Abstract
Hydraulic fracturing stimulation designs are moving towards tighter spaced clusters, longer stage length, and more proppant volumes. However, effectively evaluating the hydraulic fracturing stimulation efficiency remains a challenge. Distributed fiber optic sensing, which includes Distributed Acoustic Sensing (DAS) and Distributed Temperature Sensing (DTS), can continuously monitor the hydraulic fracturing stimulation downhole and be compared with other monitoring technology such as microseismic. The DAS and DTS data, when integrated with the microseismic, highlight processes relevant to the completion design and allow for a better understanding and interpretation of each dataset.
This paper outlines a workflow to improve processing and interpretation of DAS and DTS data. In addition, an estimate of the slurry distribution can be made. These methods will be demonstrated for a horizontal Wolfcamp well in the Permian Basin. Here we compare key aspects of the microseismic, DAS, and DTS results in several fracture stages to understand the downhole geomechanical processes. In order to interpret the DTS data a thermal model is developed (using DTS data) to simulate the temperature behavior after pumping has ceased. A slurry distribution is obtained by matching the simulated temperature with the measured temperature from DTS. In addition, the DAS data signal is studied in the frequency domain and the dominant frequencies are identified that are mostly related to fluid flow and to reduce the background noise. This time frequency analysis enhances the ability to monitor and optimize well treatments.
After reducing the background noise, the acoustic intensity is correlated to the slurry distribution. The fluid distribution data from DAS and DTS are compared with the microseismic and near field strain to better understand the completion processes. We utilized fiber optic microseismic to better understand and compare it to conventional microseismic.
Finally, we highlight the dynamics of strain and microseismic signature as fluid moves from an offset well completion into the prior stimulated fiber well to better understand the reservoir and far field effects of the completion.
