Summary This paper presents a novel technique to determine multicomponent diffusion coefficients for carbon dioxide (CO2) injection in a North Sea chalk field (NSCF) in Norway at reservoir conditions. The constant-volume-diffusion (CVD) method is used, consisting of an oil-saturated-chalk core in contact with an overlying free space, which is filled with the CO2. The experimental data are matched with an equation-of-state (EOS) -based compositional model. Transport by diffusion controls the dynamics of the constant-volume system and, together with phase equilibria, allows a consistent estimation of diffusion coefficients needed to describe the observed changes in system pressure. We conduct two experiments at reservoir conditions: One uses a core plug saturated with live oil and the other with stock-tank oil (STO). Once the experiments are completed, EOS-based compositional simulation is performed to match the experimental data by use of the oil- and gas-diffusion coefficients as history-matching parameters. The modeling work is conducted with a commercial reservoir simulator by use of a 2D radial-grid model to describe the experimental setup. The experiment uses an outcrop chalk core mounted in a vertically oriented core holder. The chalk is shorter than the core holder, thus resulting in an overlying void space. The system is initially saturated with oil at reservoir conditions. CO2 is then injected from the top, forming an overlying CO2 chamber and displacing oil toward the bottom of the core holder. Once CO2 fills the overlying bulk space, the system is isolated with no further injection or production. The CO2 and oil reach and remain in equilibrium locally at the gas/oil interface throughout the test, beginning and maintaining the diffusion mechanism. Diffusion of CO2 into the oil results in a decreasing pressure, which is the main history-matching parameter. The multicomponent diffusion coefficients are found to match the model pressure/time prediction to the experimental data. This suggests the modeling work flow incorporates a representative EOS model and the main transport dynamics controlled by diffusion are being treated properly. Proper simulation of CO2 injection in fractured-chalk reservoirs requires the ability to model multicomponent diffusion accurately. The proposed CVD method provides such modeling capabilities. Our modeling and experimental work indicate the novelty of the CVD method to determine the diffusion coefficients of a system where diffusion is the dominant displacement mechanism. The fact that the oil is contained within a low-permeability-chalk sample reduces density-driven convection that could result because of nonmonotonic oil-density changes as CO2 dissolves into the oil.

Past studies have shown that use of diluent injection with ESPs can be an efficient artificial lift method for heavy oil fields. It consists of injecting a light hydrocarbon liquid to reduce the oil density and viscosity. This paper describes an integrated modeling solution designed to maximize the reservoir oil production while minimizing the diluent requirement and keeping the crude oil quality within technical and marketing specifications. The field studied is an offshore heavy oil asset. It consists of two reservoirs with API gravities of 14 and 12, and oil viscosities at reservoir conditions of 70 cp and 500 cp. The field includes some 60 production wells. Diluent can be injected (1) in each individual well at the ESP and (2) in the surface processing facility prior to the second stage separator. Operating constraints include (1) minimum wellhead pressure, (2) diluent availability, (3) final crude quality specifications, (4) maximum field oil and liquid production rate. The difficulty of the production optimization problem lies in the nonlinearity of the well production curves and viscosity model. In this paper, we develop a Mixed Integer Linear Programming (MILP) formulation by piecewise linearizing the nonlinear behaviors. For each well at each time step, we adjust the black-oil rates from a reservoir simulator to create piecewise linear well performance curves giving the reservoir oil production as a function of diluent injected at the ESP. The proposed integrated solution is used for the entire production life of the field, which is still in the development phase. The solution is coupled with a reservoir simulator (1) to determine optimal diluent requirements over time, (2) forecast field production of reservoir oil, diluent, water and gas, and (3) foresee eventual bottlenecks in the infrastructure design (e.g. limiting constraints). The proposed solution can easily be used as a Real Time Production Optimization (RTPO) tool to find the optimal operating point based on the latest measurements (or real-time data). The optimal solution ensures the highest field reservoir oil production while meeting all constraints and keeping the diluent consumption at a minimum. The increase of the field oil production rate due to optimal diluent allocation ranges from 2 to 10 %. Cumulative reservoir oil production increases by approximately 3 million std m3. The uniqueness of the solution comes from the integration of all operating constraints into a single mathematical formulation. The computational time (1s – 10s) of the proposed solution outperforms any classical nonlinear approach. This allows running many sensitivity analyses of the entire integrated asset model.

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