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Identification of Hydraulic Fracture Orientation from Ground Surface Using the Seismic Moment Tensor

E.V. Birialtcev1, V.A. Ryzhov1, S.A. Feofilov1, I.R. Sharapov1, M.R. Kamilov2, D.A. Ryzhov1, E.V. Mokshin2

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Microseismic monitoring from ground surface is applied in the development of hard-to-recover reserves, especially in the process of hydraulic fracturing (HF). This paper compares several methods of HF microseismic monitoring from the surface, including diffraction stacking, time reverse modeling, and spectral methods. In (Aki and Richards, 1980) it is shown that signal enhancement from seismic events under correlated noises significantly improves when applying the maximum likelihood method. The maximum likelihood method allows to exclude influence of the correlated noise, and also to estimate the seismic moment tensor from ground surface. Estimation of the seismic moment tensor allows to detect type and orientation of source. Usually, the following source types are identified: “Explosion Point” (EXP), “Tensile Crack” (TC), “Double-Couple” (DC) and “Compensated Linear Vector Dipole” (CLVD). The orientation of the hydraulic fracture can be estimated even when there is no obvious asymmetry of the spatial distribution of the cloud of events. The features of full-wave location technology are presented. The paper also reviews an example of microseismic monitoring of hydraulic fracturing when there is no obvious asymmetry of microseismic activity cloud, but due to the estimation of the seismic moment tensor it becomes possible to identify with confidence the dominant direction of the fracture.

Microseismic monitoring, seismic moment tensor inversion, fracturing, seismic event, maximum likelihood method

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1Gradient CJSC, Kazan, Russia
2Gradient Technology LLC, Kazan, Russia

For citation:

Birialtsev E.V., Ryzhov V.A., Feofilov S.A., Sharapov I.R., Kamilov M.R., Ryzhov D.A., Mokshin E.V. Identification of Hydraulic Fracture Orientation from Ground Surface Using the Seismic Moment Tensor. Georesursy = Georesources. 2017. V. 19. No. 3. Part 1. Pp. 229-233. DOI: