Ranking Reservoirs for Carbon Dioxide Flooding Processes

Abstract

Summary The screening of large number of reservoirs for the application of EOR processes has been generally done through "rules of thumb" which often times fail to identify the most suitable reservoirs, due to their binary characteristics, which do not take into account synergistic effects on process performance. Therefore, a new screening process performance. Therefore, a new screening method is developed in this work to rank reservoirs for carbon dioxide flooding which attempts to solve this shortcoming. The method is based on a parametric study, carried out systematically to determine the effect of reservoir properties on reservoir response to the gas injection. The study was done using a fully compositional simulator, a black oil model with a mixing parameter, and a semi-analytical predictive model. Results obtained with the three simulators are presented and compared in this paper. Reservoir parameters examined were temperature, pressure, porosity, permeability, dip, API gravity, oil saturation, net oil sand thickness, minimum miscibility pressure, saturation pressure, remaining oil in place, and reservoir pressure, remaining oil in place, and reservoir depth. The optimum set of parameters which gave the best average oil production rate for a base case was obtained from the simulation studies. The base case consisted of the injection of 2000 MSCF/D of carbon dioxide in a inverted five spot, 40 acres pattern. The decrease in oil production rate with departures of the production rate with departures of the characteristic parameters from the optimum values were also determined to quantify the importance or weight of each property. Actual reservoirs were ranked by an arbitrary heuristic function, called the exponentially varying function, whose value depended exponentially on the weighted differences between the properties, characteristic of the reservoir, and the optimum values obtained from the simulation studies. Results obtained with the three simulators compare quite well and indicate that on the average, the best reservoir for carbon dioxide injection should have an oil gravity of 36 degrees API, a temperature of 150 degrees F, a permeability of 300 mD, an oil saturation at the start of the injection of 60 %, a reservoir pressure at the time of injection of around 200 psi over minimum miscibility pressure, a porosity of 20 %, a net sand thickness of 40 ft and a reservoir dip of 20 deg. Of the above parameters, those whose changes around the optimum influence the most process performance are API gravity, oil process performance are API gravity, oil saturation and reservoir pressure. Therefore, the reservoirs with these three parameters closer to the optimum values are the best candidates for CO injection. This is taken adequately by the exponentially varying function defined in the paper. The procedure was applied to rank about six hundred reservoirs in the greater Anaco and Oficina areas of Eastern Venezuela in order to identify the most suitables for a pilot test. The reservoir ranked 30th by the method hereby described was chosen to implement the pilot. This procedure could be easily extended to other EOR processes once the necessary simulations are carried out.

A Review of CO2-Enhanced Oil Recovery with a Simulated Sensitivity Analysis

“…This is because, at higher initial reservoir pressures, there is less "room" for CO 2 to be injected into the reservoir, causing a reduction in CO 2 injectivity, which in turn leads to reduced oil production, which is important in miscible CO 2 floods. This observation is consistent with the findings of Rivas et al [69] and Thomas [51]. Rivas et al [69] found an increment in average oil production with reservoir pressure up to 1.3 MMP, however, it started to reduce with pressure with further increase of reservoir pressure (>1.3 MMP).…”

“…This observation is consistent with the findings of Rivas et al [69] and Thomas [51]. Rivas et al [69] found an increment in average oil production with reservoir pressure up to 1.3 MMP, however, it started to reduce with pressure with further increase of reservoir pressure (>1.3 MMP). According to these researchers, this is related to the correlation between CO 2 formation factor and live oil viscosity.…”

Arctic Energy Technology Development Laboratory

“…Where P o,j is the magnitude of parameter (j) in an optimum reservoir, which results in optimum CO 2 flooding; these optimum parameters were obtained from the studies by Rivas et al (1992). The optimum properties for the most favorable reservoir were determined by performing a numerical simulation, which optimized the reservoir response to gas flooding.…”

“…The values of gravity for various oils from the ANS oil database generally delineate the suitability of an oil pool for CO 2 -EOR. Table 2.3 lists the petrophysical properties of a few ANS oil pools, while the last column gives the rank of oil pools, according to the study by Rivas et al (1992). …”

Analysis of reservoir properties and parameters of oil fields suitable for the application of CO2-EOR method

“…The criteria used for selecting oil fields were proposed by numerous authors, e.g. [7,8,11,17,18,21,22,23,24,26,28,29].…”