科研之友
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摘要
The Chicontepec Formation is a complex and heterogeneous calcitric-lithic sandstone reservoir with significant historical problems of borehole collapse. To predict and mitigate the subsurface issues, it is essential to characterize the formation rock strength. This paper presents two new correlations for predicting the unconfined compressive strength (UCS) of turbidite sandstones in the Chicontepec Formation based on a function of transit time, grain diameter, and Young's modulus. Extensive laboratory tests, wireline and logging-while-drilling data (LWD), and borehole images from 24 offset wells were used to develop the new UCS correlations. A small dispersion of the data was identified using grain size and transit time, and this new model presented a median value (P-50) of 76 MPa, a P-10 of 55 MPa, and a P-90 of 89 MPa. This paper also demonstrates the use of an artificial neural network (ANN) to capture the nonlinear interaction of the UCS model with the complex lithological lateral variations of the Chicontepec Basin by using the new correlation of grain size and transit time, and a regression analysis to build a three-dimensional (3D) UCS model to understand the vertical and lateral heterogeneity. The prediction of the UCS using the ANN yielded a highly reliable prediction; the coefficient of determination (R-2) was 0.95 compared with the multiple regression analysis (R-2), which was 0.88. The results show that the prediction performance of the ANN models is higher than the multiple regression models. The results also indicate that the UCS varies between 27.57 until 89.63 MPa.
- 出版日期2018-8
