The first-ever polymer flood field pilot to enhance the recovery of heavy oils on the Alaska North Slope is ongoing. This study seeks to evaluate the oil recovery and economic performance of the project via machine-assisted reservoir simulation. First, a reservoir simulation model is calibrated to the production data through the introduction and modification of transmissibility contrasts. Machine-assisted history matching techniques are crucial to the success of this procedure. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are emplaced in the reservoir model to force the viscous fingering behavior expected when water is used to displace this 330 cp heavy oil. After injection is switched to tertiary polymer flooding, the transmissibility contrasts are reduced to replicate the significant decrease in the producing water cut. This behavior indicates the dampening of viscous fingering effects, which is expected from the switch to a less mobile injected fluid. Later, transmissibility contrasts are reinstated in the simulation model to recreate a producing water cut surge. This surge indicates a decrease in the injection conformance, likely from the overextension of fractures developed at the injecting wells. Next, oil recovery forecasts are produced using calibrated simulation models from each stage of the history matching process. These production forecasts are then input into an economic model, incremental to waterflooding expectations. The decision to pursue incremental economic analysis is fit-for-purpose, allowing for a focused evaluation of the decision to switch from waterflooding to polymer flooding whilst canceling out a number of impertinent and uncertain cash flows. In all cases, the forecasts demonstrate that the polymer flood will produce a much greater heavy oil recovery than waterflooding, yielding attractive project economics even under conservative oil price and polymer cost assumptions. Thus, we conclude this polymer flood field pilot is both technically and economically successful. However, significant variations in recovery and economics between the simulation scenarios indicate that a simulation model only remains valid for prediction if the flow structure in the reservoir remains consistent with its historic behavior. Thus, a simulation model calibrated for waterflooding may not capture the full technical and economic benefit of polymer flooding or other enhanced oil recovery processes. Furthermore, the overextension of fractures from injecting wells reduces the expected performance of the polymer flood, perhaps necessitating future conformance treatments.

The first ever polymer flood field pilot to enhance the recovery of heavy oils on the Alaska North Slope is ongoing. This study constructs and calibrates a reservoir simulation model to predict the oil recovery performance of the pilot through machine-assisted reservoir simulation techniques. To replicate the early water breakthrough observed during waterflooding, transmissibility contrasts are introduced into the simulation model, forcing viscous fingering effects. In the ensuing polymer flood, these transmissibility contrasts are reduced to replicate the restoration of injection conformance during polymer flooding, as indicated by a significant decrease in water cut. Later, transmissibility contrasts are reinstated to replicate a water surge event observed in one of the producing wells during polymer flooding. This event may represent decreased injection conformance from fracture overextension; its anticipated occurrence in the other production well is included in the final forecast. The definition of polymer retention in the simulator incorporates the tailing effect reported in laboratory studies; this tailing effect is useful to the simultaneous history match of producing water cut and produced polymer concentration. The top 24 best-matched simulation models produced at each stage of the history matching process are used to forecast oil recovery. The final forecast clearly demonstrates that polymer flooding significantly increases the heavy oil production for this field pilot compared to waterflooding alone. This exercise displays that a simulation model is only valid for prediction if flow behavior in the reservoir remains consistent with that observed during the history matched period. Critically, this means that a simulation model calibrated for waterflooding may not fully capture the benefits of an enhanced oil recovery process such as polymer flooding. Therefore, caution is recommended in using basic waterflood simulation models to scope potential enhanced oil recovery projects.

The first-ever polymer flood pilot to enhance heavy oil recovery on Alaska North Slope (ANS) is ongoing. After more than 2.5 years of polymer injection, significant benefit has been observed from the decrease in water cut from 65% to less than 15% in the project producers. The primary objective of this study is to develop a robust history-matched reservoir simulation model capable of predicting future polymer flood performance. In this work, the reservoir simulation model has been developed based on the geological model and available reservoir and fluid data. In particular, four high transmissibility strips were introduced to connect the injector-producer well pairs, simulating short-circuiting flow behavior that can be explained by viscous fingering and reproducing the water cut history. The strip transmissibilities were manually tuned to improve the history matching results during the waterflooding and polymer flooding periods, respectively. It has been found that higher strip transmissibilities match the sharp water cut increase very well in the waterflooding period. Then the strip transmissibilities need to be reduced with time to match the significant water cut reduction. The viscous fingering effect in the reservoir during waterflooding and the restoration of injection conformance during polymer flooding have been effectively represented. Based on the validated simulation model, numerical simulation tests have been conducted to investigate the oil recovery performance under different development strategies, with consideration for sensitivity to polymer parameter uncertainties. The oil recovery factor with polymer flooding can reach about 39% in 30 years, twice as much as forecasted with continued waterflooding. Besides, the updated reservoir model has been successfully employed to forecast polymer utilization, a valuable parameter to evaluate the pilot test’s economic efficiency. All the investigated development strategies indicate polymer utilization lower than 3.5 lbs/bbl in 30 years, which is economically attractive.

Since August 2018, a polymer flooding field pilot has been underway in an unconsolidated heavy oil reservoir on the Alaska North Slope (ANS). Previously, a reservoir simulation model was constructed and calibrated to predict the oil recovery of the field test; it demonstrated that polymer flooding is technically feasible to significantly improve oil recovery from heavy oil reservoirs on the Alaska North Slope. However, the economic performance of the pilot, critical to determining its success, has not been investigated, which is another key metric used in assessing the overall performance of the field pilot. Therefore, this study focuses on evaluating the project's economic performance by integrating the calibrated simulation model with an economic model. The investigation results demonstrate that the project value remains profitable for all polymer flood scenarios at conservative economic parameters. Thus, the use of polymer flooding over waterflooding is attractive. However, the predicted value changes meaningfully between the scenarios, emphasizing that a simulation model should be taken as a "living forecast". Subsequently, an economic sensitivity analysis is conducted to provide recommendations for continued operation of the ongoing field pilot and future polymer flood designs. The results indicate that a higher polymer concentration can be injected due to the development of fractures in the pilot reservoir. The throughput rate should remain high without exceeding operating constraints. A calculated point-forward polymer utilization parameter indicates a decreasing efficiency of the polymer flood at later times in the pattern life. Future projects will benefit from starting polymer injection earlier in the pattern life. A pattern with tighter horizontal well spacing will observe a greater incremental benefit from polymer flooding. This case study provides important insight for the broader discussion of polymer flood design from the economic perspective. It illustrates how expectations for performance may change as additional data is collected. It also formalizes the concept of "point-forward utilization" to evaluate the incremental efficiency of additional chemical injection.

West Sak is a shallow viscous oil reservoir located partially within the Kuparuk River Unit on the North Slope of Alaska. The poorly consolidated reservoir is prone to sand production, leading to a significant risk for the development of void space conduits, locally known as matrix bypass events (MBEs). MBEs result in pattern breakage and lost production capacity, and this needs to be accounted for in production forecasting. In this study, a data-driven analysis is performed to identify factors that cause differential risk for MBE formation in each well. This analysis is then used to inform the creation of a tool that determines the expected production impacts of future MBEs and derates the forecast accordingly. The well patterns and MBE history in the West Sak reservoir are analyzed for differential risk based on sand geomechanics and producer/injector well completions. Specifically, the B sand was found to have the highest MBE risk due to its lower geomechanical strength, the D sand was found to have a significant yet lesser risk, and the A sand was found to have negligible risk. MBE risk is greater for patterns with horizontal production laterals without sand control and is negligible for horizontal producers with sand-exclusion screens or vertical producers. MBE risk is reduced when vertical injectors are used instead of horizontal injection laterals. This history is used to inform the development of MBE risk type curves based on the fatigue life distribution family of curves. These curves are used as input into an MBE deration forecasting tool, which produces a range of risk-informed MBE schedules. Based on each schedule, the tool "breaks" and "repairs" patterns accordingly, determining production losses based on allocation to each pattern. These individual production loss forecasts are then averaged to provide the expected outcome for forecast deration attributed to MBEs. The tool was successful in developing reasonable deration expectations on a well-by-well basis. The work done offers a probabilistic workflow to predict well downtime due to MBEs. Data-driven evidence is provided for factors that influence MBE risking, providing a means to capture expected production losses. This evidence proves to be consistent with physical models of this enigmatic phenomenon and informs future development opportunities to mitigate this risk. The approach pursued here can be applied to other known risks to production.