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Design of an ASP Pilot for the Mangala Field: Laboratory Evaluations and Simulation Studies

机译:曼加拉田的ASP飞行员设计:实验室评估和模拟研究

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Mangala is the largest discovered oil field in the Barmer Basin of Rajasthan, India having a STOIIP of over 1 billion barrels in multiple stacked fluvial clastic reservoirs. It contains medium gravity (20-28oAPI), waxy, viscous crude (9-17 cp) in high permeability (1-25 Darcy) clean sandstone reservoirs. Initial development plans for the field are based on waterflooding, with at least the initial volumes of water heated to minimize any issues with wax dropout in the reservoir. Owing to the relatively high oil viscosity and adverse mobility displacement for waterflooding, the desirability of implementing an appropriate EOR process was identified shortly after the field discovery. Screening studies identified aqueous-based chemical flooding processes as the most favorable for Mangala. Detailed laboratory studies have now identified the potential of alkaline-surfactant-polymer (ASP) processes in significantly improving the sweep and displacement efficiency. The laboratory studies involved screening and optimization of the ASP slug formulation based on IFT measurements, adsorption measurements, polymer rheological and thermal stability studies;followed by a series of linear and radial corefloods. Experiments indicate the ASP process is the most effective chemical EOR process for Mangala, with improvement in recovery efficiency above the waterflood recovery of over 30% STOIIP. Chemical EOR simulations with STARSTM have been used extensively to understand the process mechanisms via matching of the coreflood experiments. Simulation parameters tuned to the laboratory data were used to evaluate the process performance under field conditions. A closely spaced five-spot pilot with 100m well spacing has been designed to evaluate the process. The pilot consists of four injectors, the central producer, three saturation monitoring wells and two post-pilot core holes. An ASP pilot will be implemented in the field shortly after startup of the waterflood.
机译:Mangala是Rajasthan的Barmer盆地的最大发现的油田,在印度的STOIIP,在多堆叠的河流泥浆储层中有超过10亿桶。它含有高渗透性(1-25达西)清洁砂岩储层的中等重力(20-28Oapi),蜡质,粘性原油(9-17cp)。该领域的初始开发计划是基于水上的,至少加热初始水量,以最大限度地减少水库中蜡辍学的任何问题。由于具有相对高的油粘度和用于水上的迁移率位移,在现场发现之后不久识别实施适当的EOR过程的可取性。筛选研究将基于水性的化学洪水过程确定为mangala最有利。详细的实验室研究现在已经确定了碱性表面活性剂 - 聚合物(ASP)过程的潜力,可显着提高扫描和位移效率。实验室研究涉及基于IFT测量,吸附测量,高分子流变和热稳定性研究的ASP SLUG制剂的筛选和优化;随后是一系列线性和径向核心。实验表明,ASP过程是Mangala最有效的化学EOR方法,随着30%以上的恢复超过30%STOIIP的恢复效率提高。具有Starstm的化学EOR模拟已广泛用于通过CoreFlood实验的匹配来了解过程机制。调整到实验室数据的仿真参数用于评估现场条件下的过程性能。具有100米井间距的紧密间隔的五点飞行员旨在评估该过程。飞行员由四个喷射器,中央生产商,三个饱和监测井和两个后飞行员芯孔组成。在喷水机构启动后不久将在该领域实施ASP飞行员。

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