超大型卢拉油田储层特征地质统计反演面临的挑战与对策

E. Kneller, L. Teixeira, B. Hak, N. Cruz, Teresa Oliveira, J. M. Cruz, R. Cunha
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引用次数: 3

摘要

储层模型属性的创建已经成为一门艺术,它将硬数据和软数据结合在一起,收集地质学家和地球物理学家的想法,并用井内和井外的测量值来限制它们。在油田的整个生命周期中,信息覆盖范围不断扩大——新井正在钻探,新的地震采集正在进行,新的地质概念正在发展。巴西盐下油田也不例外。然而,这些油田面临着额外的挑战,其中碳酸盐岩显示出显著的横向和垂直变化,盐层限制了地震信号的照明和穿透。在本文中,我们研究了三种技术在卢拉油田的性能:模拟,它在井之间“传播”属性;确定性反演,将地震振幅转化为弹性性质;地质统计反演,将模拟与地震驱动反演相结合。我们证明,地质统计反演结合了这两种技术的优点,有助于解决盐下碳酸盐岩表征的挑战。
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Challenges and Solutions of Geostatistical Inversion for Reservoir Characterization of the Supergiant Lula Field
Summary The creation of reservoir model properties has become an art of bringing together hard and soft data, gathering ideas of geologists and geophysicists, constraining them with measured values in- and outside wells. Through lifecycle of the oil field the information coverage is growing - new wells are being drilled, new seismic acquisitions are performed, and new geological concepts are developed. The Brazilian pre-salt fields are no exception. However, these fields experience additional challenges, where the carbonates show significant lateral and vertical variability and the salt layer limits illumination and penetration of the seismic signal. In this paper, we investigate performance of three techniques on the Lula field: simulation, which "propagates" properties between wells; deterministic inversion, which transforms seismic amplitudes into elastic properties; and geostatistical inversion, which combines simulation and seismic-driven inversion. We demonstrate that geostatistical inversion brings together the best of both techniques and helps address the challenges of characterization of pre-salt carbonates.
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