Physics-guided data-driven seismic inversion
Webb16 okt. 2024 · CycleFCN: A Physics-Informed Data-driven Seismic Waveform Inversion Method Full Record Related Research Authors: Lin, Youzuo [1]; Feng, Shihang [1]; Jin, Peng [1]; Wohlberg, Brendt Egon [1]; Moulton, John David [1] + Show Author Affiliations Publication Date: Fri Oct 16 00:00:00 EDT 2024 Research Org.: WebbPhysics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion IEEE Signal Processing Magazine, Vol. 40, No. 1 Data …
Physics-guided data-driven seismic inversion
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WebbExperienced Seismic Petrophysicist / Rock physicist in Schlumberger SRC Seismic Reservoir Characterization group since November 2011. معرفة المزيد حول تجربة عمل Omar Aly وتعليمه وزملائه والمزيد من خلال زيارة ملفه الشخصي على LinkedIn
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 … Webb1 apr. 2024 · A new hybrid computational approach to solve FWI that combines physics-based models with data-driven methodologies and develops a data augmentation strategy that can not only improve the representativity of the training set but also incorporate important governing physics into the training process and, therefore, improve the …
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 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 …
Webb8 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 ...
WebbDeep learning-based methods gain great popularity because of their powerful ability to obtain exact solutions for geophysical inverse problems. However, those deep learning … star wars the force awakens stormtrooperWebbDeep 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). star wars the force awakens wikipediaWebb2 Deep learning techniques for electromagnetic forward modeling + Show details-Hide details p. 25 –65 (41) In this chapter, we introduce the approaches of applying deep learning techniques to electromagnetic forward modeling. These approaches are divided into three types: fully data-driven forward modeling, deep learning-assisted forward … star wars the force imagesWebbABSTRACT 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 … star wars the force awakens star ridleyWebbSeismic 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 … star wars the force awakens snokeWebbSeismic 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. star wars the force theme 1 hourWebbPhysics-Guided Data-Driven Seismic Inversion: Recent progress and future opportunities in full-waveform inversion Lin, Youzuo; Theiler, James; Wohlberg, Brendt; Abstract. … star wars the force unl