Variational Mode Decomposition-Based Processing of Time-Domain Induced Polarization Data

Research output: Contribution to conferenceConference abstract for conferenceResearchpeer-review

Abstract

Time domain induced polarization (TDIP) method suffers from a plethora of undesired responses which prominently includes powerline harmonics, electric spikes, self-potentials of the earth and random noise. These undesired responses restrict access to the spectral content which is vital in characterizing rocks, soil and minerals present in the subsurface. Hence, mitigating the impact of these noisy responses measured along with the IP potentials is among the core processing challenges faced by TDIP method today. To this end, we propose the use of variational mode decomposition (VMD) that can decompose time series data into its intrinsic frequency modes (IMFs) which are essentially time series containing a narrowband signal component. Such a decomposition is vital in TDIP signal processing because IP decay is known to have a dominantly low frequency spectrum while noise has considerably higher spectral range. Hence, we employ successive use of VMD on the raw TDIP signal to gradually extract and accumulate the low frequency components of the IP decay in initial IMFs (while noise is distributed among latter modes). We validate the performance of the proposed VMD based approach through synthetic as well as field examples.

Original languageEnglish
Publication date2023
DOIs
Publication statusPublished - 2023
EventNSG2023 29th European Meeting of Environmental and Engineering Geophysics - Edinburgh , United Kingdom
Duration: 3 Sept 20237 Sept 2023
Conference number: 29

Conference

ConferenceNSG2023 29th European Meeting of Environmental and Engineering Geophysics
Number29
Country/TerritoryUnited Kingdom
CityEdinburgh
Period03/09/202307/09/2023

Fingerprint

Dive into the research topics of 'Variational Mode Decomposition-Based Processing of Time-Domain Induced Polarization Data'. Together they form a unique fingerprint.

Cite this