site stats

Deep learning inversion

WebJun 12, 2024 · Unlike the conventional inversion method based on physical models, supervised deep-learning methods are based on big-data training rather than prior-knowledge assumptions. During the training stage, the network establishes a nonlinear projection from the multishot seismic data to the corresponding velocity models. WebMay 2, 2024 · Machine learning (ML) methods have been the focus of increasing attention in the geoscience community in recent years. The principal reason for this is the recent rise of deep learning (DL) in almost every field of science and engineering following the great success in computer vision tasks in the early 2010s (Krizhevsky et al. 2012). In the ...

Deep learning inversion with supervision: A rapid and cascaded …

WebAug 7, 2024 · The subsurface velocity model is crucial for high-resolution seismic imaging. Although full-waveform inversion (FWI) is a high-accuracy velocity inversion method, it inevitably suffers from challenging problems, including human interference, strong nonuniqueness, and high computing costs. As an efficient and accurate nonlinear … WebApr 13, 2024 · Abstract. Borehole resistivity measurements are routinely employed to measure the electrical properties of rocks penetrated by a well and to quantify the hydrocarbon pore volume of a reservoir. Depending on the degree of geometrical complexity, inversion techniques are often used to estimate layer-by-layer electrical … boulder county jail in longmont https://tanybiz.com

[1901.07733] Deep-Learning Inversion of Seismic Data

WebMay 1, 2024 · The inversion results show that when dealing with multiple defects of complex shape on a plate-like structure, DLIS methods can reduce the scale of training set effectively compared with other deep learning algorithms in experiment because a good starting model is provided and the nonlinearity between the global minimum and … WebFeb 1, 2024 · The deep-learning-based inversion does not depend on the kernel matrix and depth weighting, especially it can automatically extract useful inversion information without the need for human-curated activities. Compared with conventional inversion methods, deep learning is a data driven process that does not need to deal with non … WebMar 24, 2024 · Simulation results demonstrate that compared with the conventional matched-field inversion (MFI), the CNN with MRP alleviates the coupling between the geoacoustic parameters and is more robust to different source depths in the shallow water environment. ... Liu, H. Niu, Z. Li, and M. Wang, “ Deep-learning source localization … boulder county jobs board

Machine-learning inversion via adaptive learning and …

Category:Dreaming to Distill: Data-free Knowledge Transfer via

Tags:Deep learning inversion

Deep learning inversion

Deep learning inversion with supervision: A rapid and cascaded …

WebNFs are generative models that take advantage of invertible deep neural network architectures to learn complex distributions from training examples (Dinh, Sohl-Dickstein, and Bengio 2016). For example, in seismic inversion applications, we are interested in approximating the distribution of Earth models to use as priors in downstream tasks. WebABSTRACT We develop a novel physics-adaptive machine-learning (ML) inversion scheme showing optimal generalization capabilities for field data applications. We apply …

Deep learning inversion

Did you know?

WebSep 1, 2024 · How can deep learning be used by the geophysical community? ... For example, geophysical inversion requires good initial values and high accuracy modeling and suffers from local minimization. WebSep 3, 2024 · To demonstrate the effectiveness of the proposed DBN inversion method, two experiments were conducted as follows: experiment 1, scaled momentum learning …

WebNeural networks have been applied to seismic inversion problems since the 1990s. More recently, many publications have reported the use of Deep Learning (DL) neural networks capable of performing seismic inversion with promising results. However, when solving a seismic inversion problem with DL, each author uses, in addition to different DL models, … WebSep 3, 2024 · In this study, we propose an inversion strategy based on the deep learning (DL) deep belief network (DBN) to realise the instantaneous inversion of MT data. A scaled momentum learning rate is introduced to improve the convergence performance of the restricted Boltzmann machine during the DBN pre-training stage, and a novel activation …

WebNFs are generative models that take advantage of invertible deep neural network architectures to learn complex distributions from training examples (Dinh, Sohl-Dickstein, … WebMachine learning, and specifically deep-learning (DL) techniques applied to geophysical inverse problems, is an attractive subject, which has promising potential and, at the …

WebOct 13, 2024 · Analyzing the inversion results of the two methods, we can find that the joint deep learning inversion method is superior to the single-parameter deep learning inversion method in terms of boundary inscription and resistance value degree for both faults and caves. In particular, for the geological model of two water-bearing caves, …

WebSep 23, 2024 · Several deep-learning inversion strategies have been developed for geophysical modeling and are mainly applicable for two-dimensional (2-D) subsurface imaging. Despite their effectiveness, deep-learning inversions suffer from appropriate generalization to new case scenarios. In this study, a novel 3-D gravity inversion … boulder county jobs coloradoWebJan 23, 2024 · Deep learning Inversion of Seismic Data. In this paper, we propose a new method to tackle the mapping challenge from time-series data to spatial image in … boulder county job descriptionsWebMar 3, 2024 · In this work, we propose an offline-online computational strategy for coupling classical least-squares based computational inversion with modern deep learning … boulder county jail programsWebJan 12, 2024 · Training a deep learning inversion network usually requires hundreds of thousands of complex velocity models, which is labor-intensive and expensive to acquire. … boulder county jail work release programWebThe inversion accuracy and adaptability of the algorithms have been unsatisfactory. In view of the great success of deep learning in the field of image processing, this Letter … boulder county job opportunitiesWebMay 14, 2024 · Compared to other applications, deep learning models might not seem too likely as victims of privacy attacks. However, methods exist to determine whether an entity was used in the training set (an adversarial attack called member inference), and techniques subsumed under "model inversion" allow to reconstruct raw data input given just model … boulder county justice center boulderWebJan 23, 2024 · The inversion results are more consistent with the target from the aspects of velocity values, subsurface structures, and geological interfaces. … boulder county justice center