Integrating seismic attribute maps and well logs for porosity modeling in a west Texas carbonate reservoir: addressing the scale and precision problem

Abstract

A 3-D porosity field in a west Texas carbonate reservoir is modeled conditional to both “hard” porosity data sampled by wells and 2-D seismic attribute map with less vertical resolution than the well log data. The difference-of-scales between the two sources of data is resolved by a prior 2-D estimation of vertically averaged porosity using well and seismic data. These 2-D estimates are then used to condition the 3-D stochastic simulation of porosity. The algorithm used to merge 2-D average values and 3-D data values, i.e., to solve the difference-of-scale problem, is a form of block kriging, which ensures that vertical averages of the 3-D estimates reproduce exactly the 2-D average data values. The precision of the 2-D conditioning data is also addressed. Several new geostatistical algorithms, such as automatic covariance modeling and direct sequential simulation algorithms, are weaved into the application. These new algorithms facilitate the process of integration of the soft data in petrophysical modeling.