Well-monitoring before, during, and after hydraulic fracturing treatment is essential to accomplish a successful fracture completion program. By knowing the geometry, orientation, and propagation of the hydraulic fractures, we can identify potential completion issues during fracturing operations and help in the design of more efficient unconventional reservoir completions. Distributed Acoustic Sensing (DAS) is an emerging technology in hydraulic fracture monitoring that enables continuous, real-time measurements along the entire length of a fiber optic cable. The low-frequency band of DAS records strain perturbations of the medium, due to fracture propagation, which provides critical constraints on hydraulic fracture geometry. In this study, the low-frequency DAS strain fronts was analyzed, with their corresponding pumping curves, for one hydraulic fracturing treatment to obtain information on the hydraulic fractures like fracture azimuth, propagation speed, number of fractures created during each stage and re-stimulation of pre-existent fractures. Then, the microseismicity of the treatment was analyzed to obtain information on hydraulic fractures like length, height, trajectory and cloud growth over time. The microseismicity was also projected onto the strain fronts to study the development of the events with respect to the fracture signal and to find correlations between the strain changes and the microseismic events. Finally, the PKN model was computed using parameters from the stimulation treatment and the DAS strain fronts to forecast anticipated fracture lengths against observations. The PKN modeling results were compared to the microseismic and DAS results to find stages where the hydraulic fractures did not grow or propagate as expected. The low-frequency DAS is able to obtain information on hydraulic fractures that would need extra processing or might not be picked up using other records as microseismicity. However, the spatial constraint of the measurements in DAS needs to be taken into consideration. This spatial constraint can be addressed by the integration of other records. In general, there is good agreement between the LF DAS data, the pumping information, the microseismic data and the PKN model. But when they do not agree on a stage, that gives us an indication that something unexpected happened during injection. Models describing the expected behavior of the different records analyzed in this research were created to explain some possible scenarios of fracture propagation. Most stages in this treatment fall within one of these models.