Application of GSTAR(1,1) model for layer peat soil predicted based on resistivity log data

Abstract

In this study, GSTAR modeling was carried out with the inverse of distance weight matrix obtained from Geoelectrical Resistivity data at several peatland locations around the Universitas Tanjungpura, Pontianak. This data can identify the subsurface layer of the soil through the electric current that binds into the soil. However, due to the limitation of the tool to measure the resistivity value, it can only measure 1/5 of the depth of the observation length. To overcome this problem, predictions are made at the next depth using the GSTAR model. The study began by measuring the resistivity value of the land using the geoelectric method and mapping it. Through this GSTAR modeling, predictions are made for the unobserved subsurface to determine the type of soil layer. Knowing the type of deeper soil layer can help contractors build plant concrete stakes to keep buildings safe on peatland. The results of the GSTAR(1.1) model are not accurate enough to estimate the resistivity value data. This is possible because the correlation between rock ages is not the same, so further analysis is required.

GSTAR (1,1) Modeling with Time-Correlated Errors for Geoelectric Resistivity Log Data in Pontianak City

“…Prameswari et al [12] [8] analyzed rock resistivity using the concept of anisotropy with the GSTAR model. Yundari et al [13] performed analysis using a Gamma-Ray log on the GSTAR model with kernel spatial weight, and Jonathan et al [14] modeled GSTAR(1,1) with independent errors on the geoelectric resistivity data in the Universitas Tanjungpura area. Although the findings of these studies seem promising, they ignored the behavior of the errors in the model.…”