Measurements such as in-well and cross-well fiber optics, perforation-imaging, and slant well coring have indicated that fracs from perforation clusters grow unevenly in the near wellbore and far-field. Sub-optimal cluster efficiency is caused by in-situ rock variations, poor cement bond behind casing, flow dynamics within wellbore, and stress shadowing as fracs propagate. Thus, optimizing cluster efficiency is a multi-dimensional, and time dependent problem. This paper highlights observations made using various downhole measurements from Permian Basin wells for different completion designs. A physics-based workflow has been created to model and match field observations. The results showcase how calibrated models were leveraged to further optimize the completion strategy for field implementation.

Downhole measurements (e.g. perforation imaging and fiber) were collected in several wells with conventional geometric perforation designs and tapered perforation designs. Results of fluid and proppant distribution with various perf-tapering, number of holes, and number of clusters were analyzed. Physics-based models were applied to a variety of completion strategies to match the measurements observed in the field. These models integrate proppant transport dynamics in a perforated wellbore with an efficient multi-cluster hydraulic fracturing simulator to quantitatively estimate fluid and proppant distribution among multiple clusters. With the calibrated model, several more completion strategies were tested, which led to the identification of optimum designs to apply to future wells.

Perforation imaging data was utilized to measure the pre- and post-stimulation diameters of all perforations and to provide an estimate of erosion created during pumping operations. It is important to note that the evolution of the perf erosion over pumping time stays uncaptured by imaging technologies. Initial observations of conventional geometric perforation design led to a heel biased proppant distribution. However, a tapered design with the same or fewer number of total perforations resulted in a toe biased erosion profile. With the help of offset-well fiber data and mechanistic models, significant impacts of inter-stage stress shadow effects were observed on far-field cluster efficiency. Using physics-based models, observed trends were captured with a maximum of 10% error in the prediction.

In this collaborative work, cluster efficiency was studied to see the impacts on both near-wellbore and far-field fracturing dynamics. The availability of multiple types of downhole data was critical to calibrate physics-based models and improve predictability of the results. Special emphasis was placed on integrating wellbore (proppant + fluid) flow modeling, including inertial effects of proppant that can lead to early screenout of certain clusters along with stress-shadow effects amongst multiple fractures. This effort allowed for optimization of completion designs at a rapid pace and develop strategies for future field development. With the help of optimized design, cluster efficiency and frac uniformity improved by 30% when compared to the historical base completion design.