基于模拟退火算法的阵列声波测井组分波慢度提取

为了提高阵列声波测井组分波慢度提取的精度,基于模拟退火算法以及慢度—时间相关(STC)法的原理,提出了模拟退火算法与慢度—时间相关法结合的阵列声波测井资料处理新方法。该算法核心是将慢度—时间相关法的相关系数经过变换作为模拟退火算法的能量函数,利用模拟退火的全局寻优能力求取组分波慢度。对于纵波,在退火前使用长短时窗能量比法进行波至点的求取可以将二维搜索简化为一维;对于其他组分波,分别使用该算法进行慢度—波至点二维搜索以提取慢度。实例表明,与常规的纵波速度测井对比,该算法提取的纵波精度比传统STC方法处理结果高9.94%;横波结果与传统STC方法的差别为0.29%;斯通利波结果与传统STC方法的差别为0.42%。算法在一定程度上提高了解释精度,在实际应用中有较好效果。

The research of the slowness extraction method of component waves in array acoustic logging data based on simulated annealing algorithm

To enhance the precision of slowness extraction of component waves in array acoustic logging data,the authors,based on simulated annealing algorithm and the theory of slowness-time coherence(STC)method,put forward a new method to process array acoustic data by combining simulated annealing algorithm with slowness-time coherence method.The core of the algorithm is to transform the correlation coefficient of slowness-time coherence method into the energy function of simulated annealing algorithm so that the global optimization capability of simulated annealing algorithm can be utilized to extract the slownesses of component waves.For compressional wave,the energy ratio of short window versus long window method can be applied to the computation of arrival before annealing,so that the two-dimensional search can be simplified to one-dimensional;for other component waves,the algorithm is used respectively to extract the slownesses by two-dimensional search of slowness and arrival.Examples show that,compared with conventional compressional wave logging,the precision of the processed results of compressional wave is 9.94%better than that of conventional STC;the results of shear wave have a difference of 0.29%to those of conventional STC while the difference of Stoneley wave is 0.42%.The algorithm can enhance the precision of slowness extraction of component waves to a certain extent,performing well in application.