EOR

Modeling foam for enhanced oil recovery in 6X

Using 6X to model foam creation and its effect on gas mobility

In EOR foam can be particularly useful in highly fractured reservoirs such as in unconventional and tight oil fields. Here the primary challenge is to maintain gas within the target formation and prevent it from escaping into adjacent wells.

Without conformance improvement techniques, the gas might simply rush through the high conductivity fractures, channels, or weakness planes in the reservoir.

Foam generation

Foam is created by injecting a mix of water and surfactant into the reservoir. Surfactants decrease surface tension, enabling gas to be encapsulated in water-based films, thus generating foam. The foam then decreases the mobility of the gas by increasing its viscosity.

Foam modelling within 6X

Traditional simulator foam models use empirical methods to represent surfactant-induced foam generation, selecting certain variables while leaving others out.

6X enables dynamic scripting, which allows for the creation of custom foam models that incorporate userderived data and insights.

6X employs tracers to simulate the transport of surfactants, carried by the aqueous or liquid phases.

Custom foam models in 6X can be used in simulating the entire life-span of foam in a reservoir, including its
generation, stability, and collapse.

Variables such as surfactant concentration, foam quality, velocities, pressure, saturation of phases, and temperature effects are all taken into account.

The models also simulate the time decay of foam effectiveness and collapse, and the adsorption of surfactant into the rock as a function of surface area.

For this type of foam modeling it is essential to utilize multi-well models to account for connectivity among the wells. 6X is fully equipped to integrate these models into its simulations.

The following figures display gas saturation within the fractures, filtered to highlight only the middle part of the reservoir. Gas is injected from the right side of the wells and subsequently migrates to the left side. In the second figure, the introduction of a surfactant has effectively limited the spread of gas.

Enhanced Oil Recovery – Extract extra oil from unconventional reservoirs

Using 6X to predict recovery from an EOR cyclic gas injection campaign

The hydraulic fracturing of wells in unconventional reservoirs has resulted in high initial oil production. However the decline rates are very high with low recovery factors. Recently, Enhanced Oil Recovery (EOR) through cyclic gas injection (huff & puff) has increased recovery factors in the Eagle Ford and is being investigated for use in other shale basins.

When planning an EOR campaign, or when analysing the early results from a well/pilot, a reservoir simulator (together with a model of the subsurface) is the only tool available to predict the production and the economics of the project.

6X has been successfully used in many EOR projects, for example see the 2021 URTeC paper: 5649 A Simulation Study to Evaluate Operational Parameter Ranges for a Successful Cyclic Gas Injection in Different Areas of Eagle Ford by M. Gaddipati, B. Basbug, T. Firincioglu of NITEC LLC.

Requirement for a tuned hydraulic fracture description

Most EOR projects follow on from a period of natural depletion. A 6X model can be tuned to both the hydraulic fracturing data (pressures and flow back) and the subsequent production. This provides a solid basis to predict the behavior of the gas injection period.

Quick look prediction using a black-oil fluid description

Gas injection at high pressures will typically form a supercritical fluid with the reservoir oil. Hence the simulator fluid description needs to take care of the full phase behavior. The most efficient solution is achieved by starting with an equation of state (EOS) fluid model and converting this to black-oil tables using 6X’s internal converter. 6X’s EOS to black-oil convertor ensures consistency and robustness.

More detailed prediction – composition fluid

Given that the huff & puff process relies on a complex set of fluid behaviors, an EOS based compositional model is more accurate and provides extra information – typically the composition of the produced fluids.

The compositional model describes the fluid using pseudocomponents, typically 7-12 of them, where the black-oil model uses just 2 components. As the number of
components increase so does the simulation run time. As the compositional model is only required when gas injection starts, an efficient workflow is to use the black oil model for the frac and initial production period, then to restart in
compositional mode for the huff & puff phase.

In US light oils, the compositional and black-oil approaches have given broadly similar results.