The capability of accurately predicting mineralogical brittleness index(BI)from basic suites of well logs is desir-able as it provides a useful indicator of the fracability of tight formations.Measuring mineralogical components in rocks is expensive and time consuming.However,the basic well log curves are not well correlated with BI so correlation-based,machine-learning methods are not able to derive highly accurate BI predictions using such data.A correlation-free,optimized data-matching algorithm is configured to predict BI on a supervised basis from well log and core data available from two published wells in the Lower Barnett Shale Formation(Texas).This transparent open box(TOB)algorithm matches data records by calculating the sum of squared errors be-tween their variables and selecting the best matches as those with the minimum squared errors.It then applies optimizers to adjust weights applied to individual variable errors to minimize the root mean square error(RMSE)between calculated and predicted(BI).The prediction accuracy achieved by TOB using just five well logs(Gr,pb,Ns,Rs,Dt)to predict BI is dependent on the density of data records sampled.At a sampling density of about one sample per 0.5 ft BI is predicted with RMSE~0.056 and R2~0.790.At a sampling density of about one sample per 0.1 ft BI is predicted with RMSE~0.008 and R2~0.995.Adding a stratigraphic height index as an additional(sixth)input variable method improves BI prediction accuracy to RMSE~0.003 and R2~0.999 for the two wells with only 1 record in 10,000 yielding a BI prediction error of>±0.1.The model has the potential to be applied in an unsupervised basis to predict BI from basic well log data in surrounding wells lacking mineralogical measure-ments but with similar lithofacies and burial histories.The method could also be extended to predict elastic rock properties in and seismic attributes from wells and seismic data to improve the precision of brittleness index and fracability mapping spatially. 相似文献
The correlations between three different methods of measuring brittleness and both drillability and borability were statistically investigated using the raw data obtained from the experimental works of different researchers.
Strong exponential relationships between the penetration rates of tunnel boring machine (TBM) and the brittleness of B1 (the ratio of compressive strength to tensile strength) and B2 (the ratio of compressive strength minus tensile strength to compressive strength plus tensile strength) were found. There is no correlation between the penetration rates of the diamond drilling tool and the brittleness values. Strong exponential correlations exist between the penetration rates of rotary drills and the brittleness of B1 and B2. However, no correlation between the penetration rate of rotary drills and the brittleness of B3 (the product of percentage of fines in impact strength test and compressive strength) was found. The penetration rate of percussive drills does not exhibit a correlation with the brittleness of B1 and B2, but the penetration rate of percussive drills is strongly correlated with the brittleness of B3.
It was concluded that each method of measuring brittleness has its usage in rock excavation depending on practical utility. 相似文献