Improvement of seismic attributes based on gray level co-occurrence matrix using non-linear transform to gray scale for identification of salt dome geobody

Authors

Abstract

Geophysical methods, especially reflection seismology, are one of the methods of identification the subsurface structures of the earth, and are widely used in the exploration of hydrocarbon resources. Salt domes are one of the most important geological structures. Determination of their geobody in seismic data is of great importance for various reasons. Due to different texture of salt domes compared to the surrounding sediments, texture seismic attributes are a useful tool for identifying and distinguishing these structures in seismic data. The gray level co-occurrence matrix (GLCM) has been used as a tool to generate multiple textural attributes in seismic data that includes two main steps: 1. rescaling of the seismic domain to user-defined gray levels, and 2. calculation of GLCM and extraction of texture features from it. Traditionally, linear transform is simply used to scale the seismic data domain to gray levels. The most important feature of this approach is to preserve the maximum of the distribution histogram of the original seismic data domains. However, the seismic features of interest to interpreters often cover only a small part of the amplitude histogram, and to display them more effectively, it is better to display them with more gray levels. The non-linear transform to gray scale provides the possibility of emphasizing the part of the amplitude distribution histogram in which the seismic feature is of interest, and it causes the enhancement of that feature in the gray scale image and improves the resulting textural attributes. In this paper, the classification of texture attributes based on the improved GLCM is used to determine the geobody of the salt dome in the two-dimensional marine seismic data of the bay of Hormuz. The obtained results show that the accuracy of identifying the salt dome using the improved attributes has an acceptable increase compared to the conventional ones. Furthermore, in this paper, to improve the salt dome geobody detection, nonlinear transform is used with the help of sigmoid transform function in the calculation of textural attributes based on GLCM, and its results are compared with the conventional linear transform. Finally, the geobody of the salt dome is determined using the classification of seismic attributes and its result is compared with the result of manual interpretation.

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References

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Volume 8, Issue 3
July 1401
Pages 243-255

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