基于优选地震参数的缝洞型油藏单井产能预测模型  

Well productivity prediction model for fracture-cavity reservoirs based on optimized seismic parameters

作　　者：解慧[1,2] 赵进[1,2] 郭臣[1,2] 陈勇[1,2] XIE Hui;ZHAO Jin;GUO Chen;CHEN Yong(Research Institute of Exploration and Development,Northwest Oilfield Company,SINOPEC,Urumqi,Xinjiang,830011,China;Key Laboratory of Enhanced Oil Recovery of Fracture-cavity Carbonate Reservoir,SINOPEC,Urumqi,Xinjiang,830011,China)

机构地区：[1]中国石化西北油田分公司勘探开发研究院,新疆乌鲁木齐830011 [2]中国石化碳酸盐岩缝洞型油藏提高采收率重点实验室,新疆乌鲁木齐830011

出　　处：《油气地质与采收率》2022年第4期150-158,共9页Petroleum Geology and Recovery Efficiency

摘　　要：缝洞型碳酸盐岩油藏的储层非均质性强、流体分布复杂,产能预测相关参数往往难以获取,为单井产能准确预测带来较大困难。通过对常见的地震参数进行优选,提出了一种单井产能预测新方法。基于建立基质-裂缝-溶洞三重介质模型,利用Spearman和Pearson相关系数法优选出影响单井产能的地震参数,进而建立优选地震参数与窜流系数和弹性储容比的关系式,将其引入三重介质产能方程中,从而对不同地质背景下的缝洞型碳酸盐岩油藏单井产能进行预测。以新疆某缝洞型碳酸盐岩油藏实际生产数据及前期测试资料为基础,利用新方法对断裂区、暗河区、明河区及复合岩溶区4个区域134口油井进行产能预测和误差分析,结果表明:该方法对暗河区油井产能预测精度最高,可达87%;对明河区和复合岩溶区预测精度较低,为80%;同时,该方法的平均预测精度为83%,高于多元线性回归、BP神经网络、支持向量机等方法的预测结果。新方法充分利用已有地震资料,进一步提高了产能预测精度,为复杂缝洞型碳酸盐岩油藏产能预测提供了新思路。Fracture-cavity carbonate reservoirs have strong heterogeneity and complex fluid distribution.It is often difficult to obtain parameters related to productivity prediction by conventional methods,which brings a great challenge for accurately predicting the single well productivity.This paper proposes a new method for predicting the single well productivity by selecting optimized common seismic parameters.After establishing a matrix-fracture-cave triple medium model,this paper optimizes seismic parameters affecting the single well productivity by Spearman and Pearson method,establishes the relationships between the optimized seismic parameters and the interporosity flow coefficient and storativity ratio,and introduces it into the triple medium productivity equation to predict the single well productivity of the reservoirs with different geological conditions.Based on the actual production data and preliminary test data of a fracture-cavity carbonate reservoir in Xinjiang,this paper uses the new method to predict the productivity of 134 oil wells in four areas(fault areas,underground river areas,aground river areas,and composite karst areas)and analyze errors.The results show that this method has the highest accuracy in predicting the productivity of oil wells in underground river areas,up to 87%,and for oil wells in aground river areas and composite karst areas,the prediction accuracy is low and is about 80%.The average prediction accuracy of this method is 83%,which is higher than those of multiple linear regression,BP neural network,and support vector machine.The new method makes full use of the existing seismic data,further improves the productivity prediction accuracy,and provides a new idea for predicting the productivity of complex fracture-cavity carbonate reservoirs.

关 键 词：缝洞型碳酸盐岩油藏 单井产能预测 三重介质模型 三维地震参数 岩溶区 

分 类 号：TE344[石油与天然气工程—油气田开发工程]