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Reconciliation of Core and Log Data Analysis in Very Thin Reservoirs of Krishna Godavari Basin, India

机译:印度克里希纳戈达瓦里盆地非常薄的水库核心和日志数据分析的调节

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Deep water Tertiary reservoirs of Krishna Godavari basin are generally very complex and heterogeneous, ranging from massive thick sands to highly laminated very thin sand/shale sequences beyond the vertical resolution of imaging tools. Verification of log-derived quantities in very thin reservoirs is frequently difficult because of bias and scatter introduced by non-uniform or incomplete plugging of the available over 750 meters of conventional cores. As laminar shale does not occupy or alter the intergranular sand porosity, the conventional way of validation of log derived porosity and water saturation with core data showing excellent correlation does not ensure the correctness of petrophysical evaluations. In this paper, it has been demonstrated that there are potential problems associated with the integration of petrophysical evaluation and core data. Sources of errors are mainly due to the use of different parametric systems viz. using of the terms shale volume and clay volume interchangeably and validating log derived shaliness with clay abundance from XRD core data. Shaliness derived from logs cannot be directly correlated with such core data because neither de-averaging of lithology on log analysis nor averaging of core data is possible for the effective core-log integration. Average hydrocarbon pore volume in laminated reservoirs is linearly related to the average cumulative net sand fraction or shaliness of the formation. Laminar sand porosity and water saturations are independent of shaliness or net sand. Excellent correlation of log derived deconvolved data sets like porosity and water saturation with core measurements does not validate the correctness of hydrocarbon pore volume estimation, which is linearly related to net sand. Accurate estimation of hydrocarbon pore volume requires an accurate calibration of laminar sand/shale volumes, which can be precisely validated only with lamcount data.
机译:Krishna Godavari盆地的深水三级储层通常非常复杂和异质,从大规模的厚砂岩,高度层压的非常薄的砂/页岩序列超出成像工具的垂直分辨率。由于偏置和散射通过750米的传统核心超过750米的可用的偏置和分散引入,验证非常薄的储存器中的数量通常是困难的。由于层流量不占用或改变晶状体孔隙率,因此具有显示出优异相关性的核心数据的日志衍生孔隙率和水饱和的常规验证方式并不能确保岩石物理评估的正确性。在本文中,已经证明存在与岩石物理评估和核心数据集成相关的潜在问题。错误来源主要是由于使用不同的参数系统viz。使用术语页岩体积和粘土体积互换,并验证与XRD核心数据的粘土丰富的日志衍生的Shaliness。从日志派生的Shaliness无法与此类核心数据直接相关,因为对数分析上的岩性的降级也不是核心数据的平均值,可以实现有效的核心日志集成。层压储层中的平均烃孔体积与平均累积净砂分数或形成的股骨头线性相关。层状砂孔隙率和水饱和性与股骨头或净砂无关。 Log衍生的Deconvolved数据集的优异相关性与核心测量的孔隙率和水饱和度不验证碳氢化合物孔隙体积估计的正确性,这与网砂线性相关。准确估计烃孔体积需要精确校准层砂/页岩体积,只能用LAMCOUNT数据精确验证。

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