Completed Ensemble Empirical Mode Decomposition: a Robust Signal Processing Tool to Identify Sequence Strata

• Published in: IOP conference series. Earth and environmental science Vol. 132; no. 1; pp. 12033 - 12041
• Main Authors: Purba, H, Musu, J T, Diria, S A, Permono, W, Sadjati, O, Sopandi, I, Ruzi, F
• Format: Journal Article
• Language: English
• Published: Bristol IOP Publishing 01.03.2018
• Subjects: Data logging; Data processing; Decomposition; Empirical analysis; Gamma rays; Information processing; Signal analysis; Signal processing; Stratigraphy
• ISSN: 1755-1307; 1755-1315
• DOI: 10.1088/1755-1315/132/1/012033

Well logging data provide many geological information and its trends resemble nonlinear or non-stationary signals. As long well log data recorded, there will be external factors can interfere or influence its signal resolution. A sensitive signal analysis is required to improve the accuracy of logging interpretation which it becomes an important thing to determine sequence stratigraphy. Complete Ensemble Empirical Mode Decomposition (CEEMD) is one of nonlinear and non-stationary signal analysis method which decomposes complex signal into a series of intrinsic mode function (IMF). Gamma Ray and Spontaneous Potential well log parameters decomposed into IMF-1 up to IMF-10 and each of its combination and correlation makes physical meaning identification. It identifies the stratigraphy and cycle sequence and provides an effective signal treatment method for sequence interface. This method was applied to BRK- 30 and BRK-13 well logging data. The result shows that the combination of IMF-5, IMF-6, and IMF-7 pattern represent short-term and middle-term while IMF-9 and IMF-10 represent the long-term sedimentation which describe distal front and delta front facies, and inter-distributary mouth bar facies, respectively. Thus, CEEMD clearly can determine the different sedimentary layer interface and better identification of the cycle of stratigraphic base level.