基于随钻岩石热解参数的原油密度预测模型

Crude oil density predictive models based on rock pyrolysis parameters while drilling

原油性质的准确判断对试油方式的优选具有指导性作用,在流体相较为复杂的渤海油田,目前测井、录井均缺乏有效评价手段。为了合理有效地预测井场随钻储层的原油密度,根据岩样的岩石热解参数与油样实测原油密度的散点关系,基于最小二乘法的多元线性回归分析方法,通过建立岩样的岩石热解参数与原油密度的预测模型,实现了原油密度预测。应用该模型已完成渤海油田61口井616个数据点的原油密度预测工作,其中完成测试的共12口井139个数据点,预测密度误差在±0.01 g/cm^(3)之内的共129个点,符合率达到92.80%。采用多元线性回归方法建立的模型进行原油密度预测,具有广泛的应用前景。

The accurate judgment of crude oil properties has a guiding effect in the optimization of oil testing mode.In Bohai Oilfield with relatively complex fluid phase,well logging and mud logging lack effective evaluation means.In order to reasonably and effectively predict the oil densities of reservoirs while drilling at the well site,according to the scatter relationship between the rock pyrolysis parameters of the rock samples and the measured crude oil densities of the oil samples,the multiple linear regression analytical approach based on the least squares method has achieved the prediction of crude oil density by building the predictive models for rock pyrolysis parameters of rock samples and crude oil densities.The models have been applied to predict crude oil densities for 616 data points from 61 wells in Bohai Oilfield,among which 139 data points from 12 wells were tested.A total of 129 points had the predictive density errors within±0.01 g/cm^(3),and the coincidence rate reached 92.80%.The models built by multiple linear regression method have a wide application prospect for crude oil density prediction.