利用机器辅助油藏模拟技术评估阿拉斯加北坡首次聚合物驱油田试验的采收率和经济效益,以提高稠油的采收率

C. Keith
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引用次数: 0

摘要

为了提高阿拉斯加北坡稠油的采收率,首个聚合物驱油田试验正在进行中。本研究旨在通过机器辅助油藏模拟来评估该项目的采收率和经济效益。首先,通过引入和修正透射率对比,将油藏模拟模型与生产数据进行校准。机器辅助的历史匹配技术对手术的成功至关重要。为了重现水驱过程中观察到的早期水侵现象,在油藏模型中进行了渗透率对比,以模拟用水驱替330立方厘米稠油时预期的粘性指动行为。在注入转换为三级聚合物驱后,渗透率对比降低,以复制生产含水率的显着下降。这种行为表明,切换到流动性较低的注入流体时,粘性指入效应得到了抑制。随后,在模拟模型中恢复透射率对比,以重现生产含水浪涌。这种波动表明注入一致性下降,可能是由于注入井的裂缝过度延伸。接下来,利用历史匹配过程中每个阶段的校准模拟模型进行原油采收率预测。然后将这些产量预测输入到经济模型中,增量到注水预期。进行增量经济分析的决定是符合目的的,可以对从水驱转向聚合物驱的决定进行集中评估,同时消除一些不相关和不确定的现金流。在所有情况下,预测表明聚合物驱的稠油采收率比水驱高得多,即使在保守的油价和聚合物成本假设下,也能产生具有吸引力的项目经济效益。因此,我们得出结论,该聚合物驱油田试验在技术和经济上都是成功的。然而,不同模拟情景之间采收率和经济性的显著差异表明,只有当油藏的流动结构与历史行为保持一致时,模拟模型才能有效预测。因此,为水驱校正的模拟模型可能无法捕捉聚合物驱或其他提高采收率工艺的全部技术和经济效益。此外,注入井裂缝的过度延伸降低了聚合物驱的预期性能,这可能需要未来的一致性处理。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Evaluation of the Oil Recovery and Economic Benefit of the First-Ever Polymer Flood Field Pilot to Enhance the Recovery of Heavy Oils on Alaska's North Slope using Machine-Assisted Reservoir Simulation
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.
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