川东南地区海相页岩气层TOC含量多参数融合预测

A comprehensive prediction of multiple parameters of TOC in marine gas shale,southeastern Sichuan Basin,China

探讨川东南地区海相页岩总有机碳(TOC)含量的关联参数以及更准确的预测方法。利用已钻井处实测TOC含量与各类地震敏感参数进行交会分析,选取相关度较高的参数,分别进行单参数拟合;再进行多参数综合拟合,获得综合预测公式;最后通过地震反演获得相应数据体,并得到全区预测结果。结果表明密度、自然伽马、弹性模量、切变模量与TOC含量具有较高的相关度,通过叠前反演获得的数据体稳定、可靠,在已钻井处TOC含量预测结果与实测值相关性可达到0.95,且整体结果符合该地区沉积地质理论。多参数预测能有效提高预测准确度,二次拟合方法和叠前反演技术为预测TOC含量奠定了良好的基础。

In the study of shale oil and gas reservoirs,the total organic carbon content(TOC)is one of the important indexes to evaluate the hydrocarbon generation capability.Based on the TOC values and seismic sensitive parameters from a certain drilling well in southeastern Sichuan Basin,the parameters of high correlation are obtained with the seismic susceptibility parameters related to physical and gas bearing characteristics by intersection analysis,including density,natural gamma,shear modulus,Young's modulus.Linear curve fitting method is used for density and natural gamma parameters,and the exponential curve fitting method is adopted for the shear modulus and Young's modulus parameters.Then,four fitting formulas for the relevant parameters are obtained.Subsequently,the quadratic fitting for the four fitted parametric equations is used to build the comprehensive prediction formula.Hence,a bridge crossing over seismic sensitive parameters and TOC is established.Based on the density,Young's modulus and shear modulus parameters acquired by inversion of the pre-stack elasticity parameters,the natural gamma ray can be calculated directly by the extended pre-stackelastic impedance inversion.With pre-stack data,the inversion accuracy increased significantly.Finally,the prediction results of the TOC content in the region are deduced by fitting the formula and it shows that the correlation between the predicted results and the measured TOC content reaches 0.95 at the location of proven drilling well.In addition,the overall distribution satisfies the geological regulation of the Sichuan Basin.The method demonstrates its feasibility and generalizability.