Seismic Acoustic Impedance Inversion in
Reservoir Characterization Utilizing gOcad
By Steven Clawson and Hai-Zui (“Hai-Ray”) Meng, iReservoir.com
Presented at the 2000 gOcad Users Meeting
Presented at the 2000 gOcad Users Meeting
Introduction
In Seismic oil and gas , the workflows for utilizing seismic data inverted to acoustic impedance data in reservoir characterization will be shown. We are using the public domain 3D seismic dataset at Boonsville Field in North-Central Texas for our example. This public domain dataset is fairly complete with seismic, well, and production data:
•5.5 sq. Miles of 3D seismic data
•Vertical seismic profile (VSP) near center of survey
•Digital well logs from 38 wells
•Well markers for the bend conglomerate group
•Perforations, reservoir pressures, production and Petrophysical data for the 38
wells
We acknowledge Oxy USA, Inc., Enserch, Arch Petroleum, Bureau of Economic
Geology, GRI and the DOE as contributing members for making this dataset available.
This data is made publicly available as part of the technology transfer activities of the Secondary Gas Recovery (SGR) program funded by the U. S. Department of Energy and the Gas Research Institute.
This 2nd iteration of inversion shows the transformation of the seismic amplitudes to rock properties.
Qualitative correlation to the key well: B Yates 18D yields similar results as before.
Now cross-plotting the seismically derived acoustic impedance and the log properties in
depth shows a better correlation. These correlations are good enough to use in a colocated
co-Kriging of the well log properties.
Rock property models are now generated by co-located co-Kriging of the gamma ray logs
for lithology discrimination and resistivity logs controlled by the seismically derived AI
properties
A reservoir model of sandstone porosity can be derived by the relationships of lithology
to gamma ray and resistivity. Where these models of gamma ray and resistivity are
related back to the seismically derived acoustic impedance.
to gamma ray and resistivity. Where these models of gamma ray and resistivity are
related back to the seismically derived acoustic impedance.
By segmenting the data into a sandstone region defined by where:
Gamma ray is less than 90 and
Log10(Resistivity) is greater than 0.8
A sandstone porosity relationship is defined.
Gamma ray is less than 90 and
Log10(Resistivity) is greater than 0.8
A sandstone porosity relationship is defined.
Constructing the density model in the sandstone facies then is represented here.
