کد مقاله | کد نشریه | سال انتشار | مقاله انگلیسی | نسخه تمام متن |
---|---|---|---|---|
4739859 | 1641127 | 2016 | 12 صفحه PDF | دانلود رایگان |
![عکس صفحه اول مقاله: Fast inversion of probability tomography with gravity gradiometry data based on hybrid parallel programming Fast inversion of probability tomography with gravity gradiometry data based on hybrid parallel programming](/preview/png/4739859.png)
• We extended probability tomography inversion to multiple gravity gradiometry tensors
• The inversion algorithm is modified and improved specially for the gravity gradiometry tensors
• Hybrid parallel programming with MPI and CUDA for large-scale data is applied
• The more accurate results are achieved in delineating the boundary of the adjacent bodies
• Testing real geophysical data confirmed the algorithm to be reliable and feasible
Geophysical exploration generates a very large amount of data, which require special techniques to process meaningfully. This paper presents a modification of the inversion method of probability tomography and a practical application of the method for the joint inversion with multiple gravity gradiometry tensors. The depth-weighting matrix is introduced to increase the vertical resolution. The problems associated with choosing tensors are discussed. We combine the high-performance computing techniques, Message Passing Interface with Compute Unified Device Architecture, for hybrid programming to build a faster parallel program. In the synthetic model tests, it is found that the joint inversion with multiple tensors is superior to the classical algorithm with a single tensor for delineating the boundary of the adjacent geological bodies. The hybrid parallel program has a speedup of far more than 100, which is higher than the program using one parallel technique alone; thus, the program could be used for large-scale data. The parallel algorithm is applied to real geophysical exploration data from Vinton Dome and we obtained a good density result. Our algorithm is demonstrated to be reliable and feasible.
Journal: Journal of Applied Geophysics - Volume 124, January 2016, Pages 27–38