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Validation of Permeability and Relative Permeability Data Using Mercury Injection Capillary Pressure Data

机译:使用注汞毛细管压力数据验证渗透率和相对渗透率数据

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This paper reports on a study with the objective to validate a set of core analysis data using a combination of mercury injection capillary pressure (MICP) data and statistical correlation techniques. The data set is from an off-shore reservoir in Atlantic Canada. Analysis of this reservoir was complicated by the fact that the permeabilities of the samples were high, greater than 2400 mD. The analysis was done using an existing data set, not a data set specifically tailored for the techniques used in the analysis. The data analyzed included samples that represented seven zones in a single well. Porosities and permeabilities were available for the MICP samples. Electrical properties, along with porosities and permeabilities, were available on samples from each zone, but not from the same depths as the MICP samples. Steady-state relative permeabilities (SSRP) were available for stacked samples in each zone; one of the samples in the stack was a companion sample for one of the MICP samples from that zone. The MICP results were used to validate the permeability measurements using both the Swanson method (SM) and the Ruth-Lindsay-Allen (RLAM) method. The SM, using published correlation parameters, significantly under-predicted the permeabilities; the RLAM, which uses no correlation parameters, gave predictions within a maximum error of just over 33% and a mean error of -12%. The MICP data was used to validate the shapes of the SSRP curves using the Gates and Tempelaar-Lietz method (GT-LM), the Burdine method (BM), and a modified Burdine method (MBM). The GT-LM, which uses no correlation parameters, provided good predictions of the wetting phase SSRP curves but very poor predictions of the non-wetting phase SSRP curves. The BM, using published correlation parameters, provided poor predictions of the wetting phase SSRP curves but improved predictions of the non-wetting phase SSRP curves. The MBM provided good predictions of the wetting phase SSRP curves and acceptable predictions of the non-wetting phase SSRP curves. The MBM method does use a correlation parameter but a single value was used for all seven zones. This work provides a protocol for validating core analysis data that can be implemented in a straightforward manner to determine the “quality” of the data. The results emphasize the importance of MICP as an experimental technique. A proposed modified workflow is presented that would optimize the validation protocol.
机译:本文报告了一项研究,目的是结合使用汞注入毛细管压力(MICP)数据和统计相关技术来验证一组岩心分析数据。数据集来自加拿大大西洋的一个近海水库。由于样品的渗透率很高,大于2400 mD,因此对该储层的分析变得复杂。分析是使用现有数据集完成的,而不是专门为分析中使用的技术量身定制的数据集。分析的数据包括代表单个井中七个区域的样本。 MICP样品具有孔隙率和渗透率。每个区域的样品都具有电学性质以及孔隙率和磁导率,但深度与MICP样品不同。每个区域中的堆叠样品都可以使用稳态相对磁导率(SSRP)。堆栈中的一个样本是来自该区域的MICP样本之一的伴随样本。 MICP结果用于通过Swanson方法(SM)和Ruth-Lindsay-Allen(RLAM)方法验证渗透率测量结果。使用已发布的相关参数,SM大大低估了渗透率;不使用任何相关参数的RLAM给出的预测最大误差在33%以上,平均误差为-12%。使用盖茨和滕普拉-里兹方法(GT-LM),布尔丁方法(BM)和改进的布尔丁方法(MBM),使用MICP数据来验证SSRP曲线的形状。不使用相关参数的GT-LM提供了对润湿阶段SSRP曲线的良好预测,但对非润湿阶段SSRP曲线的预测非常差。 BM使用已发布的相关参数,对润湿阶段SSRP曲线的预测较差,但对非润湿阶段SSRP曲线的预测却有所改进。 MBM为润湿阶段SSRP曲线提供了良好的预测,并且为非润湿阶段SSRP曲线提供了可接受的预测。 MBM方法确实使用了相关参数,但是所有七个区域都使用了一个值。这项工作提供了一种用于验证核心分析数据的协议,可以以一种简单的方式来实施该协议以确定数据的“质量”。结果强调了MICP作为实验技术的重要性。提出了将优化验证协议的建议工作流程。

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