Light time-lapse seismic monitoring for SAGD: a new approach & operational model
Paper presented at the Geoconvention 2021 – Virtual, Calgary, Canada , September 2021, and co-written by Victoria Brun, Elodie Morgan, Brad Gerl, Luis Cardozo, Richard Habiak.
Steam Assisted Gravity Drainage (SAGD) techniques are commonly used to develop oil sand fields in Alberta, Canada. To monitor the enhanced oil recovery process and caprock integrity, highly repeatable 4D seismic surveys have been completed over the years, and numerous fields have been equipped with permanent receiver layouts and cased shot locations.
A light and novel innovative seismic approach to monitor SAGD operations in Surmont on a pad had been blind tested on legacy data. It has proven the possibility to monitor steam effect by extracting time-shifts matching temperature data on optimal raw seismic traces acquired every 6 months between 2010 and 2015. This success led to the planning of a specifically designed field measurement on another in the Surmont area. For this monitoring, 4 different areas with approximately 20 spots repeating only 17 shots locations & 20 receiver locations were designed. The goal of this field acquisition was to assess the capability of the method to perform reliable 3-months time-lapse monitoring to better capture reservoir dynamics.
An efficient collaboration between the operator (ConocoPhillips), the seismic acquisition provider (Echo Seismic) and the processing start-up (SpotLight) was key to optimize the operational model, thus leading to detections better reflecting the reservoir dynamics. Critical areas to be monitored were indicated by the operator, with the processing company designing the optimal source & receiver locations and acquisition parameters using existing 3D data that were then passed on to the acquisition provider. The acquisition was performed and feedbacks about the in-field accessibility to help further optimize future detection were provided. Finally, the processing company presented the detection results to the operator.
In this paper the workflow & operational model is presented with a focus on how we were able to reduce the number of sources & receivers needed to provide reliable information about the area’s dynamics. We then present the detection results obtained on each 4 areas with a comparison of some of the observation wells. Finally, detection threshold, method limitations, further optimization & ways forward are discussed.