In this paper, 2D seismic data and petrophysical logs of the Pabdeh Formation from four wells of the Mansuri oil field are utilized. ΔLog R method was used to generate a continuous TOC log from petrophysical data. The calculated TOC values by ΔLog R method, used for a multi-attribute seismic analysis. In this study, seismic inversion was performed based on neural networks algorithm and the resu...

Seismic tomography is a technique for illuminating the physical dynamics of the Earth by seismic waves generated by earthquakes or explosions. In both industry and academia, the seismic exploration does not yet have the capability of imaging seismic tomography in real-time and with high resolution. There are two reasons. First, at present raw seismic data are typically recorded on sensor nodes ...

In the seismic inversion model, as the neural network algorithm there are some problems, the convergence bad, accuracy is not high. This paper presents a seismic inversion based on artificial fish Swarm Optimization neural network models. First to initialize fish mapping of chaos optimization and ergodicity of artificial fish-swarm search and adaptive strategies of artificial fish-swarm algorit...

The main contribution of the present paper is to train efficient neural networks for seismic design of double layer grids subject to multiple-earthquake loading. As the seismic analysis and design of such large scale structures require high computational efforts, employing neural network techniques substantially decreases the computational burden. Square-on-square double layer grids with the va...

Power networks are among the most important infrastructures that without them, industrial, economic and social procedures will halt. Therefore, they should be planned for the most difficult conditions to provide services with minimum disruption. Power substations are of great importance to a power network, because any disruption in their components can produce extensive problems through the net...

This paper reviews the Quake-Catcher Network (QCN), a distributed computing seismic network that uses lowcost USB accelerometers to record earthquakes, and discusses the potential to incorporate QCN stations with traditional seismic networks. These very dense urban networks could then be used to create a working earthquake early warning system, as has been shown by our preliminary tests of the ...

The article describes the design of the Community Seismic Network, which is a dense open seismic network based on low cost sensors. The inputs are from sensors hosted by volunteers from the community by direct connection to their personal computers, or through sensors built into mobile devices. The server is cloud-based for robustness and to dynamically handle the load of impulsive earthquake e...

Presented herein is a methodology for the seismic and hydraulic assessment of the re-liability of urban water distribution networks (UWDN) based on general seismic assessment standards, as per the American Lifelines Alliance (ALA) guidelines, localized historical records of critical risk-of-failure metrics pertaining to the specific UWDN under assessment, and hydraulic simulations using adapted...

• “An Efficient Training Technique for a Neural-Network Controller for Seismically Excited Structures,” (reference [54]) by Liut et al. • “An overview of Some Non-Traditional Neural-Network Training Strategies for Seismic Response Suppression of Building Structures,” (reference [56]) by Liut et al. • “A Modified Gradient-Search Training Technique for Neural-Network Structural Control,” (referen...

The modern seismic sensor used to monitor volcanic activity can record raw seismic data for several years. This massive amounts of raw data recorded consists of information regarding earthquake’s origin time, location, velocity the wave traveled etc. To extract this information from the raw samples, current state of the art volcano monitoring systems rely on gathering these high volume data bac...