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首页> 外文会议>SPWLA annual logging symposium >JOINT STOCHASTIC INVERSION OF PETROPHYSICAL LOGS AND 3DPRE-STACK SEISMIC DATA TO ASSESS THE SPATIAL CONTINUITYOF FLUID UNITS AWAY FROM WELLS: APPLICATION TO A GULFOF MEXICO DEEPWATER HYDROCARBON RESERVOIR
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JOINT STOCHASTIC INVERSION OF PETROPHYSICAL LOGS AND 3DPRE-STACK SEISMIC DATA TO ASSESS THE SPATIAL CONTINUITYOF FLUID UNITS AWAY FROM WELLS: APPLICATION TO A GULFOF MEXICO DEEPWATER HYDROCARBON RESERVOIR

机译：石油测井和3DPRE地震数据的联合随机反演，以评估远离井的流体单元的空间连续性：在墨西哥湾深水油气藏中的应用

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We implement a novel methodology to integrate welllogs and 3D pre-stack seismic data. The objective is toassess lateral continuity and spatial extent of lithologyand fluid units penetrated by a well. Pre-stack seismicdata are used to fill the spatial gap between sparse welllocations. The approach is based on a stochastic globalinversion method that concomitantly honors well logsand multiple angle stacks of seismic amplitude data.Inversion results consist of 3D spatial distributions ofelastic properties, litho-facies, and petrophysicalproperties between wells that exhibit a verticalresolution intermediate between that of well logs and3D seismic data.Examples of the application of this technique are shownusing high-quality 3D seismic data acquired byWesternGeco in the deepwater Gulf of Mexico.Reservoir units consist of stacked turbidite sands.Petrophysical and litho-facies logs are synthesized andcorrelated with elastic properties inferred from P- andS-wave sonic logs to assess the sensitivity of elasticproperties to variations of porosity and fluid saturation.Both petrophysical logs and elastic-petrophysicalcorrelations, together with four angle stacks of prestackseismic amplitude data, are input to the stochasticinversion algorithm to estimate 3D distributions oflitho-facies, porosity, permeability, and fluid saturation.When tested at blind-well locations, the estimatedspatial distributions of porosity, permeability, andsaturation of individual sand units agree well with thesame properties derived from well logs. Sensitivityanalyses indicate that the inversion results are slightlyconditioned by both the choice of variogram model andrange, as well as by the assumed global lithologyproportions. Uncertainty analysis is performed to assessthe reliability of the estimated distributions ofpetrophysical properties away from wells. This exerciseconfirms that the seismic and well-log measurementsproperly condition the extrapolation of petrophysicalproperties of flow units penetrated by a well. Theuncertainty of the extrapolation decreases with anincrease in sand thickness and porosity.
机译：我们采用一种新颖的方法来很好地整合 日志和3D叠前地震数据。目的是 评估岩性的横向连续性和空间范围 和流体单元被井穿透。叠前地震 数据用于填补稀疏井之间的空间缺口 位置。该方法基于随机的全局 伴有测井资料的反演方法 以及地震振幅数据的多个角度堆栈。 反演结果由3D空间分布组成 弹性，岩石相和岩石物理 垂直井之间的性质 分辨率介于测井和 3D地震数据。 显示了此技术的应用示例 使用通过以下方式获得的高质量3D地震数据 WesternGeco在墨西哥湾深水区。 储层单元由堆积的浊积砂组成。 合成了岩石物理和岩石相测井并 与从P-和P-推断的弹性有关 S波声波测井仪评估弹性的敏感性 孔隙度和流体饱和度变化的特性。 岩石物理原木和弹性岩石物理 相关性，以及四个叠前叠角 地震振幅数据输入到随机 反演算法来估计3D分布 岩石相，孔隙度，渗透率和流体饱和度。 在盲井位置进行测试时，估计 孔隙度，渗透率和 单个砂单元的饱和​​度与 源自测井的相同属性。灵敏度 分析表明，反演结果略有不同。 取决于方差图模型的选择和 范围，以及假定的全球岩性 比例。进行不确定性分析以评估 估计分布的可靠性 远离井的岩石物性。这项练习 确认地震和测井测量 适当地调整岩石物理的外推 井穿透的流动单元的特性。这 外推的不确定性随着 增加砂的厚度和孔隙率。

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