**1. Introduction**

Following the success in exploiting shale gas resources by multi-stage hydraulic fracturing with slickwaters or low-viscosity fluid (i.e., linear gel) in horizontal wells in North America, there has been a lot of interest in applying this technique to other regions and other types of tight reservoirs. This is due in part to the fact that conventional gel fracturing treatments have been less successful in some naturally fractured reservoirs due to excessive unexpected fluid loss and proppant bridging in natural fractures, leading often to premature screen-outs. Additionally, the high-viscosity gel left inside the natural fractures causes the loss of virgin permeability of the reservoir in the case of inefficient gel breaking.

However, the challenge for doing this is that the physical mechanism responsible for this kind of stimulation is yet to be fully understood and a standard work flow for design and evaluation is yet to be developed. Furthermore, industry so far mainly relies on performance analogs to improve understanding of each shale play, and thus it usually takes years to advance up the learning curve for determining which factors best affect well production [1].

Currently, the general opinion on the mechanism leading to the success of waterfrac in shale gas reservoirs is that a complex fracture network is created by stimulation of pre-existing natural fractures. Although it is difficult to observe the processes acting during stimulation, microseismic imaging has enabled us to understand that both simple, planar fractures and complex fracture networks can be created in hydraulic fracture stimulations under different settings [2]. Fracture complexity is thought to be enhanced when pre-existing fractures are oriented at an angle to the maximum stress direction, or when both horizontal stresses and horizontal stress anisotropy are low, because these combinations of stress and natural fractures allow fractures in multiple orientations to be stimulated [3]. The result of stimulation therefore depends both on the geometry of the pre-existing fracture systems and on the in-situ stress state. It is now generally accepted that stimulation in shale gas reservoirs occurs through a combination of shear slip and opening of pre-existing (closed) fractures and the creation of new hydraulic (tensile) fractures [4-6]. In wells that are drilled along the minimum horizontal stress (Shmin) direction, stimulation generally creates a primary radial hydraulic fracture that is perpendicular to Shmin. Then, pressure changes caused by fluid diffusion into the surrounding rock and the modified near-fracture stress field induced by fracture opening cause shear slip on pre-existing natural fractures. If the horizontal stress difference is small enough, new hydraulic fractures perpendicular to the main fracture can open. Each slip or oblique opening event radiates seismic energy, which, if the event is large enough, can be detected using downhole or surface geophones.

Founded on the idea that productivity enhancement due to stimulation results not just from creation of new hydraulic fractures but also from the effect of the stimulation on pre-existing fractures (joints and small faults), a new workflow dubbed "shale engineering", was estab‐ lished by combining surface and downhole seismic, petro-physical, microseismic, stimulation, and production data [7, 8]. In this new workflow (Figure 1), the change in flow properties of natural fractures is predicted using a comprehensive geomechanical model based on the concept of critically stressed fractures [9-11]. Existing reservoir simulation tools can then be used to model the hysteresis of fracture flow properties that result from the microseismically detectable shear slip, which is critical to the permanent enhancement in flow properties and increased access to the reservoir that results from stimulation. The primary hydraulic fracture created and propped during the stimulation can be modeled using conventional commercial hydraulic fracture models by taking into account fluid leaked into natural fractures in the surrounding region. The propped conductivity is estimated using laboratory-based proppant conductivity data adjusted for the proppant concentration in the fracture. The propped main fracture model and the reservoir model with stimulated natural fracture properties can then be integrated into production simulators to predict production after the slickwater hydraulic fracturing treatment. When available, microseismic data can be used to help define the network of stimulated natural fractures that comprises the stimulated reservoir volume (SRV).

Although this new workflow was developed based on experiences in shale gas reservoirs, we believe it can also be applied to any unconventional reservoir requiring stimulation that has pre-existing natural fractures. Both Coal Bed Methane (CBM) and fractured tight gas reservoirs are examples of where this approach could be applied. In this paper, we will illustrate the workflow using the results of a study conducted in a fractured tight gas reservoir in the Kuqa Depression, Tarim Basin.
