Compositional Modeling of Oil-Based Mud-Filtrate Cleanup During Wireline Formation Tester Sampling

Abstract

Abstract Miscible oil-based mud (OBM) filtrate contamination poses a major challenge to the acquisition of representative fluid samples using wireline formation testers (WFTs). A sound understanding of the physics of OBM filtrate clean-up and identification of first-order impact parameters is of paramount importance for the design of new generation WFT probes that can operate in OBM filtrate environments with enhanced efficiency. Analytical as well as numerical models reported in the formation testing literature rely predominantly on simplifying assumptions in terms of the compositions of flowing fluid phases. These models characteristically assume single-component phases in the case of two-phase immiscible formulation, or a two-/three-component hydrocarbon phase in cases of black-oil/extended black-oil formulations. In turn, compositional interactions are entirely neglected or represented through simplistic empirical correlations. Such conventional models are deemed sufficient for pre-job planning and interpretation of measurements acquired in formations subject to water-base mud (WBM) filtrate contamination. Dynamics of flow in OBM filtrate contaminated formations is significantly more complex. A time-dependent coupling between fluid dynamics and phase behavior constitutes the governing physics of OBM filtrate clean-up process. Therefore, for OBM filtrate environments, accuracy of conventional formulations in representing the actual physics of flow is limited. We have constructed a numerical model for the OBM filtrate clean-up within the framework of an equation-of-state (EOS) compositional fluid-flow simulator. Our numerical framework simultaneously honors the physics of multi-component fluid flow and the thermodynamics of phase behavior. The numerical model was verified against analytical solutions for zeroth-order models for which analytical solutions exist. Simulation results exhibited close agreement with the analytical predictions and with field data for the time dependence of contamination during sampling. A rapid approximate response surface based model, which can serve as a pre-job planning or real-time analysis tool, was derived from extensive simulations conducted with the compositional numerical model. Our simulation and rapid modeling results compare well with empirical observations made in the field. In particular, the rate of change of miscible contamination with time has been found empirically to vary as t5/12. For the first time, modeling has been shown to give essentially the same results as empirical observations. The agreement between our model and common field observation motivates use of our model to analyze the more complex WFT probes, which have recently become available.