石油地球物理勘探2024，Vol.59Issue(4)：856-864,9.DOI:10.13810/j.cnki.issn.1000-7210.2024.04.023
一种基于多波地震的多尺度属性融合
A multi-scale attribute fusion based on multi-wave seismic
摘要
Abstract
Compared with the multi-wave seismic data acquisition and processing methods,the progress of multi wave seismic data interpretation methods is relatively slow,which makes it difficult to demonstratethe superio-rity of multi-wave seismic technology.Conventional seismic attribute extraction and analysis are mostly based on P-wave seismic data,without fully utilizing reservoir P-wave and S-wave information.Therefore,a multi-scale attribute fusion technology is proposed to enhance the oil and gas sensitivity of multi-wave composite attri-butes.For an actual 2D seismic profile,firstly,a Gaussian pyramid is constructed to generate various compo-site attributes of different resolutions.Secondly,all attributes of different scales are fused to form an effective multi-scale enhanced attribute.Thirdly,by leveraging image superposition theory,different multi-scale en-hanced attributes are mixed and superimposed,which can effectively highlight the reservoir development area and retain the differences between various attributes,thus better describing the oil and gas bearing properties of the sand body.The model test shows that for complex two-dimensional models with small differences between oil-bearing sandstone and surrounding rock,the multi-wave seismic fusion attribute based on RGB can detect reservoirs and identify the location of reflection interfaces.The actual data test shows that the proposed method can accurately distinguish the distribution of channel sand body in the target area.关键词
多波地震/地震属性/高斯金字塔/图像分析/多尺度融合Key words
multi-wave seismic/seismic attribute/Gaussian pyramid/image analysis/multi-scale fusion分类
天文与地球科学引用本文复制引用
潘辉,高建虎,桂金咏,李胜军,陈启艳..一种基于多波地震的多尺度属性融合[J].石油地球物理勘探,2024,59(4):856-864,9.基金项目
本项研究受中石油前瞻性基础性课题"复杂气藏地震识别与预测技术研究"(2021DJ0606)、直属院所基础研究和战略储备技术研究基金""孔、渗、饱"多参数联合智能化地震反演技术研究"(2022D-XB01)和甘肃省科技重大科技专项"陇东地区天然气藏地球物理预测关键技术研发及应用"(23ZDGA004)联合资助. （2021DJ0606）
