山东科技大学学报:自然科学版
山東科技大學學報:自然科學版
산동과기대학학보:자연과학판
Journal of Shandong Univ of Sci and Technol: Nat Sci
2011年
4期
51-57
,共7页
匹配追踪%时频分析%油气检测%Morlet小波
匹配追蹤%時頻分析%油氣檢測%Morlet小波
필배추종%시빈분석%유기검측%Morlet소파
matching trace%time-frequency analysis%hydrocarbon detection%Morlet wavelet
地震波穿过地下含油气区时会表现为低频能量相对增强、高频能量相对减弱,准确提取地震波的低频能量和高频能量可以实现地下岩石的含油气性检测。利用短时傅里叶变换、S变换和引入尺度参数的匹配追踪算法对合成信号进行了试算,结果表明,引入尺度参数的Morlet小波匹配追踪算法不仅算法速度快,而且有更好的时频分辨率;通过对实际地震资料的匹配追踪计算,表明该算法也适用于实际资料;利用匹配追踪算法较准确地提取地震波的低频和高频能量,并对实际资料进行了含油气性预测,取得了与钻井一致的结果。
地震波穿過地下含油氣區時會錶現為低頻能量相對增彊、高頻能量相對減弱,準確提取地震波的低頻能量和高頻能量可以實現地下巖石的含油氣性檢測。利用短時傅裏葉變換、S變換和引入呎度參數的匹配追蹤算法對閤成信號進行瞭試算,結果錶明,引入呎度參數的Morlet小波匹配追蹤算法不僅算法速度快,而且有更好的時頻分辨率;通過對實際地震資料的匹配追蹤計算,錶明該算法也適用于實際資料;利用匹配追蹤算法較準確地提取地震波的低頻和高頻能量,併對實際資料進行瞭含油氣性預測,取得瞭與鑽井一緻的結果。
지진파천과지하함유기구시회표현위저빈능량상대증강、고빈능량상대감약,준학제취지진파적저빈능량화고빈능량가이실현지하암석적함유기성검측。이용단시부리협변환、S변환화인입척도삼수적필배추종산법대합성신호진행료시산,결과표명,인입척도삼수적Morlet소파필배추종산법불부산법속도쾌,이차유경호적시빈분변솔;통과대실제지진자료적필배추종계산,표명해산법야괄용우실제자료;이용필배추종산법교준학지제취지진파적저빈화고빈능량,병대실제자료진행료함유기성예측,취득료여찬정일치적결과。
The seismic waves will comparatively enhance the low frequency energy and weaken the high frequency energy when propagating through the subsurface oil-gas-bearing media zone.Accurately extracting low frequency energy and high frequency energy of the seismic waves can realize the detection of the oil-gas-bearing nature of strata underground.In this paper,the synthetic signal was calculated by means of the short-time Fourier transform,S transform and introducing the matching trace algorithm with the scale parameters.The results show that the matching trace algorithm by introducing Morlet wavelet with the scale parameters not only holds a high speed but also has better time-frequency resolution.The application of field seismic data shows that the matching trace algorithm can achieve a good match of the field seismic data.The low frequency energy and high frequency energy of the seismic waves were exactly extracted by means of the matching trace algorithm and the prediction of oil-gas-bearing nature was conducted by using field data,conforming to the actual drilling data.