Physics-guided data-driven seismic inversion

Author: qwta

August undefined, 2024

WebbDeep learning-based methods gain great popularity because of their powerful ability to obtain exact solutions for geophysical inverse problems. However, those deep learning methods that use seismic data as the only input lead to difficult training and unstable inversion results (i.e., transverse discontinuity or geologic unreliability). Webb19 mars 2024 · The second approach is referred to as “physics-guiding.” Based on recent progress in wave theory-designed (i.e., physics-based) networks, we have developed a …

Physics-Guided Data-Driven Seismic Inversion: Recent Progress …

http://brendt.wohlberg.net/publications/lin-2024-physics.html Webb29 nov. 2024 · Particularly, data-driven seismic inversion techniques have been recently developed (Zhang and Lin, 2024;Wu and Lin, 2024;Araya-Polo et al., 2024). To give an idea of how much training data... crawfish house near me

Physics-guided convolutional neural network (PhyCNN) for data-driven …

Webb17 sep. 2024 · Physics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling Ruiyang Zhang, Yang Liu, Hao Sun Seismic events, among … Webb6 jan. 2024 · Seismic Inversion Physics-guided deep learning for seismic inversion with hybrid training and uncertainty analysis DOI: 10.1190/geo2024-0312.1 Authors: Jian Sun … djays fashion

Physics-guided deep learning for seismic inversion

Deep physics-aware stochastic seismic inversion GEOPHYSICS

WebbCurrently, most seismic inversion problems are addressed by: physics-driven seismic inversion based on adjoint theory (commonly used in the geophysical community). This method attempts to minimize iteratively a cost function defined by the differences between the observed and calculated data (e.g., \(l^2\)-norm). WebbABSTRACT Seismic velocity inversion plays a vital role in various applied seismology processes. A series of deep learning methods have been developed that rely purely on … crawfish house houmaWebb15 sep. 2024 · A pre-stack inversion is performed to estimate elastic properties like VP, VS, r of the earth’s subsurface. Pre-stack inversions are generally solved employing a global or local optimization technique and performed on each CDPs (common-depth-point) separately to estimate the elastic properties. djays institute of cosmetology

"Webb1 sep. 2024 · In this paper, we develop new physics-informed data augmentation techniques based on convolutional neural networks. Specifically, our methods leverage … " - Physics-guided data-driven seismic inversion

Physics-guided data-driven seismic inversion

IET Digital Library: Applications of Deep Learning in …

Webb9 aug. 2024 · Seismic inversion is the inverse problem: given actual surface measurements, infer what subsurface configuration would give rise to those … WebbPhysics-guided Convolutional Neural Network (PhyCNN) for Data-driven Seismic Response Modeling Ruiyang Zhanga, Yang Liub, Hao Suna,c, aDepartment of Civil and Environmental Engineering, Northeastern University, Boston, MA 02115, USA bDepartment of Mechanical and Industrial Engineering, Northeastern University, Boston, MA 02115, USA

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Webbgreater generalization ability than purely physics-based and purely data-driven approaches. 1 Introduction Seismic full-waveform inversion (FWI) attempts to reconstruct an image of the subsurface geology from measurements of natural or artiﬁcially produced seismic waves that have travelled through the subsurface. WebbAbstract: We present the Seismic Laboratory for Imaging and Modeling/Monitoring (SLIM) open-source software framework for computational geophysics and, more generally, inverse problems involving the wave-equation (e.g., seismic and medical ultrasound), regularization with learned priors, and learned neural surrogates for multiphase flow …

WebbResults indicate that the predictions of the trained network are susceptible to facies proportions, the rock-physics model, and source-wavelet parameters used in the training data set. Finally, we apply CNN inversion on the Volve field data set from offshore Norway. Webb14 dec. 2024 · Abstract: Geostatistical seismic rock physics amplitude-versus-angle (AVA) inversion allows the joint prediction of rock and fluid properties from seismic reflection …

WebbIn traditional model-driven impedance inversion methods, the low-frequency impedance background is from an initial model and is almost unchanged during the inversion process. Moreover, the inversion results are limited by the quality of the modeled seismic data and the extracted wavelet. WebbSeismic Converted Waves Velocity Model Building using VSP-driven Approach Ali Abdulla Shaiban (Saudi Aramco) 14:35 - 14:55 Coffee Break - 20 min Session 3 IMPACT OF SEISMIC ACQUISITION AND PROCESSING ON QI -PART 2 14:55 - 16:10 Session Chairs: Mohamed Zainal (Saudi Aramco) & TBC Impact of Pre-Stack Seismic Data Conditioning …

Webb13 apr. 2024 · Adaptive learning is implemented via an iterative physics-driven data augmentation strategy. A deterministic inversion is regularized by a penalty term built …

Webb22 nov. 2024 · Abstract: The low-frequency seismic data provide crucial information for guiding the full-waveform inversion (FWI), especially when strong reflectors exist in the velocity model. However, hardware limitations make it difficult to acquire low-frequency data. To overcome the nonlinearity and ill-posedness caused by the absence of the low … djay software freeWebbSeismic inversion is the inverse problem: given actual surface measurements, infer what subsurface configuration would give rise to those measurements. Like most inverse … djay software with spotifyWebb1 juli 2024 · Figure 1 Flow chart showing the discovery of dynamics from physical modeling to data-driven modeling Despite great progress in seeking accurate numerical approximator to nonlinear structural... djay twitchWebb23 mars 2024 · Data-Driven Seismic Waveform Inversion: A Study on the Robustness and Generalization Abstract: Full-waveform inversion is an important and widely used … djay websiteWebb8 apr. 2024 · Physics-Constrained Deep Learning of Geomechanical Logs. 地震数据点云上采样. Deep Learning for Irregularly and Regularly Missing 3-D Data Reconstruction. 地震检测. Intelligent Real-Time Earthquake Detection by Recurrent Neural Networks. 地震数据反演. Well-Logging Constrained Seismic Inversion Based on Closed-Loop ... djays school of beauty baton rougeWebbABSTRACT Velocity model inversion is one of the most important tasks in seismic exploration. Full-waveform inversion (FWI) can obtain the highest resolution in traditional velocity inversion methods, but it heavily depends on initial models and is computationally expensive. In recent years, a large number of deep-learning (DL)-based velocity model … djay streaming migrationWebbPhysics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion IEEE Signal Processing Magazine, Vol. 40, No. 1 Data … crawfish house opelousas