scholarly journals Assessing the Impact of Uncertainty Parameters on Forcasting Production Parameters

2020 ◽  
Vol 20 (4) ◽  
pp. 356-368
Author(s):  
Nikita D. Nikita D. ◽  
◽  
Aleksey Yu. Vishnyakov ◽  
Ivan S. Putilov ◽  
◽  
...  
Keyword(s):  
Input Data ◽  
Approximate Algorithm ◽  
Economic Evaluations ◽  
Model Parameters ◽  
Reservoir Model ◽  
Hydrodynamic Simulation ◽  
Production Parameters ◽  
Uncertainty Parameters ◽  
The Impact ◽  
Selection Of

At the stage of developing a geological and hydrodynamic reservoir model, uncertainties in input data may lead to errors in simulation results and subsequent inaccurate economic evaluations of oil or gas field potentials. In order to improve predictive reliability, a study was completed to assess how input data of a hydrodynamic model influence forecasts of main parameters of a production using the example of the Tournaisian site of the Soldatovskoye field. The study presents an approximate algorithm reducing uncertainties and improving the forecast reliability of the production parameters obtained using a geological and hydrodynamic reservoir model. The algorithm includes a substantiated selection of the initial sensitivity parameters, an evaluation of the impact of the initial parameters on the hydrodynamic reservoir model using the sensitivity analysis, as well as a selection of an optimal range of variations of the uncertainty parameters as a result of the multivariant hydrodynamic simulation adaptation, calculation and analysis of the multivariant hydrodynamic reservoir model forecast. The study aims to clarify the design process parameters of the development, assess the risks of non-confirmation of the hydrodynamic simulation forecasting, and make recommendations and proposals to study those uncertainty parameters, which influence most on certain predicted production parameters of an asset. As a result, a block diagram of the approach is presented in order to generalize and replicate it on potential and important oil and gas fields. The described approach of the model adaptation and calculations of the predicted options in conditions of uncertainty of the initial model parameters make it possible to obtain a more accurate and less arbitrary hydrodynamic reservoir model, which reduces probability of an incorrect evaluation of potentials of a young field or a field at an early production stage.

Probabilistic Economical Evaluation for Business Decisions Through Integrated Uncertainty Assessment and Reliable Ensemble-Based Production Forecasts

2021 ◽  
Author(s):  
Mohammed Abd-Allah ◽  
Ahmed Abdelrahman ◽  
Luke Van Den Brul ◽  
Taha Taha ◽  
Mohammad Ali Javed
Keyword(s):  
Economic Evaluation ◽  
History Matching ◽  
Dynamic Models ◽  
Traditional Approach ◽  
Integrated Modelling ◽  
Economic Evaluations ◽  
Reservoir Model ◽  
Model Uncertainties ◽  
Reservoir Models ◽  
The Impact

Abstract Economic evaluation of exploration and production projects ensures a positive return for asset operators and stakeholders and evaluates risk in field development decisions related to both reservoir model uncertainties and fluctuations in oil and gas prices. Traditionally, such evaluation is performed manually and deterministically using single or limited number of cases (limited number of reservoir models and few values of economic parameters). Such traditional approach does not integrate seismic-to-simulation reservoir model uncertainties, the reservoir model used is often unreliable due to inconsistent property modifications during the history matching process, full span of prediction uncertainty isn't properly propagated for economic evaluation and the whole process is not fully automated. This paper presents an integrated and automated forward modelling approach where static and dynamic models are connected to integrate the impact of uncertainties at the different modelling stages (seismic interpretation through geological modelling to dynamic simulation and further to economic evaluations). The approach is demonstrated using synthetic 3D model data mimicking a real North Sea field. It starts by building an integrated modelling workflow that can capture the various reservoir model uncertainties at different stages to automatically generate multiple probable model realisations. Proxy models are constructed and used to refine the history match in successive batches. For each prediction development scenario, prediction probabilities are estimated using posterior ensemble of geologically consistent runs that matches historical observed data. The ensemble of reservoir models is automatically evaluated against different possible economic scenarios. The approach presents a seamless and innovative workflow that benefits from new-generation hardware and software, enables faster simultaneous realisations, produces consistent and more reliable reservoir models. Probabilistic economic evaluation concept is implemented to calculate the statistical probabilities of economic indicators.

scholarly journals Comparing impacts of parameter and spatial data uncertainty for a grid-based distributed watershed model

2016 ◽  
Vol 18 (6) ◽  
pp. 961-974 ◽  
Author(s):  
Younggu Her ◽  
Conrad Heatwole
Keyword(s):  
Land Cover ◽  
Parameter Uncertainty ◽  
Input Data ◽  
Hydrologic Model ◽  
Data Uncertainty ◽  
Model Parameters ◽  
Model Output ◽  
Model Errors ◽  
Land Cover Data ◽  
The Impact

Parameter uncertainty in hydrologic modeling is commonly evaluated, but assessing the impact of spatial input data uncertainty in spatially descriptive ‘distributed’ models is not common. This study compares the significance of uncertainty in spatial input data and model parameters on the output uncertainty of a distributed hydrology and sediment transport model, HYdrology Simulation using Time-ARea method (HYSTAR). The Shuffled Complex Evolution Metropolis (SCEM-UA) algorithm was used to quantify parameter uncertainty of the model. Errors in elevation and land cover layers were simulated using the Sequential Gaussian/Indicator Simulation (SGS/SIS) techniques and then incorporated into the model to evaluate their impact on the outputs relative to those of the parameter uncertainty. This study demonstrated that parameter uncertainty had a greater impact on model output than did errors in the spatial input data. In addition, errors in elevation data had a greater impact on model output than did errors in land cover data. Thus, for the HYSTAR distributed hydrologic model, accuracy and reliability can be improved more effectively by refining parameters rather than further improving the accuracy of spatial input data and by emphasizing the topographic data over the land cover data.

scholarly journals The impact of parametric uncertainty and topographic error in ice-sheet modelling

2008 ◽  
Vol 54 (188) ◽  
pp. 899-919 ◽  
Author(s):  
Felix Hebeler ◽  
Ross S. Purves ◽  
Stewart S.R. Jamieson
Keyword(s):  
Heat Flux ◽  
Input Data ◽  
Ice Sheets ◽  
Ice Sheet ◽  
Parametric Uncertainty ◽  
Lapse Rate ◽  
Model Parameters ◽  
Geothermal Heat ◽  
Ice Dynamics ◽  
The Impact

AbstractIce-sheet models (ISMs) developed to simulate the behaviour of continental-scale ice sheets under past, present or future climate scenarios are subject to a number of uncertainties from various sources. These sources include the conceptualization of the ISM and the degree of abstraction and parameterizations of processes such as ice dynamics and mass balance. The assumption of spatially or temporally constant parameters (such as degree-day factor, atmospheric lapse rate or geothermal heat flux) is one example. Additionally, uncertainties in ISM input data such as topography or precipitation propagate to the model results. In order to assess and compare the impact of uncertainties from model parameters and climate on the GLIMMER ice-sheet model, a parametric uncertainty analysis (PUA) was conducted. Parameter variation was deduced from a suite of sensitivity tests, and accuracy information was deduced from input data and the literature. Recorded variation of modelled ice extent across the PUA runs was 65% for equilibrium ice sheets. Additionally, the susceptibility of ISM results to modelled uncertainty in input topography was assessed. Resulting variations in modelled ice extent in the range of 0.8–6.6% are comparable to that of ISM parameters such as flow enhancement, basal traction and geothermal heat flux.

scholarly journals Estimating the impacts and uncertainty of changing spatial input data resolutions on streamflow simulations in two basins

2012 ◽  
Vol 14 (4) ◽  
pp. 902-917 ◽  
Author(s):  
X. Zhang ◽  
G. Hörmann ◽  
N. Fohrer ◽  
J. Gao
Keyword(s):  
Spatial Data ◽  
Input Data ◽  
Distribution Patterns ◽  
Parameter Distribution ◽  
Model Parameters ◽  
Site Analysis ◽  
Daily Streamflow ◽  
Model Efficiency ◽  
Rainfall Runoff Model ◽  
The Impact

The impact of different grid resolutions of spatial input data on modelled river runoff are investigated using the simple rainfall-runoff model KIDS (Kielstau Discharge Simulations) in PCRaster modelling language for two watersheds – Kielstau and XitaoXi. In this study, the grid-based spatial data are aggregated to coarser resolutions to support the multi-resolution, multi-calibration and multi-site analysis for grid-scale investigations. Daily streamflow is simulated and model parameters are calibrated at each spatial resolution. The study suggests that re-calibration is critically needed when the grid resolution is changed. Altering grid sizes has an apparent impact on the parameter distribution patterns. Resolution uncertainty bands obtained by the overlapping hydrographs generated with different resolutions of input data are reported with a sufficient coverage of the observations for both basins. The analysis of model efficiency in terms of IC-ratio (a ratio between the input grid area and the catchment area) indicates that coarser resolutions with an IC-ratio of <0.001 may be used as an effective alternative for conducting preliminary analyses in streamflow simulation for the Kielstau basin. The modelling outputs are more sensitive to the spatial distribution of input data at the XitaoXi watershed, showing that accurate input data are required to achieve optimum modelling performance.

Methods for Restricting Maximum Exposure Rate in Computerized Adaptative Testing

Methodology ◽  
2007 ◽  
Vol 3 (1) ◽  
pp. 14-23 ◽  
Author(s):  
Juan Ramon Barrada ◽  
Julio Olea ◽  
Vicente Ponsoda
Keyword(s):  
Measurement Accuracy ◽  
Computerized Adaptive Testing ◽  
Computation Time ◽  
Adaptive Testing ◽  
Exposure Rate ◽  
Control Parameters ◽  
The Impact ◽  
Two Alternatives ◽  
Selection Of ◽  
Maximum Exposure

Abstract. The Sympson-Hetter (1985) method provides a means of controlling maximum exposure rate of items in Computerized Adaptive Testing. Through a series of simulations, control parameters are set that mark the probability of administration of an item on being selected. This method presents two main problems: it requires a long computation time for calculating the parameters and the maximum exposure rate is slightly above the fixed limit. Van der Linden (2003) presented two alternatives which appear to solve both of the problems. The impact of these methods in the measurement accuracy has not been tested yet. We show how these methods over-restrict the exposure of some highly discriminating items and, thus, the accuracy is decreased. It also shown that, when the desired maximum exposure rate is near the minimum possible value, these methods offer an empirical maximum exposure rate clearly above the goal. A new method, based on the initial estimation of the probability of administration and the probability of selection of the items with the restricted method ( Revuelta & Ponsoda, 1998 ), is presented in this paper. It can be used with the Sympson-Hetter method and with the two van der Linden's methods. This option, when used with Sympson-Hetter, speeds the convergence of the control parameters without decreasing the accuracy.

Estimating OLED Display Device Lifetime from pixel and screen brightness and its application

2019 ◽  
Vol 2019 (1) ◽  
pp. 331-338 ◽  
Author(s):  
Jérémie Gerhardt ◽  
Michael E. Miller ◽  
Hyunjin Yoo ◽  
Tara Akhavan
Keyword(s):  
Image Processing ◽  
Power Consumption ◽  
Model Parameters ◽  
Display Device ◽  
Image Processing Algorithm ◽  
Pixel Value ◽  
Device Lifetime ◽  
The Impact ◽  
Oled Display

In this paper we discuss a model to estimate the power consumption and lifetime (LT) of an OLED display based on its pixel value and the brightness setting of the screen (scbr). This model is used to illustrate the effect of OLED aging on display color characteristics. Model parameters are based on power consumption measurement of a given display for a number of pixel and scbr combinations. OLED LT is often given for the most stressful display operating situation, i.e. white image at maximum scbr, but having the ability to predict the LT for other configurations can be meaningful to estimate the impact and quality of new image processing algorithms. After explaining our model we present a use case to illustrate how we use it to evaluate the impact of an image processing algorithm for brightness adaptation.

Impact of removing ESBL designation from culture reports on the selection of antibiotics for the treatment of infections associated with ESBL-producing organisms

2020 ◽  
Vol 41 (5) ◽  
pp. 604-607 ◽  
Author(s):  
Mark D. Lesher ◽  
Cory M. Hale ◽  
Dona S. S. Wijetunge ◽  
Matt R. England ◽  
Debra S. Myers ◽  
...  
Keyword(s):  
Antimicrobial Stewardship ◽  
Antibiotic Prescribing ◽  
The Impact ◽  
Inhibitor Combination ◽  
Lactamase Inhibitor ◽  
Selection Of

AbstractWe characterized the impact of removal of the ESBL designation from microbiology reports on inpatient antibiotic prescribing. Definitive prescribing of carbapenems decreased from 48.4% to 16.1% (P = .01) and β-lactam–β-lactamase inhibitor combination increased from 19.4% to 61.3% (P = .002). Our findings confirm the importance of collaboration between microbiology and antimicrobial stewardship programs.

scholarly journals The Impact of Alkaloid-Producing Epichloë Endophyte on Forage Ryegrass Breeding: A New Zealand Perspective

Toxins ◽  
2021 ◽  
Vol 13 (2) ◽  
pp. 158
Author(s):  
Colin Eady
Keyword(s):  
Seed Production ◽  
Health Issues ◽  
Abiotic Stressors ◽  
Livestock Health ◽  
The Right ◽  
The Impact ◽  
The Relationship ◽  
And Storage ◽  
Selection Of ◽  
Epichloë Endophyte

For 30 years, forage ryegrass breeding has known that the germplasm may contain a maternally inherited symbiotic Epichloë endophyte. These endophytes produce a suite of secondary alkaloid compounds, dependent upon strain. Many produce ergot and other alkaloids, which are associated with both insect deterrence and livestock health issues. The levels of alkaloids and other endophyte characteristics are influenced by strain, host germplasm, and environmental conditions. Some strains in the right host germplasm can confer an advantage over biotic and abiotic stressors, thus acting as a maternally inherited desirable ‘trait’. Through seed production, these mutualistic endophytes do not transmit into 100% of the crop seed and are less vigorous than the grass seed itself. This causes stability and longevity issues for seed production and storage should the ‘trait’ be desired in the germplasm. This makes understanding the precise nature of the relationship vitally important to the plant breeder. These Epichloë endophytes cannot be ‘bred’ in the conventional sense, as they are asexual. Instead, the breeder may modulate endophyte characteristics through selection of host germplasm, a sort of breeding by proxy. This article explores, from a forage seed company perspective, the issues that endophyte characteristics and breeding them by proxy have on ryegrass breeding, and outlines the methods used to assess the ‘trait’, and the application of these through the breeding, production, and deployment processes. Finally, this article investigates opportunities for enhancing the utilisation of alkaloid-producing endophytes within pastures, with a focus on balancing alkaloid levels to further enhance pest deterrence and improving livestock outcomes.

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