**Author details**

There are, however, some uncertainties in the modeling of the natural fracture stimulation for

**1.** The pressure-permeability relationship used in modeling the permeability enhancement by slickwater stimulation is taken from a shale gas field. It is unclear whether the data from the analogue field drilled through mudstones will be applicable to the modeled fractured tight sandstone reservoir. Post-stimulation production simulation, or a prestimulation injectivity test in nearby wells in open hole could help to better constrain this

**2.** Due to the lack of knowledge of fracture distribution between wells, the fractures interpreted from all three offset wells were used to predict the stimulation behavior of natural fractures, and it was assumed that a similar fracture distribution would be found in all formations. In reality, the fracture distribution is likely to be different, depending among other things on the lithology and structural location. For example, it is already noticed that there are fewer fractures in the lower part of the reservoir than in the upper part in the D3 well. Intervals with dense fracture networks are more likely to benefit from slickwater treatment compared to formations with no or very sparse fractures. A 3D

**3.** Micro-seismic imaging is not available in the study area. No wells are close enough to work as a monitoring well and surface monitoring is also impossible due to the great depth of the reservoir. The lack of microseismic data made it impossible to calibrate the predic‐

The main uncertainty in gel frac productivity estimation comes from the propped fracture conductivity estimation. This conductivity is based on proppant testing in the laboratory. The proppant inside fractures involves clogging, crashing and embedment over the production period. There is no analytical method available to model these long-term effects on propped fracture conductivity. An approximate conductivity damage factor has been used in this study

Although there are still some shortcomings with the workflow, it can assist in the assessment of development concepts and the evaluation of stimulation enhancement options. The anisotropy in the slickwater treatment can be reasonably well-predicted and applied into the production simulation, which provides a more robust prediction than a simple isotropy model. The new workflow can be used in naturally fractured shale gas, tight gas/oil and CBM

The authors wish to thank PetroChina Tarim Oil Company for providing us with the data and for permission to publish this paper, and Baker Hughes internal support to carry out the work.

relationship, hence improve the accuracy of the prediction.

description of the fracture distribution is always preferred.

this fractured tight gas reservoir.

1036 Effective and Sustainable Hydraulic Fracturing

tion of the shape of SRV.

to consider these effects.

**Acknowledgements**

reservoirs.

Feng Gui1\*, Khalil Rahman1 , Daniel Moos2 , George Vassilellis3 , Chao Li3 , Qing Liu4 , Fuxiang Zhang5 , Jianxin Peng5 , Xuefang Yuan5 and Guoqing Zou5

