Evaluating the Performance of Hydraulic-Fractures in Unconventional Reservoirs using Production Data: Comprehensive Review
Abstract
Understanding the performance of the reservoir productivity in the post-stimulation conditions has recently gained an extensive emphasis from the specialist researchers and operators. Although there have been different tools used to evaluate the fracturing process and to predict the well performance, using production data as an indirect tool to calibrate the fracturing design and to forecast the reservoir performance has been considered the most potential technique. However, different methods with a high ambiguity have been used in this area of research over the last decade. Therefore; developing, screening, and specializing different methods and techniques to diagnose and evaluate the post-fracture reservoir performance by using flowback data has a significant priority. Determining the performance of hydraulic fractures from flowback data is considered the actual calibration to estimate the effective volume, length, height, conductivity, and width of hydraulic fractures. This paper presents a comprehensive review on most of the approaches, which have been recently introduced in this area of research, including their applicability, pros and cons. Furthermore, this study explains how each method can be valid at a specific time range. The potential tools, which could be more successful to be used in this direction of research, have been extensively discussed and recommended.
Recommended Citation
D. Alfarge et al., "Evaluating the Performance of Hydraulic-Fractures in Unconventional Reservoirs using Production Data: Comprehensive Review," Journal of Natural Gas Science and Engineering, vol. 61, pp. 133 - 141, Elsevier, Jan 2019.
The definitive version is available at https://doi.org/10.1016/j.jngse.2018.11.002
Department(s)
Geosciences and Geological and Petroleum Engineering
International Standard Serial Number (ISSN)
1875-5100; 2212-3865
Document Type
Article - Journal
Document Version
Citation
File Type
text
Language(s)
English
Rights
© 2019 Elsevier, All rights reserved.
Publication Date
01 Jan 2019