Role of Detailed Reservoir Characterization and Lateral Placement on Well Performance in the Marcellus Shale Gas Reservoir

2013 ◽  
Author(s):  
M.A. Shebl ◽  
C. Nyaaba ◽  
R. Yalavarthi
Keyword(s):  
Shale Gas ◽  
Reservoir Characterization ◽  
Marcellus Shale ◽  
Well Performance ◽  
Gas Reservoir ◽  
Shale Gas Reservoir

Permeability inversion using induced microseismicity: A case study for the Longmaxi shale gas reservoir

2020 ◽  
Vol 8 (2) ◽  
pp. SG21-SG31
Author(s):  
Yadong Zhang ◽  
Reza Rezaee ◽  
Tobias M. Müller ◽  
Guangjie Zheng ◽  
Jimmy X. Li ◽  
...  
Keyword(s):  
Shale Gas ◽  
Large Scale ◽  
Reservoir Characterization ◽  
Fluid Pressure ◽  
Kriging Interpolation ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Pressure Diffusion ◽  
Significant Difference ◽  
Longmaxi Shale

We have predicted the flow permeability and its spatial distribution for the Longmaxi shale gas reservoir using microseismicity induced during hydraulic-fracturing stimulation. In the time-of-occurrence versus distance-from-injector plot, we find that microseismic points exhibit a parabolic envelope, which we interpret as a triggering front. This reveals that fluid pressure diffusion is at least one of the underlying mechanisms of microseismicity generation. We derive the large-scale equivalent diffusivity from the triggering front plot and thereafter obtain a 3D diffusivity map of the heterogeneous reservoir by solving an eikonal-like equation suggested previously. During this process, we apply kriging interpolation to increase the density of sparsely distributed microseismic points. The resulting diffusivity ranges between 1.0 and [Formula: see text] with the peak probability attained at [Formula: see text], which is consistent with the estimate we obtain from the triggering front analysis. We transform the diffusivity map into a permeability map using three different theories of fluid pressure diffusion in porous media: the seismicity-based reservoir characterization method (SBRC) based on Biot’s theory of poroelasticity, the quasirigid medium approximation (QRMA), and the deformable medium approximation (DMA) based on the de la Cruz-Spanos theory. The permeability according to QRMA is slightly higher than that from SBRC, yet we observe no significant difference. However, these estimates are by one order of magnitude higher compared with the permeability estimate from DMA. Furthermore, the permeability from all three theories is much higher than that from previously reported core sample measurements. We interpret this as the difference between large-scale equivalent and matrix permeability and therefore lend weight to the hypothesis that there exist highly conducting fluid pathways, such as natural fractures.

Shale gas reservoir characterization and sweet spot prediction

2018 ◽  
Author(s):  
Gang Yu ◽  
Yusheng Zhang ◽  
Ximing Wang ◽  
Xing Liang ◽  
Wei Liu ◽  
...  
Keyword(s):  
Shale Gas ◽  
Reservoir Characterization ◽  
Sweet Spot ◽  
Gas Reservoir ◽  
Shale Gas Reservoir

Prestack seismic data inversion for shale gas reservoir characterization in China

2016 ◽  
Author(s):  
Gang Yu ◽  
Yusheng Zhang ◽  
Ximing Wang ◽  
Xing Liang ◽  
Uwe Strecker ◽  
...  
Keyword(s):  
Shale Gas ◽  
Seismic Data ◽  
Reservoir Characterization ◽  
Gas Reservoir ◽  
Shale Gas Reservoir ◽  
Data Inversion

Shale-gas reservoir characterization and sweet-spot prediction

2017 ◽  
Author(s):  
Gang Yu ◽  
Yusheng Zhang ◽  
Ximing Wang ◽  
Wei Liu ◽  
Rui Guo ◽  
...  
Keyword(s):  
Shale Gas ◽  
Reservoir Characterization ◽  
Sweet Spot ◽  
Gas Reservoir ◽  
Shale Gas Reservoir
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