How to ensure that miscibility of oil and gas is achieved in each reservoir is a fundamental issue for miscible gasfloods involving different oil reservoirs with varying fluid properties. This paper reports on all the work done to help decide on how to optimally blend available gas such that miscibility can be achieved in all reservoirs with appropriate focus on the first reservoirs to be flooded. These studies have resulted in an investment decision to undertake a miscible gasflood already in 2005, whereas initial production from four reservoirs had only started in March 2004. Main components of this paper are:

  1. Design of experiments for a wide spectrum of fluids (from near-critical systems to black oil systems) using miscible sour gas-blends while minimizing cost and the time spent on the experiments.

  2. Acquisition, interpretation of the data

  3. Utilization of the data for reservoir engineering/design calculations using a consistent approach for a cluster of sour reservoir fluids,

  4. Recommendations based on the experimental data and calibrated simulation models.


A recently discovered cluster of reservoirs in the South of Oman consists of 8 different fields containing 10 reservoirs. All the reservoirs are carbonate reservoirs at 3.5 to 5.5 km deep embedded in salt. The reservoirs are all very similar carbonate slabs of about 100 m thick and generally have low permeability (1 to 10 md). Probably related to their position in the salt, some of the reservoirs are at hydrostatic pressures, whereas others are close to lithostatically pressured. Because of slight differences in charge history the fluid properties vary from a retrograde gas condensate to black oil with moderate GOR (185 m3/m3), as shown in Table 1. Fluids from reservoirs A,B,D,E,G,I and J are black oils, from H a volatile oil, from C a critical fluid, and from F a gas condensate.

Development of the cluster takes place in a phased manner with a shared central facility. Details of the strategies employed to mature the reservoirs are given by O'Dell et al1. Implementation of miscible gas injection from day one of full production sets this project apart from others in the world, where miscible gas injection is mostly used as a tertiary or sometimes secondary oil recovery method. This paper deals with the PVT-related work that was performed to ensure that each reservoir gets the appropriate gas quality required for miscible conditions.

An important boundary condition for the miscible gasflood projects in the cluster is that the combined cluster has to be self-sufficient in injection gas, i.e., no gas will be imported from other sources. This means that the miscible agents need to be a cocktail of associated gas and gas from the only gas condensate reservoir in the cluster. As no additional gas will be imported, full voidage replacement in the entire cluster cannot be maintained. However, this will not be a problem when we analyze the cluster as some of the reservoirs are at very high pressure and one gas condensate reservoir is available. Some of the high-pressure reservoirs that are on primary depletion will provide injection gas for those reservoirs that are on miscible gasflood. With proper phasing there will be enough gas for all reservoirs to be gasflooded within a 30-year period.

Fluid Sampling and Analysis

As for many enhanced oil recovery projects, fluid samples and well-designed experiments with those fluid samples are critical for evaluating and implementing a miscible gasflood. In simple terms, one of the main advantages of a miscible or near-miscible gas injection process is the interaction of the injectant with the in-situ fluid. Reservoir simulators require calibrated phase behavior/PVT data to be able to correctly quantify the interaction of phase behavior and flow. Therefore, experiments that can quantify the phase behavior between the injected fluid and the reservoir oil(s) are extremely important for the design of such floods. In addition, dynamic effects of fluid-fluid interaction, and transition zone development and/or miscibility development in the presence of porous medium (reservoir scale to core-slimtube scale) are normally quantified using the learnings from the combination of experiments and reservoir simulation.

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