Abstract
Minimum miscibility pressure (MMP) is an important parameter when designing a miscible gas flood. Traditionally, the MMP is evaluated using slimtube tests, which are time-consuming and expensive. Since it is typically not feasible to test more than a few injection gases on a subset of relevant reservoir fluids, reliable methods are required to estimate the MMP. The most popular correlations are often based on data from low-temperature reservoirs and are not always very reliable.
In this work, we make use of the new, comprehensive ADNOC PVT database, which contains more than 100 slimtube MMP measurements for a variety of injection gases, including sour gases. We then complement this data source by performing equation of state (EOS) based miscibility calculations covering a large temperature range with appropriately tuned EOS models. The combination of measured and simulated data is then used as input for development of a general correlation.
The new correlation is a modification of the Eakin-Mitch formulation. It has been tuned to a large variety of injection gases and reservoir fluid compositions, and covers a wider temperature range. The average deviation is 5% and the maximum error is less than 20%. Results show that the MMP exhibits a maximum versus temperature, a feature also noticed previously during development of CO2 miscibility (Yuan et al., 2005; Alshuaibi et al., 2019).
One of the novelties of this work is the identification of a more complicated temperature-dependency of the MMP. Furthermore, the new correlation considers not just lean gases but also rich gases and sour gases, which develop miscibility based on the combined condensing-vaporizing mechanism. We believe that this model is more robust because it covers a much larger parameter range compared to existing correlations.
