We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilis...We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilistic setting,financial performance risk and to understand the importance of the different factors that impact investment.The methodology developed in this study combines,through Monte Carlo simulation,the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion(GMB).To illustrate the methodology's validity,we apply it to an analysis of investments in shale gas wells.Our results show that gas price volatility is a key variable in the performance of an investment of this type,in such a way that at high volatilities,the potential return on an investment in shale gas increases significantly,but so do the risks of economic loss.This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures.展开更多
基金partially funded by Goverment of Spain,Ministry of Science,Innovation and Universities(grant:RTI2018093366-B-I00)by Goverment of Spain,Ministry of Universities(grant:Subsidies to Public Universities for the Requalification of the Spanish University System,“Margarita Salas”Grants Modality for the Training of Young Doctors,RD 289/2021 of April 20)+1 种基金by the Xunta de Galicia,Consellería de Educacion e Ordenación Universitaria(grant:#ED431C 2018/41)by the Group of Numerical Methods in Engineering of the Universidade de A Coruna。
文摘We present a new methodology to statistically determine the net present value(NPV)and internal rate of return(IRR)as financial estimators of shale gas investments.Our method allows us to forecast,in a fully probabilistic setting,financial performance risk and to understand the importance of the different factors that impact investment.The methodology developed in this study combines,through Monte Carlo simulation,the computational modeling of gas production from shale gas wells with a stochastic simulation of gas price as a geometric Brownian motion(GMB).To illustrate the methodology's validity,we apply it to an analysis of investments in shale gas wells.Our results show that gas price volatility is a key variable in the performance of an investment of this type,in such a way that at high volatilities,the potential return on an investment in shale gas increases significantly,but so do the risks of economic loss.This finding is consistent with the history of shale gas operations in which huge investment successes coexist with unexpected investment failures.
