Sparse image domain wavefield tomography for low-cost CCS monitoring in repurposed hydrocarbon fields

Seismic time-lapse (4D) imaging has been considered as a key solution to monitor CO₂ reservoirs. However, traditionally this technology requires dense data acquisition to produce high-resolution images. It is anticipated that monitoring will be required for more than 50 years after CCS operations cease and the monitoring phase is profit-negative. Developing cheaper 4D seismic imaging techniques is necessary. Historical knowledge of the subsurface structure in and near abandoned hydrocarbon fields, could reduce the dense data requirement of 4D imaging.

Here we present preliminary results of 4D seismic (image-domain) wavefield tomography (IDWT) using pre-stack gathers from a sparse monitoring acquisition. IDWT uses short-offset data to exploit primarily kinematic changes rather than amplitude changes. IDWT minimises the shift between baseline and monitor migrations by optimising the monitor velocity model. Pre-stack IDWT, unlike post-stack methods, can use individual shot gathers to calculate the migration images. This property is beneficial when using sparse data acquisition permitting reliable measurement of shifts between monitor and baseline. Knowing the structure of the subsurface, we can design sparse acquisition surveys for seismic deployment, to minimize uncertainty in target areas. 

We create synthetic models based on Tyra gas field, a prospective future repository of CO₂ in the Danish sector of North Sea and simulate CCS and subsequent leakage scenarios. The presence of CO₂ in the reservoir, as well as the effect of reservoir pressure on the overburden stress-state, changes the seismic velocity structure of the reservoir and the overburden. These velocity changes cause an apparent depth (or time) shift when migrating the data.