Flow pattern identification in oil wells by electromagnetic image logging

Petroleum production logging needs to determine the interpretation models first and flow pattern identification is the foundation, but traditional flow pattern identification methods have some limitations. In this paper, a new method of flow pattern identification in oil wells by electromagnetic image logging is proposed. First, the characteristics of gas-water and oil-water flow patterns in horizontal and vertical wellbores are picked up. Then, the continuous variation of the two phase flow pattern in the vertical and horizontal pipe space is discretized into continuous fluid distribution models in the pipeline section. Second, the electromagnetic flow image measurement responses of all the eight fluid distribution models are simulated and the characteristic vector of each response is analyzed in order to distinguish the fluid distribution models. Third, the time domain changes of the fluid distribution models in the pipeline section are used to identify the flow pattern. Finally, flow simulation experiments using electromagnetic flow image logging are operated and the experimental and simulated data are compared. The results show that the method can be used for flow pattern identification of actual electromagnetic image logging data.

A new damping ratio identification method based on pattern search

In order to improve the effectiveness of traditional time domain identification methods in identifying damping ratios, a new damping ratio identification method based on pattern search is proposed by fluctuating the reliable natural frequency obtained through traditional time domain identification methods by about 10% to build the boundary conditions, using all the initial identification results to establish the free decay response of the system, and using the pattern search method to correct the initial identification results with the residual sum of squares between the free decay response and the actually measured free-decay signal as the objective function. The proposed method deals with the actually measured free-decay signal with curve fitting and avoids enlarging the identified error caused by intermediate conversion, so it can effectively improve the identified accuracy of damping ratios. Simulations for a room-sized vibration isolation foundation show that the relative errors of analyzed three damping ratios are down to 1.05%, 1.51% and 3.7% by the proposed method from 8.42%, 5.85% and 8.5% by STD method when the noise level is 10%.

Analysis on the traditional Chinese medicine syndromes and Six-Meridian Pattern Identification of coronavirus disease 2019

Zhongjing Zhang’s Shang Han Lun(Treatise on Cold-induced Diseases,an ancient Chinese medical book written by Zhongjing Zhang in the Eastern Han Dynasty)was pioneering to conduct the Six-Meridian Pattern Identification,which provided later generations with a theoretical basis for the treatment of Exogenous Febrile Diseases.The coronavirus disease 2019 belongs to the category of“Pestilence”(the general term for virulent infectious epidemic diseases)in“Febrile Diseases”(the general term for acute externally contracted diseases caused by Warm Pathogens,with fever as the chief manifestation,also known as Warm Diseases)and the treatment of coronavirus disease 2019 is mostly based on the Triple Energizer Pattern Identification(the a categorization of Pattern Identification according to the theory of the Triple Energizer)or Defense,Qi,Nutrient and Blood Pattern Identification(the categorization of Febrile Diseases Pattern Identification according to the theory of Defense,Qi,Nutrient and Blood which indicates the stages of the clinical course with corresponding pathological changes).Although the theory of Cold-induced Diseases(the condition caused by Cold,manifested as chills and fever,absence of sweating,headache and floating-tense pulse)and the theory of Febrile Disease seem to be entirely distinct with each other,Zhongjing Zhang’s theory contained Triple Energizer Pattern Identification or Defense,Qi,Nutrient and Blood Pattern Identification,and Triple Energizer Pattern Identification or Defense Qi,Nutrient and Blood Pattern Identification also contained Zhongjing Zhang’s Six-Meridian Pattern Identification(the categorization of Pattern Identification according to the theory of the Six Meridians,applied to the diagnosis of acute Febrile Diseases at different stages,and also useful for the Pattern Identification of other diseases).The basic principles and therapeutic methods of Cold-induced Diseases and Febrile Diseases are intertwined.Therefore,this paper will combine the two theories to analyze the traditional Chinese medicine syndromes of coronavirus disease 2019,and try to use Six-Meridian Pattern Identification to guide the treatment of this disease.

IDENTIFICATION AND SIMULATION OF X-RAY POWDER DIFFRACTION PATTERN

A new method for pattern identification and simulation of X-ray powder diffraction data is described, which can give definite phase composition of the unknown rapidly and correctly. The method is implemented in Microsoft Fortran 77 for the IBM PC/XT/AT personal computer or their compatibles.

An adaptive electrical resistance tomography sensor with flow pattern recognition capability

The all traditional electrical resistance tomography (ERT) sensors have a static structure, which cannot satisfy the intelligent requirements for adaptive optimization to ERT sensors that is subject to flow pattern changes during the real-time detection of two-phase flow. In view of this problem, an adaptive ERT sensor with a dynamic structure is proposed. The electrodes of the ERT sensor are arranged in an array structure, the flow pattern recognition technique is introduced into the ERT sensor design and accordingly an ERT flow pattern recognition method based on signal sparsity is proposed. This method uses the sparse representation of the signal to express the sampling voltage of the ERT system as a sparse combination and find its sparse solution to achieve the classification of different flow patterns. With the introduction of flow identification information, the sensor has an intelligent function of adaptively and dynamically adapting the sensor structure according to the real-time flow pattern change. The experimental results show that the sensor can automatically identify four typical flow patterns: core flow, bubble flow, laminar flow and circulation flow with recognition rates of 91%, 93%, 90% and 88% respectively. For different flow patterns, the dynamically optimized sensor can significantly improve the quality of ERT image reconstruction.

Gas monitoring data anomaly identification based on spatio-temporal correlativity analysis

Based on spatio-temporal correlativity analysis method, the automatic identification techniques for data anomaly monitoring of coal mining working face gas are presented. The asynchronous correlative characteristics of gas migration in working face airflow direction are qualitatively analyzed. The calculation method of asynchronous correlation delay step and the prediction and inversion formulas of gas concentration changing with time and space after gas emission in the air return roadway are provided. By calculating one hundred and fifty groups of gas sensors data series from a coal mine which have the theoretical correlativity, the correlative coefficient values range of eight kinds of data anomaly is obtained. Then the gas moni- toring data anomaly identification algorithm based on spatio-temporal correlativity analysis is accordingly presented. In order to improve the efficiency of analysis, the gas sensors code rules which can express the spatial topological relations are sug- gested. The experiments indicate that methods presented in this article can effectively compensate the defects of methods based on a single gas sensor monitoring data.

Reporting Children’s Development below the Test Floor: Looking Back and Forth to Describe Individual Strengths and Needs

The test floor effects seen in standardised tests lead to a standardised score of 1 or less with a flat profile that hides a child’s individual strengths and needs. The Griffiths III community of practitioners requested advice on the reporting of children’s development below the floor of the test, so that individual strengths and needs can be described. This paper reports the third phase of research following an earlier Scoping Review and a wider literature review. To confirm quality control, Phase 3 was conducted in a retrospective manner using the same methodology as the earlier phases but in a reverse direction. Peer reviewer comments and key elements from the Scoping Review and keywords from the publications were tabulated. Data analysis included a change of perspective to that of the child and their individual rights with respect to the literature themes already described in Phase 2. These confirmed that there is little specific guidance in the literature, but that computational advances for homogeneous populations and especially disaggregated data offer some solutions. A greater balance between broad biopsychosocial models and standardised models of assessment should be sought by practitioners together with the use of disaggregated data to highlight issues that pertain to individual subsets of results. This will ensure that the child’s right for their individual strengths and needs to be described together with a plan for management, may be met.

Monitoring Tool Wear States in Turning Based on Wavelet Analysis

To monitor the tool wear states in turning, a new way based on the wavelet transformation to get the signal characters, which can reflect the tool wear states, was proposed. Using discrete dyadic wavelet transform, the acoustic emission(AE) signal of cutting process was decomposed; the root mean square(RMS) values of the decomposed signals at different scales were taken as the feature vector; the technique of fuzzy pattern identification was used to real time monitor the tool wear states. Based on choosing the suitable standard samples, this method can correctly identify the tool wear states. Experiments showed that the technique based on wavelet analysis is suitable for real time implementation in manufacturing application.

Time-Frequency Signal Processing for Gas-Liquid Two Phase Flow Through a Horizontal Venturi Based on Adaptive Optimal-Kernel Theory

A time-frequency signal processing method for two-phase flow through a horizontal Venturi based on adaptive optimal-kernel （AOK） was presented in this paper.First,the collected dynamic differential pressure signal of gas-liquid two-phase flow was preprocessed,and then the AOK theory was used to analyze the dynamic differ-ential pressure signal.The mechanism of two-phase flow was discussed through the time-frequency spectrum.On the condition of steady water flow rate,with the increasing of gas flow rate,the flow pattern changes from bubbly flow to slug flow,then to plug flow,meanwhile,the energy distribution of signal fluctuations show significant change that energy transfer from 15-35 Hz band to 0-8 Hz band;moreover,when the flow pattern is slug flow,there are two wave peaks showed in the time-frequency spectrum.Finally,a number of characteristic variables were defined by using the time-frequency spectrum and the ridge of AOK.When the characteristic variables were visu-ally analyzed,the relationship between different combination of characteristic variables and flow patterns would be gotten.The results show that,this method can explain the law of flow in different flow patterns.And characteristic variables,defined by this method,can get a clear description of the flow information.This method provides a new way for the flow pattern identification,and the percentage of correct prediction is up to 91.11%.

The Diagnostic Criteria of Blood-Stasis Syndrome:Considerations for Standardization of Pattern Identification

Pattern identification （PI）, also called Bian Zheng （辨证）, syndrome differentiation, pattem diagnosis, or pattem classification, is the basic principle and the key concept of Chinese medicine （CM）. The core of PI is CM syndrome, on which CM theory, therapeutic method, prescribing formula and the use of Chinese herbal medicine are basically based. PI, in fact, is another classification method anticipated to improve the clinical efficacy. How to make an exact PI seems to be very important for taking full advantage of PI in clinical practice. Therefore, the establishment of diagnostic criterion of pattern has been the prerequisite for the standardization of PI. In recent years, a lot of diagnostic criteria of different CM patterns have been formulated. Taking the diagnostic criteria for blood-stasis syndrome as a model, the methodologies and considerations in establishing a pattern diagnostic criterion were discussed in this paper, which might be of great reference value in future PI standardization research.

Effect of Chinese Medicine Treatment Based on Pattern Identification on Cellular Immunophenotype of Myelodysplastic Syndrome

Objective： To observe the influence of treatment based on Chinese medicine pattem identification on cellular immunophenotype of the myelodysplastic syndrome （MDS）. Methods： Sixty patients with MDS were randomly and equally assigned to the treatment group and the control group using a randomized digital table. Thirty patients in each group included 3 risk levels （low, moderate and high risks） with each level 10 patients according to the international prognostic scoring system. The control group was given conventional therapy which was also used in the treatment group. While the treatment group was given Zuogui Pill （左归丸） and Yougui Pill （右归丸） for low risk patients; Qingwen Baidu Decoction （清瘟败毒饮） and Bazhen Decoction （八珍汤） for moderate risk patients; Gexia Zhuyu Decoction （膈下逐瘀汤） and Qinghao Biejia Decoction （青蒿鳖甲汤） combined with Shiquan Dabu Decoction （十全大补汤 ） for high risk patients. After the treatment, the differences of overatl response rate and immunophenotype （CD13, CD14, CD15, CD33 and CD34） of each group were analyzed. Results： The overall response rate of the treatment group was significantly higher than the control group in low risk and moderate risk patients （P=0.029）, there was no statistical differences of overall response rate between the treatment group and the control group in high risk patients （P=0.089）. The expressions of CD13, CD14, CD33 and CD34 in all three risk levels of the treatment group were obviously decreased after the treatment, while CD15 in all three risk levels of the treatment group was obviously increased after the treatment （P〈0.05 or P〈0.01）. Meanwhile, the difference values of CD13 and CD33 in low risk level of the treatment group, CD33 and CD34 in moderate risk level of the treatment group as well as CD34 and CD15 in high risk level of the treatment group, were all greater than the control groups and they were statistically significant （P〈0.05 or P〈0.01）. Conclusions： It shows a better therapeutic effect if the MDS patients treated with Chinese medicine pattern identification in addition to conventional therapy. Since the treatment may inhibit the malignant clones and improve the dysmaturity of granulocyte differentiation, it is a feasible option in clinical practice.

Incorporating Pattern Identification of Chinese Medicine into Precision Medicine:An Integrative Model for Individualized Medicine

On 20 January, 2015, U.S. President Obama announced an ambitious plan called ＂Precision Medicine （PM） Initiative＂, aiming to deliver genetics- based medical treatments. PM has shown a promising prospect by tailoring disease treatments and preventions to individuals. However, a predominantly genetics-based method restricts its benefit and applicability in most chronic and complex diseases. Pattern identification （PI） is one of the representative characteristics of Chinese medicine implying the concept of holism and individualized treatment. It is another classification method taking environmental, psychosocial and other individual factors into account. Integrating PI with disease diagnosis of Western medicine will provide a strong complement to genetics-based PM, thus establish an integrative model for individualized medicine. PI provides new perspectives for PM, not only in clinical practice, but also in new drug development and clinical trial design. It is for sure that the integrative approach will ultimately lead to a safer, more convenient and effective patient-centered healthcare and most patients will benefit in the era of PM.

Designing Clinical Studies That Take into Account Traditional East Asian Medicine's Systems and Methods-with Focus on Pattern Identification

This article is based on two presentations held at Chinese medicine conference in Rothenburg （2013）, Germany and at the 19th Anniversary of Korean Institute of Oriental Medicine （KIOM） International Symposium of Current Research Trends in Traditional Medicine - Pattern of Identification （2013）. In designing clinical studies, it is a research question that leads to appropriate study design. However, they are mostly diagnostic procedures and techniques that are the key points to reflect the application of systems and methods in all forms of medicine - traditional East Asian medicine （TEAM） is no exception. The challenges within TEAM based on research reflect in different systems of medicine/theories such as traditional Japanese acupuncture, traditional Korean acupuncture and traditional Chinese acupuncture. This diversitv of medical svstems and methods applied in East Asia seems to have beenfruitful within the different countries and traditional medicines have found their places within the respective countries health systems. The existing diversity, from a clinician＇s point of view, may be viewed as a treasure when dealing with patients in the ＇real world＇. On the other hand, this diversity seems to challenge the scientific mind worldwide, esoeciallv when it comes to research. Hence. there is a and between clinical practice and research.

Dynamic Visualization Approach of the Multiphase Flow Using Electrical Capacitance Tomography

Identifying the flow patterns is vital for understanding the complicated physical mechanisms in multiphase flows.For this purpose,electrical capacitance tomography(ECT) technique is considered as a promising visualization method for the flow pattern identification,in which image reconstruction algorithms play an important role.In this paper,a generalized dynamic reconstruction model,which integrates ECT measurement information and physical evolution information of the objects of interest,was presented.A generalized objective functional that simultaneously considers the spatial constraints,temporal constraints and dynamic evolution information of the objects of interest was proposed.Numerical simulations and experiments were implemented to evaluate the feasibility and efficiency of the proposed algorithm.For the cases considered in this paper,the proposed algorithm can well reconstruct the flow patterns,and the quality of the reconstructed images is improved,which indicates that the proposed algorithm is competent to reconstruct the flow patterns in the visualization of multiphase flows.

Standardization and Future Directions in Pattern Identification Research: International Brainstorming Session

An international brainstorming session on standardizing pattern identification（PI） was held at the Korea Institute of Oriental Medicine on October 1, 2013 in Daejeon, South Korea. This brainstorming session was convened to gather insights from international traditional East Asian medicine specialists regarding PI standardization. With eight presentations and discussion sessions, the meeting allowed participants to discuss research methods and diagnostic systems used in traditional medicine for PI. One speaker presented a talk titled ＂The diagnostic criteria for blood stasis syndrome： implications for standardization of PI＂. Four speakers presented on future strategies and objective measurement tools that could be used in PI research. Later, participants shared information and methodology for accurate diagnosis and PI. They also discussed the necessity for standardizing PI and methods for international collaborations in pattern research.

An artificial immune and incremental learning inspired novel framework for performance pattern identification of complex electromechanical systems

Performance pattern identification is the key basis for fault detection and condition prediction,which plays a major role in ensuring safety and reliability in complex electromechanical systems(CESs).However,there are a few problems related to the automatic and adaptive updating of an identification model.Aiming to solve the problem of identification model updating,a novel framework for performance pattern identification of the CESs based on the artificial immune systems and incremental learning is proposed in this paper to classify real-time monitoring data into different performance patterns.First,an unsupervised clustering technique is used to construct an initial identification model.Second,the artificial immune and outlier detection algorithms are applied to identify abnormal data and determine the type of immune response.Third,incremental learning is employed to trace the dynamic changes of patterns,and operations such as pattern insertion,pattern removal,and pattern revision are designed to realize automatic and adaptive updates of an identification model.The effectiveness of the proposed framework is demonstrated through experiments with the benchmark and actual pattern identification applications.As an unsupervised and self-adapting approach,the proposed framework inherits the preponderances of the conventional methods but overcomes some of their drawbacks because the retraining process is not required in perceiving the pattern changes.Therefore,this method can be flexibly and efficiently used for performance pattern identification of the CESs.Moreover,the proposed method provides a foundation for fault detection and condition prediction,and can be used in other engineering applications.

Experimental study of gas-water elongated bubble flow during production logging

In order to improve the interpretation of production log data on gas-water elongated bubble （EB） flow in horizontal wells, a multi-phase flow simulation device was set up to conduct a series of measurement experiments using air and tap water as test media, which were measured using a real production logging tool （PLT） string at different deviations and in different mixed flow states. By understanding the characteristics and mechanisms of gas-water EB flow in transparent experimental boreholes during production logging, combined with an analysis of the production log response characteristics and experimental production logging flow pattern maps, a method for flow pattern identification relying on log responses and a drift-flux model were proposed for gas-water EB flow. This model, built upon experimental data of EB flow, reveals physical mechanisms of gas-water EB flow during measurement processing. The coefficients it contains are the specific values under experimental conditions and with the PLT string used in our experiments. These coefficients also reveal the interference with original downhole flow patterns by the PLT string. Due to the representativeness that our simulated flow experiments and PLT string possess, the model coefficients can be applied as empirical values of logging interpretation model parameters directly to real production logging data interpretation, when the measurement circumstances and PLT strings are similar.

Perception of pattern identification in traditional medicine:a survey of Korean medical practitioners

OBJECTIVE: To survey assesses the perception of pattern identification(PI) diagnosis of Traditional Medicine(TM)by Korean medical doctors(KMDs).METHODS: A total of 14 485 KMDs affiliated with the Association of Korean Medicine were sent surveys via email, and 1646(11.1%) responded to the questionnaire on their perception of PI diagnosis.RESULTS: Of the 1646 respondents, more than ninety percent(1562, 94.9%) reported that they treated patients using PI.The most critical problem with PI diagnosis was the lack of objective diagnostic indicators(561, 34.1%). Ninety percent had issues diagnosing patients because of different diagnoses between KMDs(1491, 90.5%). The majority of respondents thought herbal medicine was most related to PI(1528, 92.8%). Half of the respondents answered that PI of Ba Gang was the most commonly used PI system. Participants reported that it was most important to study standardisation of PI diagnosis and to develop standardised PI diagnoses using the classification system of the Korean Standard Classification of Diseases. The foremost PI type that physicians thought should be included in standardisation and objectification of PI of TKM was the PIof Ba Gang.CONCLUSION: Our data suggest that we should focus on the standardisation of PI diagnosis and PI of Ba Gang in future research on PI diagnosis inTM.However, we cannot completely discount the possibility that a biased selection of subjects and a low response rate limit the generalisability of the findings.

Intelligent decision support system of operation-optimization in copper smelting converter

An artificial intelligence technique was applied to the optimization of flux adding systems and air blasting systems, the display of on line parameters, forecasting of mass and compositions of slag in the slagging period, optimization of cold material adding systems and air blasting systems, the display of on line parameters, and the forecasting of copper mass in the copper blow period in copper smelting converters. They were integrated to build the Intelligent Decision Support System of the Operation Optimization of Copper Smelting Converter(IDSSOOCSC), which is self learning and self adaptating. Development steps, monoblock structure and basic functions of the IDSSOOCSC were introduced. After it was applied in a copper smelting converter, every production quota was clearly improved after IDSSOOCSC had been run for 4 months. Blister copper productivity is increased by 6%, processing load of cold input is increased by 8% and average converter life span is improved from 213 to 235 furnace times.

Current Research and Future Directions in Pattern Identification： Results of an International Symposium

A symposium on pattern identification（PI）was held at the Korea Institute of Oriental Medicine（KIOM）on October 2,2013,in Daejeon,South Korea.This symposium was convened to provide information on the current research in PI as well as suggest future research directions.The participants discussed the nature of PI,possible research questions,strategies and future international collaborations in pattern research.With eight presentations and an extensive panel discussion,the symposium allowed participants to discuss research methods in traditional medicine for PI.One speaker presented the topic,＇Clinical pattern differentiation and contemporary research in PI.＇Two speakers presented current trends in research on blood stasis while the remaining five other delegates discussed the research methods and future directions of PI research.The participants engaged in in-depth discussions regarding the nature of PI,potential research questions,strategies and future international collaborations in pattern research.