scholarly journals Application of OpenMP to Wireline Triaxial Induction Logging in 1D Layered Anisotropic Medium

2012 ◽  
Vol 2012 ◽  
pp. 1-12 ◽  
Author(s):  
Zhijuan Zhang ◽  
Ning Yuan ◽  
Richard Liu

Efficient and accurate forward modeling of logging tool responses is essential for data inversion in the log data interpretation in both real time and postprocessing. With the aggressive advancement of various high-performance computing techniques and computer hardware technology, it is possible to significantly improve the efficiency of the forward modeling. In this paper, we apply OpenMP to parallelize the simulation of triaxial induction logging tools in 1D multilayered anisotropic formation. The parallel process is explained in detail and numerical examples are presented to demonstrate the effect of the parallel programming. Comparison of the original code and the parallel code shows that the latter is much faster without loss of accuracy, which is very promising for future real-time inversion.

Geophysics ◽  
2016 ◽  
Vol 81 (1) ◽  
pp. D71-D82 ◽  
Author(s):  
Zhili He ◽  
Kai Huang ◽  
Richard C. Liu ◽  
Chen Guo ◽  
Zhao Jin ◽  
...  

We have developed a forward-modeling method to compute the response of a triaxial induction logging tool in a layered biaxial anisotropic dipping formation without borehole and invasion zones. The purpose of this development is to provide a fast-forward computation algorithm to handle cracks in transverse isotropic (TI) formations in oil exploration, which is a mathematically challenging problem for log data inversion. We solve for the spectral-domain transverse electromagnetic (EM) field equations, propagation matrix, and reflection matrix in a biaxial anisotropic planarly layered media. The EM fields in the space domain are obtained by a 2D inverse Fourier transform. We derive formulations of the EM fields generated by three orthogonal transmitting coils in a fully anisotropic layered media. The proposed formulations are based on arbitrary relative dipping and azimuthal and tool angles; thus, we obtain the full coupling matrix connecting source excitations and magnetic fields anywhere along the tool axis. Computation results using this method in the response of triaxial induction tools in several cases were compared with published data in TI formations and biaxial layered formations. Our results agreed very well with the published data.


Geophysics ◽  
2002 ◽  
Vol 67 (2) ◽  
pp. 517-524 ◽  
Author(s):  
Zhiyi Zhang ◽  
Zhiqiang Zhou

We present a quasi-2-D real-time inversion algorithm for a modern galvanic array tool via dimensional reduction and neural network simulation. Using reciprocity and superposition, we apply a numerical focusing technique to the unfocused data. The numerically focused data are much less subject to 2-D and layering effects and can be approximated as from a cylindrical 1-D earth. We then perform 1-D inversion on the focused data to provide approximate information about the 2-D resistivity structure. A neural network is used to perform forward modeling in the 1-D inversion, which is several hundred times faster than conventional numerical forward solutions. Testing our inversion algorithm on both synthetic and field data shows that this fast inversion algorithm is useful for providing formation resistivity information at a well site.


10.14311/981 ◽  
2008 ◽  
Vol 48 (3) ◽  
Author(s):  
S. Gross ◽  
T. Stehle

Imaging technology is highly important in today’s medical environments. It provides information upon which the accuracy of the diagnosis and consequently the wellbeing of the patient rely. Increasing the quality and significance of medical image data is therefore one the aims of scientific research and development. We introduce an integrated hardware and software framework for real time image processing in medical environments, which we call RealTimeFrame. Our project is designed to offer flexibility, easy expandability and high performance. We use standard personal computer hardware to run our multithreaded software. A frame grabber card is used to capture video signals from medical imaging systems. A modular, user-defined process chain performs arbitrary manipulations on the image data. The graphical user interface offers configuration options and displays the processed image in either window or full screen mode. Image source and processing routines are encapsulated in dynamic library modules for easy functionality extension without recompilation of the entire software framework. Documented template modules for sources and processing steps are part of the software’s source code.


Geophysics ◽  
2018 ◽  
Vol 83 (3) ◽  
pp. D73-D81 ◽  
Author(s):  
Javid Shiriyev ◽  
Yaniv Brick ◽  
Peng Zhang ◽  
Ali E. Yilmaz ◽  
Carlos Torres-Verdín ◽  
...  

The monitoring and diagnostics of induced fractures are important for the real-time performance evaluation of hydraulic fracturing operations. Previous electromagnetic-based studies show that single backbone triaxial induction logging tools are promising candidates for real-time monitoring and diagnosis of fractures in noncased wells. With a fast-forward solver and reliable parametric inversion techniques, it may be possible to estimate many features of the propped fracture geometry (e.g., area, dip, conductivity) from the measured induced voltages. To support the development of field deployable tools, the concept must be tested in experiments, in a controllable environment, before it is tested under field-like conditions. To this end, we have designed and built a prototype induction tool and performed two sets of tests to compare with numerical simulation results. The experimental setup consists of triaxial transmitter and receiver coils in coaxial, coplanar, and cross-polarized configurations. Thin (highly conductive) metallic targets of various sizes, shapes, and orientations are used to emulate various fracture geometries. The laboratory and shallow earth measurements are shown to be in good agreement with simulations for all examined cases. The average relative and maximum discrepancies of the measured signals from the simulated ones are lower than 3% and 10%, respectively. With the prototype tool, strong signals sensitive to the fracture’s surface area and dip are measured in a coaxial coil configuration, whereas weaker signals sensitive to the fracture’s aspect ratio are observed in a coplanar configuration. Cross-polarized signals are also shown to be strong and sensitive to the fracture’s dip. The results suggest that a tool of similar specifications can be used for the detection and extraction of the parameters of fractures propped with sufficiently electrically conductive proppant.


Author(s):  
Muhammad Faris Roslan ◽  
◽  
Afandi Ahmad ◽  
Abbes Amira ◽  
◽  
...  

Author(s):  
Yuchen Luo ◽  
Yi Zhang ◽  
Ming Liu ◽  
Yihong Lai ◽  
Panpan Liu ◽  
...  

Abstract Background and aims Improving the rate of polyp detection is an important measure to prevent colorectal cancer (CRC). Real-time automatic polyp detection systems, through deep learning methods, can learn and perform specific endoscopic tasks previously performed by endoscopists. The purpose of this study was to explore whether a high-performance, real-time automatic polyp detection system could improve the polyp detection rate (PDR) in the actual clinical environment. Methods The selected patients underwent same-day, back-to-back colonoscopies in a random order, with either traditional colonoscopy or artificial intelligence (AI)-assisted colonoscopy performed first by different experienced endoscopists (> 3000 colonoscopies). The primary outcome was the PDR. It was registered with clinicaltrials.gov. (NCT047126265). Results In this study, we randomized 150 patients. The AI system significantly increased the PDR (34.0% vs 38.7%, p < 0.001). In addition, AI-assisted colonoscopy increased the detection of polyps smaller than 6 mm (69 vs 91, p < 0.001), but no difference was found with regard to larger lesions. Conclusions A real-time automatic polyp detection system can increase the PDR, primarily for diminutive polyps. However, a larger sample size is still needed in the follow-up study to further verify this conclusion. Trial Registration clinicaltrials.gov Identifier: NCT047126265


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