The tracer-based production logging technology can be used to obtain the well production data continuously for several years without the need for risky well interventions and expensive equipment. The paper examines the case of placing polymer-coated tracers dopped proppant in a horizontal well with ten multi-stage frac intervals and using two different tracers dopped proppant codes for two frac ports (the first and the last ones) to identify the performance of the far and near zones of a hydraulic fracture.
Upon the completion of the hydraulic fracturing operations, the collected reservoir fluid samples were studied in the laboratory. Chemical tracers contained in the samples were detected by flow cytofluorometry using custom-tailored machine learning-based software. The studies helped identify the productivity of each frac port, calculate the contribution of each port in percentage points, and also evaluate the productivity of the near and far hydraulic fracture zones in the first and the last intervals.
The analysis provided data on the exact content of oil and water in the production profile for each frac interval. The results of tracer-based logging in the well in question revealed that the interval productivity is changing in the course of several months of surveillance. The most productive ports and those showing increasing oil flow rate were identified during quantitative analysis.
The use of tracer dopped proppant with different codes within one multi-stage frac interval enabled detecting a peak release of chemical tracers from the far fracture zone in the initial periods of well operation followed by a consistent smoothing of the far and near zones’ production profiles. Laboratory analysis of reservoir fluid samples and hydraulic fracturing simulations proved the uniform distribution of proppant across the entire reservoir pay zone and laid the foundation for further research required to better understand the fracture geometry and reduce uncertainties in production optimization operations.