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Reservoir Connectivity, Water Washing and Oil to Oil Correlation: An Integrated Geochemical Petroleum Engineering Approach

机译:水库连接,水洗和油与油相关:综合地球化学和石油工程方法

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Oil Fingerprinting by gas chromatography techniques are among the most sensitive and accurate tools utilized to study reservoir compartmentalization and oil to oil correlations. The greatest challenge of the technique, however, lies in recognizing and identifying if any oils have undergone post-generative alteration processes such as water washing or biodegradation that may prohibit accurate correlation. These effects, even when subtle, may alter or transform oils resulting in misleading interpretations and invalid outcomes. Understanding the controls on the oil composition is critical for all fingerprinting studies and can promote new characterization methods to ensure any negative post-generative alteration effects are mitigated. The study aims to illustrate the use of various geochemical fingerprinting methods to assess the reservoir connectivity between two oil accumulations. Furthermore, the effect of water washing on the oil compositions, and its relationship with gas to oil ratio (GOR) and salinity were investigated. A total of 11 oil samples from an Ordovician siliciclastic formation across 10 locations in a field were analyzed for API gravity light hydrocarbons (C5-C7) and whole-oil fingerprinting (C8 to C20) gas chromatography (GC) characterization methods. Light hydrocarbons (LHC) analysis used to correlate different oils to their sources was interpreted using five specially selected source dependent ratios plotted in a C7 star diagram. If the oils have a similar pattern, this indicates a similar source and vice versa. The results suggest that the oils can be correlated to two different source rocks that charged the study area from independent northeast and southwest directions. A second set of light hydrocarbon ratios sensitive to water washing and biodegradation effects suggested a noticeable water washing trend increasing to the north. The whole-oil fingerprinting analysis employs a multivariate statistical model across all the samples to determine the most variant 12 ratios from the chromatograms to construct a specialized star diagram. From this analysis, five separate reservoir compartments were identified. It was further observed that a set of samples from a specific compartment differed in one of the 12 ratios. This ratio was plotted against the water washing transformation ratio from LHC and revealed a strong positive correlation. The difference in this ratio is attributed to water washing. Both parameters suggest that water washing possesses strong negative correlations with total dissolved salts (TDS) of the formation water and gas to oil ratio (GOR). These relationships accentuate the potential of utilizing the geochemical ratios to predict the GOR and consequently improve the production planning. The study shed the lights on the potential utilization of new rapid and cost-effective geochemical methods to predict some production engineering parameters.
机译:通过气相色谱技术的油指纹印刷是最敏感和准确的工具,用于研究水库舱门化和油与油相关的工具。然而,该技术的最大挑战在于识别和识别任何油在发生后发生的后期改变过程,如水洗或可禁止准确相关的生物降解。这些效果,即使是微妙的,也可能改变或改变油,导致误导性解释和无效结果。了解油组合对照对所有指纹识别研究至关重要,可以促进新的表征方法,以确保减轻了任何负面发生的改变效应。该研究旨在说明各种地球化学指纹方法的使用来评估两个油累积之间的储层连通性。此外,研究了水洗对油组合物的影响及其与气体与油比(GOR)和盐度的关系。针对API重力光烃(C5-C7)和全油指纹(C8至C20)气相色谱(GC)表征方法,分析了总共11个来自田间硅基硅形成的油型硅基样品。用于将不同油状物与它们来源相关的光碳氢化合物(LHC)分析使用C7星图中绘制的五个特殊选择的源依赖性比来解释。如果油具有类似的模式,则表示类似的源,反之亦然。结果表明,石油可以与两个不同的源岩相关,从独立的东北和西南方向收取研究区域。对水洗和生物降解效应敏感的第二组轻烃比例提出了对北方的显着水洗趋势。全油指纹识别分析在所有样品中采用多元统计模型,以确定来自色谱图的最大5个比率,以构建专用的星形图。从该分析来看,确定了五个单独的水库隔室。进一步观察到,来自特定隔室的一组样品在12个比例之一中不同。该比率符合来自LHC的水洗涤转化率,并显示出强烈的正相关性。该比率的差异归因于水洗。这两个参数表明水洗具有与地层水和气体的总溶解盐(TDS)具有强烈的负相关性,与油比(GOR)。这些关系突出了利用地球化学比率来预测GOR并因此改善生产计划的潜力。该研究揭示了新的快速和经济高效地球化学方法的潜在利用来预测一些生产工程参数。

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