Summary Low-frequency distributed acoustic sensing (LF-DAS) has recently received much attention for its ability to monitor fracture propagation at offset wells. Hydraulic Fracture Test Site-2 (HFTS-2), a Department of Energy–sponsored field-based research experiment, has acquired LF-DAS data sets during the stimulation of many horizontal wells in the Wolfcamp Formation of the Permian Basin. Over 100 stimulated stages with different completion designs in four horizontal wells were monitored by two horizontal offset wells and one vertical pilot hole with permanent fibers. The parent well depletion affected all four horizontal wells in almost half of their lateral section. Several studies have been performed on the acquired comprehensive data set. In this study, we apply our novel Green’s function-based inversion algorithm to calculate the fracture width of each stage and investigate the impact of parent well depletion on fracture geometry. The Green’s function-based inversion algorithm has been successfully applied to a few stages of field case studies. The Green’s function matrix was built based on linear elasticity theory (3D displacement discontinuity method) to relate the fracture openings with strain responses measured along the length of the fiber. This novel algorithm only relies on measured strain to solve fracture geometry at the monitoring well. Therefore, it is independent of the physics of the fracture propagation process and can be used to validate hydraulic fracture modeling results. Using our inversion algorithm, we can efficiently and quantitatively interpret LF-DAS data to provide information on fracture geometry and completion efficiency. We analyze more than 100 stages of the LF-DAS measurements obtained at the fiber wells B3H and B4H during B1H, B2H, and B4H stimulations. We apply our inversion algorithm for four data sets covering the stimulation of the abovementioned three wells. The fracture growth at stages in the parent well’s depleted zone is biased more toward upper formation and in the easterly direction. The fracture width at the stages in the parent well’s depletion zone is reduced compared to fracture widths at stages in the nondepleted zone irrespective of the monitoring well location relative to the treatment wells. This difference in fracture widths will affect the proppant distribution to a great extent, thereby affecting the effectiveness of the stimulation. We also illustrate the application of the inversion algorithm for stages that have both conventional fracture hits with “heart-shaped” signals as well as fracture reopening signals. Our inversion algorithm gives a reasonable estimate of the fracture width that aligns with the qualitative analysis of microseismic data sets and statistic summary of fracture hit numbers of HFTS-2. We believe that this quantitative study provides us with insights into the fracture geometry due to parent well depletion effects.
Summary Distributed acoustic sensing (DAS) has recently gained importance in monitoring hydraulic fracturing treatments in the oil and gas industry. DAS data contain critical information about the fracture geometry as linearly relatable induced strain variations during the stimulation. The low-frequency components of the DAS (LF-DAS) data are known for their complexity as they exhibit various characteristic signals—caused by several mechanisms—that complicate their interpretation. LF-DAS data from horizontal monitoring wells (HMWs) have been used to detect fracture hits and characterize fracture geometry. However, the LF-DAS data from vertical monitoring wells (VMWs) have not been studied extensively as a means to infer fracture geometry. The major limitation of VMWs is the number of monitored stages, but the data contain more information about fracture height compared with LF-DAS measurements from HMWs. Hence, it is necessary to have a physical rock deformation model to simulate the strain rate responses in offset VMWs during fracture propagation to understand and interpret the various patterns that are observed in the field data sets. The objective of this study is to simulate strain rate signals in VMWs during hydraulic fracturing and to analyze the measurements to obtain information on the fracture geometry, especially the fracture height. The fracture boundary can be directly related to the strain rate signals. In this study, we propose a workflow to determine fracture height at different fiber-to-fracture (dff) distances for fracture heights ranging from 20 m to 300 m. We conduct a detailed sensitivity analysis to understand the impacts of the dff, the perforation location, the fracture passing time, and the well inclinations on the measured strain rate signals. The analysis helps interpret the various patterns observed in field data and the underlying mechanisms. Interpretation of field data from the Hydraulic Fracture Testing Site 2 (HFTS-2) using the results from our forward physical model provides valuable information on the fracture characteristics that can be captured by the physical model. The results of this study are expected to provide better interpretations of LF-DAS signals from VMWs.
Low-frequency distributed acoustic sensing (LF-DAS) has recently received much attention for its ability to monitor fracture propagation at offset wells. Hydraulic Fracture Test Site-2 (HFTS-2), a DOE- sponsored field-based research experiment, has acquired LF-DAS datasets during the stimulation of many horizontal wells in the Wolfcamp Formation of the Permian Basin. Over 100 stimulated stages with different completion designs in four horizontal wells were monitored by two horizontal offset wells and one vertical pilot hole with permanent fibers. The parent well depletion affected all four horizontal wells in almost half of their lateral section. Several studies have been done on the acquired comprehensive dataset. In this study, we apply our novel Green's function-based inversion algorithm to calculate the fracture width of each stage and investigate the impact of parent well depletion on fracture geometry. The Green's function-based inversion algorithm (Liu et al., 2021) has been successfully applied to a few stages of field case studies. The Green function matrix was built based on linear elasticity theory (Three- Dimensional Displacement Discontinuity Method) to relate the fracture openings with strain responses measured along the length of the fiber. This novel algorithm only relies on measured strain to solve fracture geometry at the monitoring well. Therefore, it is independent of the physics of the fracture propagation process and can be used to validate hydraulic fracture modeling results. Using our inversion algorithm, we can efficiently and quantitatively interpret LF-DAS data to provide information on fracture geometry and completion efficiency. We analyze more than 100 stages of the LF-DAS measurements obtained at the fiber wells B3H and B4H during B1H, B2H, and B4H stimulations. We apply our inversion algorithm for four datasets covering the stimulation of the above mentioned three wells. The fracture growth at stages in the parent well depleted zone is biased more towards upper formations and in the east direction. The fracture width at the stages in the parent well depletion zone is reduced compared to fracture widths at stages in the non- depleted zone irrespective of the monitoring well location relative to the treatment wells. This difference in fracture widths will affect the proppant distribution to a great extent, thereby, affecting the effectiveness of the stimulation. We also illustrate the application of the inversion algorithm for stages that have both conventional fracture hits with "heart-shaped" signals as well as fracture reopening signals. Our inversion algorithm gives a reasonable estimate of the fracture width that aligns with the qualitative analysis of microseismic datasets and statistic summary of fracture hit numbers of HFTS-2. We believe that this study provides us with insights into the fracture geometry due to parent well depletion effects quantitatively.
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