自动划分层序单元的测井多尺度数据融合方法

测井信号应用于地层分层主要是利用信号中突变点或突变区域的信息,小波变换系数模极大值随尺度的变化规律可以精确地描述突变点的位置和形态,因此,基于模极值多尺度重构思想,提出基于小波多尺度边缘检测的测井数据融合方法,并将其应用于层序地层单元的定量划分中.以胜坨油田A井为例,利用二次样条小波分别对单条测井曲线和多尺度融合曲线进行二进小波变换,在不同尺度上定量划分出不同级别的层序单元界面.结果表明,利用融合曲线的多尺度分析来划分层序单元能够得到更好的应用效果,其小波变换时频色谱图上的能量聚集和分布能够更清晰地反映准层序组和准层序单元的界面信息及旋回类型.这些探索将为地层层序的定量划分及其内部特征研究提供一种新的思路.图5参19

Automatic demarcation of sequence stratigraphy using the method of well logging multiscale data fusion

Strata division with well logging utilizes the abrupt changing points or regions of signals, while the changing law of the wavelet modulus maxima under different scales can exactly describe the position and modality of the changing points. Based on the idea of reconstruction of wavelet modulus maxima, the well logging data fusion method built on the multiscale edge detection principle is put forward and is applied to the quantitative demarcation of sequence stratigraphy. For case study, single logging curve and multiscale fusion curve in well A in Shengtuo Oilfield are processed by quadric spline wavelet and thereby sequence boundaries on different scales can be detected. The result shows: by demarcating sequence stratigraphic units with the multiscale fusion curve analysis, better effect could be obtained. The energy accumulation and distribution on the wavelet time-frequency graph could clearly reflect the boundaries and cycle types of parasequences and parasequence sets. All these researches provide a completely new method for the quantitative demarcation of sequence and its inner depositional features.