A graphics processing unit implementation of time-domain full-waveform inversion

Geophysics ◽  
2015 ◽  
Vol 80 (3) ◽  
pp. F31-F39 ◽  
Author(s):  
Pengliang Yang ◽  
Jinghuai Gao ◽  
Baoli Wang
Keyword(s):  
Time Domain ◽  
Graphics Processing Unit ◽  
Waveform Inversion ◽  
Processing Unit ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Graphics Processing

Velocity model estimation of karstic fault reservoirs using full-waveform inversion accelerated on graphics processing unit

2020 ◽  
Vol 8 (4) ◽  
pp. SP191-SP203
Author(s):  
Ziying Wang ◽  
Jianping Huang ◽  
Zhenchun Li ◽  
Li-Yun Fu ◽  
Wenqiang Luo ◽  
...  
Keyword(s):  
High Precision ◽  
Graphics Processing Unit ◽  
Waveform Inversion ◽  
Velocity Model ◽  
Carbonate Reservoir ◽  
Processing Unit ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Seismic Image ◽  
Graphics Processing

The karstic fault reservoir is a type of hydrocarbon-enriched carbonate reservoir. It is a combination of small-scale caves, vugs, and fractures developing near deep-seated faults, which makes it difficult to delineate using traditional seismic imaging methods. Recent research on geologic characteristics of paleokarst reservoirs facilitates hydrocarbon exploration and exploitation in western China. To interpret karstic fault systems and reservoirs, the seismic image is an effective tool. A high-quality velocity model is essential for high-resolution migration. These seismic results contain crucial information to interpret reservoirs. Full-waveform inversion (FWI) is a powerful method to obtain high-precision velocity models because it makes use of the kinematic and dynamic information in the seismic full wavefield. To image such complicated and irregular fractured-cavity reservoirs accurately, we have applied a multiscale FWI method accelerated on graphics processing unit devices to fault-controlled paleokarst reservoir models. According to the model test results, FWI shows high performance in delineating the boundaries of fault-controlled karstic reservoirs. The proposed method also has the potential to characterize inner structures. Based on the high-precision velocity model provided by FWI, the seismic image obtained by reverse time migration is also improved. These seismic results will show the location, width, and shape of the fault-karst structure, which gives detailed information for fault-controlled paleokarst reservoir interpretation.

scholarly journals 3D variable-grid full-waveform inversion on GPU

2019 ◽  
Vol 16 (5) ◽  
pp. 1001-1014 ◽  
Author(s):  
Zi-Ying Wang ◽  
Jian-Ping Huang ◽  
Ding-Jin Liu ◽  
Zhen-Chun Li ◽  
Peng Yong ◽  
...  
Keyword(s):  
Graphics Processing Unit ◽  
Computing Time ◽  
Waveform Inversion ◽  
3D Models ◽  
Processing Unit ◽  
Full Waveform Inversion ◽  
Full Waveform ◽  
Wavefield Simulation ◽  
3D Processing ◽  
Processing Techniques

Abstract Full-waveform inversion (FWI) is a powerful tool to reconstruct subsurface geophysical parameters with high resolution. As 3D surveys become widely implemented, corresponding 3D processing techniques are required to solve complex geological cases, while a large amount of computation is the most challenging problem. We propose an adaptive variable-grid 3D FWI on graphics processing unit devices to improve computational efficiency without losing accuracy. The irregular-grid discretization strategy is based on a dispersion relation, and the grid size adapts to depth, velocity, and frequency automatically. According to the transformed grid coordinates, we derive a modified acoustic wave equation and apply it to full wavefield simulation. The 3D variable-grid modeling is conducted on several 3D models to validate its feasibility, accuracy and efficiency. Then we apply the proposed modeling method to full-waveform inversion for source and residual wavefield propagation. It is demonstrated that the adaptive variable-grid FWI is capable of decreasing computing time and memory requirements. From the inversion results of the 3D SEG/EAGE overthrust model, our method retains inversion accuracy when recovering both thrust and channels.

scholarly journals Time domain viscoelastic full waveform inversion

2017 ◽  
Vol 209 (3) ◽  
pp. 1718-1734 ◽  
Author(s):  
Gabriel Fabien-Ouellet ◽  
Erwan Gloaguen ◽  
Bernard Giroux
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Full Waveform Inversion ◽  
Full Waveform

Multiscale time-domain time-lapse full-waveform inversion with a model-difference regularization

2017 ◽  
Author(s):  
Musa Maharramov ◽  
Ganglin Chen ◽  
Partha S. Routh ◽  
Anatoly I. Baumstein ◽  
Sunwoong Lee ◽  
...  
Keyword(s):  
Time Domain ◽  
Waveform Inversion ◽  
Time Lapse ◽  
Full Waveform Inversion ◽  
Full Waveform
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