基于储层类别构建核磁伪毛管压力曲线及产能预测技术

摘要

综合成本高昂是海上油气勘探的显著特点.因此,有效的利用核磁共振测井及常规测井系列进行储层评价及产能预测,为油公司决策层测试作业提供及时有效的决策依据,具有十分重要的现实意义.首先根据岩心毛管压力的类别进行储层分类,然后对每类储层采用分段非线性刻度转换方法由核磁共振测井T2谱构建伪毛管压力曲线.在此基础上结合常规测井、电缆武地层测试等测井资料,建立储层物性和孔隙结构参数计算模型.通过多元统计分析方法优选对比采油指数敏感的参数,最终建立适合于本地的储层自然产能预测模型并确定储层产能级别的评价标准.%Compared with land oil and gas exploration, integrated high cost of offshore oil and gas exploration is a notable feature. Therefore, the effective use of NMR logging to forecast productivity is of great practical significance when decision-makers of oil companies decided whether DST operations or not. Reservoir category can be classified from both core capillary pressure curves (Pc) and NMR T2 distribution. The non-linear method is adopted to transform T2 to Pseud-Pc for each reservoir category, then the rock pore structure parameters from the pseud-Pc and other physical properties from conventional log and formation pressure test can be incorporate into the productivity forecast model by multi-variables statistical analysis. This regional productivity forecast model can be used to classify the reservoir natural productivity level.