Feasibility of borehole ambient noise interferometry for permanent reservoir monitoring
The analysis of seismic ambient noise acquired during temporary or permanent microseismic monitoring campaigns (e.g., improved/enhanced oil recovery monitoring, surveillance of induced seismicity) is potentially well suited for time-lapse studies based on seismic interferometry. No additional data acquisition required, ambient noise processing can be automatized to a high degree, and seismic interferometry is very sensitive to small medium changes. Thus there is an opportunity for detection and monitoring of velocity variations in a reservoir at negligible additional cost and effort. Data and results are presented from an ambient noise interferometry study applied to two wells in a producing oil field in Romania. Borehole microseismic monitoring on three component geophones was performed for four weeks, concurrent with a water-flooding phase for improved oil recovery from a reservoir in ca. 1 km depth. Both low-frequency (2 Hz–50 Hz) P- and S-waves propagating through the vertical borehole arrays were reconstructed from ambient noise by the virtual source method. The obtained interferograms clearly indicate an origin of the ambient seismic energy from above the arrays, thus suggesting surface activities as sources. It is shown that ambient noise from time periods as short as 30 seconds is sufficient to obtain robust interferograms. Sonic log data confirm that the vertical and horizontal components comprise first arrivals of P-wave and S-waves, respectively. The consistency and high quality of the interferograms throughout the entire observation period further indicate that the high-frequency part (up to 100 Hz) represents the scattered wave field. The temporal variation of apparent velocities based on first-arrival times partly correlates with the water injection rate and occurrence of microseismic events. It is concluded that borehole ambient noise interferometry in production settings is a potentially useful method for permanent reservoir monitoring due to its high sensitivity and robustness.