盐池地区延长组长8段致密油储层脆性指数测井评价

Logging evaluation of brittleness index of tight oil sandstone in Chang 8 member of Yanchang Formation in Yanchi area

致密砂岩油气通常需要通过压裂等技术措施方可获得工业产量,而脆性指数是评价储层可压裂性的重要参数,对致密油储层勘探开发甜点优选至关重要。以鄂尔多斯盆地盐池地区三叠系延长组长8段为例,针对致密砂岩储层脆性指数测井评价方法开展系统研究。首先,利用阵列声波测井、岩石声波特性室内实验测试资料,通过求取杨氏模量、泊松比等岩石弹性力学参数,定量计算长8段脆性指数;随后,将利用阵列声波测井资料计算的脆性指数作为目标值,寻找其与自然伽马、横波时差等常规测井资料之间的对应关系;在此基础上,建立基于岩石脆性指数测井预测模型;最后,通过多元回归,全面提取常规测井信息,建立基于常规测井资料的脆性指数多元函数评价模型。根据研究区内单井实例,测井预测脆性指数与岩石声波特性实验测试结果匹配良好,对于脆性指数定量预测,基于岩性指数模型的拟合优度为0.733,基于物性指数模型的拟合优度为0.719,基于多元回归模型的拟合优度为0.789。通过实例验证,脆性指数预测值与实测值变化趋势一致,相关性明显,相关系数达0.936。

Tight sandstone hydrocarbon resources usually need technical measures such as fracturing to obtain industrial production,and brittleness is a parameter for formation fracturing analysis,which is important for the selection of sweet spot in exploration and development of tight oil reservoir.Taking Chang 8 member of Yanchi Formation of Triassic in Ordos Basin as an example,the logging evaluation method of brittleness index is carried out.Firstly,based on the array acoustic logging data and the experimental test data of rock acoustic characteristics,the brittleness index is calculated by the rock elastic parameters such as Young's modulus and Poisson's ratio.Then,the calculatedbrittleness index is taken as the target value to find the corresponding relationship between it and conventional logging data such as gamma ray logging and acoustic logging.On this basis,a logging prediction model based on rock brittleness index is established.Finally,through multiple regression,the conventional logging information is extracted,and the multiple function evaluation model of brittleness index based on conventional logging data is established.According to the example of single wells,the brittleness index predicted by logging is well matched with the experimental results.For quantitative prediction of brittleness index,the goodness of fit based on lithology index model,physical property index model and multiple regression model is 0.733,0.719 and 0.789 respectively,and the correlation is obvious,with a correlation coefficient of 0.936.