Fracture Network Evaluation Using Tracer Flowback: A Case Study
Authors
Linkai Li (China University of Petroleum-Beijing, University of Calgary) | Verapich Pinprayong (Weatherford KSP Company Limited) | Fanle Meng (China University of Petroleum-Beijing) | Hanqiao Jiang (China University of Petroleum-Beijing) | Junjian Li (China University of Petroleum-Beijing)
Publisher
SPE - Society of Petroleum Engineers
Publication Date
November 7, 2017
Source
SPE Symposium: Production Enhancement and Cost Optimisation, 7-8 November, Kuala Lumpur, Malaysia
Paper ID
SPE-189273-MS
Abstract
Hydraulic fracturing is extensively applied in the exploitation of unconventional reservoirs. The evaluation for fracture networks after fracturing treatments has a great significance for hydrocarbon production prediction. In order to characterize fracture networks, the tracer is injected into the formation and it will flow back along with fracturing fluid. In this study, we estimate fracture networks using tracer flowback profiles (TFPs) based on temporal moment analysis.
Firstly, we conduct a correlation analysis between TFPs and microseismic (MS) event distribution for Xinjiang tight oil reservoir in China. And then, the relationship between cumulative flow capacity and cumulative storage capacity (F-C type curve) is developed using tracer flowback data by temporal moment method. The derivative of F-C type curve is applied to identify types of fracture networks. Finally, the results of fracture network evaluation obtained from tracer flowback are verified by the results from MS monitoring.
The correlation analysis indicates that fracture networks can be classified into three types: the first type of fracture network only comprised of several primary fractures, and TFP is multi-peak; the second type of fracture network comprised of primary fractures with some secondary fractures, and TFP is single-peak with a long tail; the third type of fracture network comprised of relatively uniform fractures, TFP is similarly of normal distribution. F-C derivative curve can be used to evaluate the types of fracture networks. If it does not have an abrupt change in F-C derivative curve, the fracture network can be considered as uniform distribution. If it has, the nearly horizontal line can be used to identify the number of primary fractures or fracture clusters.
Fracture network evaluation using tracer flowback is timely and of low-cost, which provides key information for reservoir-scale modeling and an alternative method for fracture evaluation. This study will definitely promote the management of tracer flowback.