Space-time Modeling in Rock Layers through Resistivity Data Yundari, Nurhasanah, Ryan Jonathan, Odila Yupama EN
Universitas Tanjungpura Pontianak
Abstract
West Kalimantan has the largest peat-land in Kalimantan Island after Central Kalimantan, which is 29.99%. Peat soils in West Kalimantan classified as low-maturity soils- therefore, it is still highly weathered. These could affect the infrastructure sector, especially in planting concrete piles for a building. The planted concrete stakes must reach a layer of soil/rock could be done by drilling, measuring log data, density data, or resistivity data. The data obtained requires considerable time, weather, cost, and energy factors. In addition, reaching a certain depth will take more time, effort, and cost as well. One way to make these factors more effective is to perform predictive modeling for unmeasured/observable depths. In this article, stochastic modeling is carried out to predict the depth of soil/rock layers based on resistivity data in the West Kalimantan region and interpreted in the description of rock layers. The results obtained that the depth of the peat layer in West Kalimantan is up to a depth of 17 meters measured from above sea level. This is number obtained from data estimation using the generalized space-time autoregressive (GSTAR) model with uniform spatial weights and Euclidean distances. The random variable is represented by the resistivity value, while the time parameter index used is the depth of the soil layer. Prediction results are carried out for the 2-meter layer below outside the model data (in samples) with a 0.2-meter interval difference.
Keywords: resistivity, peat-land, GSTAR, stochastic process
