Theoretical Analysis and Numerical Modeling of Fiber Slippage to Reduce Uncertainty in Fiber Deployment and Improve Data Interpretation Accuracy

Abstract Low-frequency Distributed Acoustic Sensing (LF-DAS) with single-use fiber is widely used for cross-well fracture monitoring due to its lower cost and ease of deployment than permanent or wireline fiber. However, uncertainties in strain measurements arise due to slippage effects caused by decoupling between the fiber and the wellbore. These uncertainties pose significant challenges to accurate fracture interpretation. This study aims to model fiber slippage to reduce deployment uncertainty and improve the accuracy of data interpretation. Our methodology integrates theoretical analysis and numerical modeling to investigate fiber deployment, slippage effects, and their impact on strain measurement quality. We begin with a theoretical assessment of fiber deployment mechanics, focusing on the resulting initial strain and displacement distribution along the fiber. This is followed by forward numerical simulations of cross-well strain measurements using single-use fiber, incorporating both initial strain and slippage effects. A sensitivity analysis is conducted to evaluate the influence of initial strain on fiber slippage behavior. Finally, we validate the theoretical and numerical results against field data to ensure practical relevance and accuracy. In addition to the friction coefficient between the fiber and the wellbore surface, initial strain and displacement induced during fiber deployment are critical factors affecting fiber coupling. These are primarily generated by fluid drag forces during the fiber pump-down process. Incorporating both low friction coefficient and initial strain into the numerical model successfully reproduces the asymmetric slippage patterns observed in field data. Significant initial strain can lead to extended slippage zones, complicating strain signal interpretation. Over time, the initial tension in the fiber relaxes, leading to reductions in fiber strain. This relaxation process explains why data quality is generally better in heel-side stages than in toe-side stages. By accounting for low friction, initial strain, and its relaxation in the numerical modeling, we successfully replicate the observed fiber slippage behavior. Based on theoretical analysis and modeling results, we made three recommendations for field operation: (1) Reduce fiber injection rates during deployment to minimize initial strain. (2) Allow a waiting period after deployment to allow fiber relaxation and settling. (3) Periodically measure the initial fiber strain profile using Brillouin-based strain measurements to assess and mitigate its impact on data quality. This study, for the first time, provides new insights into how fiber deployment impacts coupling and strain data quality by introducing a quantitative framework for evaluating and mitigating slippage effects. Through this high-impact research, we offer practical recommendations for optimizing fiber deployment in the field to significantly enhance data acquisition. In addition, our findings improve the accuracy of field data interpretation, thereby reducing uncertainty in data analysis.