Application of the Monte Carlo Simulation in evaluating unconventional gas well economy
- DOI
- 10.2991/icseee-16.2016.172How to use a DOI?
- Keywords
- Unconventional gas; Monte Carlo; index optimization; economic evaluation; decline analysis; gas price; sensitivity analysis
- Abstract
This paper starts with constructing the optimal process of shale gas economic indexes through selecting suitable statistics and prediction methods to confirm the major evaluation parameters of shale gas, such as single well recoverable reserves, single well composite cost and gas price. Then, economic benefit of shale gas single well projects was evaluated. Monte Carlo simulation was used to determine the probability distribution of the indexes that influence economic evaluation of single well projects. The sensitive factors that can influence financial internal return rate and net present value of shale gas single well projects were quantitatively analyzed. The correlations between impact factors and indexes were calculated and sorted. Finally, feasibility and risk level of single well projects were confirmed. This study determined the main factors that affect the economic performance of shale gas single well, evaluated the feasibility of shale gas single well projects, which can provide theoretical support for effectively controlling shale gas well cost, and reasonably and commercially developing shale gas reservoirs.
- Copyright
- © 2016, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Nan Wang AU - Qun Zhao AU - Wei Guo AU - Huanrong Zang AU - Dexun Liu PY - 2016/12 DA - 2016/12 TI - Application of the Monte Carlo Simulation in evaluating unconventional gas well economy BT - Proceedings of the 2016 5th International Conference on Sustainable Energy and Environment Engineering (ICSEEE 2016) PB - Atlantis Press SP - 978 EP - 981 SN - 2352-5401 UR - https://doi.org/10.2991/icseee-16.2016.172 DO - 10.2991/icseee-16.2016.172 ID - Wang2016/12 ER -