Discrete Element Modeling (DEM) Improves Fundamental Understanding of Microseismicity Data and Provides Capabilities for Predicting Events
Gil, Ivan1, Marisela Sanchez1, Matt Pierce2, Paul Young3, Sean
1Itasca Houston, Houston, TX
2Itasca Consulting Group, Minneapolis, MN
3Applied Seismology Consultants, Toronto, ON
4Canadian Spirit Resources, Calgary, AB
Microseismic data from hydraulic fracturing field operations
were analyzed using a Discrete Element Model to understand fracture
propagation processes in a complex environment. The case history
presented is a thick gas reservoir package; composed of coal
(adsorbed gas), shale absorbed and free gas), and tight, gas-charged
sands. This rock package is located at rather shallow depths (less than
3000 ft). While the resource is good, economic and optimized
producibility mandates developing an optimized stimulation program.
Current “standard” methods for microseismic interpretation have limitations such as inherent non-uniqueness, difficulty in identifying failure mechanisms (tensile vs. shear), the existence of events located away from the fracture fronts, and also the fact that up to 90% of rock failure may be aseismic. In the model presented, rock is represented by an assembly of individual particles that are bonded at their contact points. Seismic events are generated when these bonds break under stress and deformation; stored strain energy is transformed into kinetic energy which is recorded as (micro)seismicity. This model is capable of replicating not only different failure modes of rock under a given stress field (shear and tensile events) but the associated seism locations and amplitudes as well.
Stimulation treatments in the rock package were monitored. The stimulations have been numerically represented and the location and chronology of microseismic events have been matched. The simulations are qualitatively validated by comparing the simulated seismicity with the actual data. This provides indications of the effective fracture network extent and the consequent fracture system conductivity.
AAPG Search and Discovery Article #90071 © 2007 AAPG Rocky Mountain Meeting, Snowbird, Utah