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Application of the Multi-Parameter Geostatistical Inversion in the Carbonate Reservoir Prediction

机译:在碳酸盐储层预测中的多参数地质统计反演的应用

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Four lithologies were developed in the study area and they were pore-bearing grainstone, compact sparite, shaly limestone and limy mudstone. The pore-bearing grainstone was the main reservoir rock. The characteristic analysis of the electrical and physical properties showed that the acoustic impedance of the pore-bearing grainstone was medium to relatively low. If we only use the inversion data of acoustic impedance, it is difficult to distinguish between the pore-bearing grainstone and other lithologies. In addition, it is difficult to distinguish the reservoir using any single given electrical parameter such as GR, density and resistivity. Therefore, we selected several sensitive logging parameters through crossplot analysis. On the basis of the geostatistical inversion, several volume data were combined, thereby the favorable reservoirs were determined. The multi-parameter geostatistical inversion integrated and constrained by logging data and seismic data. It not only takes the advantage of the geostatistical inversion which does not simply use the acoustic impedance to joins the calculation, but it also uses the curves such as GR, porosity which directly reflect the lithology and physical properties of the formation, to join the calculation. Compared with the conventional acoustic inversion, it greatly improved the vertical resolution, finely characterized the distribution of the reservoirs, and better conquered the problem of the multiplicity of the reservoir prediction and resolution.
机译:在研究区开发了四种岩性,它们是轴承毛孔,紧凑的光源,谢利石灰石和砂岩泥岩。轴承毛孔是主储层岩石。电物理性质的特征分析表明,轴承毛石的声阻抗是培养基相对较低的。如果我们只使用声阻抗的反转数据,则难以区分轴承的磨石和其他岩性。另外,难以使用诸如GR,密度和电阻率的任何单一给定的电气参数来区分储存器。因此,我们通过交叉图分析选择了几个敏感的测井参数。在地统计反转的基础上,组合了几个体积数据,从而确定有利的储层。通过记录数据和地震数据集成和约束的多参数地质统计反演。它不仅占据了地质稳态反演的优势,它不仅仅是使用声阻抗来加入计算,而且还使用诸如GR的曲线,直接反映地层的岩性和物理性质的孔隙度,加入计算。与传统的声反转相比,它大大提高了垂直分辨率,精细表征了储存器的分布,更好地征服了储层预测和分辨率的多重问题。

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