Maximum Entropy Multi-Resolution EM Tomography by Adaptive Subdivision
- 282 Downloads
Audio band electromagnetic (EM) waves have a great potential for success in bore hole to bore hole or surface to bore hole tomography for geophysical exploration or environmental tests. Low resolution is generally the major limitation in the EM tomography. If a high resolution is sought, many artifacts with random patterns will show in the resultant image of the reconstruction if a least square error criterion is applied. The maximum entropy constraint can certainly reduce the artifacts. However, the conflict of high resolution and fewer artifacts still exists. This paper proposes an adaptive procedure which produces a tomography image with different resolution in different subdivisions according to the details the subdivision may possess. This procedure can reduce unnecessary resolution in those areas where no more interesting details are shown while showing high resolution in other areas where interesting details may occur. Thus, the artifacts can be reduced to a minimum. Computer simulations on the proposed method compared with least square error method and a conventional maximum entropy method show that the proposed method can produce higher resolution images with significantly reduced artifacts. All experimental results are encouraging and show great potential in practical applications.
KeywordsMaximum Entropy Tomographic Image Maximum Entropy Principle Interesting Detail Adaptive Subdivision
Unable to display preview. Download preview PDF.
- M. J. Wilt, H. F. Morrison, A. Becker, and K. H. Lee, “Cross-Borehole and Surface-to- Borehole Electromagnetic Induction for Reservoir Characterization,” DOE/BC/91002253 Report, Lawrence Livermore National Lab., Livermore, CA, Aug. 1991Google Scholar
- D. T. Iseley and D. H. Cowling, “Obstacle Detection to Facilitate Horizontal Directional Drilling,” Final report of AGA project PR222-9218, Pipeline Research Committee at American Gas Association, Jan. 1994Google Scholar
- Q. Zhuo, “Audio Frequency Numerical Modeling and Tomographic Inversion for Reservoir Evaluation,” Ph.D dissertation, Department of Engineering Geosciences, University of California at Berkeley, 1989Google Scholar
- A. Albert, “Regression and Moore-Penrose pseudoinverse” New York: Academic PressGoogle Scholar