Parallel processor for real-time structural control

1993 ◽  
Author(s):  
Bert L. Tise
Keyword(s):  
Real Time ◽  
Structural Control ◽  
Parallel Processor

SCC-100 parallel processor for real-time imaging

1990 ◽  
Author(s):  
William J. Jacobi ◽  
William B. Kendall ◽  
Leo A. Wadsworth
Keyword(s):  
Real Time ◽  
Parallel Processor ◽  
Real Time Imaging

REAL-TIME 3D IMAGING OF COMPLEX TURBIDITIC RESERVOIR ARCHITECTURE

2021 ◽  
Author(s):  
Supriya Sinha ◽  
◽  
Karol Riofrio ◽  
Arthur Walmsley ◽  
Nigel Clegg ◽  
...  
Keyword(s):  
Real Time ◽  
Structural Control ◽  
Seismic Signal ◽  
Time Inversion ◽  
3D Inversion ◽  
Reservoir Architecture ◽  
The North ◽  
Oil Water ◽  
3D Em ◽  
Accurate Imaging

Siliciclastic turbidite lobes and channels are known to exhibit varying degrees of architectural complexity. Understanding the elements that contribute to this complexity is the key to optimizing drilling targets, completions designs and long-term production. Several methods for 3D reservoir modelling based on seismic and electromagnetic (EM) data are available that are often complemented with outcrop, core and well log data studies. This paper explores an ultra-deep 3D EM inversion process during real-time drilling and how it can enhance the reservoir understanding beyond the existing approaches. The new generation of ultra-deep triaxial EM logging tools provide full-tensor, multi-component data with large depths of detection, allowing a range of geophysical inversion processing techniques to be implemented. A Gauss-Newton-based 3D inversion using semi-structured meshing was adapted to support real-time inversion of ultra-deep EM data while drilling. This 3D processing methodology provides more accurate imaging of the 3D architectural elements of the reservoir compared to earlier independent up-down, right-left imaging using 1D and 2D processing methods. This technology was trialed in multiple wells in the Heimdal Formation, a siliciclastic Palaeocene reservoir in the North Sea. The Heimdal Fm. sandstones are generally considered to be of excellent reservoir quality, deposited through many turbiditic pulses of variable energy. The presence of thin intra-reservoir shales, fine-grained sands, heterolithic zones and calcite-cemented intervals add architectural complexity to the reservoir and subsequently impacts the fluid flow within the sands. These features are responsible for heterogeneities that create tortuosity in the reservoir. When combined with more than a decade of production, they have caused significant localized movement of oil-water and gas-oil contacts. Ultra-deep 3D EM measurements have sensitivity to both rock and fluid properties within the EM field volume. They can, therefore, be applied to mapping both the internal reservoir structure and the oil-water contacts in the field. The enhanced imaging provided by the 3D inversion technology has allowed the interpretation of what appears to be laterally stacked turbidite channel fill deposits within a cross-axial amalgamated reservoir section. Accurate imaging of these elements has provided strong evidence of this depositional mechanism for the first time and added structural control in an area with little or no seismic signal.

A Network Implementation of Real-Time Dynamic Simulation With Interactive Animated Graphics

1988 ◽  
Author(s):  
M. W. Dubetz ◽  
J. G. Kuhl ◽  
E. J. Haug
Keyword(s):  
Real Time ◽  
Dynamic Simulation ◽  
High Speed ◽  
Dynamic Performance ◽  
Data Communication ◽  
Computing System ◽  
Data Sets ◽  
Parallel Processor ◽  
Network Computing ◽  
Time Dynamic

Abstract This paper presents a network based implementation of real-time dynamic simulation methods. An interactive animated graphics environment is presented that permits the engineer to view high quality animated graphics rendering of dynamic performance, to interact with the simulation, and to study the effects of design variations, while the simulation is being carried out. An industry standard network computing system is employed to interface the parallel processor that carries out the dynamic simulation and a high speed graphics processor that creates and displays animated graphics. Multi-windowing and graphics processing methods that are employed to provide visualization and operator control of the simulation are presented. A vehicle dynamics application is used to illustrate the methods developed and to analyze communication bandwidth requirements for implementation with a compute server that is remote from the graphics workstation. It is shown that, while massive data sets are generated on the parallel processor during realtime dynamic simulation and extensive graphics data are generated on the workstation during rendering and display, data communication requirements between the compute server and the workstation are well within the capability of existing networks.

A Scalable Massively Parallel Processor for Real-Time Image Processing

2011 ◽  
Vol 46 (10) ◽  
pp. 2363-2373 ◽  
Author(s):  
Takashi Kurafuji ◽  
Masaru Haraguchi ◽  
Masami Nakajima ◽  
Tetsu Nishijima ◽  
Tetsushi Tanizaki ◽  
...  
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Massively Parallel ◽  
Parallel Processor ◽  
Real Time Image Processing ◽  
Real Time Image ◽  
Massively Parallel Processor ◽  
Time Image

scholarly journals Real-Time Shape Recognition Using a Pixel-Parallel Processor

2005 ◽  
Vol 17 (4) ◽  
pp. 410-419 ◽  
Author(s):  
Takashi Komuro ◽  
◽  
Yoshiki Senjo ◽  
Kiyohiro Sogen ◽  
Shingo Kagami ◽  
...  
Keyword(s):  
Image Processing ◽  
Parallel Processing ◽  
Real Time ◽  
Shape Recognition ◽  
Parallel Processor ◽  
Vision Chip ◽  
Time Operation ◽  
Time Shape ◽  
Real Time Operation ◽  
Partially Occluded

We propose a method to realize robust real-time shape recognition against noise and occlusion by using information of an entire image, and by performing image processing in a pixel parallel manner. The evaluation by simulation showed that the proposed method was effective for images with noise or partially occluded images. We implemented the algorithm to a vision chip which performs pixel-parallel processing and confirmed real-time operation. We also estimated the performance of the method on an ideal processor.

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