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Integration of Seismic Anisotropy and Reservoir-Performance Data for Characterization of Naturally Fractured Reservoirs Using Discrete-Feature-Network Models

机译:地震各向异性和储层性能数据的集成,用于使用离散特征网络模型表征自然裂缝储层

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This paper proposes a method for quantitative integration of seismic (elastic) anisotropy attributes with reservoir-performance data as an aid in characterizing systems of natural fractures in hydrocarbon reservoirs. This method is demonstrated through application to history matching of reservoir performance using synthetic test cases. Discrete-feature-network (DFN) modeling is a powerful tool for developing fieldwide stochastic realizations of fracture networks in petroleum reservoirs. Such models are typically well conditioned in the vicinity of the wellbore through incorporation of core data, borehole imagery, and pressure-transient data. Model uncertainty generally increases with distance from the borehole. Three-dimensional seismic data provide uncalibrated information throughout the interwell space. Some elementary seismic attributes such as horizon curvature and impedance anomalies have been used to guide estimates of fracture trend and intensity (fracture area per unit volume) in DFN modeling through geostatistical calibration with borehole and other data. However, these attributes often provide only weak statistical correlation with fracture-system characteristics. The presence of a system of natural fractures in a reservoir induces elastic anisotropy that can be observed in seismic data. Elastic attributes such as azimuthally dependent normal moveout velocity (ANMO), reflection amplitude vs. azimuth (AVAZ), and shear-wave birefringence can be inverted from 3D-seismic data. Anisotropic elastic theory provides physical relationships among these attributes and fracture-system properties such as trend and intensity. Effective-elastic-media models allow forward modeling of elastic properties for fractured media. A technique has been developed in which both reservoir-performance data and seismic anisotropic attributes are used in an objective function for gradient-based optimization of selected fracture-system parameters. The proposed integration method involves parallel workflows for effective elastic and effective permeability media modeling from an initial DFN estimate of the fracture system. The objective function is minimized through systematic updates of selected fracture-population parameters. Synthetic data cases show that 3D-seismic attributes contribute significantly to the reduction of ambiguity in estimates of fracture-system characteristics in the interwell rock mass. The method will benefit en-hanced-oil-recovery (EOR) program planning and management, optimization of horizontal-well trajectory and completion design, and borehole-stability studies.
机译:本文提出了一种将地震(弹性)各向异性属性与储层性能数据进行定量积分的方法,以帮助表征油气藏天然裂缝系统。通过使用综合测试案例将其应用于储层性能的历史匹配中,证明了该方法。离散特征网络(DFN)建模是开发油田储层裂缝网络在现场范围内随机实现的强大工具。通过合并岩心数据,井眼图像和压力瞬变数据,此类模型通常在井眼附近条件良好。模型不确定性通常随距井眼的距离而增加。三维地震数据在整个井间空间中提供了未经校准的信息。一些基本的地震属性,例如层曲率和阻抗异常,已被用于通过钻孔和其他数据的地统计校准来指导DFN建模中的断裂趋势和强度(每单位体积的断裂面积)的估计。但是,这些属性通常仅提供与裂缝系统特征的弱统计相关性。油藏中天然裂缝系统的存在会引起弹性各向异性,这种各向异性可以在地震数据中观察到。可以根据3D地震数据反转诸如与方位角有关的法向运动速度(ANMO),反射幅度与方位角(AVAZ)和剪切波双折射等弹性属性。各向异性弹性理论提供了这些属性与裂缝系统特性(例如趋势和强度)之间的物理关系。有效的弹性介质模型可以对断裂介质的弹性特性进行正向建模。已经开发出一种技术,其中在目标函数中使用储层性能数据和地震各向异性属性,以基于梯度优化所选裂缝系统参数。所提出的整合方法涉及并行工作流程,用于根据断裂系统的初始DFN估算值进行有效的弹性和有效渗透介质建模。通过系统更新选定的裂缝人口参数,可将目标函数降至最低。综合数据实例表明,在井间岩体的裂缝系统特征估计中,3D地震属性显着降低了歧义。该方法将有利于提高采油率(EOR)计划和管理,水平井轨迹和完井设计的优化以及井眼稳定性研究。

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