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Scaling for Wettability Alteration Induced by the Addition of Surfactants in Completion Fluids: Surfactant Selection for Optimum Performance

机译:通过在完井中添加表面活性剂诱导的润湿性改变的缩放:表面活性剂选择以获得最佳性能

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Experimental laboratory evidence of enhanced production by spontaneous imbibition via the addition of surfactants into completion fluids, as well as field observations, indicate a significant improvement in EUR with the use of surfactants to improve oil recovery from unconventional liquid reservoirs (ULR). During a hydraulic fracture treatment, the surfactant molecules interact with the rock surface, altering its wettability and interfacial tension. The wettability alteration of the rock surface from oil-wet to water-wet enables the spontaneous imbibition of water into the matrix, which expels the oil out of the pore space towards the fractures. Several laboratory and numerical studies have investigated the effectiveness of surfactant-assisted spontaneous imbibition (SASI) on various ULR. However, the understanding of surfactant selection for the optimization of enhancing recovery in ULR is not well studied. Capillary pressure is the dominant force for spontaneous imbibition process. Contact angle (CA) and interfacial tension (IFT) are essential terms in the Young-Laplace capillary pressure equation as well as in published scaling analysis of the spontaneous imbibition process. With the large amount of data released on SASI, it is natural to develop a correlation between the two properties to the recovery factor. However, no work has been conducted to investigate the relationship of contact angle and IFT on ultimate recovery by spontaneous imbibition in ULR. In this manuscript, a compilation of CA, IFT, and spontaneous imbibition experiments from two of the most prolific shale reservoirs is presented to give an insight into the relationship between the three variables. Then, based on the observed trends and correlations, a new scaling model for SASI in ULR is proposed. The ultimate goal is to develop a surfactant selection method based on scaling analysis results and laboratory data for optimal performance in ULR. A total of 35 independent SASI correlated experiments data were compiled, which includes CA, IFT, recovery factor, porosity, core plug dimensions, and capillary pressure calculated from the Young-Laplace equation. Experimental procedure on each data point followed the robust data gathering methodology that was already developed for the past four years. The reliable procedure ensures the representability of the reservoir condition in the laboratory measurements to provide an accurate description of the effectivity of different surfactants on a corresponding oil/water/rock system. Two systems were analyzed and assembled into three groups, Wolfcamp, Eagle Ford A, and Eagle Ford B. An inversely proportional correlation between CA and recovery factor was observed, while on the IFT and recovery factor analysis, a less apparent correlation was found. Theoretically, a directly proportional correlation between capillary pressure and recovery factor can be expected due to spontaneous imbibition that is primarily dominated by capillary forces, which is consistent with experimental data analysis. The high dependence of recovery factor on contact angle and the less significant effects from IFT lead us to conclude that a substantial wettability altering surfactant is highly preferred to enhance through SASI. In addition, based on the observed correlation, a new dimensionless scaling equation fully accounting for the effect of surfactant addition was developed to generalize the flow behavior of SASI.
机译:实验实验室证据通过将表面活性剂添加到完井流体中,以及现场观察,以及使用表面活性剂来提高欧元的显着改善,以改善来自非常规液体储层(ULR)的油回收。在液压断裂处理期间,表面活性剂分子与岩石表面相互作用,改变其润湿性和界面张力。从油湿到水湿的岩石表面的润湿性改变使得水中水中的水中进入基质,这将油从孔隙空间排出到骨折中。若干实验室和数值研究已经研究了表面活性剂辅助自发性吸收(SASI)对各种ULR的有效性。然而,对优化ulr复苏的优化的表面活性剂选择的理解并未得很好。毛细管压力是自发性吸收过程的主导力。接触角(CA)和界面张力(IFT)是幼拉毛细管压力方程中的基本术语,以及发表的自发性吸收过程的缩放分析。随着SASI释放的大量数据,它是自然的,在两个属性之间发展到恢复因子之间的相关性。然而,没有进行任何工作来研究接触角和IFT在ULR中自发性吸收的最终恢复的关系。在此稿件中,提出了来自最多产物水库中的两个的CA,IFT和自发性吸收实验的编辑,以了解三个变量之间的关系。然后,基于观察到的趋势和相关性,提出了ULR中SASI的新缩放模型。最终目标是基于缩放分析结果和实验室数据进行表面活性剂选择方法,以便在ULR中最佳性能。编译了总共35个独立的SASI相关实验数据,包括CA,IFT,恢复因子,孔隙率,核心塞尺寸,以及从幼术方程计算的毛细管压力。每个数据点的实验程序遵循过去四年已经开发的强大数据收集方法。可靠的过程确保了实验室测量中的储层条件的可见性,以便在相应的油/水/岩系统上提供不同表面活性剂的有效性的准确描述。分析并组装成三组,Wolfcamp,Eagle Ford A和Eagle Ford B的两个系统。观察到CA和恢复因子之间的成反比度,而在IFT和恢复因子分析上,发现了不太明显的相关性。从理论上讲,由于自发性吸收,可以预期毛细管压力和恢复因子之间的直接比例相关性,其主要由毛细力占据毛细力,这与实验数据分析一致。回收因子对接触角的高依赖性和IFT的显着效果导致我们得出结论,改变改变表面活性剂的显着润湿性是通过SASI增强的。另外,基于观察到的相关性,开发了一种新的无量纲缩放方程,完全占表面活性剂添加的影响,以概括SASI的流动行为。

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