Minimum Sample Size and Optimum Depth Difference Study based on Time Series Analysis of Gamma-Ray Log Data Yundari, Ryan Jonathan, Udjianna S Pasaribu, Utriweni Mukhaiyar, Mohamad N Heriawan
Universitas Tanjungpura Pontianak
Abstract
Minimum sample size selection is one of the issues that need to be studied in statistical sciences. This affects the results of the estimation model based on observation data. However, the minimum sample size depends on the data and issues examined. In this paper, the data used Gamma-ray well logging using the ARIMA time series model. This is one of novelty in the application of time-series data. The purpose of modeling is also back-casting using time parameters index such as depth. So it is necessary to study the optimum determination of depth difference to produce good stochastic models. The simulation results of some depth showed that different minimum depths of 0.2 m with a sample of more than 450 is the best result for modeling the time series data especially Gamma-ray log data.
Keywords: Minimum sample, ARIMA Model, time-series model, well logging data
