Abstract

Hydraulic fracturing plays a significant role in unconventional oil and gas reservoirs. The hydraulic fracture initiation and propagation mechanism is fundamental important, but is understood unclearly. The large-scale hydraulic fracturing experiment, with the sample size of 30in*30in*36in, can simulate reservoir stimulation under the in-situ stress with the acoustic emission (AE) monitoring. AE is used to monitor fracture initiation and propagation in real-time and analyze the source mechanism of rocks.

The shear slippage can effectively enhance reservoir permeability, which makes the source of AE events important. In order to characterize the source mechanism, two methods are used in this paper: (1) the moment tensor inversion analysis, using P-wave first-motion polarities and amplitudes to determine crack type classifications from a unified decomposition of eigenvalues; (2) the single wave characteristic parameter analysis, using RA value (=the rise time/the maximum amplitude in mV) and average frequency (= AE ring down-count/the duration time) respectively as horizontal axis and vertical axis to plot a scatter diagram.

According to large-scale experiments with sandstone, coal and shale, results show that: (1) The conclusions obtained by the two methods are similar. Using the single wave characteristic parameter analysis to evaluate fracture mechanism in fracturing simulation experiment, the fractures are classified into two major groups: tensile fractures and shear fractures. (2) Tight sandstone only produces tensile fractures. The coal, shale and naturally fractured sandstone blocks have more complex mechanism with tensile and shear fractures, due to the existence of favorable natural fractures under specific in-situ stress and the injection pressure. (3) Spatial and temporal distribution of hypocenters is observed. A bi-wing planar fracture is formed in tight sandstone, but non- planar fracture networks exist in coal and shale blocks.

This work can help engineers establish a proper model for the estimation of effective stimulated reservoir volume (ESRV) using the microseismic data in hydraulic fracturing.

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