Performance Forecasting Research Articles

EVALUATION OF WIND ENERGY POTENTIAL OF THE BLACK SEA COAST USING CFSR

The quality of the source data (sufficient spatial and temporal frequency) is decisive in the calculation of wind energy. In recent years, specialized data bases are increasingly used for regional assessments of wind potential and wind farm performance forecast. These databases provide the results of averaging the ground observation data, satellite data and mathematical modeling. In this connection, an important task is to verify such data and involvement reanalysis data in wind energy calculations. The work carries out verification of reanalysis NCEP CFSR on measurements of ground stations (Roshydromet network) and data of SODAR at altitudes up to300 m. A detailed comparison of the different wind characteristics that calculated on base of the reanalysis and specialized databases (NASA SSE, NASA POWER) is proposed. Calculation methods of wind speed and repeatability at a predetermined height based on CFSR are described. Region of research is the territory of the Black Sea coast of theNorth Caucasus, which is characterized by rather complex and diverse topography. Map of wind on the Black Sea coast of theCaucasus(height50 m), built using reanalysis data about average speeds allows the researchers to highlight the most productive areas for further detailed investigation. The proposed methodology for calculating wind speed and repeatability at a predetermined height, which based on reanalysis of high spatial resolution can be productively used to evaluate the wind energy potential.

Performance Comparison and Forecast Analysis between KVM and Docker

Performance Comparison and Forecast Analysis between KVM and Docker

Performance prediction between horizontal and vertical source heat pump systems for greenhouse heating with the use of artificial neural networks

This paper presents the suitability of artificial neural networks (ANNs) to predict the performance and comparison between a horizontal and a vertical ground source heat pump system. Performance forecasting is the precondition for the optimal control and energy saving operation of heat pump systems. In this study, performance parameters such as air temperature entering condenser fan-coil unit, air temperature leaving condenser fan-coil unit, and ground temperatures (2 and 60 m) obtained experimental studies are input data; coefficient of performance of system (COPsys) is in output layer. The back propagation learning algorithm with three different variants such as Levenberg–Marguardt, Pola–Ribiere conjugate gradient, and scaled conjugate gradient, and also tangent sigmoid transfer function were used in the network so that the best approach can be found. The results showed that LM with three neurons in the hidden layer is the most suitable algorithm with maximum correlation coefficients R2 of 0.999, minimum root mean square RMS value and low coefficient variance COV. The reported results confirmed that the use of ANN for performance prediction of COPsys,H–V is acceptable in these studies.

Reservoir Characterization and History Matching of the Horn River Shale: An Integrated Geoscience and Reservoir-Simulation Approach

Summary We present a systematic approach to integrate geoscience and dynamic reservoir modeling for two multiwell pads in the Horn River basin, Canada. The Horn River shale-gas play is a world-class unconventional gas resource and is being exploited by use of multistage hydraulic fracturing along horizontal wells. The two well pads, Pad-1 and Pad-2, selected for this study comprise eight and seven horizontal wells, respectively, with 1 to 7 years of production history. Numerical modelling of shale reservoirs has historically been a problematic low-confidence exercise because of the difficulties associated with inadequate characterization of the geologic framework of shale plays; the problems of estimating the properties of induced-fracture networks; and the complexities of capturing multiphase flow in fracture networks and wellbores during production, especially in the face of offset-well activity. This paper provides insights into these issues. The geoscience modelling activity begins with integrating information from cores, well logs, petrophysical analyses, and seismic data into a 3D geocellular model. At first, the model is built upon a simple lithostratigraphic concept, which is the basis of the numerical-flow-modelling exercise of Pad-1. The 3D geocellular model is thereafter thoroughly reworked to incorporate a sequence-stratigraphic perspective to the Horn River shale. This reworked geocellular model has a profound impact on the dynamic modelling of Pad-2. Also, hydraulic conductivity of induced and natural fractures is measured on Horn River core plugs at reservoir conditions to constrain conductivity values assigned to primary, secondary, and tertiary flow paths into dynamic reservoir modelling. As a result of the integrated work flow, we have achieved a history match allowing us to further understand the hydraulic-fracturing behaviour and its impact on producing shale reservoirs of the Horn River formation. On the basis of the findings, we recommend targeting the Evie and Otter Park shale reservoirs for landing horizontal wells and multistage fracturing when the Carbonate Fan is thin; this approach can produce all three compartmentalized shale reservoirs of the Horn River formation. Ultimately, the objective of any reservoir modelling project is to provide a range of reliable forecast of future performance that is grounded in representative geoscience interpretations and that takes operational constraints into account. The technical learnings described in this work will be helpful to further understand hydraulic-fracturing behaviour and its impact on producing shale reservoirs.

A semi-analytical mathematical model for transient pressure behavior of multiple fractured vertical well in coal reservoirs incorporating with diffusion, adsorption, and stress-sensitivity

Vertically fractured wells have been widely used in coal gas reservoirs. Investigating transient pressure behaviors (TPB) of these wells is a considerably significant task for fracturing evaluation as well as productivity prediction. Although some studies have been done in this area, most of them focus on two-wing fractured wells. Both micro-seismic fracture imaging and samples testing strongly showed that multiple fractures can develop during hydraulic fracturing in naturally fractured reservoirs like coal seam. However, little work has been done to study the TPB of multiple fractured vertical wells (MFVW) in coal reservoirs.In this paper, to study this problem thoroughly, a well testing model of MFVW at a constant production rate was established with consideration of multiple mechanisms including diffusion, adsorption, and stress-sensitivity effect. Applying line source function, superposition principle, Pedrosa's substation, Gauss elimination, and Stehfest numerical inversion, the transient pressure solution of the mathematical model was solved. Based on this solution, model validation was conducted by selecting a case in literature. In addition, the influences of some critical parameters on TPB were studied, containing fracture length, fracture conductivity, fracture number, fracture length asymmetry, fracture conductivity asymmetry, and fracture angle asymmetry.This work provides important references for some reservoir engineers in performance forecast and completion design of MFVW in coal gas reservoirs.

A high performing meta-heuristic for training support vector regression in performance forecasting of supply chain

The prevalence of the use of third-party logistics (3PL) providers is noticeable. The complexity of the relationships pertinent to 3PL is greater than that of any traditional logistics supplier relationships. Moreover, they can be considered as truly strategic alliances. The use of the mentioned relationships to increase the flexibility of the organization to address the rapid changes occurring in market conditions has become popular while these relationships concentrate on the core competencies as well as the development of long-term growth strategies. A good number of studies have examined the selection of service providers. With respect to the selection of the service providers, the most recent studies approved the better performance of neural networks in comparison with the conventional methods to provide a solution for the real-world engineering problems, one of the sociopolitically inspired optimization strategies named imperialist competitive algorithm (ICA) is used. In order to select the 3PL, integration of the support vector regression (SVR) and self-adaptive ICA (SAICA) has offered a novel model, in which SAICA is utilized to adjust the parameters of the SVR. The suggested model is applied for cosmetics production. Moreover, the comparison of the suggested model and back-propagation neural networks, pure SVR, and ICA---SVR is presented. Higher estimation accuracy is achieved as the results of the proposed model reveal, which leads to the effective prediction.

An Improved Method for the Short-Term Forecasting of Electric Power Market Performance with Increased Penetration of Renewable Energy

This study extends the system pattern short-term forecasting method for power systems to incorporate non-dispatchable renewable energy, thus permitting the forecasting of CO2 emissions along with the forecasting of prices, line congestion, and other system variables. It also develops an empirically-based system pattern transition matrix permitting a dynamic extension of the method. The practical usefulness of the resulting extended forecasting method is illustrated by means of a 5-bus test system based on data from the Midcontinent Independent System Operator.

The method of analys of reliability of the system of air signals based on frequency pressue sensors

The system of air signals (SAS) is intended for the issue of main aerobatic information on indicators of instrumentation in the cockpit and on-board systems. Under the reliability of SAS we understand property systems remain operational continuously for a certain time or a certain operating time. This feature is especially important for objects, refusal to work is related to danger to life. In many technical systems determining parameter (DP), which dominates as the weakest link in terms of parametric reliability, that is a quantitative measure of quality, has the ability to change over time and beyond the permissible limits. In the SAS at the frequency of air pressure sensors DP is such a frequency output sensors. The relevance of the study is that the method allows to find time to failure SAS, which will allow for practice time to prevent rejection, as well as control the frequency-dependent system, spending adjustments or changing operating conditions of the system. The goal of research is to develop a method for the analysis of parametric reliability of SAS frequency pressure sensors to improve the economic efficiency of the known methods of reliability analysis. Object is a parametric reliability SAS. The subject is research a system of air signals based on frequency pressure sensors. The novelty of the method is that instead of the number of the objects used for the first time the number of intervals of one research facility, which greatly improves the cost-effectiveness of the method. Practical application of the method is that having information about the real meaning of time to reach DP limit the design phase of SAS frequency pressure sensors can determine experimentally and analytically calculate parametric indicators of reliability of the system, that make a reasonable forecast of future performance.

The practical performance forecast and analysis of thermoelectric module from macro to micro

The practical operating conditions of thermoelectric products, such as the input power source and the thermal resistance of hot side heat exchanger, are different from the theoretical study. Thus the equations, which are used to estimate the practical maximum cooling performance just according to the datum in datasheet of commercial thermoelectric module (TEM), are given. The nested loop method is adopted to solve the numerical model. This study provides a method to choose a suitable TEM for thermoelectric product to meet the application requirement. It finds that the minimum cold side temperature increase and the voltage for achieving the minimum cold side temperature step decrease with the increase of thermal resistance of hot side heat exchanger, respectively. The maximum temperature difference increase and the voltage for achieving the maximum temperature difference step increase with the increase of thermal resistance of hot side heat exchanger, respectively. According to the dimension, three kinds of thermoelectric module, bulk TEM, miniature TEM and micro TEM, are studied. The novel scale effect are discovered by comparing these TEMs. It found that the step-change phenomenon become more and more obvious with the decrease of the dimension of thermoelectric module. The influence ratio of thermal resistance of hot side heat exchanger on the maximum cooling performance increases and the influence ratio of input power source decreases from macro to micro, respectively. It forecasts that there exists a critical value for the dimension of thermoelectric module, when the dimension of thermoelectric module is smaller than this critical value, the maximum voltage or current of thermoelectric module is constant and does not change with the thermal resistance of hot side heat exchanger.

Energy 360: Invited Perspective: Reservoir Modeling Today and Tomorrow

President's column Reservoir performance forecasting is still the “Grand Central Station” of all the exploration and production (E&P) disciplines because this is where everything (the large-scale reservoir plumbing system, reservoir properties, fluid properties, wells, completions, lift curves/hydraulics, facilities, fluid handling capacities, and much more) is integrated and comes together in a life-of-field forecast. The revenue from the field development is the composite oil and gas production rates into the future multiplied by the forward oil and gas prices. The reservoir description, which I call the “subsurface plumbing system,” in a forecasting model can range from a simple homogeneous analytical tank model to an unbelievably complex dual porosity, compositional simulation model with one billion grid cells, pseudos ( from endless upscaling), and many other sophisticated features built in to try to mimic a very complex reality. I had the opportunity to discuss the state of the art and the future of reservoir modeling and reservoir performance forecasting with one of the finest members of the reservoir engineering profession, professor Larry W. Lake, of the University of Texas at Austin (UT). You have taught reservoir modeling to undergraduates and graduate students for more than 30 years. How has the reservoir modeling discipline evolved? The biggest evolution has been caused by the capacity of computers. The capacity has allowed combinations of traditional simulation with facilities, improved resolution of heterogeneity, progress in automated history matching, and uncertainty estimation to name just a few. In order for universities such as UT to understand the main reservoir modeling challenges of the E&P industry, close collaboration and a dialogue on real industry needs must happen. What is your view of the state of industry/academia collaboration? Are you collaborating more with service companies than with international oil companies, national oil companies, and independents? We at UT do well in the collaboration department and on all the major avenues of E&P. The challenge for us is the boundary between technology development and research. We do, or at least we should do, research.

Performance Forecast of Air-Cooled Steam Condenser under Windy Conditions

AbstractAmbient wind has adverse impacts on the thermal-flow performances of air-cooled steam condensers (ACSCs). It is useful to understand the mechanisms of such influences so as to improve and optimize the performance of condensers. The flow fields around an ACSC at different wind speeds and directions are numerically investigated in this paper. It is found that the negative pressure region under the ACSC platform results in volumetric effectiveness reduction of the windward fans with increasing wind speed, and hot air recirculation or reversed flow in condenser cells causes a fan inlet air temperature increase. Under windy conditions, if a main building blockage effect exists, either hot air recirculation will occur, or else reversed flow may arise. The negative pressure region under the platform plays a leading role in the heat transfer effectiveness reduction. From the scale of condenser cell instead of the whole ACSC, stable backpressures corresponding to the windy conditions are forecasted by the ...

Systematic Evaluation Method of Water Aquifer Energy for Water-Drive Gas Reservoir

On the basis of present relevant research about water aquifer energy for water-drive gas reservoir, systematic evaluation method of water aquifer energy for water-drive gas reservoir is constructed from water invasion recognition, water aquifer size calculation, water influx volume calculation, water aquifer active degree evaluation and drive energy composition analysis. According to static and dynamic data of an actual typical water-drive gas reservoir, water aquifer energy was evaluated systematically. Research results indicated that this method can evaluate water aquifer energy of water-drive gas reservoir quickly and systematically, which can offer reference to development performance forecast and development adjustment of this kind of gas reservoir, and realize reasonable and effective development of this kind of gas reservoir.

Improved characterization and performance prediction of shale gas wells by integrating stimulated reservoir volume and dynamic production data

Gas flow in shale gas reservoirs occurs primarily from ultra low permeability shale rocks through a complex network of natural and induced hydraulic fractures. Consequently, fracture parameters (conductivity and half length), fracture location and distribution are the dominant factors influencing well drainage volumes and shale gas well performance. Stimulated reservoir volume or SRV, estimated from microseismic event clouds or rate/pressure transient analysis, describes a measurement of overall reservoir volume impacted by fracture treatments. With SRV as well as the dynamic production/pressure response, reservoir simulation models can be calibrated to actual well performance in shale gas reservoirs leading to improved understanding, forecasting and future well placement. In this paper, we first introduce a novel approach for computing well drainage volume for shale gas wells with multistage fractures and fracture clusters. Next, we calibrate the shale gas reservoir model by matching the drainage volume with the SRV within specified confidence limits. The matching of the SRV is done in addition to the traditional history matching of production/pressure response and further constrains the estimation of fracture parameters. An evolutionary algorithm with design of experiments is used for the assisted history matching. Sensitivities to various parameters such as fracture conductivity, fracture half lengths and rock compaction have also been investigated. The proposed approach has been applied to a generic shale gas well designed after a real field case. The results clearly indicate the benefits of including SRV during history matching, leading to improved fracture/matrix parameter estimation and performance forecasting. Our proposed approach provides an important tool that can be used to optimize well placement, fracture treatments and improve the economics of shale gas plays.

Rho Has No Role: Correlation Coefficient Instability and Non-asymptotic Simulation Volatility

This paper calculates the per quarter pairwise correlation coefficients (Rho) of the daily returns from December 5, 2005 to December 8, 2014 of 30 stocks randomly selected from the Russell 3000 index. For the time series correlation coefficients of 435 pairs of assets, we employ the Elliot-Rothenberg-Stock Point Optimal procedure to examine the stability of correlation coefficients. Our results indicate the inappropriateness of using correlation coefficients in portfolio management and Monte Carlo simulation. More than one-third of the correlation coefficient series generate non-asymptotic simulation volatility and using ex post correlation coefficients in Cholesky decomposition performance forecast can lead to severe deviation from the investment policy mandate.

Effect of Irradiation on Hydrogen Sensors Based on MISFET

The electron irradiation effect on hydrogen sensitivity of the sensors based on metal-insulator-semiconductor transistor (MISFET) element with structure Pd-Ta2O5-SiO2-Si have been investigated. The MISFET threshold voltage as a function of hydrogen concentration was determined before and after each irradiation. It is found that under irradiation this function was monotonically drifting. In addition after irradiations by doses more than ∼ 700Gy the hydrogen sensitivity are steadily decreasing. The models of hydrogen and radiation sensitivity were developed. According to represented models the estimations of critical doses and the forecast of hydrogen sensor performance under irradiation have been done.

Assurance networks in qualitative analysis of projects of technical diagnostics of portal cranes

The main means of mechanization of technological processes of the functioning of sea and river ports, dockyards are ship repair enterprises are the lifting machines, and in particular, portal cranes (PC). Operability, performance and mode of operation of such cranes depend on their technical condition which is determined by the value of the defects (cracks, deformation, breaks of the elements of the tap metal construction, etc.). This approach in the diagnosis of the crane ignores the fact that such defects during operation of the PC are affected by a number of factors (technical, natural, human, loads characteristics etc.) which may affect their further development and thus result in an unusable state of the crane and thereby form an uncertain events system. This requires solving the problem of probabilistic inference which refers to the calculations of the probability of events based on the known probabilities of the other related events. To solve these problems several methods are proposed (output based on probability trees, probability trees, goal trees, etc.), however, such techniques have certain disadvantages along with their positive qualities. For example, when the number of uncertain events systems increase, the dimensions of the trees grow so fast that it becomes difficult to operate with them. Therefore, the approach based on the assurance networks seems promising to analyze such situations. This approach is demonstrated on the example of the problem of forecasting of the port gantry cranes performance.

Simple tools for forecasting waterflood performance

Empirical and/or semianalytical tools are frequently applied in most waterflood operations, although grid-based models are also often used. This paper examines the performance of some commonly used tools, such as the water–oil ratio (WOR), Y-function, and Arps. Besides those tools, we introduce a semianalytical approach, which is a modified version of the Y-function formulation. Two other tools that have gained significant traction in unconventional-reservoir performance forecasting, the stretched-exponential decline model (SEDM) and the capacitance–resistance model (CRM) are also used here. Based on synthetic and field data, the results show that the Arps method is remarkably accurate in all flooding situations, regardless of the underlying physical mechanisms; other published data tend to support this notion. Similarly, both the SEDM and the proposed modified-Y-function method also yield solutions with good accuracy. The latter solutions tend to be pessimistic, however.

Dynamic Control Thresholds for Consistent Earned Value Analysis and Reliable Early Warning

AbstractEarned value management (EVM) facilitates practicing management-by-exception by triggering control actions only when they are needed. The efficiency and effectiveness of project control actions are influenced by the control thresholds used to identify meaningful performance deviations or trends from the plan. This paper presents a quantitative method for establishing dynamic control thresholds (DCTs) that change at different percent completion points according to the degree of achievability of the project objectives in time and money. The DCTs in this paper overcome two limitations of conventional fixed control thresholds. First, the DCTs provide consistent measures of risk and early warning signals for different EVM performance measurements and forecasts. Second, the DCTs provide additional information to detect false warnings from deterministic performance analysis and forecasting monitored by fixed control thresholds, especially early in a project. This paper mainly focuses on schedule performa...

Integrated CO2, cost, and schedule management system for building construction projects using the earned value management theory

Although the construction phase in a building's life cycle is relatively very short, the density of the CO2 emissions in the construction phase is very higher than that in the other phases (i.e., operations and maintenance phase). However, there was little research on scheduling, monitoring, evaluating and forecasting CO2 emissions based on the construction schedule. To address this challenge, this research aimed to develop an integrated CO2, cost and schedule management (ICCSM) system for building construction projects using the earned value management theory. The proposed ICCSM system consisted of five steps: (i) definition of the project scope and organization; (ii) project planning and scheduling; (iii) estimation and budgeting of the CO2 emissions and construction costs; (iv) establishment and weighting of the project performance measurement baseline; and (v) monitoring and forecasting of the project performance. The case study showed that the ICCSM system can evaluate and forecast the project performance earlier and more accurately, based on the construction schedule, (i) when integrated weighting was implemented, the project performance can be estimated faster (i.e., one day earlier); and (ii) when 0.8 × (cost performance index) + 0.2 × (schedule performance index) was implemented as the index for calculating an estimate at completion, the project performance can be more accurately predicted (i.e., error rate = −0.24%). The ICCSM system could allow a project manager to monitor and forecast CO2 emissions and costs based on the construction schedule, simultaneously.

Predicting Financial Stability of Select BSE Companies Revisiting Altman Z Score

In the era of globalization, prediction of financial distress is of interest not only to managers but also to external stakeholders of a company. The stakeholders are continuously seeking the optimal solution for performance forecasting, as a way to rationalize the decision-making process. The recent past shows that financial stability of companies is at the stake. Stockholders, Managers, Creditor and employees of the business are always concerned about financial stability of the companies. The most frequently tool for financial analysis is financial ratios. However, financial ratios are no-longer proved appropriate for „Stockholders‟ equity position and creditors‟ claims. Stakeholder‟s have concerns about the consequences of financial distress for companies, and controls of capital adequacy through the regulatory capital requirement (Mingo, 2000). This shared interest creates persistent investigations and continuing attempts to answer an incessant question that how financial distress can be predicted, or what reveals the credit risk of firms. For this purpose most commonly used tool is Altman Z score, but due to nature of the explanatory variables, financial distress prediction research has not reached an unequivocal conclusion. The primary goal of this paper is to analyze and reexamine the Altman Z score. In order to facilitate the current research, various ratios were taken from Altman‟s Z score. To fulfill our objective Z score ratios were used to divide sample firms into healthy and unstable among BSE-30 companies. First the Z score is calculated for 10 companies selected for this purpose for a period of 5 years each. And then it is divided as per z scores, later the significant in the changes in the ratio is calculated with the help of One sample Komogrov-Smirnow test, which resulted that the change in the z scores is not significant in case of all the companies.