利用核测井资料预测海相页岩储集层总有机碳含量

Predicting Total Organic Carbon Content in Marine Shale Reservoirs With Nuclear Logging Data

总有机碳含量是反映页岩储集层资源量的重要参数,而核测井包含着大量烃源岩有机质丰度的信息。分析川东南地区X1井、X2井和X3井的核测井曲线响应值与总有机碳含量的相关关系,并从影响总有机碳含量的地质因素出发,选出对总有机碳含量敏感的核测井曲线和能够反映总有机碳含量地质成因的核测井曲线组合参数。通过BP神经网络建立适用于该地区的总有机碳含量核测井曲线预测模型,预测川东南地区X4井的总有机碳含量,预测结果与113块岩心分析结果的平均相对误差为0.41,模型预测精度较高,能满足该地区生产需求。将该模型应用到川南地区威远区块和永川区块的海相页岩储集层,均取得较好的效果,证明该预测模型可操作性强、通用性较好、评价精度较高,为海相页岩储集层总有机碳含量评价提供了有效的技术手段。

Total organic carbon(TOC)content is an important parameter reflecting the amount of shale reservoir resources,and nuclear logging data can provide a lot of information about the abundance of organic matter in source rocks.In this paper,the correlations between the response values of various nuclear logging curves and TOC in the wells X1,X2 and X3 in the southeastern Sichuan basin are analyzed.Con-sidering the geological factors that affect the content of TOC,the single nuclear logging curve which is sensitive to TOC content and the combination of the nuclear logging curves that can reflect the genesis of TOC are selected.Then a TOC content prediction model with nuclear logging curves suitable for this area is established through BP neural network.Finally,the model was applied to Well X4 in the southeastern Sichuan basin.Compared with the TOC contents obtained from the core analysis of 113 core samples,the mean relative error of the model prediction results is 0.41,indicating that the prediction accuracy of the new model is high,which can meet the actual production demands in the area.Then the model was applied to the marine shale reservoirs in W and Y blocks of the southern Sichuan basin and good effects have been gained,which can prove the good operability,wide versatility and high evaluation accuracy of the model.The new method provides an effective technological mean for the evaluation of total organic carbon content in marine shale reservoirs.