Stochastic programming models for optimal shale well development and refracturing planning under exogenous and endogenous uncertainties

DROUVEN, MARKUS G.; GROSSMANN, IGNACIO E.; CAFARO, DIEGO C.

Québec

Conferencia; 21st Conference of the International Federation of Operational Research Societies (IFORS); 2017

International Federation of Operational Research Societies (IFORS)

In this work we present a comprehensive optimization framework to address the shale gas well development and refracturing planning problem. At its core, this problem is concerned with if and when a new shale gas well should be drilled at a prospective location, and whether or not it should be refractured eventually over its lifespan. Within the optimization framework, we account for two major sources of uncertainty: exogenous gas price uncertainty and endogenous well performance uncertainty. We propose a mixed-integer linear, two-stage stochastic programming model embedded in a moving horizon strategy to dynamically solve the practical planning problem under exogenous and endogenous uncertainty. The framework is based on a novel, generalized production estimate function that predicts the gas production over time depending on how often a well has been refractured and when exactly the well was restimulated last. Based on a detailed case study we conclude that early in the life of a shale well, refracturing makes economic sense even in low-price environments, whereas additional restimulations are only justified if prices are elevated.