含气储层预测方法及应用
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摘要
由于红台气田储层物性横向变化剧烈,利用地震属性及反演预测含气储层效果不明显,而利用地震资料高阶谱分析非高斯信息的方法进行含气储层预测,几乎还没有人在此方面开展过研究。为此,在对吐哈盆地红台油气田构造、沉积研究分析基础上,研究利用地震资料进行砂体储层含油气预测的新技术。从讨论实际地震记录高阶累积量分析入手,研究利用高阶累积量计算高阶谱的方法;在分析高阶累积量及高阶谱提取分离具有非高斯分布信号时,详细讨论了产生具有高斯分布及非高斯分布的地震记录的地质条件及原因;阐明了用地震资料的低频高阶谱预测砂体含油气性的机制;从理论模型上论证了研究方法的正确性。并利用该方法把计算结果和实际产油气井资料进行符合率验证分析,验证结果总体符合率超过70%,较好地解决了该地区含气储层的预测问题,并在此基础上进行了有利含气储层的预测。
As lateral reservoir properties changes dramatically in Hongtai gas field, seismic attributes and inversion can not be used to predict gas-bearing reservoir effectively, and up till now studies have never been carried out on gas-bearing reservoir predicted by using high order spectrum seismic data to analyze the non-Gaussian information. Therefore, based on the analysis on the structure and deposit of Hongtai oil and gas field, this study put forward a new method of predicting oil-and gas-bearing reservoirs by seismic data. Starting with the actual sesmic data, the research used high order spectrum to calculate high order accumulation. When the non-Gaussian distribute information was collected by means of analyzing the high order spectrum and high order accumulation, the geological conditions and reasons of coming into Gaussian and non-Gaussian distributes were discussed in detail. It clarified the mechanism of predicting oil and gas-bearing reservoirs using lower frequency seismic data. The method was approved by theory model, and finally it was used to analyze the coincidence rate of the observed data and calculating results. The result showed that the overall coincidence rate was over 70%. Obviously, the prediction of gas-bearing reservoir in Hongtai area was acceptable. Based on which, gas layers can be predicted more effectively.
As lateral reservoir properties changes dramatically in Hongtai gas field, seismic attributes and inversion can not be used to predict gas-bearing reservoir effectively, and up till now studies have never been carried out on gas-bearing reservoir predicted by using high order spectrum seismic data to analyze the non-Gaussian information. Therefore, based on the analysis on the structure and deposit of Hongtai oil and gas field, this study put forward a new method of predicting oil-and gas-bearing reservoirs by seismic data. Starting with the actual sesmic data, the research used high order spectrum to calculate high order accumulation. When the non-Gaussian distribute information was collected by means of analyzing the high order spectrum and high order accumulation, the geological conditions and reasons of coming into Gaussian and non-Gaussian distributes were discussed in detail. It clarified the mechanism of predicting oil and gas-bearing reservoirs using lower frequency seismic data. The method was approved by theory model, and finally it was used to analyze the coincidence rate of the observed data and calculating results. The result showed that the overall coincidence rate was over 70%. Obviously, the prediction of gas-bearing reservoir in Hongtai area was acceptable. Based on which, gas layers can be predicted more effectively.
引文
[1]王树勋.高阶统计量在系统理论中的应用[J].自动化学报,1994,20(6):288-294.
[2]杨晨明.高阶统计量在检测中的应用[J].信号处理,1995,11(4):710-717.
[3]杜宁平,史军,朱红涛.高阶统计量分析在油气预测中的应用[J].海洋地质动态,2004,20(8):27-29.
[4]宋维琪,曹自强,刘仕友.多尺度四阶累积量相关分析方法及其应用[J].石油物探,2006,45(6):607-610.
[5]李勇,李琼,李正文,等.基于GA-ANFIS的油气储层地震预测方法及应用[J].天然气工业,2006,26(5):40-42.
[6]乐友喜,袁全社.支持向量机方法在油气储层参数预测中的应用[J].天然气工业,2005,25(12):45-47.
[7]WENKAI LU,YANDONG LI,SHANWEN ZHANG,et al.Higher-order-statistics and supertrace-basedcoher ehce-esti mational gorithm[J].Geophysics,2005,70(3):13-18.
[8]WALDEN A T.Non-Gaussianreflectivity,eentroy,and deconvolution[J].Geophysics,1985,50(12):2862-2888.
[9]LIANG G H,CAAI X P,LI Q Y.Using high-order cu-mulants to extrapolate spatially variant seismic wavelets[J].Geophysics,1997,62(6):1947-1876.
[2]杨晨明.高阶统计量在检测中的应用[J].信号处理,1995,11(4):710-717.
[3]杜宁平,史军,朱红涛.高阶统计量分析在油气预测中的应用[J].海洋地质动态,2004,20(8):27-29.
[4]宋维琪,曹自强,刘仕友.多尺度四阶累积量相关分析方法及其应用[J].石油物探,2006,45(6):607-610.
[5]李勇,李琼,李正文,等.基于GA-ANFIS的油气储层地震预测方法及应用[J].天然气工业,2006,26(5):40-42.
[6]乐友喜,袁全社.支持向量机方法在油气储层参数预测中的应用[J].天然气工业,2005,25(12):45-47.
[7]WENKAI LU,YANDONG LI,SHANWEN ZHANG,et al.Higher-order-statistics and supertrace-basedcoher ehce-esti mational gorithm[J].Geophysics,2005,70(3):13-18.
[8]WALDEN A T.Non-Gaussianreflectivity,eentroy,and deconvolution[J].Geophysics,1985,50(12):2862-2888.
[9]LIANG G H,CAAI X P,LI Q Y.Using high-order cu-mulants to extrapolate spatially variant seismic wavelets[J].Geophysics,1997,62(6):1947-1876.
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