川东北元坝地区长兴组生物礁储层预测研究

2011年 50卷 第No. 2期
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Prediction on reef reservoir in Changxing group of Yuanba area,Northeast Sichuan Basin
中国石油化工股份有限公司石油物探技术研究院,江苏南京210014
Chen Yong,Sinopec Geophysical Research Institute,Nanjing 210014,China
地震、地质、钻井和测井资料表明川东北元坝地区长兴组生物礁储层发育。该地区地震相带明显,有开阔台地相、台地边缘礁滩相、斜坡相、深海相,其中台地边缘礁滩相是生物礁储层主要分布区。生物礁由于其特有的沉积过程和沉积作用,具有特有的地貌和岩石学特征,在地震记录上呈典型的丘状外形,顶、底强反射,内部杂乱、空白、成层反射,翼部披覆等地震响应特征。从生物礁储层地震响应特征入手,以地震相的划分、优选为指导,以预测生物礁储层含油气有利分布区为目标,利用地震相分析方法、地震属性分析方法、波阻抗反演技术、多属性融合技术对生物礁储层进行了综合预测,结果表明,在生物礁分布区内,对应弱振幅、低频率、较大频率衰减梯度、低阻抗、低速度的区域为含油气有利区带。钻井资料证实有利区带有较好的油气显示,证明了储层预测方法的有效性。
Seismic,geological,drilling and log data reveals that reef reservoir is developed in Changxing group of Yuanba area.Its seismic facies belts include open platform facies,platform margin reef flat facies,slope facies,deep sea facies.Among the seismic facies,the platform margin reef flat facies is the main distribution area of reef reservoir.Because of the unique deposition and sedimentation,reef has its own characteristics and lithological characteristics,which displays mound seismic reflection,strong reflection on the top and bottom,disorder,blank and layered reflection in interior,as well as onlap in the limb.Starting from the seismic responses of reef reservoir,taking the classification and optimization of seismic facies as guidance and the prediction of beneficial oil/gasbearing area in reef reservoir as target,we utilized seismic facies analysis method,seismic attribute analysis method,wave impedance inversion technique and multiattribute fusion to comprehensively predict the reef reservoir.The result indicates that in the reef reservoir,the beneficial oil/gasbearing area corresponds to the characteristics such as weak amplitude,low frequency,relatively large frequency attenuation gradient,low impedance and low velocity.Drilling data proved the beneficial area has good oil/gasshow,which demonstrates that the reservoir prediction method is available.
生物礁; 储层预测; 地震相; 地震属性; 波阻抗反演; 多属性融合;
reef; reservoir prediction; seismic facies; seismic attributes; impedance inversion; multiattribute fusion;