applications with various applications. Nevertheless, in some applications the decomposition of the tasks is not trivial, as can be appreciated in this paper. Unlike a trivial decomposition of the domain, we proposed to decompose the problem by sets of prisms and use different memory spaces per processing CUDA core, avoiding the performance decay as a result of the constant calls to kernels functions which would be needed in a parallelization by observations points. The design and implementation created are the main contributions of this work, because the parallelization scheme implemented is not trivial. The performance results obtained are comparable to those of a small processing cluster.

A modified-boundary condition algorithm for efficient 3D forward modeling of CSEM data

2021 ◽  
Author(s):  
Rahul Dehiya
Keyword(s):  
Boundary Condition ◽  
Finite Difference ◽  
Source Term ◽  
Forward Modeling ◽  
Field Vector ◽  
Fine Grid ◽  
Boundary Field ◽  
Radiation Boundary ◽  
3D Forward Modeling ◽  
Modeling Algorithm

<p>I present a newly developed 3D forward modeling algorithm for controlled-source electromagnetic data. The algorithm is based on the finite-difference method, where the source term vector is redefined by combining a modified boundary condition vector and source term vector. The forward modeling scheme includes a two-step modeling approach that exploits the smoothness of the electromagnetic field. The first step involves a coarse grid finite-difference modeling and the computation of a modified boundary field vector called radiation boundary field vector. In the second step, a relatively fine grid modeling is performed using radiation boundary conditions. The fine grid discretization does not include stretched grid and air medium. The proposed algorithm derives computational efficiency from a stretch-free discretization, air-free computational domain, and a better initial guess for an iterative solver. The numerical accuracy and efficiency of the algorithm are demonstrated using synthetic experiments. Numerical tests indicate that the developed algorithm is one order faster than the finite-difference modeling algorithm in most of the cases analyzed during the study. The radiation boundary method concept is very general; hence, it can be implemented in other numerical schemes such as finite-element algorithms.</p>

The physics and simulation of wave propagation at the ocean bottom

Geophysics ◽  
2004 ◽  
Vol 69 (3) ◽  
pp. 825-839 ◽  
Author(s):  
José M. Carcione ◽  
Hans B. Helle
Keyword(s):  
Wave Propagation ◽  
Seismic Waves ◽  
Differential Operators ◽  
Plane Boundary ◽  
Acoustic Medium ◽  
Frequency Domain Method ◽  
Ocean Bottom ◽  
Interface Waves ◽  
Physical Phenomena ◽  
Modeling Algorithm

We investigate some aspects of the physics of wave propagation at the ocean bottom (ranging from soft sediments to crustal rocks). Most of the phenomena are associated to the presence of attenuation. The analysis requires the use of an anelastic stress‐strain relation and a highly accurate modeling algorithm. Special attention is given to modeling the boundary conditions at the ocean‐bottom interface and the related physical phenomena. For this purpose, we further develop and test the pseudospectral modeling algorithm for wave propagation at fluid‐anelastic solid interfaces. The method is based on a domain‐decomposition technique (one grid for the fluid part and another grid for the solid part) and the Fourier and Chebyshev differential operators. We consider the reflection, transmission, and propagation of seismic waves at the ocean bottom, modeled as a plane boundary separating an acoustic medium (ocean) and a viscoelastic solid (sediment). The main physical phenomena associated with this interface are illustrated, namely, amplitude variations with offset, the Rayleigh window, and the propagation of Scholte and leaky Rayleigh waves. Modeling anelasticity is essential to describe these effects, in particular, amplitude variations near and beyond the critical angle, the Rayleigh window, and the dissipation of the fundamental interface mode. The physics of wave propagation is investigated by means of a plane‐wave analysis and the novel modeling algorithm. A wavenumber–frequency domain method is used to compute the reflection coefficient and phase angle from the synthetic seismograms. This method serves to verify the algorithm, which is shown to model with high accuracy the Rayleigh‐window phenomenon and the propagation of interface waves. The modeling is further verified by comparisons with the analytical solution for a fluid‐solid interface in lossless media, with source and receivers away from and at the ocean bottom. Using the pseudospectral modeling code, which allows general material variability, a complete and accurate characterization of the seismic response of the ocean bottom can be obtained. An example illustrates the effects of attenuation on the propagation of dispersive Scholte waves at the bottom of the North Sea.

scholarly journals Design and Implementation of a Programmable Multi-Parametric Five Degrees of Freedom Seismic Waves Geo-Mechanics Simulation IoT Platform

2019 ◽  
Author(s):  
Hasan Tariq ◽  
Farid Touati ◽  
Mohammed Abdulla E. Al-Hitmi ◽  
Damiano Crescini ◽  
Adel Ben Mnaouer
Keyword(s):  
Web Application ◽  
Degrees Of Freedom ◽  
Seismic Waves ◽  
Ground Motions ◽  
Machine Learning Algorithms ◽  
Event Management ◽  
Observation Study ◽  
Arrival Times ◽  
Design And Implementation ◽  
Prime Concern

Natural calamities observation, study and simulation has always been a prime concern for disaster management agencies. Billions of dollars are spent annually to explore geo-seismic movements especially earthquakes but it has always been a unique accident. The real-time study of seismic waves, ground motions, and earthquakes always needed a programmable mechanical structure capable of physically producing the identical geo-seismic motions with seismology domain definitions. A programmable multi-parametric five degrees of freedom electromechanical seismic wave events simulation platform to study and experiment seismic waves and earthquakes realization in the form of geo-mechanic ground motions is exhibited in this work. The proposed platform was programmed and interfaced through an IoT cloud-based Web application. The geo-mechanics was tested in the range of i) frequencies of extreme seismic waves from 0.1Hz to 178Hz; ii) terrestrial inclinations from -10.000° to 10.000°; iii) velocities of 1km/s to 25km/s iv) variable arrival times 1us to 3000ms; v) magnitudes M1.0 to M10.0 earthquake; vi) epi-central and hypo-central distances of 290+ and 350+ kilometers. Wadati and triangulation methods have been used for entire platform dynamics design and implementation as one of key contributions in this work. This platform is as an enabler for a variety of applications such as training self-balancing and calibrating seismic-resistant designs and structures in addition to studying and testing seismic detection devices as well as motion detection sensors. Nevertheless, it serves as an adequate training colossus for machine learning algorithms and event management expert systems.

The parallel 3D magnetotelluric forward modeling algorithm

2006 ◽  
Vol 3 (4) ◽  
pp. 197-202 ◽  
Author(s):  
Tan Handong ◽  
Tong Tuo ◽  
Lin Changhong
Keyword(s):  
Forward Modeling ◽  
Modeling Algorithm

3D forward modeling of controlled-source electromagnetic data based on radiation boundary method

Geophysics ◽  
2020 ◽  
pp. 1-79
Author(s):  
Rahul Dehiya
Keyword(s):  
Electromagnetic Field ◽  
Boundary Conditions ◽  
Forward Modeling ◽  
Coarse Grid ◽  
Fine Grid ◽  
Radiation Boundary Conditions ◽  
Controlled Source ◽  
Electromagnetic Data ◽  
Radiation Boundary ◽  
Modeling Algorithm

I have developed an efficient three-dimensional forward modeling algorithm based on radiation boundary conditions for controlled-source electromagnetic data. The proposed algorithm derives computational efficiency from a stretch-free discretization, air-free computational domain, and a better initial guess for an iterative solver. A technique for estimation of optimum grid stretching for multi-frequency modeling of electromagnetic data is described. This technique is similar to the L-curve method used for the estimation of the trade-off parameter in inversion. Using wavenumber-domain analysis, it is illustrated that as one moves away from the source, the electromagnetic field varies smoothly even in case of a complex model. A two-step modeling algorithm based on radiation boundary conditions is developed by exploiting the smoothness of the electromagnetic field. The first step involves a coarse grid finite-difference modeling and computation of a radiation boundary field vector. In the second step, a relatively fine grid modeling is performed with radiation boundary conditions. The fine grid discretization does not include stretched grid and air medium. An initial solution derived from coarse grid modeling is used for fine grid modeling. Numerical experiments demonstrate that the developed algorithm is one order faster than the finite-difference modeling algorithm in most of the cases presented.

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