© 2011 EAGE www.firstbreak.org 99 special topic first break volume 29, July 2011 Passive Seismic Identifying faults and fractures in unconventional reservoirs through microseismic monitoring Scott A. Wessels, * Alejandro De La Peña, Michael Kratz, Sherilyn Williams-Stroud and Terry Jbeili of Microseismic describe how in microseismic monitoring of low permeability reservoirs the use of source mechanism inversion, b values, and energy release rates enables identifica- tion and differentiation between fracture stimulation and fault activation, critical issues for effective hydraulic treatment. M icroseismic monitoring in low permeability res- ervoirs is a valuable source of information for unconventional resource play optimization. The application of new technologies, such as efficient horizontal drilling and hydraulic fracturing (‘fracking’) has resulted in the ability for the industry to produce from organic rich shales. Prior to such technology developments, hydrocarbons from such formations were typically not economically accessible or even recoverable. Monitoring of microseismicity is essential to understanding how a forma- tion responds to the injection of frac fluids and proppant because many of the most active shale plays remain in the early stages of development and a wide range of geologic hazards may be present, such as faults, karst collapse fea- tures, and proximal aquifers. Microseismic monitoring provides the necessary information to estimate stimulated reservoir volume (SRV) and identify faults that are unresolv- able with reflection seismic data that may pose a hazard to completion operations. A successful frac will typically increase the permeability of fine-grained hydrocarbon reservoirs – thus enhancing the well’s production and delivering a significant rate of return. This is achieved by stimulating an existing network of natural fractures (Maxwell et al., 2006; Gale et al., 2007). Hydraulically stimulated natural fractures are generally near the wellbore and are a primary receiver of proppant neces- sary to create a flow pathway to the wellbore. In some cases, a horizontal wellbore will encounter a pre-existing stressed tectonic fault. Pumping of fluids and proppant into a fault can bring about one or more unintended negative effects. A non-target formation may be stimulated and give rise to hydraulic connectivity with aquifers that ultimately increase water production. Another risk is diversion of fluid and proppant to a fault zone that lies several hundred feet away from the target fracture stage. The end result is decreased stimulation of the target formation, a potential increase in water production, and a significant cost to the operator in terms of time and materials. Having the ability to differenti- ate between faults and fractures in a timely manner is critical to reducing such material waste which could be otherwise employed in areas that are more favourable for effective stimulation. Understanding the source mechanism of a microseismic event leads to improved event location and provides infor- mation vital to generating realistic reservoir models. Source mechanisms indicate how the formation fails under stress; the polarity of the first P-wave arrival indicates relative motion along the failure plane. Identification of one or more source mechanisms within microseismic data recorded during hydraulic fracturing provides information about the current stress state of the formation and, where multiple source mechanisms exist, can also be used to differentiate between reactivation of a stressed tectonic fault and desirable natural fracture stimulation. Statistical analysis using frequency magnitude distribution histograms (FMD) may be indicative of changes in the stress magnitude (Schorlemmer et al., 2005; Gulia et al., 2010), and in the following case study, determines if a population of events is generated by fault motion or natural fractures. The FMD relationship was first identified by Gutenberg and Richter (1954) and demonstrated in the formula: log N = A - bM s where N is the number of events with magnitudes within a fixed interval around M s . A and b are constants. The constant b for a specific event population represents the frequency of occurrence for different size events; a higher slope indicates fewer large events and more small events than a lower slope b value. Maxwell et al. (2009) and Downie et al. (2010) observed during a hydraulic treatment that fault related microseismicity is correlated to b values of ~1 while desirable induced natural fracture related microseismicity exhibits a b value of ~2. * Corresponding author, E-mail: swessels@microseismic.com