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随着油气勘探和开发程度的逐渐深入,迫切需要解决薄层划分和厚层细分及薄层评价问题,因此有必要进行测井曲线的高分辨率处理,以提高薄层评价精度。交叉偶极子阵列声波测井处理软件提取的声波时差的纵向分辨率不能满足现场的要求。在充分调研了国内外大量声波时差曲线高分辨率处理方法的基础上,提出了基于遗传算法提取阵列声波测井高分辨率时差的方法。该方法选择跨同一深度地层所有最小子阵列(二个接收器),然后用慢度—时间相关法与遗传算法结合提取每个子阵列的声波时差,最后取其算术平均值作为最终时差。用该方法处理了大庆油田2口阵列声波测井资料,并与高分辨率声波对比,具有较好的一致性,表明该方法可行、实用。
With the gradual deepening of exploration and development of oil and gas, there is an urgent need to solve the problems of thin layer division and thick layer division and thin layer evaluation. Therefore, it is necessary to process high resolution logging curves to improve the evaluation accuracy of thin layer. Longitudinal resolution of acoustic time difference extracted by crossed dipole array acoustic logging software can not meet the requirements of the site. Based on the full investigation of a large number of high-resolution processing methods of acoustic wave time-lag at home and abroad, a method based on genetic algorithm to extract high-resolution jet lag of array acoustic logging is proposed. This method selects all the smallest subarrays (two receivers) across the same depth and then extracts the time lag of each subarray using a combination of slowness-time correlation and genetic algorithm. Finally, the arithmetic mean is taken as the final time difference. By using this method, the acoustic logging data of 2 arrays in Daqing Oilfield are processed and compared with the high-resolution acoustic waves. The results show that this method is feasible and practical.