Shallow shelf carbonate reservoirs like the Eocene heavy oil reservoirs of Kuwait-Saudi Arabian divided zone exhibit a high degree of fluid flow heterogeneity where carbonate admixture with anhydrite. Diagnosing shallow shelf carbonate fluid flow heterogeneity is a very complex problem and represents a big challenge. Moreover, assessment of vertical and lateral permeability variation is a key factor for success of any reservoir development plan. The Eocene heavy oil reservoirs are producing since 1956. limited old well core data, and absence of reliable transient pressure test has added challenges for assessing accurate permeability distribution.
This paper shows how the Eocene wells productivity could be correlated with the common available well logs to develop a log based-permeability model. A series of cross plots for the perforated intervals of highest and lowest productivity wells were constructed. These cross plots show a relationship between the well productivity and location of log parameters on the plots. Based on this observation a relation between rock quality or productivity and conventional log parameters was established. Regression analysis as well as neural net work was used to develop a relationship between permeability and log parameters. The technique was validated by comparison with new wells data; mobility from Modular dynamic tester (MDT), core data and wells productivity.
Based on the developed model, Eocene wells vertical permeability and interwell continuity can be used to optimize new well placement for the horizontal and vertical infill drilling. Also the developed model represents an effective tool to predict the steam injectivity profile and to understand the interesting anomaly related to temperature-depth distribution. Moreover, the developed model will be used to optimize Steam flood process and steam pattern well completion for improving efficiency of formation heating and delaying steam flood break through.