Mixed Integer Model Predictive Control of Multiple Shale Gas Wells

Abstract

Horizontal wells with multistage hydraulic fracturing are today the most important drilling technology for shale gas extraction. Considered unprofitable before, the production has now become economically profitable due to advances in technology. Shales main characteristics is its low permeability, making the gas challenging and expensive to extract. Hydraulic fracturing stimulates the wells by creating additional conductivity, making the gas flows from storage pores to the well. This flow only possible in a short time scale, and states the need for multistage fracturing. Shale gas flow therefore exhibits a high initial peak, followed by a rapid decline in production rates. The use of shut-ins of shale gas wells allows for pressure build-up and may prevent liquid loading, as a means of boosting production. Shut-ins are used as on/off control variables in short-term model-based optimization of multiple shale gas wells with the objective of tracking a reference rate, while at the same time avoiding liquid loading. Previous work have focused on open-loop optimization. Here, an open-loop formulation is compared to a closed-loop formulation, in the form of mixed integer model predictive control. Both formulations are implemented in IBM ILOG CPLEX, with and without disturbances. Optimal production settings are solved in the presence of global constraints on production rates and minimal shut-in time. This allows for shut-ins with variable periods. The implementation is sensitive to initial conditions, horizons and weighting factors. The closed-loop formulation shows the best ability to reduce the effects of disturbances.