Reservoir Monitoring With True4D Surface Seismic Data

Harris et al., (2007) proposed a strategy, called True4D, for quasi-continuous reservoir monitoring with sparse data. True4D introduced two concepts for processing sparse but continuously recorded datasets: (1) dynamic imaging and inversion, (2) data evolution, and (3) model evolution. Arogunmati and Harris (2009, 2010) presented an approach to data evolution, i.e., inversion or imaging using data estimated from sparse recordings. In this paper, we examine the practicability of their approach, and present its application to full trace synthetic and field surface seismic data. The True4D approach is implemented by acquiring as little as 5% of the conventional 3-D survey data volume at small time intervals. Unrecorded data at each time interval are then estimated using recorded data at all intervals to produce an image with good spatial resolution of the subsurface. The high temporal resolution obtained using the True4D approach is its main benefit.