(371ag) Economic Model-Based Controller Design Framework to Optimize Shale Gas Production and Water Management in Hydraulic Fracturing

Authors: 
Cao, K., Texas A&M Energy Institute, Texas A&M University
Siddhamshetty, P., Texas A&M Energy Institute, Texas A&M University
Ahn, Y., Texas A&M Energy Institute, Texas A&M University
Mukherjee, R., Gas and Fuels Research Center, Texas A&M Engineering Experiment Station
Natural gas is playing a significant role in meeting current global energy demand and shale gas extracted from unconventional reservoirs has become the main contributor to the growth of natural gas production in these years [1]. The recent large-scale shale gas production would not have been economically viable without the use of horizontal drilling and hydraulic fracturing techniques. In hydraulic fracturing, the water issues arise due to the difficulty in supplying sufficient freshwater and treating wastewater with high concentration of total dissolved solids (TDS). Several studies are conducted using optimization approaches for effective water management [2-7]. However, very few of them considered pumping schedules for hydraulic fracturing, which directly determine the amount of freshwater required and the productivity of shale wells. Recently, several efforts have been made to compute the optimal pumping schedules to achieve the desired fracture geometry [8, 9]; however, the obtained pumping schedules did not consider the environmental and economic impacts of wastewater generated during the post-fracturing process.

Motivated by this consideration, we developed a novel economic model-based control framework for hydraulic fracturing to maximize the net profit from shale gas development by simultaneously minimizing the cost associated with water management. Initially, a reduced-order model and a Kalman filter are developed based on the high-fidelity simulation data to correlate the pumping schedule and the final fracture geometry. Second, a data-based dynamic input-output model is developed to obtain the flowrate and TDS concentration of wastewater from fractured wells. Third, a numerical reservoir simulator and mixed-integer nonlinear programming model are applied to generate two maps describing the revenue from selling shale gas produced and cost from managing wastewater recovered, respectively. Fourth, with the two maps and including the cost from purchasing freshwater, an economic model predictive control system is formulated. The proposed control framework is applied to an actual field case study to demonstrate its superior performance over other conventional techniques.

References:

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