Bayesian Non-Linear Quantile Regression with Application in Decline Curve Analysis for Petroleum Reservoirs

Download or read book Bayesian Non-Linear Quantile Regression with Application in Decline Curve Analysis for Petroleum Reservoirs written by Youjun Li and published by . This book was released on 2017 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: In decline curve analysis for hydrocarbon reservoirs, the use of quantile regression instead of the conventional mean regression would be appropriate in the context of oil industry requirement as the fitted quantile regression curves have the correct interpretation for the predicted reserves. However, quantiles of a mean regression result have been commonly reported. In this thesis, we consider non-linear quantile regression model where the quantiles of the conditional distribution of the production rate are expressed as some standard non-linear functions of time, under a Bayesian frame work. The posterior distribution of the regression coefficients and other parameters is intractable mainly due to the non-linearity in the quantile regression function, hence Metropolis Hastings algorithm is used to sample from the posterior. A quantitative assessment of the uncertainty of the decline parameters and the future prediction would be provided for two real datasets.