@conference {Nagel2012,
	title = {{Understanding "SRV": A numerical investigation of "wet" vs. "dry" microseismicity during hydraulic fracturing}},
	booktitle = {Proceedings - SPE Annual Technical Conference and Exhibition},
	volume = {4},
	year = {2012},
	pages = {3375{\textendash}3386},
	abstract = {Effective monitoring of hydraulic fracturing stimulations is critical to their optimization, and the evaluation of field microseismic data is now commonly used in many of the active shale plays for this purpose. The concept of Stimulated Reservoir Volume (SRV), for example, is a common technique wherein the extent of the microseismic data is used to represent the size of the fluid drainage area for a fracture or well. A principal challenge with the interpretation of microseismic data - and its use to determine drainage area or some other metric for the success of the stimulation - is the understanding of the actual cause of the microseismicity itself. Basic geomechanics principles show that rock failure - the cause of microseismicity - is a result of changes in the in-situ effective stresses relative to a given rock strength. Effective stress - which is the stress acting on the rock matrix - may change either through a change in pore pressure (leading to {\textquoteright}wet{\textquoteright} microseismicity) or through a change in the total stress (leading to {\textquoteright}dry{\textquoteright} microseismicity). Dry microseismicity may occur well beyond the pressure field and be hydraulically disconnected from the wellbore. In this paper, we present the results of a numerical study of hydraulic fracturing-induced microseismicity using a discrete element code, where the mechanical behavior of the natural fractures is modeled explicitly, which allows for the quantitative evaluation of {\textquoteright}wet{\textquoteright} versus {\textquoteright}dry{\textquoteright} microseismicity. Copyright 2012, Society of Petroleum Engineers.},
	isbn = {9781622764150},
	url = {http://www.scopus.com/inward/record.url?eid=2-s2.0-84874038119\&partnerID=tZOtx3y1},
	author = {Nagel, Neal B. and Garcia, Xavier and Nagel, Marisela Sanchez and Lee, Byungtark}
}
