Interval pressure transient tests (IPTT) are commonly used in the industry to obtain permeability distribution along the wellbore. Despite the remarkable progress achieved in IPTT analysis in last two decades, interpretation of IPTT is still unclear if test interval consists of oil zone with vertically connected transition zone and water aquifer. One easy and common approach for interpreting such data is to assume that oil zone, transition zone, and water aquifer as a distinct zone and then perform non-linear regression to measured IPTT pressure data set using single phase layer cake model. In this approach, due to the single-phase nature of the model, capillary pressure and relative permeability effects are totally ignored, however, it is assumed that water saturation data is available from log analysis and saturation weighted viscosity value represents the transition zone. As expected, it is determined only effective horizontal and vertical permeability values from this analysis rather than absolute permeability. It is also important to highlight that reliable effective permeability data is estimated solely in the zone where a test is performed. In fact, accurate prediction well and reservoir performance require values of absolute permeability information. As a second approach to analyze IPTT data, it is assumed that water saturation, relative permeability, and capillary pressure data are known parameters and optimization technique is used based on numerical reservoir simulation to estimate absolute permeability values. Like the previous case, horizontal and vertical permeability values are reliably obtained only in the zone where a test is performed. The only difference with the previous approach is that estimated permeability values are absolute permeability values rather than effective permeability. In practice in IPTT jobs, water cut is generally measured with pressure data in various depths in the transition zone to fine tune free water level. It is also important to note that relative permeability and capillary pressure data are not always available before IPTT interpretation. As a last approach in this study, both pressure and water cut data are simultaneously used in the optimization to find each zone’s horizontal and vertical permeability values, relative permeability and capillary pressure curves. Fairly satisfactory estimations are obtained from simultaneous regression of water cut and pressure data obtained from IPTT.

This content is only available via PDF.
You can access this article if you purchase or spend a download.