## Modeling simulfracs and subsurface implications

Simulfrac’s are growing in popularity (see 2021 JPT article for when the trend was just gaining momentum). The idea is that one pumping crew can treat two wells simultaneously versus one well at a time. As such, a frac crew may zipper four wells at a time versus two. At ResFrac we are seeing an increase in simulfrac interest across our consulting and license customers. Simulfrac’ing wells within the ResFrac software is simple to set up without any complicated modifications – so this makes ResFrac an ideal platform to investigate the effects of simulfracs.

## A New Approach for Interference Test Analysis: Quantifying the Degree of Production Impact

This blog post summarizes a new procedure for interpreting interference tests in shale. The full procedure and a detailed writeup are provided by Almasoodi et al. (2023). Interference tests are one of the most effective diagnostics for assessing communication between neighboring wells. This information is critical for optimizing completion design and well spacing.

## Optimization of perforation orientation for achieving uniform proppant distribution between clusters

Previously, a mathematical model for the problem of slurry flow in a perforated wellbore was described and the underlying physical mechanisms were discussed. The purpose of this blog post, on the other hand, is to couple the model with an optimization algorithm to investigate optimal perforation orientations that lead to the desired uniform proppant distribution between perforations. A brief description of the model is added at the beginning to cater for readers who are not familiar with the previous blog post.

## Proppant distribution between perforation clusters

This blog post summarizes the model for calculating proppant distribution between perforation clusters. A very detailed description of the model and literature review are available in [1]. The purpose here is to outline the model and its main features, to demonstrate the comparison with some of the available data (more comparisons in [1]), as well as to discuss limiting cases and sensitivities to various parameters. This blog post is solely focused on presenting the mathematical model. In future work, the results will be applied to practical optimization decisions.

## Simulating ‘Fractal Fracture Swarms’ in a General-Purpose Reservoir Simulator

This blog post describes a new capability in ResFrac to capture the effect of ‘fracture swarms’ on production decline trends. Based on work from Acuna (2020), the idea is that variable spacing between fractures causes a gradual onset of production interference. Fractures in a swarm may be numerous and tightly spaced,  so rather than representing each individual crack in the model, we treat each swarm as a single crack and use a numerical technique to capture their effects. In ResFrac, this capability is useful because it provides another mechanism for explaining (and matching) production drawdown trends. For further details, refer to Section 19.10 from McClure et al. (2022).

## How to Diagnose False Radial Flow in a Diagnostic Fracture Injection Test (DFIT)

Genuine radial flow is rare in shale DFITs. If it does occur, it is typically observed in tests with very low injection volume (less than 10-20 bbl), unusually long shut-in (longer than one week), and relatively high permeability (greater than one microdarcy). Genuine radial flow should only be diagnosed if it occurs after an extended (at least one log cycle) period of after-closure linear flow. If ‘false radial’ flow is misdiagnosed and used to estimate permeability, it leads to a large overestimate (10-100x).