How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle co...How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.展开更多
In the present paper, the authors compared the therapeutic effects of acu moxibustion and medication in the treatment of 80 cases of aorto arteritis and observed their effects on blood rheology of the limbs. Results s...In the present paper, the authors compared the therapeutic effects of acu moxibustion and medication in the treatment of 80 cases of aorto arteritis and observed their effects on blood rheology of the limbs. Results showed that in acu moxibustion group (n=40) and medication group (n=40), the cure rates were 15% and 0, the markedly effective rates 62.5% and 12.5%, and the total effective rates 95% and 75% respectively. The therapeutic effect of acu moxibustion group was significantly superior to that of medication group (P<0.01). Following acu moxibustion treatment, the blood pressure and blood flow velocity of the brachial artery, the amplitude of the air volume wave of the wrist and the amplitude of the digital volume pulse wave increased remarkably compared with pre treatment (P<0.01), and after treatment with medication, only the blood velocity of brachial artery increased evidently in comparison with pre treatment (P<0.05). Comparison between two groups showed that values of the 4 indexes of acu moxibustion group were all significantly higher than those of medication group (P<0.01), displaying that the therapeutic effect of acu moxibustion is superior to that of medication. It provides experimental evidence for clinical effective treatment of aorto arteritis (branchiocephalic artery type) with acupuncture and moxibustion.展开更多
基金National Key Science & Technology Special Projects(Grant No.2008ZX05000-004)CNPC Projects(Grant No.2008E-0610-10).
文摘How to extract optimal composite attributes from a variety of conventional seismic attributes to detect reservoir features is a reservoir predication key,which is usually solved by reducing dimensionality.Principle component analysis（PCA） is the most widely-used linear dimensionality reduction method at present.However,the relationships between seismic attributes and reservoir features are non-linear,so seismic attribute dimensionality reduction based on linear transforms can＇t solve non-linear problems well,reducing reservoir prediction precision.As a new non-linear learning method,manifold learning supplies a new method for seismic attribute analysis.It can discover the intrinsic features and rules hidden in the data by computing low-dimensional,neighborhood-preserving embeddings of high-dimensional inputs.In this paper,we try to extract seismic attributes using locally linear embedding（LLE）,realizing inter-horizon attributes dimensionality reduction of 3D seismic data first and discuss the optimization of its key parameters.Combining model analysis and case studies,we compare the dimensionality reduction and clustering effects of LLE and PCA,both of which indicate that LLE can retain the intrinsic structure of the inputs.The composite attributes and clustering results based on LLE better characterize the distribution of sedimentary facies,reservoir,and even reservoir fluids.
文摘In the present paper, the authors compared the therapeutic effects of acu moxibustion and medication in the treatment of 80 cases of aorto arteritis and observed their effects on blood rheology of the limbs. Results showed that in acu moxibustion group (n=40) and medication group (n=40), the cure rates were 15% and 0, the markedly effective rates 62.5% and 12.5%, and the total effective rates 95% and 75% respectively. The therapeutic effect of acu moxibustion group was significantly superior to that of medication group (P<0.01). Following acu moxibustion treatment, the blood pressure and blood flow velocity of the brachial artery, the amplitude of the air volume wave of the wrist and the amplitude of the digital volume pulse wave increased remarkably compared with pre treatment (P<0.01), and after treatment with medication, only the blood velocity of brachial artery increased evidently in comparison with pre treatment (P<0.05). Comparison between two groups showed that values of the 4 indexes of acu moxibustion group were all significantly higher than those of medication group (P<0.01), displaying that the therapeutic effect of acu moxibustion is superior to that of medication. It provides experimental evidence for clinical effective treatment of aorto arteritis (branchiocephalic artery type) with acupuncture and moxibustion.
