The low-frequency distributed acoustic sensing (LF-DAS) data acquired through fiber-optic cables cemented behind the fracturing well casing can dynamically capture the hydraulic fracturing process. After removing the thermal effect, the LF-DAS data can reveal the strain evolution induced by the initiation of hydraulic fractures. This paper presented an improved strain–temperature decoupling method for LF-DAS measurements based on joint LF-DAS/distributed temperature sensing (DTS) monitoring. The decoupling method was based on strain change and temperature change pre-processed from the raw DAS and DTS data to avoid the enhancement of DTS data noise. The moving window function method and the image processing parameter cosine similarity was introduced to cope with the differences in temporal and spatial resolution between LF-DAS and DTS data. The region significantly affected by temperature change could be identified automatically and the mechanical strain change could be extracted. The tensile strain response generally reached a local peak at perforation clusters and increased significantly at those with dominant fracture fluid inflow. By analyzing the evolution of strain profile during fracturing, the effectiveness of multi-cluster fracture initiation and fracture temporary plugging could be evaluated.

In-well hydraulic fracture monitoring based on joint low-frequency distributed acoustic sensing (LF-DAS)/distributed temperature sensing (DTS) enables the acquisition of optical fiber mechanical strain data, which reflect fracture propagation and rock deformation during hydraulic fracturing. This paper presents an analytical method to interpret the mechanical strain profile measured by in-well LF-DAS/DTS during the fracturing process based on strain transfer theory and the Sneddon solution for fracture propagation. The analytical method is validated by a numerical model that simulates the strain field induced by fracture propagation. The sensitivity of the fiber strain to key factors, such as fracture geometry parameters and gauge length, is analyzed. The results indicate that compressive strain in the formation adjacent to the propagating fracture remains observable from the mechanical strain profile under the low fiber lag parameter condition. The presented method is applied to analyze the mechanical strain profile measured from a fractured horizontal well. Considering the reactivation of the pre-existing fracture, the location of the fractures is identified, and the fractures’ geometric parameters are inverted. This study provides a quantitative evaluation method for fracture geometry characterization based on joint LF-DAS/DTS fracturing monitoring.