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Formation Evaluation and Permeability Prediction in a Highly Heterogeneous Reservoir - The Kuparuk C-Sand

机译:非均质储层Kuparuk C-Sand的储层评价和渗透率预测

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The Kuparuk River Field on the North Slope of Alaska is one of the largest oil accumulations in North America. Approximately one-third of the original oil-in-place (OOIP) is contained in the C-sands, which are shallow marine sandstones characterized by intense bioturbation and complex diagenesis. Siderite content is extremely variable and an important control on permeability, porosity, and capillarity on the sub-foot scale. Interpretation of wireline logs in the C-sands for mineralogy, porosity, and water saturation is relatively straightforward, provided that proper interpretation parameters for clay, siderite, and glauconite content and core heterogeneity are considered. Computing a realistic permeability log is more difficult due to extreme scatter in cross-plots of core permeability and log porosity that lim-its the effectiveness of defining a trend. Deterministic porosity-permeability transforms, where permeability is predicted from log porosity, are poor predictors since the results do not replicate the extreme variability present in the core data. Recent field description efforts at Kuparak required re-evaluation of the permeability model, with a need for predicted properties that could be scaled up in a straightforward fashion for use in populating a geo-cellu-lar model. A new method was developed for the prediction of permeability. The method is based on random selection of values of core bulk density from sub-groups based on log bulk density, RHOB, and petrofacies. For each half-foot log depth point, core bulk density values are selected at random, repeatedly, until the density averaged over a sliding window matches the RHOB log to within a pre-set tolerance, nominally 0.05 g/cm~3. The values of core porosity and permeability that correspond to the selected value of core bulk density are then selected as the final result at each depth point. The method duplicates the statistical distributions of the core porosity and permeability values, with values obtained every half-foot. Results were converted from measured depth reference to true vertical depth below mean sea level, SSTVD and up-scaled from 0.5 ft sample increment to 1 and 2 ft increments. The up-scaled permeability values match total permeability-height, kH, based on core-plug data, on a well-by-well basis. The values are also consistent with kH determined from maximum flow rates observed in a number of wells. Given the match with other measures of permeability, the up-scaled permeability values were deemed satisfactory for use in the geo-cellular model.
机译:阿拉斯加北坡的库帕鲁克河油田是北美最大的石油聚集地之一。 C砂中约含原始原始油(OOIP)的三分之一,C砂是浅海砂岩,具有强烈的生物扰动和复杂的成岩作用。菱铁矿的含量变化很大,是控制亚英尺尺度上渗透率,孔隙率和毛细作用的重要控制。如果考虑到粘土,菱铁矿和青铜石含量以及岩心非均质性的正确解释参数,则在C砂中对测井曲线进行矿物学,孔隙度和水饱和度的解释相对简单。由于岩心渗透率和测井孔隙度的交叉图极度分散,限制了趋势定义的有效性,因此计算实际渗透率测井更为困难。确定性孔隙度-渗透率转换(通过对数孔隙度来预测渗透率)是较差的预测指标,因为结果无法复制岩心数据中存在的极端变异性。最近在Kuparak进行的现场描述工作要求对渗透率模型进行重新评估,并需要能够以直接方式按比例放大的预测属性,以用于填充土工蜂窝模型。开发了一种预测渗透率的新方法。该方法是基于对数堆密度,RHOB和岩相从子组中随机选择堆芯密度的值。对于每个半英尺的测井深度点,重复地随机选择堆芯密度值,直到在滑动窗口上平均的密度与RHOB测井值相匹配在预设的公差范围内,名义上为0.05 g / cm〜3。然后,选择对应于堆密度的选定值的岩心孔隙率和渗透率值作为每个深度点的最终结果。该方法使用每半英尺获得的值来复制岩心孔隙率和渗透率值的统计分布。将结果从测得的深度参考转换为低于平均海平面的真实垂直深度,SSTVD,并从0.5英尺的样品增量升至1英尺和2英尺增量。基于岩心塞数据,逐层地将按比例放大的渗透率值与总渗透率高度kH相匹配。该值还与根据在多个孔中观察到的最大流速确定的kH一致。考虑到与其他渗透率测量值的匹配,可以认为向上渗透率值可令人满意地用于地质细胞模型。

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