Quantitative Evaluation of Hydro-Fracturing Effects to Unconventional Formation Using Borehole Acoustic Dispersion

Abstract Hydraulic fracturing has already been becoming critical EOR technology worldwide. However, present practices are still facing high costs and risks, due to limited knowledge and information about the fracturing-induced effects. Many conventional methods (like well temperature logging, production fluid profile, production dynamics) also show limitations when applied to unconventional formation with strong heterogeneity. This paper provides a new perspective to characterize the stimulated formation by using borehole dispersion phenomena. In post-fracturing evaluation, anisotropy analysis is gaining popularity recently, based on that anisotropy intensity is altered and the fast shear azimuth is indicative to stress field. However, the complex fractures geometry and the angle relative, making it inefficient in unconventional applications. Inspired by Slowness Frequency Analysis (SFA), we introduce a hierarchical density-based clustering method to classify and refine the dispersion scatters automatically. Both the amplitude and slowness information are considered during the clustering optimization, and a high-precision SFA outcome can be derived to highlight the ‘before and after’ changes caused to formation. Compared to traditional methods, the proposed method overcomes some common challenges (like soft formation and poor data quality after fracturing), and can identify and extract the dispersion information, usually within 3 iterations. By projecting the refined dispersive information into slowness dimension, the crossover formed by "before and after" fracturing provides a quantitative insight into the fracturing-induced effects. This technology has been successfully applied to many unconventional cases in China. It has enabled accurate monitoring of hydraulic fracturing location and scale of the induced alteration in a much economic and efficient way. The novel method can provide valuable information and reduce turnaround time, to better drive optimized decision-making in unconventional development and production. At the core of proposed method is a new solution to classify borehole acoustic dispersions, which can be sorted into various modes in an automatic way. When employed to hydro-fracturing effects evaluation, it is a new attempt that provides a quantitative measure of the stimulated formation in terms of slowness changes. It is a new and economic addition to current industry practices, holding potential in reducing high costs and risks of hydraulic fracture operations.