Experimental Study of Hydraulic Fracture/Natural Fracture Interaction on a Tight Sandstone Formation

Author(s):  
Xiangtong Yang ◽  
Jeffrey Burghardt ◽  
Hui Zhang ◽  
Yang Zhang ◽  
Fuxiang Zhang ◽  
...  
2015 ◽  
Vol 3 (3) ◽  
pp. SU17-SU31 ◽  
Author(s):  
Jian Huang ◽  
Reza Safari ◽  
Uno Mutlu ◽  
Kevin Burns ◽  
Ingo Geldmacher ◽  
...  

Natural fractures can reactivate during hydraulic stimulation and interact with hydraulic fractures producing a complex and highly productive natural-hydraulic fracture network. This phenomenon and the quality of the resulting conductive reservoir area are primarily functions of the natural fracture network characteristics (e.g., spacing, height, length, number of fracture sets, orientation, and frictional properties); in situ stress state (e.g., stress anisotropy and magnitude); stimulation design parameters (e.g., pumping schedule, the type/volume of fluid[s], and proppant); well architecture (number and spacing of stages, perforation length, well orientation); and the physics of the natural-hydraulic fracture interaction (e.g., crossover, arrest, reactivation). Geomechanical models can quantify the impact of key parameters that control the extent and complexity of the conductive reservoir area, with implications to stimulation design and well optimization in the field. We have developed a series of geomechanical simulations to predict natural-hydraulic fracture interaction and the resulting fracture network in complex settings. A geomechanics-based sensitivity analysis was performed that integrated key reservoir-geomechanical parameters to forward model complex fracture network generation, synthetic microseismic (MS) response, and associated conductivity paths as they evolve during stimulation operations. The simulations tested two different natural-hydraulic fracture interaction scenarios and could generate synthetic MS events. The sensitivity analysis revealed that geomechanical models that involve complex fracture networks can be calibrated against MS data and can help to predict the reservoir response to stimulation and optimize the conductive reservoir area. We analyzed a field data set (obtained from two hydraulically fractured wells in the Barnett Formation, Tarrant County, Texas) and established a coupling between the geomechanics and MS within the framework of a 3D geologic model. This coupling provides a mechanics-based approach to (1) verify MS trends and anomalies in the field, (2) optimize conductive reservoir area for reservoir simulations, and (3) improve stimulation design on the current well in near-real-time and well design/stimulation for future wells.


2011 ◽  
Vol 51 (1) ◽  
pp. 499 ◽  
Author(s):  
Vamegh Rasouli ◽  
Mohammad Sarmadivaleh ◽  
Amin Nabipour

Hydraulic fracturing is a technique used to enhance production from low quality oil and gas reservoirs. This approach is the key technique specifically in developing unconventional reservoirs, such as tight formations and shale gas. During its propagation, the hydraulic fracture may arrive at different interfaces. The mechanical properties and bounding quality of the interface as well as insitu stresses are among the most significant parameters that determine the interaction mechanism, i.e. whether the hydraulic fracture stops, crosses or experiences an offset upon its arrival at the interface. The interface could be a natural fracture, an interbed, layering or any other weakness feature. In addition to the interface parameters, the rock types of the two sides of the interface may affect the interaction mechanism. To study the interaction mechanism, hydraulic fracturing experiments were conducted using a true triaxial stress cell on two cube samples of 15 cm. Sample I had a sandstone block in the middle surrounded by mortar, whereas in sample II the location of mortar and tight sandstone blocks were changed. The results indicated that besides the effect of the far field stress magnitudes, the heterogeneity of the formation texture and interface properties can have a dominant effect in propagation characteristics of an induced fracture.


Geofluids ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-22
Author(s):  
Jun Zhang ◽  
Yu-Wei Li ◽  
Wei Li ◽  
Zi-Jie Chen ◽  
Yuan Zhao ◽  
...  

Natural fractures in tight sandstone formation play a significant role in fracture network generation during hydraulic fracturing. This work presents an experimental model of tight sandstone with closed cemented preexisting fractures. The influence of closed cemented fractures’ (CCF) directions on the propagation behavior of hydraulic fracture (HF) is studied based on the hydraulic fracturing experiment. A field-scaled numerical model used to simulate the propagation of HF is established based on the flow-stress-damage (FSD) coupled method. This model contains the discrete fracture network (DFN) generated by the Monte-Carlo method and is used to investigate the effects of CCFs’ distribution, CCFs’ strength, and in-situ stress anisotropy, injection rate, and fluid viscosity on the propagation behavior of fracture network. The results show that the distribution direction of CCFs is critical for the formation of complex HFs. When the angle between the horizontal maximum principal stress direction and the CCFs is in the range of 30° to 60°, the HF network is the most complex. There are many kinds of compound fracture propagation patterns, such as crossing, branching, and deflection. The increase of CCFs’ strength is not conducive to the generation of branched and deflected fractures. When the in-situ stress difference ranges from 3 MPa to 6 MPa, the HF network’s complexity and propagation range can be guaranteed simultaneously. The increase in the injection rate will promote the formation of the complex HF network. The proper increase of fracturing fluid viscosity can promote HF’s propagation. However, when the viscosity is too high, the complex HFs only appear around the wellbore. The research results can provide new insights for the hydraulic fracturing optimization design of naturally fractured tight sandstone formation.


2018 ◽  
pp. 79-92
Author(s):  
A. Akulich ◽  
◽  
Li Kairui ◽  
D. Pestov ◽  
V. Tyurenkova ◽  
...  

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