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A comparison between methods that discriminate fluid content in unconsolidated sandstone reservoirs

机译:疏松砂岩油藏流体判别方法的比较

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摘要

Three seismic attributes commonly used to predict pore fluid and lithology are the fluid factor (Delta F), Poisson impedance (PI), and lambda-rho (lambda rho). We evaluated the pore-fluid sensitivity of these attributes with both well-log and seismic data in Tertiary unconsolidated sediments from the Gulf of Mexico where sand and shale are the only expected lithologies. While the sensitivity of one attribute versus another to discriminate pore fluid is often debated in the literature, the sensitivities of the three attributes are not independent but can be traced back to the fluid factor, which is a function of the P- and S-wave normal-incident reflection coefficients. Interestingly, the fluid factor, which is a reflectivity attribute, at the top of a hydrocarbon-saturated reservoir, is basically independent of the shale properties above the reservoir. It is a function of the brine and hydrocarbon impedances of the reservoir. The next attribute, Poisson impedance, is thenequal to the fluid factor times the sum of the brine and hydrocarbon impedances. Finally, the lambda-rho attribute is equal to the Poisson impedance multiplied by the same impedance sum. Essentially, the same scale factor differentiates these attributes, which does not significantly affect the sensitivity of the attributes. PI is the basis of the sensitivity for these attributes. As a means of testing their sensitivity for predicting pore fluid, we generated the three attributes along with their statistical distributions for different pore fluids for 183 reservoirs. The well-log statistical descriptions were then used to calibrate the seismic amplitude in a 3D survey to reflectivity values, thus allowing pore-fluid classification schemes based on Bayes' decision rules. In essence, seismic-amplitude quantification was based on regional statistics rather than individual wells within the 3D seismic survey to delineate the portions of the reservoir that were saturated with oil, gas, or brine.
机译:通常用于预测孔隙流体和岩性的三个地震属性是流体因子(Delta F),泊松阻抗(PI)和lambda-rho(lambda rho)。我们利用测井和地震数据评估了这些属性的孔隙流体敏感性,这些数据来自墨西哥湾,其中仅有砂岩和页岩是唯一预期的岩性的第三纪非固结沉积物。虽然在文献中经常争论一种属性与另一种属性对区分孔隙流体的敏感性,但是这三种属性的敏感性不是独立的,而是可以追溯到流体因子,这是P波和S波的函数垂直入射反射系数。有趣的是,在烃饱和油藏顶部,作为反射率属性的流体因子基本上与油藏上方的页岩特性无关。它是储层盐水和碳氢化合物阻抗的函数。下一个属性泊松阻抗等于流体因子乘以盐水和碳氢化合物阻抗之和。最后,λ-rho属性等于泊松阻抗乘以相同的阻抗和。本质上,相同的比例因子可区分这些属性,而不会显着影响属性的敏感性。 PI是这些属性敏感性的基础。作为测试其预测孔隙流体敏感性的一种方法,我们生成了这三个属性,以及针对183个储层的不同孔隙流体的统计分布。然后,将测井记录的统计描述用于将3D调查中的地震振幅校准为反射率值,从而允许基于贝叶斯决策规则的孔隙流体分类方案。本质上,地震幅度量化是基于区域统计数据,而不是基于3D地震勘测中的单个井,以描绘出油,气或盐水饱和的储层部分。

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