Results 51 to 60 of about 24,964,284 (390)
Detection, Analysis, and Removal of Glitches From InSight's Seismic Data From Mars
Earth and Space Science, 2020 The instrument package SEIS (Seismic Experiment for Internal Structure) with the three very broadband and three short‐period seismic sensors is installed on the surface on Mars as part of NASA's InSight Discovery mission.
John‐Robert Scholz +35 more
semanticscholar +1 more source
Seismic data interpolation based on U-net with texture loss [PDF]
Geophysics, 2019 Seismic data interpolation is an effective way of recovering missing traces and obtaining enough information for subsequent processing. Unlike traditional methods, deep neural network (DNN)-based methods do not need to make assumptions because they can ...
Wenqian Fang +3 more
semanticscholar +1 more source
Frontiers in Earth Science, 2022 Paleostress plays an important role in controlling the formation and distribution of reservoir fractures, which is a key factor controlling the production of oil and gas from unconventional reservoirs.
Guidong Ping +6 more
doaj +1 more source
Seismic Data Interpolation Using Dual-Domain Conditional Generative Adversarial Networks
IEEE Geoscience and Remote Sensing Letters, 2020 Seismic data interpolation is an effective way to reconstruct missing seismic traces and to improve the quality of the seismic data set. In the field of deep learning, generative adversarial networks are capable of data generation and interpolation and ...
D. Chang +6 more
semanticscholar +1 more source
Estimation of acoustic impedance from seismic data using temporal convolutional network [PDF]
SEG technical program expanded abstracts, 2019 In exploration seismology, seismic inversion refers to the process of inferring physical properties of the subsurface from seismic data. Knowledge of physical properties can prove helpful in identifying key structures in the subsurface for hydrocarbon ...
Ahmad Mustafa, M. Alfarraj, G. AlRegib
semanticscholar +1 more source
Seismic data clustering management system [PDF]
, 2011 This is the abstract of the paper given at the conference. Copyright @ 2011 The Authors.Over the last years, seismic images have increasingly played a vital role to the study of earthquakes.
Banitsas, K +5 more
core
Deep-seismic-prior-based reconstruction of seismic data using convolutional neural networks [PDF]
Geophysics, 2019 The reconstruction of seismic data with missing traces has been a long-standing issue in seismic data processing. Deep learning (DL) has emerged as a popular tool for seismic interpolation; it learns priors from training data sets of incomplete/complete ...
Qun Liu, Lihua Fu, Meng Zhang
semanticscholar +1 more source
A Bottom‐Up Design Framework for Multifunctional Lattice Metamaterials
Advanced Science, EarlyView.This study introduces a generative AI framework for designing multifunctional lattice metamaterials. The method combines 3D Gaussian voxel generation with deep learning, enabling greater design freedom and structural performance. The optimized lattice metamaterials achieve enhanced energy absorption by 40–200% compared to conventional structures and ...
Zongxin Hu +13 more
wiley +1 more source
Re-Analysis of HFT Data Using the Apollo Lunar Surface Gravimeter Data [PDF]
, 2008 Introduction: The Apollo Passive Seismic Experiment (PSE) was carried out on Apollo 12, 14, 15 and 16. Network observations of four seismic stations were performed for five years from 1972 to 1977. The PSE was a successful mission that informed us of the
Hagermann, A. +4 more
core
Active Metamaterials with Tunable Shear Nonreciprocity and Nonlinear Dynamics
Advanced Science, EarlyView.Active gear‐based mechanical metamaterials enable simultaneous control of translational and torsional stiffnesses by 30–100×, break shear reciprocity under positive versus negative loads, broadly tune resonant frequencies, and offer programmable dynamic responses.
Xin Fang, Miao Yu, Dianlong Yu, Li Cheng
wiley +1 more source