岩石三轴抗压强度是表征地层抗钻性质的重要参数之一,是PDC钻头优选的基础和主要依据。利用测井资料获取地层岩石三轴抗压强度并进行聚类分层处理,建立了PDC钻头切削结构参数与岩石三轴抗压强度之间的定量关系,提出了基于岩石三轴抗压...岩石三轴抗压强度是表征地层抗钻性质的重要参数之一,是PDC钻头优选的基础和主要依据。利用测井资料获取地层岩石三轴抗压强度并进行聚类分层处理,建立了PDC钻头切削结构参数与岩石三轴抗压强度之间的定量关系,提出了基于岩石三轴抗压强度的PDC钻头优选方法。通过实例计算得出了311.2 mm PDC钻头切削结构参数设计结果。该方法可为现场PDC钻头优选提供必要的理论依据,具有一定的实用性。展开更多
Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented b...Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented both norm smoothing and curvature smoothing methods for NMR T2 inversion, and compared the inversion results with respect to the optimal regular- ization parameters （（Xopt） which were selected by the dis- crepancy principle （DP）, generalized cross-validation （GCV）, S-curve, L-curve, and the slope of L-curve methods, respectively. The numerical results indicate that the DP method can lead to an oscillating or oversmoothed solution which is caused by an inaccurately estimated noise level. The （Xopt selected by the L-curve method is occa- sionally small or large which causes an undersmoothed or oversmoothed T2 distribution. The inversion results from GCV, S-curve and the slope of L-curve methods show satisfying inversion results. The slope of the L-curve method with less computation is more suitable for NMR T2 inversion. The inverted T2 distribution from norm smoothing is better than that from curvature smoothing when the noise level is high.展开更多
This paper proposes a novel recursive partitioning method based on constrained learning neural networks to find an arbitrary number (less than the order of the polynomial) of (real or complex) roots of arbitrary polyn...This paper proposes a novel recursive partitioning method based on constrained learning neural networks to find an arbitrary number (less than the order of the polynomial) of (real or complex) roots of arbitrary polynomials. Moreover, this paper also gives a BP network constrained learning algorithm (CLA) used in root-finders based on the constrained relations between the roots and the coefficients of polynomials. At the same time, an adaptive selection method for the parameter d P with the CLA is also given. The experimental results demonstrate that this method can more rapidly and effectively obtain the roots of arbitrary high order polynomials with higher precision than traditional root-finding approaches.展开更多
文摘岩石三轴抗压强度是表征地层抗钻性质的重要参数之一,是PDC钻头优选的基础和主要依据。利用测井资料获取地层岩石三轴抗压强度并进行聚类分层处理,建立了PDC钻头切削结构参数与岩石三轴抗压强度之间的定量关系,提出了基于岩石三轴抗压强度的PDC钻头优选方法。通过实例计算得出了311.2 mm PDC钻头切削结构参数设计结果。该方法可为现场PDC钻头优选提供必要的理论依据,具有一定的实用性。
基金funded by Shell International Exploration and Production Inc.(PT45371)the National Natural Science Foundation of China-China National Petroleum Corporation Petrochemical Engineering United Fund(U1262114)the National Natural Science Foundation of China(41272163)
文摘Nuclear Magnetic inversion is the basis of NMR Resonance （NMR） T2 logging interpretation. The regularization parameter selection of the penalty term directly influences the NMR T2 inversion result. We implemented both norm smoothing and curvature smoothing methods for NMR T2 inversion, and compared the inversion results with respect to the optimal regular- ization parameters （（Xopt） which were selected by the dis- crepancy principle （DP）, generalized cross-validation （GCV）, S-curve, L-curve, and the slope of L-curve methods, respectively. The numerical results indicate that the DP method can lead to an oscillating or oversmoothed solution which is caused by an inaccurately estimated noise level. The （Xopt selected by the L-curve method is occa- sionally small or large which causes an undersmoothed or oversmoothed T2 distribution. The inversion results from GCV, S-curve and the slope of L-curve methods show satisfying inversion results. The slope of the L-curve method with less computation is more suitable for NMR T2 inversion. The inverted T2 distribution from norm smoothing is better than that from curvature smoothing when the noise level is high.
文摘This paper proposes a novel recursive partitioning method based on constrained learning neural networks to find an arbitrary number (less than the order of the polynomial) of (real or complex) roots of arbitrary polynomials. Moreover, this paper also gives a BP network constrained learning algorithm (CLA) used in root-finders based on the constrained relations between the roots and the coefficients of polynomials. At the same time, an adaptive selection method for the parameter d P with the CLA is also given. The experimental results demonstrate that this method can more rapidly and effectively obtain the roots of arbitrary high order polynomials with higher precision than traditional root-finding approaches.
