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.

A Practical Data Integration Approach to History Matching: Application to a Deepwater Reservoir

SPE Journal ◽  
2006 ◽  
Vol 11 (04) ◽  
pp. 464-479 ◽  
Author(s):  
B. Todd Hoffman ◽  
Jef K. Caers ◽  
Xian-Huan Wen ◽  
Sebastien B. Strebelle
Keyword(s):  
Seismic Data ◽  
History Matching ◽  
Production Data ◽  
Well Log ◽  
Initial Model ◽  
Reservoir Model ◽  
Dynamic Data ◽  
History Match ◽  
Reservoir Models ◽  
Geologic Information

Summary This paper presents an innovative methodology to integrate prior geologic information, well-log data, seismic data, and production data into a consistent 3D reservoir model. Furthermore, the method is applied to a real channel reservoir from the African coast. The methodology relies on the probability-perturbation method (PPM). Perturbing probabilities rather than actual petrophysical properties guarantees that the conceptual geologic model is maintained and that any history-matching-related artifacts are avoided. Creating reservoir models that match all types of data are likely to have more prediction power than methods in which some data are not honored. The first part of the paper reviews the details of the PPM, and the next part of this paper describes the additional work that is required to history-match real reservoirs using this method. Then, a geological description of the reservoir case study is provided, and the procedure to build 3D reservoir models that are only conditioned to the static data is covered. Because of the character of the field, the channels are modeled with a multiple-point geostatistical method. The channel locations are perturbed in a manner such that the oil, water, and gas rates from the reservoir more accurately match the rates observed in the field. Two different geologic scenarios are used, and multiple history-matched models are generated for each scenario. The reservoir has been producing for approximately 5 years, but the models are matched only to the first 3 years of production. Afterward, to check predictive power, the matched models are run for the last 1½ years, and the results compare favorably with the field data. Introduction Reservoir models are constructed to better understand reservoir behavior and to better predict reservoir response. Economic decisions are often based on the predictions from reservoir models; therefore, such predictions need to be as accurate as possible. To achieve this goal, the reservoir model should honor all sources of data, including well-log, seismic, geologic information, and dynamic (production rate and pressure) data. Incorporating dynamic data into the reservoir model is generally known as history matching. History matching is difficult because it poses a nonlinear inverse problem in the sense that the relationship between the reservoir model parameters and the dynamic data is highly nonlinear and multiple solutions are avail- able. Therefore, history matching is often done with a trial-and-error method. In real-world applications of history matching, reservoir engineers manually modify an initial model provided by geoscientists until the production data are matched. The initial model is built based on geological and seismic data. While attempts are usually made to honor these other data as much as possible, often the history-matched models are unrealistic from a geological (and geophysical) point of view. For example, permeability is often altered to increase or decrease flow in areas where a mismatch is observed; however, the permeability alterations usually come in the form of box-shaped or pipe-shaped geometries centered around wells or between wells and tend to be devoid of any geologica. considerations. The primary focus lies in obtaining a history match.

scholarly journals THE IMPACT OF ECONOMIC ANALYSIS METHODS ON PROJECT DECISION-MAKING IN AIRPORT PAVEMENT MANAGEMENT

2021 ◽  
Vol 83 (3) ◽  
pp. 11-19
Author(s):  
Buhaaldeen Mohammed Zaki ◽  
Peyman Babashamsi ◽  
Aini Hazwani Shahrir ◽  
Abdalrhman Milad ◽  
Noor Halizah Abdullah ◽  
...  
Keyword(s):  
Decision Making ◽  
Life Cycle ◽  
Economic Evaluation ◽  
Economic Analysis ◽  
Pavement Management ◽  
Economic Evaluations ◽  
Analysis Methods ◽  
Airport Pavement ◽  
The Impact ◽  
Project Decision

Airports are a part of the world transportation network. Huge investments are made annually for airport pavement construction, maintenances and  rehabilitations. The idea of integrating life-cycle cost analysis (LCCA) and life cycle assessment (LCA) is the latest approach to develop a method for assessing pavement sustainability. In this regard, research on economic evaluation analysis methods has resulted in the development and improvement of pavement management systems (PMS). This paper compares two main economic evaluations which mainly could use in LCCA namely net future value (NFV) and net present Value (NPV). To indicate the effect of economic evaluation a case study is examined. In this research LCCA comprises three main components which are direct costs, indirect costs, and salvage value. Airport Revenue Reduction Cost (ARRC) and Airline Delay Cost (ADC) considered as two specific indirect/user costs. The results show the impact of different economic analysis method on project decision-making where the use of crack sealing overlay (CSOL) is 35.8% and 28.3% more cost-effective than Portland cement concrete (PCC) and hot-mix asphalt (HMA), respectively.

scholarly journals Guidance for Demonstrating the Societal Value of new Antibiotics

2021 ◽  
Vol 11 ◽  
Author(s):  
Steven Simoens ◽  
Isabel Spriet
Keyword(s):  
Economic Evaluation ◽  
Disease Transmission ◽  
Good Practice ◽  
Population Level ◽  
Antibiotic Use ◽  
Economic Evaluations ◽  
Discussion Paper ◽  
Societal Value ◽  
New Antibiotics ◽  
The Impact

Given that antibiotic use is associated with externalities, standard economic evaluation which considers costs and health gains accruing to patients under-values antibiotics. Informed by a scoping review, this discussion paper aims to identify the societal value elements of antibiotics and to provide guidance on how these value elements can be incorporated in economic evaluation. With a view to appropriately quantify the societal value of antibiotics, there is a need for good practice guidelines on the methodology of economic evaluation for such products. We argue that it is important to assess antibiotics at population level to account for their transmission, diversity, insurance, spectrum, novel action and enablement values. In addition to the value of antibiotics to infected patients, economic evaluations need to use modeling approaches to explore the impact of different modes of employing new and existing antibiotics (for example, as last resort treatment) on disease transmission and resistance development in current and future patients. Hence, assessing the value of antibiotics also involves an ethical dimension. Further work is required about how the multiple value elements of antibiotics are linked to each other and how they can be aggregated.

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.

Some Practical Issues on Real-Time Reservoir Model Updating Using Ensemble Kalman Filter

SPE Journal ◽  
2007 ◽  
Vol 12 (02) ◽  
pp. 156-166 ◽  
Author(s):  
Xian-Huan Wen ◽  
Wen H. Chen
Keyword(s):  
Real Time ◽  
Ensemble Kalman Filter ◽  
Closed Loop ◽  
Model Updating ◽  
Reservoir Management ◽  
Time Interval ◽  
Ensemble Size ◽  
Reservoir Model ◽  
Reservoir Models ◽  
The Impact

Summary The concept of "closed-loop" reservoir management is currently receiving considerable attention in the petroleum industry. A "real-time" or "continuous" reservoir model updating technique is a critical component for the feasible application of any closed-loop, model-based reservoir management process. This technique should be able to rapidly and continuously update reservoir models assimilating the up-to-date observations of production data so that the performance predictions and the associated uncertainty are up-to-date for optimization of future development/operations. The ensemble Kalman filter (EnKF) method has been shown to be quite efficient for this purpose in large-scale nonlinear systems. Previous studies show that a relatively large ensemble size is required for EnKF to reliably assess the uncertainty, and a confirming step is recommended to ensure the consistency of the updated static and dynamic variables with the flow equations. In this paper, we further explore the capability of EnKF, focusing on some practical issues including the correction of the linear and Gaussian assumptions during filter updating with iteration, the reduction of ensemble size with a resampling scheme, and the impact of data assimilation time interval. Results from the example in this paper demonstrate that the proposed iterative EnKF performs better with more accurate predictions and less uncertainty than the traditional noniterative EnKF. The use of iteration reduces the impact of nonlinearity and non-Gaussianity. Results also show that iteration may only be required when predictions are considerably deviated from the observations. The proposed resampling scheme can significantly reduce the ensemble size necessary for reliable assessment of uncertainty with improved accuracy. Finally, we show that the noniterative EnKF is sensitive to the size of time interval between the assimilation steps. Using the proposed iterative EnKF, results are more stable, more accurate reservoir models and predictions can be obtained even when a large time interval is used. This also indicates that iteration within the EnKF updating serves as a process that corrects the stronger nonlinear and non-Gaussian behaviors when larger time interval is used. Introduction Reservoir models have become an important part of day-to-day decision analysis related to management of oil/gas fields. The closed-loop reservoir management concept (Jansen et al. 2005) allows real-time decisions to be made that maximize the production potential of a reservoir. These decisions are based on the most current information available about the reservoir model and the associated uncertainty of the information. One critical requirement in this real-time, model-based reservoir management process is the ability to rapidly estimate the reservoir models and the associated uncertainty reflecting the most current production data in a real-time fashion. Based on a number of studies, the EnKF method was shown to be well-suited for such applications compared to the traditional history-matching (HM) methods (Evensen 1999; Gu and Oliver 2006; Wen and Chen 2006).

Integrated Work Flow of Preserving Facies Realism in History Matching: Application to the Brugge Field

SPE Journal ◽  
2016 ◽  
Vol 21 (04) ◽  
pp. 1413-1424 ◽  
Author(s):  
Yuqing Chang ◽  
Andreas S. Stordal ◽  
Randi Valestrand
Keyword(s):  
Data Assimilation ◽  
History Matching ◽  
Gaussian Mixture ◽  
Work Flow ◽  
Model Parameters ◽  
Complex Field ◽  
Reservoir Model ◽  
Reservoir Properties ◽  
Reservoir Models ◽  
Probability Maps

Summary Data assimilation with ensemble-based inversion methods was successfully applied for parameter estimation in reservoir models. However, in certain complex-reservoir models, it remains challenging to estimate the model parameters and to preserve the geological realism simultaneously. In particular, when handling special-reservoir model parameters such as facies types concerning fluvial channels, one must realize that geological realism becomes one of the key concerns. The main objective of this work is to address these issues for a complex field with a newly extended version of a recently proposed facies-parameterization approach coupled with an ensemble-based data assimilation method. The proposed workflow combines the new facies parameterization and the adaptive gaussian mixture (AGM) filter into the data assimilation framework for channelized reservoirs. To handle discrete-facies parameters, we combine probability maps and truncated Gaussian fields to obtain a continuous parameterization of the facies fields. For the data assimilation, we use the AGM filter, which is an efficient history matching approach that incorporates a resampling routine that allows us to regenerate facies fields with information from the updated probability maps. This work flow is evaluated, for the first time, on a complex field case—the Brugge field. This reservoir model consists of layers with complex channelized structures and layers characterized by reservoir properties generated with variograms. With limited prior knowledge on the facies model, this work flow is shown to be able to preserve the channel continuity while reducing the reservoir model uncertainty with AGM. When applied to a complex reservoir, the proposed work flow provides a geologically consistent and realistic reservoir model that leads to improved capability of predicting subsurface flow behaviors.

scholarly journals A cost–benefit analysis framework for preventive health interventions to aid decision-making in Australian governments

2021 ◽  
Vol 19 (1) ◽  
Author(s):  
Jaithri Ananthapavan ◽  
Marj Moodie ◽  
Andrew Milat ◽  
Lennert Veerman ◽  
Elizabeth Whittaker ◽  
...  
Keyword(s):  
Decision Making ◽  
Economic Evaluation ◽  
Cost Benefit Analysis ◽  
Cost Benefit ◽  
Preventive Health ◽  
Health Interventions ◽  
Economic Evaluations ◽  
Benefit Analysis ◽  
Analysis Framework ◽  
The Impact

Abstract Background Australian governments are increasingly mandating the use of cost–benefit analysis (CBA) to inform the efficient allocation of government resources. CBA is likely to be useful when evaluating preventive health interventions that are often cross-sectoral in nature and require Cabinet approval prior to implementation. This study outlines a CBA framework for the evaluation of preventive health interventions that balances the need for consistency with other agency guidelines whilst adhering to guidelines and conventions for health economic evaluations. Methods We analysed CBA and other evaluation guidance documents published by Australian federal and New South Wales (NSW) government departments. Data extraction compared the recommendations made by different agencies and the impact on the analysis of preventive health interventions. The framework specifies a reference case and sensitivity analyses based on the following considerations: (1) applied economic evaluation theory; (2) consistency between CBA across different government departments; (3) the ease of moving from a CBA to a more conventional cost-effectiveness/cost-utility analysis framework often used for health interventions; (4) the practicalities of application; and (5) the needs of end users being both Cabinet decision-makers and health policy-makers. Results Nine documents provided CBA or relevant economic evaluation guidance. There were differences in terminology and areas of agreement and disagreement between the guidelines. Disagreement between guidelines involved (1) the community included in the societal perspective; (2) the number of options that should be appraised in ex ante analyses; (3) the appropriate time horizon for interventions with longer economic lives; (4) the theoretical basis and value of the discount rate; (5) parameter values for variables such as the value of a statistical life; and (6) the summary measure for decision-making. Conclusions This paper addresses some of the methodological challenges that have hindered the use of CBA in prevention by outlining a framework that is consistent with treasury department guidelines whilst considering the unique features of prevention policies. The effective use and implementation of a preventive health CBA framework is likely to require considerable investment of time and resources from state and federal government departments of health and treasury but has the potential to improve decision-making related to preventive health policies and programmes.

Real-Time Reservoir Model Updating Using Ensemble Kalman Filter With Confirming Option

SPE Journal ◽  
2006 ◽  
Vol 11 (04) ◽  
pp. 431-442 ◽  
Author(s):  
Xian-Huan Wen ◽  
Wen H. Chen
Keyword(s):  
Real Time ◽  
Ensemble Kalman Filter ◽  
History Matching ◽  
Model Updating ◽  
Production Data ◽  
Reservoir Model ◽  
Automatic History Matching ◽  
Flow Equations ◽  
Matching Process ◽  
Reservoir Models

Summary The ensemble Kalman Filter technique (EnKF) has been reported to be very efficient for real-time updating of reservoir models to match the most current production data. Using EnKF, an ensemble of reservoir models assimilating the most current observations of production data is always available. Thus, the estimations of reservoir model parameters, and their associated uncertainty, as well as the forecasts are always up-to-date. In this paper, we apply the EnKF for continuously updating an ensemble of permeability models to match real-time multiphase production data. We improve the previous EnKF by adding a confirming option (i.e., the flow equations are re-solved from the previous assimilating step to the current step using the updated current permeability models). By doing so, we ensure that the updated static and dynamic parameters are always consistent with the flow equations at the current step. However, it also creates some inconsistency between the static and dynamic parameters at the previous step where the confirming starts. Nevertheless, we show that, with the confirming approach, the filter shows better performance for the particular example investigated. We also investigate the sensitivity of using a different number of realizations in the EnKF. Our results show that a relatively large number of realizations are needed to obtain stable results, particularly for the reliable assessment of uncertainty. The sensitivity of using different covariance functions is also investigated. The efficiency and robustness of the EnKF is demonstrated using an example. By assimilating more production data, new features of heterogeneity in the reservoir model can be revealed with reduced uncertainty, resulting in more accurate predictions of reservoir production. Introduction The reliability of reservoir models could increase as more data are included in their construction. Traditionally, static (hard and soft) data, such as geological, geophysical, and well log/core data are incorporated into reservoir geological models through conditional geostatistical simulation (Deutsch and Journel 1998). Dynamic production data, such as historical measurements of reservoir production, account for the majority of reservoir data collected during the production phase. These data are directly related to the recovery process and to the response variables that form the basis for reservoir management decisions. Incorporation of dynamic data is typically done through a history-matching process. Traditionally, history matching adjusts model variables (such as permeability, porosity, and transmissibility) so that the flow simulation results using the adjusted parameters match the observations. It usually requires repeated flow simulations. Both manual and (semi-) automatic history-matching processes are available in the industry (Chen et al. 1974; He et al. 1996; Landa and Horne 1997; Milliken and Emanuel 1998; Vasco et al. 1998; Wen et al. 1998a, 1998b; Roggero and Hu 1998; Agarwal and Blunt 2003; Caers 2003; Cheng et al. 2004). Automatic history matching is usually formulated in the form of a minimization problem in which the mismatch between measurements and computed values is minimized (Tarantola 1987; Sun 1994). Gradient-based methods are widely employed for such minimization problems, which require the computation of sensitivity coefficients (Li et al. 2003; Wen et al. 2003; Gao and Reynolds 2006). In the recent decade, automatic history matching has been a very active research area with significant progress reported (Cheng et al. 2004; Gao and Reynolds 2006; Wen et al. 1997). However, most approaches are either limited to small and simple reservoir models or are computationally too intensive for practical applications. Under the framework of traditional history matching, the assessment of uncertainty is usually through a repeated history-matching process with different initial models, which makes the process even more CPU-demanding. In addition, the traditional history-matching methods are not designed in such a fashion that allows for continuous model updating. When new production data are available and are required to be incorporated, the history-matching process has to be repeated using all measured data. These limit the efficiency and applicability of the traditional automatic history-matching techniques.

scholarly journals Protocol for an economic evaluation alongside a cluster randomised controlled trial: cost-effectiveness of Learning Clubs, a multicomponent intervention to improve women’s health and infant’s health and development in Vietnam

BMJ Open ◽  
2019 ◽  
Vol 9 (12) ◽  
pp. e031721
Author(s):  
Trang Nguyen ◽  
Kim Sweeny ◽  
Thach Tran ◽  
Stanley Luchters ◽  
David B Hipgrave ◽  
...  
Keyword(s):  
Economic Evaluation ◽  
Cost Effectiveness ◽  
Randomised Controlled Trial ◽  
Controlled Trial ◽  
Cluster Randomised Controlled Trial ◽  
Economic Evaluations ◽  
Cluster Randomised ◽  
Life Years ◽  
Randomised Controlled ◽  
The Impact

IntroductionEconomic evaluations of complex interventions in early child development are required to guide policy and programme development, but a few are yet available.Methods and analysisAlthough significant gains have been made in maternal and child health in resource-constrained environments, this has mainly been concentrated on improving physical health. The Learning Clubs programme addresses both physical and mental child and maternal health. This study is an economic evaluation of a cluster randomised controlled trial of the impact of the Learning Clubs programme in Vietnam. It will be conducted from a societal perspective and aims to identify the cost-effectiveness and the economic and social returns of the intervention. A total of 1008 pregnant women recruited from 84 communes in a rural province in Vietnam will be included in the evaluation. Health and cost data will be gathered at three stages of the trial and used to calculate incremental cost-effectiveness ratios per percentage point improvement of infant’s development, infant’s health and maternal common mental disorders expressed in quality-adjusted life years gained. The return on investment will be calculated based on improvements in productivity, the results being expressed as benefit–cost ratios.Ethics and disseminationThe trial was approved by Monash University Human Research Ethics Committee (Certificate Number 2016–0683), Australia, and approval was extended to include the economic evaluation (Amendment Review Number 2018-0683-23806); and the Institutional Review Board of the Hanoi School of Public Health (Certificate Number 017-377IDD- YTCC), Vietnam. Results will be disseminated through academic journals and conference presentations.Trial registration numberACTRN12617000442303.

scholarly journals EXPERT ECONOMIC EVALUATION OF MINERAL RESOURCES IN THE FUNCTION OF ENVIRONMENTAL PROTECTION

2016 ◽  
Vol 4 (5) ◽  
pp. 106-114
Author(s):  
Radule Tosovic
Keyword(s):  
Economic Evaluation ◽  
Raw Materials ◽  
Mineral Resources ◽  
Mineral Deposits ◽  
Economic Evaluations ◽  
Successful Operation ◽  
Mineral Raw Materials ◽  
Modern Business ◽  
Expert Analysis ◽  
The Impact

The successful operation of the mineral sector in modern business conditions, labeled by transition crossing to a market mineral economy and establishing market conditions for the production and trade of mineral raw materials, requires the development of expert economic evaluations of mineral reserves and resources. This evaluation basically represents an expert analysis, which includes four important aspects, namely: geological, mining, economical and environmental. The ecological aspect is related to the previous geoecological analysis of the impact of various phases of the conquest of mineral deposits on the environment, by identifying types of impacts, character of influences, prevention of pollution measures, measures to eliminate the impact and recultivation. Expert economic evaluation is to quantify environmental costs, analyzing their share in the total costs and impact on the economic viability of valorization of mineral raw materials from the mineral deposits.

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