LEACH routing protocol equalizes the energy consumption of the network by randomly selecting cluster head nodes in a loop, which will lead to the defect of unstable network operation. Therefore, in order to solve this problem, it is necessary to reduce the energy consumption of data transmission in the routing protocol and increase the network life cycle. However, there is also a problem that cluster heads count with a wide range and the cluster head forwarding data consumed greatly power in the LEACH, which remains to be solved. In this paper, we put forward an approach to optimize the routing protocol. Firstly, the optimal number of cluster head is calculated according to the overall energy consumption per round to reduce the probability of excessive cluster head distribution. Then, the cluster head is used as the core to construct the Voronoi Diagram. The nodes in the same Voronoi diagram become a cluster, that the energy consumption communication in intra-cluster would be less. Finally, in order to optimize the multi-hop routing protocol, an ant colony algorithm is added using a cluster head near the BS to receive and forward it from a remote cluster head. According to the MATLAB simulation data, the protocol can significantly prolong the lifetime of WSNs compared with the LEACH protocol and increase the energy efficiency per unit node in per round. Energy consumption of the proposed approach is only. The approach improved the First Node Death (FND) time by 127%, 22.2%, and 14.5% over LEACH, LEACH-C, and SEP, respectively.
A novel corrosion inhibitor, hexamethylenetetramine quaternary ammonium salt, is synthesized using hexamethylenetetramine (HMTA) and bromohexane as main reactants. The inhibitive action of HQAS on QT800-2 steel in hydrochloric acid medium is evaluated by weight-loss method, electrochemical method, and quantum chemical calculation. The obtained results show that the efficiency of 0.5 wt% HQAS inhibitor in 30 wt.% HCl solution at 363 K is 92.95% and HQAS can form an excellent synergistic effect with some additives. Polarization curves reveal that HQAS behaves as a mixed-type inhibitor with dominant anodic inhibition. Furthermore, the theoretical calculation verifies the relationship between the HQAS molecular structure and corrosion inhibition properties. K E Y W O R D Sacid inhibition, acid solutions, polarization, QT800-2 steel, quantum chemical calculation
Underground strata are reflected in various information sources in petroleum exploration, including good logging and drilling data. Real-time measurement parameters obtained from mud logging can provide data support for the early discovery of oil and gas resources and the prevention of safety accidents. It plays a forward-looking role in the drilling process. In this paper, we aim at the defection of fuzzy and random characteristics of the big data of drilling element parameters in the current drilling process. A new method named grey wolf optimization-support vector machine (GWO-SVM) is proposed by analyzing the relationship between logging data and formation to solve the serious problem of formation misjudgment. Using element content and Gamma-ray value, data mining is performed by a large number of real-time data obtained from the drilling site. The obtained information is used for comprehensive estimation and prediction of strata. First, the data is normalized, and then, the best ζ and σ values are found through the optimization of gray wolf algorithm, next the SVM training is carried out, finally, the formation prediction model is established, and the error analysis of the results was conducted. In the paper, the algorithm model is subsequently applied to three actual wells. The GWO-SVM model based on drilling data is used to predict the formation, and the error analysis showed that the error range of the GWO-SVM algorithm is within 10%. Compared with the GWO-SVM, the model accuracy of SVM, Particle Swarm Optimization-Support Vector Machine (PSO-SVM) algorithm is lower 53% and 23%, respectively. The GWO-SVM has higher robustness, reliability, and achieves faster convergence speed, stronger generalization effect, and improves the identification accuracy of elements for the formation. The average accuracy of the GWO-SVM in stratum dynamic identification is 93.5%. This model is implemented to support the logging system to improve application strength.INDEX TERMS Data mining, element logging, error analysis, gray wolf algorithm, support vector machine. I. INTRODUCTIONData mining includes 8 processes, such as data cleaning, data transformation, data mining process, pattern evaluation, and knowledge representation [1]. Data mining can acquire useful analytical information by the selection of appropriate analytical tools, using of statistical methods, rule reasoning, fuzzy sets, genetic algorithms and other methods to handle information. The four main data mining tasks include modeling prediction, association analysis, clustering analysis, anomaly detection. Among the classification methods used to predict discrete target variables, the nature-inspired optimizationThe associate editor coordinating the review of this manuscript and approving it for publication was Patrick Hung.
The existing plugging removal operation in JZ9-3 oilfield has the disadvantages of small amount of plugging remover, fast injection speed, and short construction time. Under the condition of injection well suction profile reversal, plugging remover is difficult to enter the low permeability part and play the role of deep plugging removal. In order to improve the plugging removal effect, this paper used the physical simulation method to carry out the experimental study and mechanism analysis on the effect of water flooding, chemical flooding, and plugging removal measures of the multi-layer system combination model. The results showed that the recovery of general plugging removal after chemical flooding increases by only 0.70%, while the recovery of ‘profile control + plugging removal’ increases by ‘9.34% + 2.59%’, and the amount of produced liquid decreases by more than 40%. It can be seen that the combined operation of profile control and plugging removal has dual effects of plugging and dredging and synergistic effect, which not only expands the swept volume, but also reduces the inefficient and ineffective cycles. On this basis, the optimization design and effect prediction of the target well W4-2 plugging removal scheme were carried out by using the numerical simulation method. Recommended scheme: inorganic gel profile control agent volume 13,243.6 m3, produced by the main agent (Na2O·nSiO2), isolation fluid (Water), and auxiliary agent (CaCl2) through multiple rounds of alternating injection into the reservoir. The plug removal agent (K2S2O8) injection volume is 100 m3, the concentration is 0.8%. The post-implementation ‘Output/Input’ ratio is expected to be 3.7.
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