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Reservoir fluids are rarely found in homogeneous structures having homogeneous properties. The various elements and processes of the petroleum system result in complex fluid distributions and compositions. A sound understanding of these complexities can avoid disappointing results and costly mistakes when designing the completion and production of the reservoir. The earlier these complexities are understood in the exploration phase, the better are the chances of a successful decision making process in the design phase of the project. Assessing reservoir compartment connectivity is of paramount importance for a optimal field development. Recent technological advances in wireline formation testing and sampling provide asset teams with a new methodology to evaluate in situ fluid properties and reservoir connectivity. After a review of the technology of downhole fluid analysis (DFA), the currently available methods of modeling equilibrated fluid gradients are presented. Fluid composition equilibrium is a stationary state where all components have reached zero mass flux. A reservoir model is designed to simulate numerically equilibration processes over geologic timescales at isothermal conditions where diffusion and gravity are the active mechanisms. A variety of initial conditions and reservoir fluid types is considered. Non-equilibrium fluid gradients and their transient behavior as they evolve towards fluid composition equilibrium are the main interest of this study. The results are compared in case studies, that are available in published literature. The modeling methods allow modeling of vertical and lateral fluid gradients. After a discussion of the cases, this thesis gives recommendations on 1) what fluid properties should be assessed and 2) how many data points are needed to reduce the chance of misinterpretation of non-equilibrium gradients in the presence of faults. To make best use DFA data, the property that exhibits the largest gradient needs to be investigated, as it yields the greatest potential to assess connectivity. The shape of the distribution of fluid composition within a compartment is found to be an important part in investigating reservoir connectivity. During data acquisition efforts should be made to acquire enough data points to reveal this shape. In combination with the presented techniques to identify non-equilibrium conditions, this will optimize DFA data acquisition and maximize the value of the data.

Integration of dynamic data is critical for reliable reservoir description and has been an outstanding challenge for the petroleum industry. This work develops practical dynamic data integration techniques using streamline approaches to condition static geological models to various kinds of dynamic data, including two-phase production history, interference pressure observations and primary production data. The proposed techniques are computationally efficient and robust, and thus well-suited for large-scale field applications. We can account for realistic field conditions, such as gravity, and changing field conditions, arising from infill drilling, pattern conversion, and recompletion, etc., during the integration of two-phase production data. Our approach is fast and exhibits rapid convergence even when the initial model is far from the solution. The power and practical applicability of the proposed techniques are demonstrated with a variety of field examples. To integrate two-phase production data, a travel-time inversion analogous to seismic inversion is adopted. We extend the method via a 'generalized travel-time' inversion to ensure matching of the entire production response rather than just a single time point while retaining most of the quasi-linear property of travel-time inversion. To integrate the interference pressure data, we propose an alternating procedure of travel-time inversion and peak amplitude inversion or pressure inversion to improve the overall matching of the pressure response. A key component of the proposed techniques is the efficient computation of the sensitivities of dynamic responses with respect to reservoir parameters. These sensitivities are calculated analytically using a single forward simulation. Thus, our methods can be orders of magnitude faster than finite-difference based numerical approaches that require multiple forward simulations. Streamline approach has also been extended to identify reservoir compartmentalization and flow barriers using primary production data in conjunction with decline type-curve analysis. The streamline 'diffusive' time of flight provides an effective way to calculate the drainage volume in 3D heterogeneous reservoirs. The flow barriers and reservoir compartmentalization are inferred based on the matching of drainage volumes from streamline-based calculation and decline type-curve analysis. The proposed approach is well-suited for application in the early stages of field development with limited well data and has been illustrated using a field example from the Gulf of Mexico.

No description available.