Quantitative Analysis of Hydraulic Fracturing Test Site 2 Completion Designs Using Crosswell Strain Measurement

Abstract

Summary The implementation of effective completion design configurations during hydraulic stimulation is critical for the economic development of unconventional reservoirs. Low-frequency distributed acoustic sensing (LF-DAS)-based crosswell strain measurement is an advanced monitoring technique used to diagnose completion design efficiency but has been primarily restricted to qualitative analysis. In this study, we apply our novel Green-function based inversion algorithm to calculate fracture geometry (i.e., width) using the Department of Energy sponsored Hydraulic Fracturing Test Site 2 (HFTS-2) data set. The adopted algorithm relies on a 3D displacement discontinuity method to construct geomechanical models inverting linear elastic strain to hydraulic fracture widths. We use the inversion algorithm to calculate dynamic fracture widths using LF-DAS data recorded at two horizontal monitoring wells with permanent optical fiber installations. The inverted fracture widths at the monitoring wells from more than 100 hydraulic fracturing stages are used to diagnose the efficiency of eight unique completion designs implemented across three fracturing wells. We develop several metrics to evaluate completion design efficiency including the evenness of fracture widths at the monitoring wells, fracture density (i.e., number of fracture hits per foot), and fracture-width-density (i.e., fracture width/stage length). We observe a significant impact on completion efficiency with varying degrees of limited entry, tapered configurations, and stage length designs. Results indicate improved hydraulic stimulation is achieved with the implementation of limited-entry designs for extended stage lengths (ESLs), but no observable trend for normal stage lengths (NSLs). Tapered configurations significantly improve efficiency for ESLs but indicate little impact on normal-length designs. Reducing the space between perforation clusters (PCs) is determined to negatively impact design performance. Additionally, our quantitative analysis describes the impact of the nearby depletion zone on completion design efficiency. The methodology developed in this study provides operators with another level of quantitative information to optimize hydraulic fracturing treatments and reduce costs associated with the development of unconventional wells.