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首页> 外文学位 >Spatial delineation, fluid-lithology characterization, and petrophysical modeling of deepwater Gulf of Mexico reservoirs though joint AVA deterministic and stochastic inversion of three-dimensional partially-stacked seismic amplitude data and well logs.
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Spatial delineation, fluid-lithology characterization, and petrophysical modeling of deepwater Gulf of Mexico reservoirs though joint AVA deterministic and stochastic inversion of three-dimensional partially-stacked seismic amplitude data and well logs.

机译：通过三维局部叠加地震振幅数据和测井的联合AVA确定性和随机反演，对墨西哥湾深水区储层进行空间描述，流体岩性表征和岩石物理建模。

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摘要

This dissertation describes a novel Amplitude-versus-Angle (AVA) inversion methodology to quantitatively integrate pre-stack seismic data, well logs, geologic data, and geostatistical information. Deterministic and stochastic inversion algorithms are used to characterize flow units of deepwater reservoirs located in the central Gulf of Mexico. A detailed fluid/lithology sensitivity analysis was conducted to assess the nature of AVA effects in the study area. Standard AVA analysis indicates that the shale/sand interface represented by the top of the hydrocarbon-bearing turbidite deposits generate typical Class III AVA responses. Layer-dependent Biot-Gassmann analysis shows significant sensitivity of the P-wave velocity and density to fluid substitution, indicating that presence of light saturating fluids clearly affects the elastic response of sands. Accordingly, AVA deterministic and stochastic inversions, which combine the advantages of AVA analysis with those of inversion, have provided quantitative information about the lateral continuity of the turbidite reservoirs based on the interpretation of inverted acoustic properties and fluid-sensitive modulus attributes (P-Impedance, S-Impedance, density, and LambdaRho, in the case of deterministic inversion; and P-velocity, S-velocity, density, and lithotype (sand-shale) distributions, in the case of stochastic inversion).; The quantitative use of rock/fluid information through AVA seismic data, coupled with the implementation of co-simulation via lithotype-dependent multidimensional joint probability distributions of acoustic/petrophysical properties, provides accurate 3D models of petrophysical properties such as porosity, permeability, and water saturation. Pre-stack stochastic inversion provides more realistic and higher-resolution results than those obtained from analogous deterministic techniques. Furthermore, 3D petrophysical models can be more accurately co-simulated from AVA stochastic inversion results. By combining AVA sensitivity analysis techniques with pre-stack stochastic inversion, geologic data, and awareness of inversion pitfalls, it is possible to substantially reduce the risk in exploration and development of conventional and non-conventional reservoirs.; From the final integration of deterministic and stochastic inversion results with depositional models and analogous examples, the M-series reservoirs have been interpreted as stacked terminal turbidite lobes within an overall fan complex (the Miocene MCAVLU Submarine Fan System); this interpretation is consistent with previous core data interpretations and regional stratigraphic/depositional studies.
机译：本文介绍了一种新颖的振幅对角度反演方法，可以定量地整合叠前地震数据，测井，地质数据和地统计信息。确定性和随机反演算法用于表征位于墨西哥湾中部的深水储层的流动单元。进行了详细的流体/岩性敏感性分析，以评估研究区域内AVA效应的性质。标准AVA分析表明，以含烃浊石沉积物顶部为代表的页岩/砂界面产生了典型的III类AVA响应。依赖于层的Biot-Gassmann分析表明，P波速度和密度对流体替代具有显着的敏感性，表明光饱和流体的存在明显影响了砂土的弹性响应。因此，AVA确定性和随机反演结合了AVA分析和反演的优势，基于对反演声学特性和流体敏感模量属性的解释（P阻抗），提供了关于浊积岩储层横向连续性的定量信息。 ；如果是确定性反演，则为S阻抗，密度和LambdaRho；如果是随机反演，则为P速度，S速度，密度和岩石类型（砂页岩）分布）。通过AVA地震数据定量使用岩石/流体信息，并通过依赖岩石类型的多维声/岩石物理性质联合概率分布进行联合模拟，从而提供了岩石物理性质（如孔隙度，渗透率和水）的精确3D模型饱和。与从类似确定性技术获得的结果相比，叠前随机反演提供了更现实，更高分辨率的结果。此外，可以从AVA随机反演结果更准确地共同模拟3D岩石物理模型。通过将AVA敏感性分析技术与叠前随机反演，地质数据以及对反演陷阱的认识相结合，可以大大降低常规和非常规油藏勘探和开发的风险。从确定性和随机反演结果与沉积模型和类似实例的最终整合来看，M系列储层已被解释为整个扇形构造体（中新世MCAVLU潜艇扇形系统）中的堆积的终浊积叶状裂片。这种解释与以前的核心数据解释和区域地层/沉积研究一致。

著录项

  • 作者

    Contreras, Arturo Javier.;

  • 作者单位

    The University of Texas at Austin.;

  • 授予单位 The University of Texas at Austin.;
  • 学科 Geology.; Geophysics.
  • 学位 Ph.D.
  • 年度 2006
  • 页码 200 p.
  • 总页数 200
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 地质学;地球物理学;
  • 关键词

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