Such a decision making includes buyingselling the field, wherewhen to drill wells, how much oil should be. Uncertainty analysis and risk management in reservoir. Use historyconditioned simulation models as a basis for forcasting single field development 3. Specifically, geostatistical reservoir characterization allows for valid construction of a pdf of hydrocarbon volumes and other key reservoir properties. Since all geostatistical methods used in estimation of reservoir parameters are inaccurate, modeling of estimation error in form of uncertainty analysis is very important. Download pdf geostatistical reservoir modeling free. Read download geostatistical reservoir modeling pdf pdf.
Experimental design in petroleum reservoir studies. Integrated reservoir modeling of a pinedale tightgas reservoir in the greater green river basin, wyoming y. Constraining uncertainty in static reservoir modeling. The benefits of using realistic 3d models for reservoir uncertainty quantification. The text puts the focus on geostatistical modelling of facies and heterogeneities that constrain the distribution of reservoir properties including porosity, permeability and water saturation. Uncertainty modeling and analysis in engineering and the sciences presents a holistic view of understanding uncertainty in systems that are of relevance to engineers and scientists in practice, in a more generalized approach, and is a useful book that provides a fundamental understanding to analyzing uncertainty in engineering and scientific. Case study from niger delta, authorakeem arinkola, year2016.
Uncertainty analysis in reservoir characterization and. Geostatistical reservoir modeling download ebook pdf, epub. Commercially available software is used in the construction, simulation and analysis of the reservoir models. There is a shorter, largely nontechnical version, which gives a quick impression of the current and future issues in the analysis of uncertainty in water quality modeling. Our prior beliefs change as we compare the model output with the observed data. This site is like a library, use search box in the widget to get ebook that you want. That is, uncertainty in the reservoir characterization and modeling is caused by theuncertainty inthe inputdataand uncertaintyinthe inference, as shown in figure 1. In bayesian analysis, the posterior probability distribution characterizes the uncertainty in the model parameters estimated from an ensemble of models. The quantification of uncertainty in reservoir management. Part 2 covers reservoir characterization using several geoscience disciplines. The methodology includes using multiple faulted geocellular models s grids covering a range of uncertainty in input parameters with multiplepoint statistical simulation faciesbased modeling, combined static and dynamic experimental design, probabilistic history matching, and use of model building and analysis automation tools. This work critically examines the foremost statistical reservoir uncertainty analysis approaches, the current probabilistic and stochastic uncertainty modelling workflows which are typically based on various numerical models, and the very recent development of embedding some artificial intelligence algorithms which include genetic algorithms.
After nearly 50 yr of production, an updated reservoir model was required for planning further development. Proxy models are used in this paper to estimate production history and uncertainty. In this chapter, we discuss reservoir modeling and uncertainty evaluation of judy creek. This presentation covers only the static part of the modeling and uncertainty integrated workflow of a global study. Judy creek is a large carbonate reservoir in the giant swan hills oil field, located in alberta, canada. This will do the sensitivity analysis of following parametres. Oct 18, 2016 uncertainty and risk are big determining factors in reservoir engineering. Uncertainty analyses of basement fracture reservoir. Uncertainty is a function of our state of knowledge. Pdf glossary of uncertainty analysis and reservoir modeling.
Uncertainty can be modeled, but there is no objective measure of uncertainty. Uncertainty analysis is an integral part of reservoir modeling process to capture various uncertainties that influence the quality and accuracy of a reservoir model. If youd like to know how analytica, the modeling software from lumina, can help you give you the right options for both uncertainty analysis and monte carlo modeling, then try a thirty day free evaluation of analytica to see what it can do for you. To optimize the development plan for an underdeveloped reservoir associated with many uncertain parameters and subjected to this method of enhanced oil recovery, it is necessary to determine the effect of uncertain parameters on the behavior of the oil reservoir. Download pdf geostatistical reservoir modeling free online. In our case make contact is more sensitive than others like as geometrical, petro physical modeling. Correctly sampling from this distribution is therefore essential for accurate quantification of forecasted reservoir performance. Part 3 treats reservoir modeling, resource evaluation and uncertainty analysis using integrated geoscience, engineering and geostatistical methods. Fortunately, using 3d models as the basis for reservoir uncertainty quantification is now feasible due to advances in hardware and the development of reservoir modeling packages. Uncertainty modeling and analysis in engineering and the.
Keep base seed for facies and petrophysical modeling in this steps will calculate number of samples showing variable spreadsheet from case of sensitivity parameters. Petrel uncertainty enables the quantification of not only geophysical and geological uncertainties but also time and pressurebased reservoir uncertainties to provide comprehensive coverage of the quantification of the incertitude. Click download or read online button to get geostatistical reservoir modeling book now. Uncertainty assessment in 3d reservoir modeling an integrated approach uncertainty is not an inherent feature of our reservoirs. Uncertainty analysis and modeling to analyze uncertainty in reservoir characterization and modeling, it is convenient to put it under the framework of a scientific process. Estimation of prediction uncertainties in oil reservoir simulation using bayesian and proxy modelling techniques part i. Quantification of conceptual and parametric uncertainties in fractured reservoir models paul r. Even if the set of models all honour the same data measurements, there is still significant uncertainty in the production forecast. In addition, the author discusses the role of uncertainty analysis in the static model and its impact on volumetric estimation.
A probability distribution always sums up to 1 100%, stating that one of the outcomes covered on the xaxis will certainly come true. Pdf uncertainty analysis in reservoir characterization and. Case studies from the barnett shale and fractured reservoirs in the middle east are just some of the practical. In bayesian analysis, the posterior probability distribution characterizes the uncertainty in. The phrase reservoir characterization is sometimes used to refer to reservoir modeling activities up to the point when a simulation model is ready to simulate the flow of fluids. Geostatistical reservoir modeling download geostatistical reservoir modeling ebook pdf or read online books in pdf, epub, and mobi format. Part of the reservoirmodeling process can use geostatistical methods that consider the spatial nature of geologic data. Basement fracture reservoir is a particular feature with watercut performances compared to other common reservoirs due to extremely high fracture permeability and heterogeneity of reservoir properties. Case example and workflow implementation 18 estimation of prediction uncertainties 1. Uncertainty analysis in reservoir characterization and management 7 risk apparently refers to vari ability markowitz, 1991, p.
Click download or read online button to geostatistical reservoir modeling book pdf for free now. It reveals that, depending on how the solution is going to be used. The reservoir is a deepwater channel system within which 5 individual turbidite channels are identified from wells, from average amplitude maps and from seismic lines. All geostatistical methods used in estimation of reservoir parameters are inaccurate, modeling of estimation error in form of uncertainty analysis is very important. A probability density function or pdf is a mathemat. In recent years, immiscible gas injection, as an effective method for enhanced oil recovery, has been used in many oil reservoirs. Uncertainty analysis in reservoir characterization m96. Developing and managing assets in an uncertain world authors.
Prediction under uncertainty in reservoir mod eling mike christie1, sam subbey1. A geological uncertainty study was initiated to identify and quantify the input parameters of greatest impact in the reservoir model. Reservoir uncertainty assessment using machine learning. Uncertainty analysis in simulation for reservoir management. Uncertainty analysis in welllog and petrophysical interpretations. Download geostatistical reservoir modeling ebook pdf or read online books in pdf, epub, and mobi format. Consequently, the application of sensitivity analysis on stochastic models of reservoir horizons, petrophysical properties, and oilwater. Experimental design in petroleum reservoir studies concentrates on experimental design, a trusted method in reservoir management, to analyze and take the guesswork out of the uncertainties surrounding the underdeveloped reservoir. Reservoir uncertainty assessment using machine learning techniques jincong he abstractpetroleum exploration and production are associated with great risk because of the uncertainty on subsurface conditions. Pdf uncertainty analysis in reservoir characterization. These type of models include but are not limited to petroleum and geothermal reservoir models, groundwater models and surface water hydraulic and hydrologic models. Uncertainty analysis and monte carlo methods analytica. Pdf uncertainty analysis of a co2 sequestration project.
233 753 1522 1278 1354 51 448 48 543 1065 541 778 569 712 1251 350 117 1576 386 627 96 336 1329 695 1271 1134 824 1506 928 1525 1088 653 1236 819 156 297 1044 621 950 1189 1376 1309