Wireline Formation Testers Unlock Potential in a Deepwater Gas Condensate Reservoir

Abstract Reservoir-fluid properties play a key role in exploration and field development planning as accurate fluid characterization is important for designing reservoir development strategy, optimizing well completion, optimizingthe production system and efficient reservoir management. Characterization of reservoir fluids with more complex behaviors, such as gas condensates and near-critical fluids can be technically challenging, especially in a deepwater environment as reservoir development planning and production facility design is contingent on getting an accurate description of the reservoir fluid. Fluid characterization begins with the collection of representative formation fluid samples during initial wireline formation testing, bottomhole sampling and during conventional well testing operations. Traditionally these fluid samples are sent to offsite laboratories for sample analysis. However, characterizing a gas condensate fluid system based on a single sample set can be potentially misleading since PVT properties of samples acquired across a reservoir may be different due to spatial variation in their components and compositional grading. In this technical contribution we present a case study to demonstrate that characterizing gas and gas-condensate systems using only a basic set of measurements and from analysis of pressure gradients alone; could lead to potentially ambiguous results, an inappropriate fluid model or misinterpretation. In our study, we describe the practical application of advanced wireline formation sampling and testing techniques in combination with downhole fluid analysis, and their integration with laboratory PVT studies and equation-of-state (EOS) models. We describe the importance of a comprehensive data collection and fluid analysis plan early in the exploration/ appraisal process, and illustrate how high-quality fluid sample data and property measurements from advanced formation sampling and testing tools in combination with conventional well testing techniques can add significant value by helping to reduce uncertainty and aiding better technical decision making.