TY - JOUR
T1 - 1-Dimension magnetotelluric data inversion using MOEA/D algorithm
AU - Pramudiana,
AU - Sungkono,
N1 - Publisher Copyright:
© Published under licence by IOP Publishing Ltd.
PY - 2017/2/10
Y1 - 2017/2/10
N2 - Magnetotelluric (MT) data is used to derive resistivity imaging of subsurface. The subsurface resistivity is obtained by inversion of MT data. Generally, MT data contains two parts, namely: apparent resistivity and phase or real and imaginary parts. Inversion of MT data for reconstructing resistivity value of each layer is to minimize single objective (combination two parameters MT data) which used global or local optimization method. Nerveless, single objective optimization method has several disadvantages, such as; (1) weight value to combine two parameters of MT data is needed, where this weigh value depend on the amplitude of both MT data; (2) there is no validation of the inversion results. In this research, Inversion MT data to estimate 1D resistivity of subsurface uses multi-objective evolutionary algorithm based on decomposition (MOEA/D)to minimize root mean square error (RMSE) of calculated and observed data for apparent resistivity and phase data simultaneously. The algorithm has applied to synthetic and field data. This result shows that MOEA/D algorithm is robust and accurate to determine subsurface resistivity and lithology.
AB - Magnetotelluric (MT) data is used to derive resistivity imaging of subsurface. The subsurface resistivity is obtained by inversion of MT data. Generally, MT data contains two parts, namely: apparent resistivity and phase or real and imaginary parts. Inversion of MT data for reconstructing resistivity value of each layer is to minimize single objective (combination two parameters MT data) which used global or local optimization method. Nerveless, single objective optimization method has several disadvantages, such as; (1) weight value to combine two parameters of MT data is needed, where this weigh value depend on the amplitude of both MT data; (2) there is no validation of the inversion results. In this research, Inversion MT data to estimate 1D resistivity of subsurface uses multi-objective evolutionary algorithm based on decomposition (MOEA/D)to minimize root mean square error (RMSE) of calculated and observed data for apparent resistivity and phase data simultaneously. The algorithm has applied to synthetic and field data. This result shows that MOEA/D algorithm is robust and accurate to determine subsurface resistivity and lithology.
UR - http://www.scopus.com/inward/record.url?scp=85014100849&partnerID=8YFLogxK
U2 - 10.1088/1742-6596/795/1/012011
DO - 10.1088/1742-6596/795/1/012011
M3 - Conference article
AN - SCOPUS:85014100849
SN - 1742-6588
VL - 795
JO - Journal of Physics: Conference Series
JF - Journal of Physics: Conference Series
IS - 1
M1 - 012011
T2 - International Conference on Science and Applied Science 2016, ICSAS 2016
Y2 - 19 November 2016
ER -