Probabilistic approach for shale volume estimation in Bornu Basin of Nigeria

Stephen Adjei, Aggrey N. Wilberforce, D. Opoku, I. Mohammed
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引用次数: 2

Abstract

The gamma ray log has over the years provided the conventional means for shale volume (Vsh) estimation. Knowledge of Vsh is used in the prediction of petrophysical parameters like effective porosity and water saturation, which are the input parameters for the calculation of oil in place. Currently, many studies have been conducted on the Bornu Basin of Nigeria, to access its hydrocarbon potential. Unfortunately, the practice of using best gamma ray log value for the computation of gamma ray index, IGR, and subsequently Vsh estimation incorporates huge uncertainty in the estimated volumes. Uncertainty is best captured when estimates are represented in a possible range rather than single value measurements. To the best of our knowledge, this is the first time shale volume has been estimated from the gamma ray log using sampling techniques. The gamma ray log data of the two upper shaly intervals of the NGAMMAEAST_1 well, which penetrates the Gombe formation of the basin, were utilized for this study. The gamma ray log response of the zone of interest is the uncertain parameter in Vsh estimation. A histogram plot of the uncertain log data was used to assume the probability distribution of the data. In the MATLAB platform, Standard Monte Carlo (MC) and Latin Hypercube sampling techniques were used to model the uncertain log response using random numbers. Possible input log data generated from the distribution of the uncertain log data were used in the linear and non-linear models for shale volume estimation to run a series of simulations to determine the possible range of estimates with their probabilities. The Latin hypercube method has shown to be a quick and accurate alternative method to the standard MC method. The approach presented here sets a guideline for the implementation of a probabilistic approach for the volume of shale estimation. Key words: Shale volume, Monte Carlo, Latin hypercube, sampling techniques, gamma ray log.
尼日利亚Bornu盆地页岩体积估计的概率方法
多年来,伽马射线测井一直是估算页岩体积(Vsh)的常规手段。Vsh的知识用于预测岩石物理参数,如有效孔隙度和含水饱和度,这些参数是计算石油储量的输入参数。目前,人们已经对尼日利亚Bornu盆地进行了许多研究,以挖掘其碳氢化合物潜力。不幸的是,使用最佳伽马射线测井值计算伽马射线指数、IGR和随后的Vsh估计的做法在估计体积中存在巨大的不确定性。当估计在一个可能的范围内而不是在单个值测量中表示时,不确定性是最好的。据我们所知,这是第一次使用采样技术从伽马射线测井中估计页岩体积。利用ngammaeast1井的上两个泥质层段的伽马测井资料进行了研究,该井穿透了盆地贡贝组。感兴趣区的伽马测井响应是Vsh估计中的不确定参数。采用不确定日志数据的直方图来假设数据的概率分布。在MATLAB平台上,采用标准蒙特卡罗(MC)和拉丁超立方采样技术,采用随机数对不确定对数响应进行建模。利用不确定测井数据分布产生的可能输入测井数据,在页岩体积估计的线性和非线性模型中进行一系列模拟,以确定可能的估计范围及其概率。拉丁超立方法是标准MC法的一种快速、准确的替代方法。本文提出的方法为页岩体积估计的概率方法的实施提供了指导。关键词:页岩体积,蒙特卡罗,拉丁超立方体,采样技术,伽马测井。
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