Deep learning for seismic inverse problems
WebNov 2, 2024 · These properties facilitate deep learning being used to solve geophysical inverse problems (Zhu et al., 2024; Smith et al., 2024; Xiao et al., 2024; Zhang and Gao, 2024), as a wider selection of algorithms and frameworks then are available for use, such as approximate Bayesian inference techniques like variational inference. 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 …
Deep learning for seismic inverse problems
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WebSep 12, 2024 · Download Citation Towards Seismic Inverse Problems Using Deep Learning Understanding the behavior and state of fault systems is necessary to make … WebJan 15, 2024 · Star 316. Code. Issues. Pull requests. Deep Learning for Seismic Imaging and Interpretation. microsoft computer-vision deep-learning neural-networks segmentation seismic seismic-inversion seismic-imaging seismic-data seismic-processing. Updated on …
WebApr 28, 2024 · The postdoctoral researcher will develop novel deep learning algorithms for solving complex seismic inversion problems. Topics of interest include: Deep Learning … WebDec 21, 2024 · This paper presents a deep learning solution for the reconstruction of realistic 3D models in the presence of field noise recorded in seismic surveys. We implement and analyze a convolutional encoder-decoder architecture that efficiently processes the entire collection of hundreds of seismic shot-gather cubes. The proposed …
WebWe present a novel method of using explainability techniques to design physics-aware convolutional neural networks (CNNs). We demonstrate our approach… WebThe postdoctoral researcher will develop novel deep learning algorithms for solving complex inversion problems. Topics of interest include: Deep Learning for 3D seismic inversion and imaging. Multi-task deep learning. Variational Networks and regularization for deep network solutions to inverse problems. Relations between deep learning and ...
WebSummary Machine learning approaches are rapidly finding their way into many applications in processing and imaging seismic data. More specifically, various convolutional deep …
WebSeismic inversion is a process to obtain the spatial structure and physical properties of underground rock formations using surface acquired seismic data, constrained by known geological laws and drilling and logging data. The principle of seismic inversion based on deep learning is to learn the mapping between seismic data and rock properties by … pink tricycle with handleWebFeb 20, 2024 · Deep learning (DL) is emerging as a data-driven approach that can effectively solve the inverse problem. However, existing DL-based methods for seismic … stehekin pastry company menuWebDec 18, 2024 · The paper presents a new method to improve the performance of the seismic wave simulation and inversion by integrating the deep learning software platform and deep learning models with the HPC application. The paper has three contributions: 1) Instead of using traditional HPC software, the authors implement the … ste hay hollyoaksWebABSTRACT Seismic inversion allows the prediction of subsurface properties from seismic reflection data and is a key step in reservoir modeling and characterization. With the generalization of machine learning in geophysics, deep learning methods have been proposed as efficient seismic inversion methods. However, most of these methods lack … pink tricycle with basketWebDeep-learning has achieved good performance and shown great potential for solving forward and inverse problems. In this work, two categories of innovative deep-learning based inverse modeling methods are proposed and compared. The first category is deep-learning surrogate-based inversion methods, in which the Theory-guided Neural … pink tricycle with push handleWebAlthough the adoption of deep learning for seismic imaging is relatively recent (Dramsch, 2024), many authors have successfully used CNNs to image the deep subsurface ... We … pink triple diamonds slots free facebookWebAug 29, 2024 · Seismic data processing heavily relies on the solution of physics-driven inverse problems. In the presence of unfavourable data acquisition conditions (e.g., regular or irregular coarse sampling of sources and/or receivers), the underlying inverse problem becomes very ill-posed and prior information is required to obtain a satisfactory solution. … pink trilby hats