Rock physics depth trend analysis using seismic stacking velocity

• Main Author: Hoang, Phuong
• Other Authors: Norges teknisk-naturvitenskapelige universitet, Fakultet for ingeniørvitenskap og teknologi, Institutt for petroleumsteknologi og anvendt geofysikk
• Format: Master Thesis
• Language: English
• Published: Institutt for petroleumsteknologi og anvendt geofysikk 2006
• Subjects: Norwegian Sea
• Online Access: http://hdl.handle.net/11250/239270

Quantitative seismic interpretation is becoming more and more important in exploration and characterization of petroleum reservoirs. In this technology, rock physic analysis combined with seismic attributes has become a key strategy. Nature creates inhomogeneous anisotropic rocks where the rock physics properties vary at different positions and directions. It is important to analyze and quantify the property changes as a function of depositional and burial trends in order to improve our detectability of petroleum reservoirs from seismic data. In this thesis, we have presented a new methodology to obtain rock physics properties as a function of burial depth, i.e., rock physics depth trends (RPDTs), from well log and seismic data. To obtain RPDTs, several authors have suggested using rock physics models calibrated to well log data or constrained by diagenetic models. We present an alternative way to extract these from seismic stacking velocities. This is the main focus of the thesis. We apply our methodology to extract RPDTs from seismic stacking velocities in the Njord Field area, located in the Norwegian Sea. We find that the seismic interval velocity trend matches nicely to the sonic velocity at the well location, especially above Base Cretaceous. By combining empirical RPDTs with seismic RPDTs, we are able to interpret and quantify the rock properties of different rock physics events that have occurred in Njord Field at well location and in the areas without well log information. In this thesis we have successfully demonstrated how stacking velocities can be used to improve our understanding about normal mechanical compaction trends, tectonic activity and diagenetic events. This information is important for improved overburden and reservoir characterization, especially in areas with sparse or no well log data.