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The AAPG/Datapages Combined Publications Database

Indonesian Petroleum Association


IPA-AAPG Deepwater and Frontier Symposium, 2004
Pages 401-405

A Case Study: Gas in Place Sensitivities from Geocellular Modeling of the Gendalo Field, Ganal PSC

Khristina Kirschner, Skip F. Walden


The Gendalo Field is a deepwater gas field in the Ganal PSC, offshore East Kalimantan. A fieldwide geocellular model was developed for the two primary reservoir intervals. Modeling was undertaken for several purposes, one of which was to provide multiple scenarios of gas-in-place (GIP). To that end an effort was made to determine and rank the properties that produced the greatest difference in GIP. This was accomplished first by determining geological, geophysical and petrophysical ranges from core, log, seismic and analog data. These ranges were then applied in the geocellular model. GIP scenarios were generated by modeling variations in 1) gas-water contacts 2) structural configuration based on two different velocity models and structural top interpretations and 3) internal reservoir properties such as facies proportion, net-to-gross, porosity and water saturation. The volumetric effect of the established range of values for each property was analyzed by normalizing GIP to the mid case value for each set of scenarios and displaying the results in a tornado chart. Ranking the impact of parameters that contribute to GIP calculation allowed the subsurface team to evaluate the effect of ranges assigned to each property, determine if reservoir uncertainty was appropriately captured in the model and to focus future work on reducing uncertainty in key areas. In this analysis, net-to-gross and porosity were the two properties that produced the greatest variation in gas-in-place. In Resevoir A, where the GWC was relatively well known, varying the proportion of each facies also had a significant impact on GIP calculations. In Reservoir B, where only a lowest known gas was defined, variations in the placement of the gas-water-contact (GWC) produced the third largest difference in GIP. Variations in structure produced a nominal effect in GIP and prompted the team to consider whether structural uncertainty had been adequately captured in the analysis.

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