• Geophysics and Geophysical Exploration
• /
• v.20 no.2
• /
• pp.78-87
• /
• 2017

For efficient data processing, trace interpolation and regularization techniques should be antecedently applied to the seismic data which were irregularly sampled with missing traces. Among many interpolation techniques, MWNI (Minimum Weighted Norm Interpolation) technique is one of the most versatile techniques and widely used to regularize seismic data because of easy extension to the high-order module and low computational cost. However, since it is difficult to interpolate spatially aliased data using this technique, model-constrained MWNI was suggested to compensate for this problem. In this paper, conventional MWNI and model-constrained MWNI modules have been developed in order to analyze their performance using synthetic data and validate the applicability to the field data. The result by using model-constrained MWNI was better in spatially aliased data. In order to verify the applicability to the field data, interpolation and regularization were performed for two field data sets, respectively. Firstly, the seismic data acquired in Ulleung Basin gas hydrate field was interpolated. Even though the data has very chaotic feature and complex structure due to the chimney, the developed module showed fairly good interpolation result. Secondly, very irregularly sampled and widely missing seismic data was regularized and the connectivity of events was quite improved. According to these experiments, we can confirm that the developed module can successfully interpolate and regularize the irregularly sampled field data.

• Journal of the Korean earth science society
• /
• v.32 no.6
• /
• pp.586-594
• /
• 2011

Gravity Recovery and Climate Experiment (GRACE), launched in April, 2002, makes it possible to monitor Earth's mass redistribution with its time-varying gravity observation. GRACE provides monthly gravity solutions as coefficients of spherical harmonics, and thus ones need to convert the gravity spectrum to gravity grids (or mass grids) via the spherical harmonics. GRACE gravity solutions, however, include spatial alias error as well as noise, which requires to suppress in order to enhance signal to noise ratio. In this study, we present the GRACE data processing procedures and introduce some applications of time-varying gravity, which are studies of terrestrial water storage changes, Antarctic and Greenland ice melting, and sea level rise. Satellite missions such as GRACE will continue up to early 2020, and they are expected to be an essential resource to understand the global climate changes.