Correlating Natural Production, Price, Import and Export in a Neural Network Framework

Abstract

Abstract In the United States, hydrocarbon in unconventional resources such as shale gas has been dramatically changing the fossil energy prospect and transforming the energy consumption structure. Therefore, it is imperative to study how this trend has impacted the U.S. natural gas import, export and the domestic gas price. To understand the relationships, Neural Network would be used to model these variables (gas production, price, import and export) with the ultimate goal of understanding the gas price determination. The key input parameters for the Network are gas production, import and export data and the resulting output of the Network would be the gas price i.e. how well this inputs influence gas price and there magnitude of impact would be ranked in this study. Impact of Weather would be looked into as well but it is not part of the Network inputs. Data from Energy Information Administration (EIA) of the U.S. Department of Energy will be utilized in this study. This work is motivated by the recent surging interest in converting existing gas import terminals to exporting terminals due to increase in gas production as a result of major technological advancement in getting formerly untapped gas out of the ground. The changes in the gas industry trend have prompted the government to consider policy changes as well. Our study will enable us to draw some policy implications regarding the U.S. energy policy.