阿布扎比油藏储层结构与流体连通性

E. Tegelaar, P. Nederlof, C. Kloucha, Osemoahu A. Omobude, H. Al Harbi
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引用次数: 1

摘要

了解储层结构和流体连通性是一项具有挑战性的任务,但也是井、储层和设施管理(WRFM)的基本任务。通过对原油样品进行分子指纹分析,可以深入了解流体连通性(包括静态和动态)。油指纹技术也可以用于混合流体流的分配,在延时模式下,它甚至可以帮助了解地下的流体流动情况。指纹研究的结果直接用作静态和动态油藏模型的约束条件。大多数指纹识别应用的基本要求是了解初始的、生产前的流体分布。到目前为止,生产前流体的有限可用性一直是制约油指纹技术在行业中广泛应用的主要因素。储层岩石样本含有足够的残余碳氢化合物,可以进行流体指纹识别。储层岩心和岩屑样品广泛可用,因此为增加储层流体指纹的空间覆盖范围提供了极好的机会。然而,一个主要的挑战是现有指纹识别方法的准确性和可重复性,这些方法在储层岩石样品中残留的“较重”、非挥发性碳氢化合物的色谱范围内是不够的。本文介绍了一种新的、高分辨率的分子指纹技术的应用,该技术解决了这些限制。这种所谓的化合物类特异性指纹图谱(CCSF)技术在整个分析窗口内具有前所未有的准确性和可重复性,这使得它适用于油脂和提取物的指纹图谱。这种方法的另一个好处是,额外的化合物类别信息可能有助于解决流体差异的原因,因为并非所有差异都与储层连通性有关。作为第一次测试,新的CCSF技术已应用于阿布扎比海上油田的流体样品。重点研究了高裂缝带4个叠层储层的垂向分区性评价和断层传递性评价。即使在这个高度裂缝的区域,在顶部储层和下面三个储层之间也发现了垂直流体流动的障碍,这三个储层的含油量略有不同。提高了CCSF方法的分辨率,结合它提供的分子信息,可以证明下部储层的流体是垂直连接的,并且重力隔离产生了成分梯度。现有的指纹识别技术无法得出这些结论。识别生产监控的机会。由于复杂的电荷史和不完全的流体混合,该区部分储层表现出较强的成分梯度。对中侧翼产层的流体监测将有助于确定同时应用于该储层的注气和注水方案的效率。此外,流体监测将有助于预测水和/或气的突破。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Reservoir Architecture and Fluid Connectivity in an Abu Dhabi Oil Accumulation
Developing an understanding of reservoir architecture and fluid connectivity is a challenging, but essential task for well, reservoir and facilities management (WRFM). Insight into fluid connectivity (both static and dynamic) can be obtained from molecular fingerprinting of crude oil samples. Oil fingerprinting is also applied for allocation of commingled fluid streams, and in time-lapse mode it can even help to understand fluid flow in the subsurface. Results from fingerprinting studies are directly used as constraints for static and dynamic reservoir models. A basic requirement for most fingerprinting applications is an understanding of the initial, pre-production fluid distribution. The limited availability of pre-production fluids has until now been a major constraint for the widespread application of oil fingerprinting in the industry. Reservoir rock samples contain enough residual hydrocarbons for fluid fingerprinting. Reservoir core and cuttings samples are widely available and thus provide an excellent opportunity to increase the spatial coverage of fluid fingerprints in a reservoir. A major challenge, however, is the accuracy and reproducibility of existing fingerprinting methods, which are insufficient in the chromatographic range of the ‘heavier’, non-volatile, hydrocarbons remaining in reservoir rock samples. This paper describes the application of a new, high resolution, molecular fingerprinting technology that resolves these limitations. This so-called Compound Class Specific Fingerprinting (CCSF) technique has unprecedented accuracy and reproducibility over the full analytical window, which makes it suitable for fingerprinting of both oils and extracts. An added benefit of this approach is that the additional compound class information may help to resolve why fluids are different, as not all differences are related to reservoir connectivity. As a first test, the new CCSF technology has been applied to fluid samples from an offshore field in Abu Dhabi. Two specific aspects are highlighted in this paper: Assessment of vertical compartmentalization and fault transmissibility of four stacked reservoirs in a highly fractured zone. Even in this highly fractured zone, a barrier to vertical fluid flow was identified between the top reservoir and the three underlying reservoirs, which contain slightly different oil. The improved resolution of the CCSF method, combined with the molecular information it provides, made it possible to demonstrate that the fluids in the lower reservoirs are vertically connected and that gravity segregation has created a compositional gradient. These conclusions could not have been reached with existing fingerprinting technologies. Identify opportunities for production monitoring. Some of the reservoirs in this field show strong compositional gradients related to the complex charge history and incomplete fluid mixing. Fluid surveillance of the mid-flank producers will help identify the efficiency of the gas and water injection schemes that are simultaneously applied to this reservoir. In addition, fluid surveillance will help to predict water and/or gas breakthrough.
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