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Wavelet Analysis of Geophysical Well-log Data of Bombay Offshore Basin, India

机译:印度孟买近海盆地地球物理测井资料的小波分析

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Geophysical well-log (bore-hole) data facilitate understanding of the physical properties of the subsurface formations as a function of depth measured in a well. In the present study, the wavelet transformation technique was applied to the well-log data of three wells in the Bombay High oil field, India, in order to identify depths to the tops of oil and/or gas formation zones (pay zones). Continuous wavelet transformation (CWT) was performed on gamma-ray, resistivity, neutron porosity and velocity log data sets in order to determine the space-localization of the oil and/or gas formation zones. The choice of a mother wavelet is important and largely depends on the data under investigation. We have applied a variety of wavelets to the different log data sets to not only identify the depths to the tops of formation zones, but also to determine the optimum wavelet that best characterizes the pay zones. On examination of scalogram plots of each log corresponding to each wavelet for their better resolution in identifying the formation boundaries, we have found that the scalograms corresponding to the Gaus1 wavelet appeared to give the best resolution in identifying the depths of pay zones in all the well-log data sets of all three wells. To further validate the above observation, a histogram analysis of CWT coefficients is made. This showed that, of all the wavelets considered for the present study, Gaus1 wavelet is the most appropriate and optimum for determining the space-localization of pay zones in all the well-log data sets considered in the present study. The depths of pay zones estimated from scalogram plots of logs agree well with those provided by the Oil and Natural Gas Corporation Ltd., India.
机译:地球物理测井(钻孔)数据有助于理解地下岩层的物理属性,作为井中测得深度的函数。在本研究中,将小波变换技术应用于印度孟买高油田的三口井的测井数据,以识别到石油和/或天然气形成区(产油区)顶部的深度。对伽马射线,电阻率,中子孔隙度和速度测井数据集进行了连续小波变换(CWT),以便确定油气层的空间定位。子小波的选择很重要,并且在很大程度上取决于所研究的数据。我们已将各种小波应用于不同的测井数据集,不仅可以识别到地层带顶部的深度,而且可以确定最能表征产层带的最优小波。在检查与每个小波对应的每个测井的比例尺图以更好地分辨地层边界时,我们发现与Gaus1小波相对应的比例尺似乎在确定所有井中的产层深度方面提供了最佳分辨率。 -记录所有三个孔的数据集。为了进一步验证上述观察结果,对CWT系数进行了直方图分析。这表明,在本研究考虑的所有小波中,Gaus1小波是确定本研究考虑的所有测井数据集中薪水区空间定位的最合适和最佳方法。根据原木比例尺图估算的产油区深度与印度石油天然气公司提供的深度一致。

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