Horizontal wellbore drilling and hydraulic fracturing technologies have become standard development practices in unconventional gas reservoirs. In order to tap into the full potential of gas shale reservoirs and to produce them economically, it is essential to optimize not only the locations of hydraulic fracture (HF) stages along the given wellbore, but also the wellbore trajectory inside the reservoir. To deal with these two challenges simultaneously and in a seamless fashion, a framework of numerical optimization algorithms can be established. Application of such discrete optimization approach to the above-stated problem allows to enhance production from shale gas reservoirs and to increase the net present value (NPV) of unconventional assets.

The novel hierarchical optimization structure operates in the following way: it places a horizontal wellbore (or wellbores) on the upper level and then distributes HF stages along the fixed well trajectory (or trajectories) on the lower level. Both levels of the framework use gradient-based stochastic strategy, namely, the simultaneous perturbation stochastic approximation (SPSA). Application of this optimization technique permits to depart from the common practice of distributing HF stages evenly. We demonstrate utility of this idea with highly heterogeneous geologic systems that require HF spacing with non-even intensity. To assess efficiency of our approach, we compare the results obtained from SPSA optimization with those from Covariance Matrix Adaptation Evolution Strategy (CMA-ES) that is a stochastic, derivative-free numerical method. The developed framework is tested on stimulation data from synthetic models. Our findings show that the systematic approach to optimization of horizontal wellbore and HF stages placement can improve the NPV of unconventional projects.

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