Practical handling of multiple objectives using evolutionary strategy for optimal placement of hydraulic fracture stages in unconventional gas reservoirs

In this article we discuss advantages and practical ways of applying Multi-objective Optimization (MOO) to the cutting-edge problem of optimal exploitation of shale gas reservoirs. We show that by a judicious selection of the number of hydraulic fracture (HF) stages, their locations along a horizontal wellbore, and HF half-length, an optimal scenario involving multiple objectives can be achieved. Our MOO approach allows weighing different production strategies in presence of multiple production and economic goals (or objectives) and offers the algorithm that gives quantitative and qualitative measures of “goodness” of the optimal production plans. We demonstrate by means of a shale play model based on the Barnett Shale that the objectives can be of economic (short- and long-term discounted net-present-values) or production (cumulative water production) nature. The framework handles objectives effectively and produces the Pareto optimal solutions without requiring the user to assign weights to each objective inside an aggregate function. For the end user such assignment can be confusing, time consuming, and sometimes not even possible.