(708a) Single Pad Planning Under Uncertainty for Shale Gas Development

Shale gas production is expected to increase by more than 50% over the next 34 years, from 14 trillion cubic feet (TCF) in 2016 to approximately 29 TCF in 2040 [1]. This increase in production will make shale gas a major player in the natural gas field, with shale gas production fulfilling 69% of the expected total dry gas natural gas demand [1]. With this expected growth in shale gas, informed decisions, as to where, when, and how to develop assets, must be made to keep the development and production economical. To address those issues, researchers in the process systems engineering community have proposed mathematical programming models [2,3,4] that deal with planning, design and strategic decisions in shale gas industry.

Recently, Ondeck et al (2019) proposed an MILP model for multi-operational planning of shale gas pad development. In this work, we consider the scheduling of four operations, top setting, horizontal drilling, hydraulic fracturing, turning in line, for a single shale gas wellpad. The revenues come from the sales of natural gas. The costs include the operations cost and the mobilization of equipment and crew. The objective is to optimize the Net Present Value (NPV) over 15 years. For this problem, uncertainties from the price of natural gas and the fracturing cost can have significant impact on the scheduling decisions. We use stochastic programming to hedge against uncertainty. In order to make the decisions more robust, we also use different risk-metrics, including conditional value at risk (CVar) as our objective. The solutions from stochastic programming are compared with the solutions from deterministic model to highlight the importance of including uncertainties in this scheduling problem.

References:

[1] EIA (2016). Most natural gas production growth is expected to come from shale gas and tight oil plays. https://www.eia.gov/todayinenergy/detail.php?id=26552

[2] Drouven, M. G., & Grossmann, I. E. (2016). Multi-period planning, design, and strategic models for long term, quality sensitive shale gas development. AIChE Journal, 62(7), 2296-2323.

[3] Cafaro, D. C., & Grossmann, I. E. (2014). Strategic planning, design, and development of the shale gas supply chain network. AIChE Journal, 60(6), 2122-2142.

[4] Gao, J., & You, F. (2015). Deciphering and handling uncertainty in shale gas supply chain design and optimization: Novel modeling framework and computationally efficient solution algorithm. AIChE Journal, 61(11), 3739-3755.

[5] Ondeck, A., Drouven, M., Blandino, N., Grossmann, I.E.(2019) Multi-Operational Planning of Shale Gas Pad Development, Computers & Chemical Engineering, 0098-1354