This study corresponds to the second part of a paper series detailing the evolving approaches developed to improve project economics in Vaca Muerta shale formation (Lerza et al., 2020). The main objective of this work is to develop a methodology that overcomes the well-known limitations of currently existing workflows that attempt to optimize well spacing and well completion design for maximizing project value in shale and tight (S&T).
Currently published workflows on this topic generally fail to capture the interactions existing between well spacing and completion design, therefore the results obtained from applying those work steps are only optimal under a given completion design or well spacing assumption. However, most of the times, we are interested in finding the unconstrained global optimal solution rather than the local optimal solution offered by current methodologies, for which a simultaneous study of well spacing and completion design is required.
The proposed methodology consists of applying fracture and reservoir simulation to calibrate a base model by history matching fracture and production data. Next, Design of Experiments technique is leveraged to ensure most of the interaction across the previously selected parameters are correctly captured while minimizing the number of required runs. Lastly, a machine learning model is built and tested from the gathered reservoir simulation results, and later used to efficiently obtain the predicted results for 1 million possible development alternatives comprising different combinations of completion and well spacing parameters. Finally, from the vast number of scenarios run, the one that offers the desired value of the target value metric and is also operationally achievable gets selected.
By following the suggested methodology, the asset development team was able to find and propose an operationally executable development alternative that is expected to almost double the current wells Expected Ultimate Recovery (EUR) per section, while reducing the current discounted unit development cost between 10 and 30%.