基于伽马—磁共振联合反演的薄层评价研究

发布时间：2018-06-17 08:34

本文选题：核磁共振测井 + 自然伽马测井　；参考：《华中科技大学》2015年硕士论文

【摘要】：核磁共振测井方法通过测量地层流体弛豫信息和扩散信息获得流体类型和岩石物性,但是其纵向分辨率较低;自然伽马测井方法通过测量岩石天然放射性强度获取地层岩性信息,其纵向分辨率较高,但是无法对油藏做评价。为了准确识别和评价薄层,本文综合核磁共振测井方法和自然伽马测井方法的优点,提出一种自然伽马测井数据和核磁共振测井数据约束性联合反演方法。该方法首先基于自然伽马测井原理,根据GR曲线活度将地层进行划分,得到不同类型岩层厚度信息及岩性信息;然后依据薄层厚度信息,基于核磁共振地层界面响应方程和PAPS对原理,推出消除振铃噪声和围岩层影响的薄层回波数据校正方程;最后依据标准T2谱优选少数布点分量,根据T2谱模型和地层岩性构建约束条件,基于BRD反演算法得到高分辨率T2谱。本文首先对数据校正方法进行仿真。在假定薄层厚度已知的情况下,构建单峰、双峰和三峰地层界面模型,运用校正方程计算得到薄层回波数据,该校正数据反演后得到的标准T2谱与构造的T2谱基本一致。其次对单峰T2谱模型进行高分辨率联合反演算法仿真,在信噪比低至5的时候,与标准反演方法相比,该联合反演算法可以得到更准确的峰值位置和总孔隙度。最后,应用某井实际测井数据,与常规的数据处理方式相比,该约束性联合反演方法提高了薄层识别和评价的准确性。
[Abstract]:The NMR logging method obtains fluid types and petrophysical properties by measuring the relaxation and diffusion information of formation fluids, but its longitudinal resolution is relatively low. The natural gamma logging method acquires the lithologic information by measuring the natural radioactivity intensity of rock. The vertical resolution is high, but the reservoir can not be evaluated. In order to accurately identify and evaluate thin layers, a constrained joint inversion method of natural gamma logging data and nuclear magnetic resonance logging data is proposed by combining the advantages of nuclear magnetic resonance logging and natural gamma logging. The method is based on the principle of natural gamma logging and divides the strata according to the activity of gr curve to obtain the thickness information and lithology information of different types of strata, and then according to the thickness information of thin layer. Based on the response equation of nuclear magnetic resonance (NMR) stratigraphic interface and the principle of PAPS pair, a correction equation of thin-layer echo data for eliminating ringing noise and the influence of surrounding rock is derived. Finally, a few points are selected according to the standard T2 spectrum. According to the T2 spectrum model and the formation lithology construction constraints, the high resolution T2 spectrum is obtained based on the BRD inversion algorithm. Firstly, the data correction method is simulated in this paper. Under the assumption that the thickness of the thin layer is known, the single peak, two peak and three peak stratigraphic interface models are constructed, and the thin-layer echo data are calculated by using the correction equation. The standard T2 spectrum obtained from the inversion of the positive data is basically consistent with the constructed T2 spectrum. Secondly, the single-peak T2 spectral model is simulated with high resolution joint inversion algorithm. When the SNR is low to 5, compared with the standard inversion method, the combined inversion algorithm can get more accurate peak position and total porosity. Finally, compared with the conventional data processing method, the constrained joint inversion method improves the accuracy of thin layer identification and evaluation by using the actual logging data of a well.
【学位授予单位】：华中科技大学
【学位级别】：硕士
【学位授予年份】：2015
【分类号】：P631.81

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