Technical Paper: Predicting Downhole Fluid Analysis Logs to Investigate Reservoir Connectivity

Society: IPTC
Paper Number: 11488
Presentation Date: 2007


Compartmentalization is perhaps the single biggest risk factor in deepwater petroleum production. Downhole fluid analysis (DFA) is a new tool to reduce uncertainty associated with reservoir connectivity. Fluid data from DFA logs and various laboratory analyses are studied to elucidate hydrocarbon composition variations in large reservoir sand bodies. This procedure was applied in the Deepwater Tahiti field in the Gulf of Mexico uncovering a large concentration variation of asphaltenes. These asphaltene nanoparticles are shown to be colloidally suspended in the crude oil in agreement with recent laboratory results, and settle preferentially lower in the oil column in accord with the Boltzmann distribution. Relevant fluid features, in this case the asphaltene concentration gradient, are then integrated in a geologic model and used to predict crude oil properties and DFA logs for all hydraulically connected sections of the reservoir. Predicted and newly acquired DFA log data matched for the first production well, establishing that the penetrated sands are likely connected, mitigating compartmentalization risk. This DFA log prediction protocol offers a new method to optimize wireline logging.

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