Prediction of Reservoir Properties from Seismic Data by Multivariate Geostatistics Analysis

V. Bezkhodarnov, T. Chichinina, M. Korovin, V. V. Trushkin
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引用次数: 3

Abstract

A new technique has been developed and is being improved, which allows, on the basis of probabilistic and statistical analysis of seismic data, to predict and evaluate the most important parameters of rock properties (including the reservoir properties such as porosity and permeability), that is, oil saturation, effective thicknesses of reservoirs, their sand content, clay content of seals, and others; it is designed to predict the reservoir properties with sufficient accuracy and detail, for subsequent consideration of these estimates when evaluating hydrocarbon reserves and justifying projects for the deposits development. Quantitative reservoir-property prediction is carried out in the following stages: –Optimization of the graph ("scenario") of seismic data processing to solve not only the traditional structural problem of seismic exploration, but also the parametric one that is, the quantitative estimation of rock properties.–Computation of seismic attributes, including exclusive ones, not provided for in existing interpretation software packages.–Estimation of reservoir properties from well logs as the base data.–Multivariate correlation and regression analysis (MCRA) includes the following two stages: Establishing correlations of seismic attributes with estimates of rock properties obtained from well logs.Construction of multidimensional (multiple) regression equations with an assessment of the "information value" of seismic attributes and the reliability of the resulting predictive equations. (By the "informative value" we mean the informativeness quality of the attribute.)–Computation and construction of the forecast map variants, their analysis and producing the resultant map (as the most optimal map version) for each predicted parameter.–Obtaining the resultant forecast maps with their zoning according to the degree of the forecast reliability. The MCRA technique is tested by production and prospecting trusts during exploration and reserves’ estimation of several dozen fields in Western Siberia: Kulginskoye, Shirotnoye, Yuzhno-Tambaevskoye, etc. (Tomsk Geophysical Trust, 1997-2002); Dvurechenskoe, Zapadno-Moiseevskoe, Talovoe, Krapivinskoe, Ontonigayskoe, etc. (TomskNIPIneft, 2002–2013).
用多元地统计方法预测地震资料中的储层物性
一项新技术已经开发出来,并正在不断改进,该技术可以根据地震数据的概率和统计分析,预测和评估岩石性质(包括孔隙度和渗透率等储层性质)的最重要参数,即含油饱和度、储层有效厚度、含砂量、密封层粘土含量等;它的目的是充分准确和详细地预测储层性质,以便在评估油气储量和确定矿床开发项目时后续考虑这些估计。储层物性定量预测分以下几个阶段进行:—优化地震数据处理图(“场景”),既解决传统的地震勘探结构问题,又解决参数化问题,即岩石物性的定量估计。-计算地震属性,包括现有解释软件包中未提供的专有属性。-以测井资料为基础,对储层物性进行估计。-多变量相关与回归分析(MCRA)包括以下两个阶段:建立地震属性与从测井曲线中获得的岩石属性估计的相关性。构建具有地震属性“信息价值”评估的多维(多元)回归方程及其预测方程的可靠性。(通过“信息值”,我们指的是属性的信息质量)-预测图变量的计算和构建,它们的分析和生成每个预测参数的结果图(作为最优的地图版本)。-根据预测可靠性的程度,获得带有分区的最终预测图。MCRA技术在西西伯利亚几十个油田的勘探和储量估算中得到了生产和勘探信托公司的测试:Kulginskoye、Shirotnoye、yuzho - tambaevskoye等(托木斯克地球物理信托公司,1997-2002);Dvurechenskoe, Zapadno-Moiseevskoe, Talovoe, Krapivinskoe, Ontonigayskoe等(TomskNIPIneft, 2002-2013)。
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