Comparison between Sequential Gaussian Simulation and Kriging Interpolation on Soil Heavy Metal Pollution

[Objective] This study was to explore the difference of kriging interpolation and sequential Gaussian simulation on analyzing soil heavy metal pollution with a view to provide references for analyzing the heavy metal pollution of soil. [Method] The sampling data of soil copper from a county of Liaocheng, Shandong Province was set as the study objective. Kriging interpolation and sequential Gaussian simu- lation were used to simulate the spatial distribution of soil copper. And 30 sampling points were selected as the cross-validation data set to compare the two interpola- tion methods. [Result] Kriging method and Gaussian sequential simulation have their own advantages on simulating mean segment and extreme segment, therefore, re- searchers should choose the proper method based on the characteristics of test data and application purposes. [Conclusion] Analysis of soil heavy metal pollution is the prerequisite for soil management and ecological restoration. The result of this study is of important significance for choosing different interpolating and simulating methods to analyze soil heavy metal pollution based on different purposes.

Risk quantification in grade variability of gold deposits using sequential Gaussian simulation

Risk quantification in grade is critical for mine design and planning.Grade uncertainty is assessed using multiple grade realizations,from geostatistical conditional simulations,which are effective to evaluate local or global uncertainty by honouring spatial correlation structures.The sequential Gaussian conditional simulation was used to assess uncertainty of grade estimates and illustrate simulated models in Sivas gold deposit,Turkey.In situ variability and risk quantification of the gold grade were assessed by probabilistic approach based on the sequential Gaussian simulations to yield a series of conditional maps characterized by equally probable spatial distribution of the gold grade for the study area.The simulation results were validated by a number of tests such as descriptive statistics,histogram,variogram and contour map reproductions.The case study demonstrates the efficiency of the method in assessing risk associated with geological and engineering variable such as the gold grade variability and distribution.The simulated models can be incorporated into exploration,exploitation and scheduling of the gold deposit.

Analysis of the Lost Circulation Problem

The well-known“lost circulation”problem refers to the uncontrolled flow of whole mud into a formation.In order to address the problem related to the paucity of available data,in the present study,a model is introduced for the lost-circulation risk sample profile of a drilled well.The model is built taking into account effective data(the Block L).Then,using a three-dimensional geological modeling software,relying on the variation function and sequential Gaussian simulation method,a three-dimensional block lost-circulation risk model is introduced able to provide relevant information for regional analyses.

SSO Risk Evaluation for a Grid-connected PMSG-based Wind Farm Based on Sequential Monte Carlo Simulation

In a grid-connected wind farm based on permanent magnet synchronous generators(PMSGs),the wind speed and the number of operating PMSGs are the two most important influencing factors along with the stochastic nature of sub-synchronous oscillation(SSO)from the point view of the farm.This paper proposes a method of unstable SSO risk evaluation for grid-connected PMSG-based wind farms based on the sequential Monte Carlo simulation(SMCS).The determination of critical wind speed(CWS)of SSO and the sequential simulation strategy of wind speed states and PMSG states in a wind farm at the same wind speed(S-WF),as well as in a wind farm at different wind speeds(D-WF),are studied.Five indices evaluating the expectation,duration,frequency and energy loss of SsO risk are proposed.Moreover,a strategy to reduce SsO risk by adjusting the cut-in wind speed is discussed.The effectiveness of the discussed issues in this paper are proved by the case studies of a 750-PMSG wind farm based on the actual wind speed data collected.

Equation oriented method for Rectisol wash modeling and analysis

Rectisol process is more efficient in comparison with other physical or chemical absorption methods for gas purification. To implement a real time simulation of Rectisol process, thermodynamic model and simulation strategy are needed. In this paper, a method of modified statistical associated fluid theory with perturbation theory is used to predict thermodynamic behavior of process. As Rectisol process is a highly heat-integrated process with many loops, a method of equation oriented strategy, sequential quadratic programming, is used as the solver and the process converges perfectly. Then analyses are conducted with this simulator.

Application of Seismic Data to Reservoir Modeling of the Chegu 201 Block

Great uncertainty exists in reservoir models built for blocks where well spacing is uneven or large. The uncertainty in reservoir models can be significantly reduced by using Coordinate Cokriging Sequential Gaussian Simulation technology, in combination with the restriction of seismic characteristic data. Satisfactory reservoir parameter interpolation results, which are more accurate than those derived only from borehole data, are obtained, giving rise to a reasonable combination of widespread and dense-sampled seismic (soft data) data with borehole data (hard data). A significant effect has been made in reservoir parameter modeling in the Chegu 201 block of the Futai Oilfield by using this technology.

Statistical distribution of geomechanical properties and‘Sweet Spots’identification in part of the upper Bakken

Completions and Reservoir Quality are two key attributes that are used to characterize nonconventional hydrocarbon assets.This is because,for optimum exploitation of these unconventional assets,horizontal wells need to be drilled in“Sweet Spots”(i.e.,regions where Completions and Reservoir Quality are both superior).One way to quantify these qualities is to use reservoir and geomechanical properties.These properties can be estimated on a location basis from well logs,and then mapped over terrain using geostatistical modeling.This study presents a‘Sweet Spots’identification workflow based on three performance indexes(Storage Potential Index,Brittleness Index,and Horizontal Stress Index)that can be used to quantify CQ and RQ.The performance indexes are computed from petrophysical property volumes(of Young's Modulus,Bulk Modulus,Shear Modulus,Poisson's Ratio,Minimum Horizontal Stress,Volume of Shale,Total Organic Carbon,Thickness,and Porosity)which are in turn computed from well logs and geostatistical simulation.In the end,the study offers a method to compare the predicted“Sweet Spots”against available production data via their correlation coefficient.The resulting reasonable formation property maps,the successful identification of‘Sweet Spots’,and a correlation coefficient of 0.88(between the predicted“Sweet Spots”and well production data)point to the potential of the proposed effort.

Reliability Assessment of Integrated Electricity and Natural Gas Transmission Systems in Presence of Power-to-gas and Combined Heat and Power Technologies

Assessing the reliability of integrated electricity and gas systems has become an important issue due to the strong dependence of these energy networks through the power-to-gas(P2G)and combined heat and power(CHP)technologies.The current work,initially,presents a detailed energy flow model for the integrated power and natural gas system in light of the P2G and CHP technologies.Considering the simultaneous load flow of networks,a contingency analysis procedure is proposed,and reliability is assessed through sequential Monte Carlo simulations.The current study examines the effect of independent and dependent operation of energy networks on the reliability of the systems.In particular,the effect of employing both P2G and CHP technologies on reliability criteria is evaluated.In addition,a series of sensitivity analysis are performed on the size and site of these technologies to investigate their effects on system reliability.The proposed method is implemented on an integrated IEEE 24-bus electrical power system and 20-node Belgian natural gas system.The simulation procedure certifies the proposed method for reliability assessment is practical and applicable.In addition,the results prove connection between energy networks through P2G and CHP technologies can improve reliability of networks if the site and size of technologies are properly determined.

Wind and Photovoltaic Power Time Series Data Aggregation Method Based on an Ensemble Clustering and Markov Chain

Reducing the input wind and photovoltaic power time series data can improve the efficiency of time sequential simulations.In this paper,a wind and photovoltaic power time series data aggregation method based on an ensemble clustering and Markov chain(ECMC)is proposed.The ECMC method can effectively reduce redundant information in the data.First,the wind and photovoltaic power time series data were divided into scenarios,and ensemble clustering was used to cluster the divided scenarios.At the same time,the Davies-Bouldin Index(DBI)is adopted to select the optimal number of clusters.Then,according to the temporal correlation between wind and photovoltaic scenarios,the wind and photovoltaic clustering results are merged and reduced to form a set of combined typical day scenarios that can reflect the characteristics of historical data within the calculation period.Finally,based on the Markov Chain,the state transition probability matrix of various combined typical day scenarios is constructed,and the aggregation state sequence of random length is generated,and then,the combined typical day scenarios of wind and photovoltaic were sampled in a sequential one-way sequence according to the state sequence and then are built into a representative wind and photovoltaic power time series aggregation sequence.A provincial power grid was chosen as an example to compare the multiple evaluation indexes of different aggregation methods.The results show that the ECMC aggregation method improves the accuracy and efficiency of time sequential simulations.

Model and application of renewable energy accommodation capacity calculation considering utilization level of inter-provincial tie-line

At present, the problem of abandoning wind and PV power in “Three North” region of China is particularly significant, and how to alleviate this problem has become the focus of universal attention. Calculation of renewable energy accommodation capacity is the basis to solve the problem of abandoning wind and PV power. Main problems of Chinese renewable energy accommodation is analyzed from power supply, power grid and load side aspects, and it focuses on the effect of inter-provincial tie-line to renewable energy accommodation capacity. At present, the inter-provincial tie-line utilization level is limited, which affected renewable energy accommodation to a certain extent. Based on the sequential production simulation model, a new kind of renewable energy accommodation capacity model is put forward considering the utilization level of inter-provincial tie-line. According to different system stability constraints and different electricity constraints of inter-provincial tie-line, 4 schemes are designed for comparative analysis, and the evaluation model is used to calculate renewable energy accommodation capacity of “Three North” region of China in 2020. Example analysis results verify validity of the model that releasing curve constraints, electricity constraints and stability constraints in turn can significantly enhance renewable energy accommodation capacity through effective use of inter-provincial tie-line transmission capacity. Research work in this paper can provide strong support for the planning and scheduling control of power grid.