GPU parallel-based fast density inversion method of gravity gradient tensor data

A gravity gradient and density inversion technology, applied in the field of earth science, can solve the problem of increasing time-consuming iterative inversion, and achieve the effect of short calculation time and fast convergence

Inactive Publication Date: 2018-01-12
JILIN UNIV
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Problems solved by technology

However, as the amount of data increases, when the order of the coefficient matrix is ​​large, the time-consuming iterative inversion also increases significantly due to the

Method used

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  • GPU parallel-based fast density inversion method of gravity gradient tensor data
  • GPU parallel-based fast density inversion method of gravity gradient tensor data
  • GPU parallel-based fast density inversion method of gravity gradient tensor data

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Experimental program
Comparison scheme
Effect test

Embodiment

[0033] The combined noise model is used to test the inversion effect and acceleration effect of the method, the model distribution and simulated observation data such as figure 2 and image 3 shown.

[0034] The following table compares the running time of parallel algorithms and traditional algorithms

[0035]

[0036] Actual data are used to prove the applicability of this method. The data are the measured data of the Vinton Salt Dome in Louisiana, USA. The measured data and inversion results are as follows: Figure 4 and Figure 5 as shown,

[0037] The combined model test results show that the gravity tensor gradient data inversion has a higher resolution than the single gravity data inversion, and the proposed fast preprocessing method is more close to the set model than the traditional conjugate gradient method, and the density value and geometric position. The efficiency of the parallel program is evaluated by the number of iterations and the total calculation t...

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Abstract

The invention discloses a GPU parallel-based fast density inversion method of gravity gradient tensor data. Compared with single gravity data inversion, the method is higher in resolution. Compared with a traditional conjugate gradient method, a provided fast preprocessing method is closer to a set model in a density value and a geometric position. Efficiency of a parallel program is evaluated collectively through an iteration number and total computation time, and compared with serial CPU computation of a traditional algorithm, the method enables three-dimensional inversion to converge faster, is short in time used for computation, and achieves approximately a speed-up ratio of 25 times.

Description

technical field [0001] The invention relates to the field of earth science technology, in particular to a GPU-based parallel gravity gradient tensor data fast density inversion method. Background technique [0002] The existing three-dimensional gravity tensor gradient data inversion of large-scale data faces disadvantages such as large demand for computer memory, more algorithm iterations, and long time-consuming inversion calculations. The improved preprocessing algorithm can reduce the calculation storage space and the number of inversion iterations, thereby improving the inversion calculation efficiency. However, as the amount of data increases, when the order of the coefficient matrix is ​​large, the time-consuming iterative inversion also increases significantly due to the extra time required to calculate the preprocessing factors. Using GPU to achieve efficient parallel iterative method is the key to improving the solution speed Effective Ways. The efficiency of inv...

Claims

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Application Information

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IPC IPC(8): G06F17/15
Inventor 王泰涵马国庆李丽丽杜晓娟
Owner JILIN UNIV
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