After the water flooding sandstone oilfield entering the ultra-high water-cut developing phase, the remaining oil distribution has become increasingly fragmented, how to quantitative distinguish the remaining oil potential is the key to influence oilfield development, using multilevel fuzzy comprehensive evaluation mathematics method, comprehensive analyzed the classification reservoir’s producing conditions during the ultra-high water-cut developing phase, established a quantitative evaluation method from geological and develop factors, solved the problem of analyzing remaining oil in deferent kinds of reservoirs, realized the quantitative characterization of remaining oil in the ultra-high water-cut oilfield.

White noise deconvolution or input white noise estimation has a wide range of applications including oil seismic exploration, communication, signal processing, and state estimation. A globally optimal weighted fusion white noise deconvolution estimator is presented for the multisensor linear discrete systems using the Kalman filtering method. It is derived from the centralized fusion white noise deconvolution estimator so that it is identical to the centralized fuser, i.e. it has the global optimality. Compared with the existing globally suboptimal distributed fusion white noise estimators, the proposed white noise fuser is given based on the local Kalman predictors, and the computation of complex covariance matrices is avoided. A simulation for the Bernoulli-Gaussian input white noise shows the effectiveness of the proposed results.

In order to make strategic, tactical and operational decisions for the shortest path in an uncertain environment. Firstly, the information transmission time expectation-variance shortest path model in uncertain environment is proposed. Secondly, to avoid the interruption of information transmission caused by sudden situations, a fuzzy shortest path critical edge model is established. Then, an improved ant colony algorithm with traffic congestion factor and random variables is developed. Finally, to assess the performance of Improved ant colony algorithm, experiments on a set of 6 benchmark test functions are conducted, and numerical examples of these models are given to illustrate its effectiveness. INDEX TERMS Uncertain environment, shortest path problem, critical edge model, algorithm, benchmark test functions, numerical examples.

For the multisensor multichannel ARMA signal with ARMA colored measurement noises and unknown model parameters and noise variances, this paper presents a kind of multi-stage identification method. At the first stage, the on-line information fusion estimator for the unknown model parameters is presented based on the Recursive Instrumental Variable (RIV) algorithm and the Recursive Extended Least Squares (RELS) algorithm, which is realized by computing the average of local estimators for model parameter. At the second stage, the on-line information fusion estimator for the unknown variances is obtained using the correlation method, which is realized by computing the average of the local estimators for noise variances. At the third stage, the information fusion parameter estimator of MA model is presented using the correlation method and the dead zone Gevers-Wouters and LS algorithms.

In order to quantitatively identify critical hidden damage for weld joints by using the metal magnetic memory technology (MMM), the modified maximum likelihood estimation MMM model is first proposed. The experimental materials are Q235B welded plate specimens. Fatigue tension experiments were operated to find the MMM feature laws of critical hidden damage by comparing with synchronous X-ray detection results. Four MMM characteristic parameters, that is, ΔHp(y) , Kymax , mmax and S(K), are extracted corresponding to the normal state and the hidden damage state, respectively. The probability density values of ΔHp(y) , Kymax , mmax and S(K)are calculated by the optimized bandwidth kernel density estimation. The quantitative maximum likelihood estimation MMM model is established based on optimized bandwidth kernel density. The verification result shows the maximum likelihood value of hidden damage state is twice as much as that of the normal state, which is consistent with the practical results. This provides a new method for quantitative MMM identification of weld critical hidden damages.