Acquisition and analysis of transient data through unsteady-state core flooding experiments

Abstract

Dynamic displacement experiments and numerical two-phase flow estimation program are presented in this study. Unsteady-state core-flooding system was designed and utilized for oil-water dynamic displacement experiment. Two in situ sandstone core plug samples were used to investigate relative permeability via diesel and 3 wt % brine as non-wetting and wetting phase fluids. The transient data (pressure drop and produced fluid volume) were collected automatically for oil-water relative permeability computation. For relative permeability analysis, an inverse method program was constructed with four components: (a) an IMPE finite-difference numerical simulator of the flow through the core; (b) functional Corytype power law model of relative permeability in terms of a set of adjustable parameters found by minimizing an objective function; (c) the objective function formed by the sum of the square of the differences between the observations and calculated data; (4) the Gauss-Newton with Levenberg-Marquardt modification procedure for the leastsquares problem to minimize the objective function definition. All the above processes are embodied in relativepermeability calculation program, RCP, which is constructed in this study using FORTRAN language.

The effect of CO2 phase on drainage process by analysis of transient differential pressure

“…(9) indicates that the water relative permeability is mainly related to water fractional flow, water viscosity and differential pressure. As pressure difference across a high permeability core in the drainage process changes slightly, its influence on the relative permeability is insignificant (Liang et al, 2016). The differences between the relative permeability of water in different CO 2 phase core flooding is mainly caused by the water fraction flow.…”

“…For example, an early gas breakthrough at CO 2 enhanced oil recovery (EOR) could lead to poor sweep efficiency and the reduction of oil production (Gozalpour et al, 2005). In traditional measurements, breakthrough time is usually determined by the turning point on the differential pressure profiles as the production of the first-oil or the first-water in displacement experiment is invisible (Liang et al, 2016). However, it is sometimes hard to find the turning point under a low injection rate or in a high permeability core with little differential pressure change (Liang et al, 2016), and it is hard to determine the breakthrough time in a heterogeneous core with a complex differential pressure (Perrin and Benson, 2010).…”

“…In traditional measurements, breakthrough time is usually determined by the turning point on the differential pressure profiles as the production of the first-oil or the first-water in displacement experiment is invisible (Liang et al, 2016). However, it is sometimes hard to find the turning point under a low injection rate or in a high permeability core with little differential pressure change (Liang et al, 2016), and it is hard to determine the breakthrough time in a heterogeneous core with a complex differential pressure (Perrin and Benson, 2010). The method frequently used to determine the breakthrough time is CT scan through visualising changes in situ saturation distribution during core flooding experiments (Perrin et al, 2009).…”

“…Shi et al observed a CO 2 breakthrough by CT images after 0.42 pore volume (PV) of supercritical CO 2 was injected into a heterogeneous water-saturated Tako sandstone (Shi et al, 2011). Liang et al designed a two phase detector probe connected to outflow endcap of core holder to identify the CO 2 breakthrough time for oil-water unsteady-state displacement experiments (Liang et al, 2016). Once the CO 2 breakthrough time is determined, the relative permeability of CO 2 and water/oil in the unsteady state displacement can be estimated through JBN method based on Buckley-Leverett theory (Buckley and Leverett, 1942;Johnson et al, 1959).…”