Sandri, Erfani Coal Velocity and Proximate Analysis Relationship Using Multiple Linear Regression. In: ICSTAR 2020. (Submitted)

Preview

Text ICSTAR-Full-Paper-Sandri.pdf Download (57kB) | Preview

Abstract

Coal properties such a velocity (Vp) is important to build a lateral distribution of coal seam using seismic data. The experimental determination of velocity analysis is sophisticated, long time consumed, and expensive, on the contrary, statistical approach such as linear regression can be run rapidly. The two main objectives of the study were to develop models for coal velocity using well log data variables (density and natural Gamma-Ray) and found the relationship between velocity with proximate analysis results. Multiple linear regression (MLR) methods were applied to estimate relationship between Vp estimated and proximate analysis. By conducting cross-validation, the prediction analysis of the models has been tested by using R2. The result showed that between Vp estimated versus Vp log have R2 0.80 and Vp estimated versus proximate analysis that reflected have R2 of 0.52. The main merit of the correlations is the ability to estimate the relationship between Vp and proximate analysis, then applied that correlation to distributed in seismic volume to obtained coal seam characteristic.

Item Type:	Conference or Workshop Item (Paper)
Subjects:	Q Science > QC Physics
Divisions:	Fakultas Teknik (FT) > Prodi Teknik Geofisika
Depositing User:	M.Eng Sandri Erfani
Date Deposited:	16 Nov 2020 06:06
Last Modified:	16 Nov 2020 06:06
URI:	http://repository.lppm.unila.ac.id/id/eprint/25464

Actions (login required)

View Item