Improving 4D Seismic Data Interpretation using Geostatistical Filtering

@inproceedings{abreu:hal-04062054,
 abstract = {4D Seismic is becoming a conventional tool for hydrocarbon reservoirs monitoring and management, especially for heavy oil bearing fields (Calvert, 2005). In this case, 4D, or time-lapse seismic, can be used to detect important reservoir properties variations imposed by thermal enhanced oil recovery processes. This work aims at identifying remaining noise, invariant common features and time-dependent variations in oil reservoirs from post-stack amplitude time-lapse data. It involves a geostatistical multivariate technique called factorial co-kriging, an extension of the factorial kriging (FK) technique proposed by Matheron (1982). It is based on the decomposition of spatial correlations to identify redundant structures at various scales. Three seismic surveys, with different acquisition parameters, were acquired at the same site in different calendar times to monitor the progress of injected steam fronts into a heavy-oil reservoir. These seismic volumes were then carefully processed to minimize their discrepancies. Factorial co-kriging revealed possible common geological structures, 4D effects and remaining noise, and it seems to be an efficient method for extracting common regional trends from several repeated seismic datasets.},
 address = {Salvador, Brazil},
 author = {Abreu, Carlos Eduardo and Lucet, Nathalie and Nivlet, Philippe and Royer, Jean-Jacques},
 booktitle = {{9th International Congress of the Brazilian Geophysical Society \& EXPOGEF}},
 doi = {10.1190/sbgf2005-248},
 hal_id = {hal-04062054},
 hal_version = {v1},
 pages = {1249-1251},
 publisher = {{Brazilian Geophysical Society}},
 title = {{Improving 4D Seismic Data Interpretation using Geostatistical Filtering}},
 url = {https://hal.univ-lorraine.fr/hal-04062054},
 year = {2005}
}