Hilbert-Huang transform based on CEEMD for hydrocarbon detection

Abstract

Obtaining the instantaneous frequency of seismic data by Hilbert transform is widely used in reservoir prediction and fluid identification. In order to obtain high accuracy and clear physical significance instantaneous frequency, it is usually required that the analyzed signal is stationary and narrow-band. While practical seismic data is a nonstationary and bandwidth signal, directly applying Hilbert transform to seismic data to obtain instantaneous frequency will lack physical significance or even distort. Complementary Ensemble Empirical Mode Decomposition (CEEMD) can adaptively decompose a complex signal into a limited number of Intrinsic Mode Function (IMF), which is stationary, narrow-band and contains the local characteristics information of the original signal. Therefore, applying Hilbert transform to IMF can obtain high accuracy and clear physical significance instantaneous frequency. The amplitude and frequency attributes of seismic data will change abnormally after the reservoir is oil or gas bearing. Extracting the corresponding abnormal change can be used as an effective indicator to identify hydrocarbon information. In this article, the Hilbert Huang transform based on CEEMD is applied to hydrocarbon detection. First, the seismic data is processed by CEEMD to obtain IMF components. Then the IMF component which can reflect the local anomaly changes caused by hydrocarbon is selected. Finally, the instantaneous frequency of the IMF component related to hydrocarbon is obtained by Hilbert transform, and take it as the sign of hydrocarbon detection. Note: This paper was accepted into the Technical Program but was not presented at IMAGE 2021 in Denver, Colorado.