叠后烃检方法在渤海海域PL稠油区块的应用

Application of Poststack Hydrocarbon Detecting Method to Bohai PL Heavy Oil Area

针对渤海海域PL油田新近系明化镇组原油密度大,常规叠后烃检方法效果不佳的特点,利用储层含油气后高频端能量吸收衰减原理,在高精度频谱分解基础上,采用能量系数法和高频斜率衰减地震属性预测油气,效果一般;结合研究区地质特点,以神经网络多种成熟算法为基础算法,优选对油水有不同响应的地震属性作为训练参数,以含油饱和度曲线作为目标曲线,对全区地震数据体进行反演,用验证井与饱和度数据体有效响应比对,主力油层含油砂体吻合率高达75%以上。利用该方法结合其它成藏条件优选了显示很好的多套砂体作为进一步勘探潜力靶区。

In PL oilfield of Bohai Sea Area, the density of the crude oil in Neogene Minghuazhen Formation is high, and the conventional poststack hydrocarbon detection methods are not effective in these oilfields. On the basis of the principle that frequency energy will be absorbed and attenuated if there is hydrocarbon in the reservoirs, the energy coefficient method and the attribute of the slope attenuation of high frequency have been used for predicting hydrocarbon with high precision spectral decomposition technique, and the forecast results are not good enough. Combined with the geological characteristic of the study area, we select optimal seismic attributes as training parameters by using a variety of neural network algorithm based algorithm, which have different responses for oil and water. Using oil saturation curve as a target curve, we have conducted seismic inversion for the whole study area. We can know the coincidence rate of oil sands in main reservoir reached above 75% between the verification wells and the saturation volume. By using these methods, combined with study results on the geologic condition for hydrocarbon accumulation, several sets of sand bodies with good hydrocarbon shows have been selected as potential further exploration targets.