摘要
为了实现南港油田沙一下亚段板2油组孔隙-裂缝双重介质油藏的高效开发,综合岩心、常规测井、三维地震资料开展裂缝预测及成因研究。通过常规测井曲线的裂缝响应特征,建立裂缝识别常数模型,评价裂缝纵向发育情况,同时利用地震多属性的人工神经网络方法,测井与地震数据相结合预测裂缝平面分布范围。预测结果表明,区域主断裂走向为NE向,同时伴生了多条NW、NE、EW向裂缝,主要分布在G 178井断裂和B 228井断裂之间的区域,裂缝的形成与分布明显受隐伏走滑断裂带的控制,双断裂斜交的伴生破碎带所形成的地垒式构造区域裂缝最为发育。综合裂缝发育情况、砂岩厚度以及产能评价结果,将储层划分为4类,其中:裂缝发育且厚度大于10 m的砂岩为Ⅰ类储层,试油无需压裂,自喷高产;裂缝不发育但厚度大于10 m的砂岩为Ⅱ类储层,试油具备一定产能,压裂后可高产。Ⅰ类、Ⅱ类储层发育区域是下步勘探开发的重点目标区。
In order to realize the efficient development of the porous-fractured dual medium reservoir of Ban 2 Formation in Es1xof Nangang oilfield,the fracture prediction and genesis research were carried out based on core,conventional log and three-dimensional seismic data.Based on the fracture response characteristics of conventional logging curves,a fracture identification constant model was established to evaluate the longitudinal development of fractures.At the same time,the multi-attribute artificial neural network method was used to predict the plane distribution of fractures by combining well logging with seismic data.The prediction results show that the trend of the regional main fault is NE,accompanied by multiple NW,NE,and EW fractures,mainly in the area between well G178 fault and well B228 fault.The formation and distribution of fractures are obviously controlled by the burid strike-slip fault zone and the fractures are most developed in the horst-type structural area formed by the accompanying fracture zones of the double fault obliquely crossing.Based on fracture development,sandstone thickness and productivity evaluation results,the reservoirs can be divided into four types.Among them,the sandstone with fracture development and thickness greater than 10 m is type I reservoir.No fracturing is required for oil testing,and high production is achieved through flowing.Sandstone with undeveloped fractures but thickness greater than 10 m is typeⅡreservoir.Oil testing has a certain production capacity,and high yield after fracturing.The development area of type I and typeⅡreservoirs is the key target area for the further exploration and development.
作者
杨佩佩
卢异
周杨
吴刚
李文亮
任光文
YANG Peipei;LU Yi;ZHOU Yang;WU Gang;LI Wenliang;REN Guangwen(Exploration and Development Research Institute of PetroChina Dagang Oilfield Company,Tianjin 300280,China;No.1 Oil Production Plant of PetroChina Dagang Oilfield Company,Tianjin 300280,China)
出处
《录井工程》
2022年第4期118-124,共7页
Mud Logging Engineering
基金
中国石油重大科技专项“大港油区效益增储稳产关键技术研究与应用”(编号:2018E-11)
关键词
裂缝预测
致密砂岩
主控因素
人工神经网络
南港油田
fracture prediction
tight sandstone
main controlling factors
artificial neural network
Nangang oilfield