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AAPG GEO 2010 Middle East
Geoscience Conference & Exhibition
Innovative Geoscience Solutions – Meeting Hydrocarbon Demand in Changing Times
March 7-10, 2010 – Manama, Bahrain

Determining Induced Microseismic Event Position and Origin Time

Abdullah AlRamadhan1

(1) EXPEC ARC, Saudi Aramco, Dhahran, Saudi Arabia.

To optimize production and thus enhance hydrocarbon recovery, other alternatives are being considered to better understand hydrocarbon reservoirs. One technology being considered is the use of passive seismic techniques, which have recently attracted an increasing attention as an emerging technology for hydrocarbon reservoir monitoring, characterizing, and/or imaging.

Production activities within a hydrocarbon reservoir, such as extracting oil or injecting fluid, result in changing the in-situ stress conditions of the rock matrix that could trigger microseismic events. These induced microseismic events are small earthquakes producing high frequency waves, which can be useful for monitoring the hydrocarbon reservoir, if their hypocenters and origin times can be determined accurately. Moreover, because the ray-path depends on the slowness model, the relationship between the arrival time and the slowness is nonlinear.
Therefore, determining the locations of these events is a nonlinear inverse problem and under certain situations is also a multimodal problem.

We adopt a three-dimensional gridded velocity model in which traveltimes are calculated using the Previous HiteikonalNext Hit Previous HitequationTop. An objective function is constructed by fitting the model response traveltimes to a finite set of observed data through the use of the L1 norm. Then, we employ a systematic grid search algorithm to minimize the objective function and hence obtain the hypocenter position and origin time. The algorithm avoids using the derivatives of the objective function and is comparatively easy to implement and robust to optimize, when used for obtaining the event location and origin time. In addition, it seeks a global solution for the nonlinear and multimodal objective function. Thus, it has less chance of being biased to local solutions, and a better chance of obtaining superior results than the other methods. The results show application of the algorithm to both synthetic and field data.