A Method to Predict MEOR Benefits on a Field Basis

Nigel Brealey (n.brealey@senergyltd.com) Principal Reservoir Engineer with Senergy Ltd (RML) (http://www.senergyltd.com) reports on a recent assessment undertaken as part of the DTI's SHARP programme investigating the use of commercially available software to predict field scale benefits from microbial enhanced oil recovery (MEOR).

Statoil is currently pursuing an aerobic microbe programme in their Norne Field which they project will add significantly to reserves (Reference 1). This involves encouraging indigenous microbes to use residual oil as their source of carbon for growth. This gets around the problem of using large quantities of nutrients which would otherwise be required, although modest levels of minerals are still required to encourage the microbial growth.

Norne is a new development with coated injection wells designed to allow for oxygen content in the injected water. The incremental cost of the MEOR programme is understood to be very low.

MEOR is less obviously attractive elsewhere in the North Sea because the application cost would probably be somewhat greater, and remaining field life in many mature fields may be too short to capture the full benefits. Nonetheless, there does appear to be potential.

One problem in progressing this potential recognised by the DTI, has been the lack of prediction methodology for the production impacts of a pilot or field application.

David Hughes of RML reported results of MEOR field pilot predictions in the last edition of this Newsletter (Reference 2). In the absence of the source code of any other simulator being available to him, David incorporated additional features into the version MTS (Microbial Transport Simulator) of the public domain black oil simulator (BOAST) developed by the US Department of Energy (DOE).

However, this prediction methodology was seen as somewhat fragile and David has since advocated trying to incorporate the processes into a commercially supported simulator. He proposed using CMG’s STARS chemical simulation program for this application.

Under the auspices of its SHARP programme, the DTI agreed to support testing whether STARS could indeed be used.

Essentially, the processes which RML set out to model in STARS were:

• Placing indigenous microbes in the reservoir
• Injecting nutrients
• Growing microbes exponentially for some time whilst adding nutrients
• Allowing the microbes to snap off and be carried downstream after a volume of growth is achieved
• Enabling microbes to adsorb onto the rock
• Reducing effective water permeability where microbes have grown sufficiently
• Lowering the residual oil saturation dependent on the local microbe population
• Allowing oil to be used as carbon source with other nutrients being added from an external source
• Stopping microbes multiplying at some point by elimination of a critical nutrient component

The basic exponential growth was essentially represented as a chemical reaction with "stoichiometric" coefficients; with one unit of microbe reacting with one unit of nutrient to produce two units of microbe – i.e. doubling itself. This is an equation with positive feedback which is innately unstable. However, it worked in test cases when microbe growth was limited by nutrient supply, which in this case included the proportion of residual oil allowed as the carbon source.

STARS allows components to be associated with water, oil or solid phases.

Microbes associated with the water phase are displaced miscibly with displacement water.

Indigenous microbes are generally considered as existing at the oil/water interface. Although not cosmetically correct, they have been associated in STARS with the residual oil. These microbes may be “snapped off” and displaced downstream with drive-water after they reach a certain volume. This could for instance occur if there were a continuous external carbon source. This is achieved in STARS by a keyword to describe liquid/liquid partition. This would also allow microbes injected with injection water to partition to the oil-water interface.

As the desired, favourable microbes grow, they can produce surfactants and other chemicals, change wettability, create a “bio-film” and other effects that can reduce the trapped residual oil saturations. The detailed effects are neither well understood nor quantified, but their impacts have been observed in core flood experiments.  We believe the immediate need for simulation is to relate the gross impacts of the microbes on the reduction of residual oil in core. We have done this in the STARS simulator by relating the relative permeability and residual oil saturation to the growing microbe population.

Microbes may also adsorb onto rock surface and stop growing. STARS has a suitable keyword for this action. Adsorbed microbes could also interfere with water flow, which could be beneficial in blocking a high permeability thief interval. Initial attempts to represent this directly with STARS failed. However, it appeared quite possible to represent this indirectly since the adsorbed microbes are related directly to the microbes associated with the interface. Impact on water flow was then represented by relative permeability curves.

STARS was therefore able to represent the intended processes. Figure 1 illustrates some simulation output:

Figure 1: Modelled microbial effects (Click image for larger view)

We have used this to look at potential applications. Figure 2 shows predictions for a Brent type sequence:

Figure 2: Prediction results for Brent type sequence - Base Case with STOIIP of 5.8 MMstb (half pattern) (Click image for larger view)

Results are comparable to those reported by David Hughes in Reference 2 using his adapted model. However, it should be noted the pattern volume is quite small compared to normal well spacing on the UKCS.

If the pattern volume were larger, there is a significant delay in realising any benefit. Furthermore, there is a risk of delaying some production if injection were reduced by additional back-pressure. This is illustrated in Figure 3, for one particular case.

Figure 3: Prediction results for Brent Type-sequence with four-fold increase in pattern area (Click image for larger view)

MEOR may provide very attractive benefits in some cases such as infill wells. But this will not always be the case. Simulation capability is thus very important to evaluate the field opportunities.

The following are some aspects about field application indicated by modelling:

• The response time to microbial treatment in the STARS simulator was similar to that in the Microbial Transport Simulator (MTS) test case in Reference 2. However, it should be noted that the well spacing used is substantially lower than most of the current well spacing on the UKCS.
• Incremental oil in the model arises either from the development of an oil bank, or by diverting water from high permeability intervals where applicable.
• The arrival time of the oil bank depends on the rate of displacement in the reservoir.
• Current well spacing in some North Sea applications may be too wide to give a target for MEOR on a timescale suitable for a test. However, MEOR could provide a significant additional benefit to help the economic attraction of infill wells.
• Restricting water flow will not always be beneficial if it reduces injection rates.

It should, however, be noted that these conclusions are based on reasonable assumptions about what microbes may do. There is a need to obtain specific core flood data that can be used as the basis for field projections.

References

1. "Statoil Introduces Bacteria Method for Boosting Norne Recovery" Offshore, April 2001
2. MEOR – Reservoir Engineering Design Principles. David Hughes. SHARP IOR Newsletter Issue 3 September 2002

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