Sequence Stratigraphy of Sarvak Formation in One of the Southwestern Iran Oilfields using Frequency Decomposition of Petrophysical Logs based on Continuous and Discrete Wavelet Transform

Document Type : Research Paper

Authors

1 Department of Geology, Faculty of Basic Sciences, Islamic Azad University, Tabriz Branch, Iran

2 Earth Sciences Department, Faculty of Natural Science, University of Tabriz, Iran

3 Department of Geology, Faculty of Basic Sciences, Ferdowsi University of Mashhad, Iran

Abstract

In this study, a continuous wavelet transform (CWT) approach is used to decompose the gamma-ray and porosity logs into a set of wavelet coefficients at different scales. Moreover, discrete wavelet transform (DWT) was used to decompose the well logs into low-frequency components of the signal called the Approximates (A) and high-frequency components called the Details (D). In addition, this method was investigated using a case study of the Upper Sarvak Formation in Dezful embayment in southwest Iran. Moreover, various graphical visualization techniques of continuous wavelet transform results helped to understand the boundaries of the original sequences better. Also, using DWT, the maximum flooding surface was identified from each frequency analysis of petrophysical logs. There is a sharp peak in all A&D related to the maximum flooding surface (MFS), which is particularly visible in the coefficients of the fifth approximation (a5), the fifth detail (d5), the fourth detail (d4) and the third detail (d3). Moreover, sequence boundaries were best detected from the low-frequency content of the signals, especially the fifth approximation (a5). Typically, the trough of the fifth approximation corresponds to the sequence boundaries, where higher porosities have been developed in the carbonate rocks of Ilam and Upper Sarvak. Through the combination of both CWT and DWT coefficients, a more effective differentiation of stratified surfaces was achieved. Moreover, the results of this study show that the wavelet transform is a successful, fast and easy approach to identify the boundaries of the main sequence from well-logging data. Ultimatly, there is a good agreement between the results of core analysis and the results of well-logging data analysis using the wavelet transform approach.

Keywords

Main Subjects

References

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Journal of Petroleum Research
Volume 34, 1403-3 - Serial Number 136
September and October 2024
Pages 138-162

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