The formation water sample in oil and gas fields may be polluted in processes of testing, trial production, collection, storage, transportation and analysis, making the properties of formation water not be reflected t...The formation water sample in oil and gas fields may be polluted in processes of testing, trial production, collection, storage, transportation and analysis, making the properties of formation water not be reflected truly. This paper discusses identification methods and the data credibility evaluation method for formation water in oil and gas fields of petroliferous basins within China. The results of the study show that: (1) the identification methods of formation water include the basic methods of single factors such as physical characteristics, water composition characteristics, water type characteristics, and characteristic coefficients, as well as the comprehensive evaluation method of data credibility proposed on this basis, which mainly relies on the correlation analysis sodium chloride coefficient and desulfurization coefficient and combines geological background evaluation;(2) The basic identifying methods for formation water enable the preliminary identification of hydrochemical data and the preliminary screening of data on site, the proposed comprehensive method realizes the evaluation by classifying the CaCl2-type water into types A-I to A-VI and the NaHCO3-type water into types B-I to B-IV, so that researchers can make in-depth evaluation on the credibility of hydrochemical data and analysis of influencing factors;(3) When the basic methods are used to identify the formation water, the formation water containing anions such as CO_(3)^(2-), OH- and NO_(3)^(-), or the formation water with the sodium chloride coefficient and desulphurization coefficient not matching the geological setting, are all invaded with surface water or polluted by working fluid;(4) When the comprehensive method is used, the data credibility of A-I, A-II, B-I and B-II formation water can be evaluated effectively and accurately only if the geological setting analysis in respect of the factors such as formation environment, sampling conditions, condensate water, acid fluid, leaching of ancient weathering crust, and ancient atmospheric fresh water, is combined, although such formation water is believed with high credibility.展开更多
The increasingly severe state of coal burst disaster has emerged as a critical factor constraining coal mine safety production,and it has become a challenging task to enhance the accuracy of coal burst disaster predic...The increasingly severe state of coal burst disaster has emerged as a critical factor constraining coal mine safety production,and it has become a challenging task to enhance the accuracy of coal burst disaster prediction.To address the issue of insufficient exploration of the spatio-temporal characteristic of microseismic data and the challenging selection of the optimal time window size in spatio-temporal prediction,this paper integrates deep learning methods and theory to propose a novel coal burst spatio-temporal prediction method based on Bidirectional Long Short-Term Memory(Bi-LSTM)network.The method involves three main modules,including microseismic spatio-temporal characteristic indicators construction,temporal prediction model,and spatial prediction model.To validate the effectiveness of the proposed method,engineering application tests are conducted at a high-risk working face in the Ordos mining area of Inner Mongolia,focusing on 13 high-energy microseismic events with energy levels greater than 105 J.In terms of temporal prediction,the analysis indicates that the temporal prediction results consist of 10 strong predictions and 3 medium predictions,and there is no false alarm detected throughout the entire testing period.Moreover,compared to the traditional threshold-based coal burst temporal prediction method,the accuracy of the proposed method is increased by 38.5%.In terms of spatial prediction,the distribution of spatial prediction results for high-energy events comprises 6 strong hazard predictions,3 medium hazard predictions,and 4 weak hazard predictions.展开更多
1 Introduction After the Dongchuan Orogenic movement(Hudsonian Orogeny,ca.1800 Ma±),the tectonic basement layer of the continental crust on the Yangtze massif could have been formed.And then tectonic-magmatic emp...1 Introduction After the Dongchuan Orogenic movement(Hudsonian Orogeny,ca.1800 Ma±),the tectonic basement layer of the continental crust on the Yangtze massif could have been formed.And then tectonic-magmatic emplacement展开更多
This article describes the geographical indication characteristics of Zhuanbu strawberry,a special product of Yinan County,Shandong Province,a national geographical indication agricultural product,including specific p...This article describes the geographical indication characteristics of Zhuanbu strawberry,a special product of Yinan County,Shandong Province,a national geographical indication agricultural product,including specific production area,unique production environment,rich human history and unique product quality,summarizes the unique production method of Zhuanbu strawberry from selection of production area and varieties,production management,timely harvesting and other aspects,and puts forward corresponding industrial development measures,in order to maintain the brand of Zhuanbu strawberry to the greatest extent and further improve the brand awareness and market competitiveness of Zhuanbu strawberry.展开更多
Rainfall temporal patterns significantly affect variability of flash flood behaviors,and further act on hydrological model performances in operational flash flood forecasting and warning.In this study,multivariate sta...Rainfall temporal patterns significantly affect variability of flash flood behaviors,and further act on hydrological model performances in operational flash flood forecasting and warning.In this study,multivariate statistical analysis and hydrological simulations(XAJ and CNFF models) were combined to identify typical rainfall temporal patterns and evaluate model simulation capability for water balances,hydrographs,and flash flood behaviors under various rainfall patterns.Results showed that all the rainfall events were clustered into three types(Type 1,Type 2,and Type 3) in Anhe catchment in southeastern China.Type 1 was characterized by small total amount,high intensity,short duration,early peak moment,and concentrated hourly distribution.Type 3 was characterized by great total amount,low intensity,long duration,late peak moment,and uniform hourly distribution.Characteristics of Type 2 laid between those of Type 1 and Type 3.XAJ and CNFF better simulated water balances and hydrographs for Type 3,as well as all flash flood behavior indices and flood dynamics indices.Flood peak indices were competitively simulated for all the types by XAJ and except Type 1 by CNFF.The study is of significance for understanding relationships between rainfall and flash flood behaviors and accurately evaluating flash flood simulations.展开更多
基金Supported by the PetroChina Science and Technology Project(2023ZZ0202)。
文摘The formation water sample in oil and gas fields may be polluted in processes of testing, trial production, collection, storage, transportation and analysis, making the properties of formation water not be reflected truly. This paper discusses identification methods and the data credibility evaluation method for formation water in oil and gas fields of petroliferous basins within China. The results of the study show that: (1) the identification methods of formation water include the basic methods of single factors such as physical characteristics, water composition characteristics, water type characteristics, and characteristic coefficients, as well as the comprehensive evaluation method of data credibility proposed on this basis, which mainly relies on the correlation analysis sodium chloride coefficient and desulfurization coefficient and combines geological background evaluation;(2) The basic identifying methods for formation water enable the preliminary identification of hydrochemical data and the preliminary screening of data on site, the proposed comprehensive method realizes the evaluation by classifying the CaCl2-type water into types A-I to A-VI and the NaHCO3-type water into types B-I to B-IV, so that researchers can make in-depth evaluation on the credibility of hydrochemical data and analysis of influencing factors;(3) When the basic methods are used to identify the formation water, the formation water containing anions such as CO_(3)^(2-), OH- and NO_(3)^(-), or the formation water with the sodium chloride coefficient and desulphurization coefficient not matching the geological setting, are all invaded with surface water or polluted by working fluid;(4) When the comprehensive method is used, the data credibility of A-I, A-II, B-I and B-II formation water can be evaluated effectively and accurately only if the geological setting analysis in respect of the factors such as formation environment, sampling conditions, condensate water, acid fluid, leaching of ancient weathering crust, and ancient atmospheric fresh water, is combined, although such formation water is believed with high credibility.
基金supported by the National Research and Development Program(2022YFC3004603)the Jiangsu Province International Collaboration Program-Key National Industrial Technology Research and Development Cooperation Projects(BZ2023050)+1 种基金the Natural Science Foundation of Jiangsu Province(BK20221109)the National Natural Science Foundation of China(52274098).
文摘The increasingly severe state of coal burst disaster has emerged as a critical factor constraining coal mine safety production,and it has become a challenging task to enhance the accuracy of coal burst disaster prediction.To address the issue of insufficient exploration of the spatio-temporal characteristic of microseismic data and the challenging selection of the optimal time window size in spatio-temporal prediction,this paper integrates deep learning methods and theory to propose a novel coal burst spatio-temporal prediction method based on Bidirectional Long Short-Term Memory(Bi-LSTM)network.The method involves three main modules,including microseismic spatio-temporal characteristic indicators construction,temporal prediction model,and spatial prediction model.To validate the effectiveness of the proposed method,engineering application tests are conducted at a high-risk working face in the Ordos mining area of Inner Mongolia,focusing on 13 high-energy microseismic events with energy levels greater than 105 J.In terms of temporal prediction,the analysis indicates that the temporal prediction results consist of 10 strong predictions and 3 medium predictions,and there is no false alarm detected throughout the entire testing period.Moreover,compared to the traditional threshold-based coal burst temporal prediction method,the accuracy of the proposed method is increased by 38.5%.In terms of spatial prediction,the distribution of spatial prediction results for high-energy events comprises 6 strong hazard predictions,3 medium hazard predictions,and 4 weak hazard predictions.
基金financial support by The Researchon Occurrence State of Element and Tectonic Lithofacies Mapping Technique for the Iron -Oxide Copper Gold Deposits (2011EG115022, 2013EG115018)
文摘1 Introduction After the Dongchuan Orogenic movement(Hudsonian Orogeny,ca.1800 Ma±),the tectonic basement layer of the continental crust on the Yangtze massif could have been formed.And then tectonic-magmatic emplacement
基金Shandong Provincial Modern Agricultural Industrial Technology System:Project for Construction of Vegetation Innovative Team(SDAIT-05-18).
文摘This article describes the geographical indication characteristics of Zhuanbu strawberry,a special product of Yinan County,Shandong Province,a national geographical indication agricultural product,including specific production area,unique production environment,rich human history and unique product quality,summarizes the unique production method of Zhuanbu strawberry from selection of production area and varieties,production management,timely harvesting and other aspects,and puts forward corresponding industrial development measures,in order to maintain the brand of Zhuanbu strawberry to the greatest extent and further improve the brand awareness and market competitiveness of Zhuanbu strawberry.
基金National Natural Science Foundation of China,No.42171047,No.42071041。
文摘Rainfall temporal patterns significantly affect variability of flash flood behaviors,and further act on hydrological model performances in operational flash flood forecasting and warning.In this study,multivariate statistical analysis and hydrological simulations(XAJ and CNFF models) were combined to identify typical rainfall temporal patterns and evaluate model simulation capability for water balances,hydrographs,and flash flood behaviors under various rainfall patterns.Results showed that all the rainfall events were clustered into three types(Type 1,Type 2,and Type 3) in Anhe catchment in southeastern China.Type 1 was characterized by small total amount,high intensity,short duration,early peak moment,and concentrated hourly distribution.Type 3 was characterized by great total amount,low intensity,long duration,late peak moment,and uniform hourly distribution.Characteristics of Type 2 laid between those of Type 1 and Type 3.XAJ and CNFF better simulated water balances and hydrographs for Type 3,as well as all flash flood behavior indices and flood dynamics indices.Flood peak indices were competitively simulated for all the types by XAJ and except Type 1 by CNFF.The study is of significance for understanding relationships between rainfall and flash flood behaviors and accurately evaluating flash flood simulations.
