Estimation of prediction uncertainties in oil reservoir. As in all modeling and simulation studies, how the reservoir is defined and whether observed productions can be predicted are important. Uncertainty and 3d reservoir modeling understanding 3d uncertainties. The static reservoir model is usually referred to as the geological model often abbreviated geomodel, and is a digital numerical model describing the initial state of the reservoir before any production of.
Uncertainty analysis in reservoir characterization and management 7 risk apparently refers to vari ability markowitz, 1991, p. 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. A reservoir model is a mathematical representation of a specific volume of rock incorporating all the characteristics of the reservoir under study. Recent developments in modelbased optimization and control of. Since its launch in 2010, resoptima has been working on a suite of software aimed at improving reservoir management. Usually, a single history matched model, conditioned to production data, is obtained. To study the effect of uncertain parameters on the behavior of a reservoir and to forecast the probabilistic.
Read download geostatistical reservoir modeling pdf pdf. Uncertainty analysis should be conducted for investigational analyses, and for. This topic concerns the difference between a reservoir model and a geological model. In underdeveloped reservoirs, there are many uncertain parameters affecting production forecast which plays a main role in reservoir management and decision making in development plan. Conclusion if 3d modeling is now well established as a central piece of an integrated study, the systematic quantification of 3d uncertainties is quite new in our industry. A new procedure to reduce uncertainties in reservoir. Coal seam degasification improves coal mine safety by reducing the gas content of coal seams and also by generating added value as an energy source. This is especially true for coal seam reservoir models that are benchmarked using simultaneous multiwell history matching of well production. Constraining models of fractured reservoirs using seismic. Stochastic reservoir simulation for the modeling of. The state of the art and a sensitivity study, in y. Geological concepts are uncertain with respect to structure, reservoir seal, and hydrocarbon charge.
Uncertainty and risk analysis in petroleum exploration and. Notice that given the pvt data and pressure limits specified, no free gas was. Pdf a reservoir is the result of geologic processes and is not randomly. Quantification of uncertain parameters in oil reservoirs is one of the major issues of concern. When dealing with a hydrocarbon reservoir the possibilities for modeling would be. Example of judy creek reef complex in swan hills, alberta, canada authors y. Uncertainty analysis and reservoir modeling download uncertainty analysis and reservoir modeling ebook pdf or read online books in pdf, epub, and mobi format. It can be considered as a conceptual 3d construction of a single reservoir or in some cases of an oilgas field. 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. Access study documents, get answers to your study questions, and connect with real tutors for engr 2600. Elf exploration production has developed a unique set of tools. Petroleum reservoir simulation, applied science publishers 1979.
Reservoir simulation is the means by which one uses a numerical model of the geological and petrophysical characteristics of a hydrocarbon reservoir to analyze and predict fluid behavior in the. Army corps of engineers institute for water resources, hydrologic engineering center, davis, ca, william. To manage processing and manufacturing systematically, the engineer has to bring together many different techniques and analyses of the interaction between various aspects of the process. Uncertainty analysis of reservoir models featuring the application of workflow editor dr. 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.
Pdf glossary of uncertainty analysis and reservoir modeling. Pdf on dec 1, 2011, zee ma and others published glossary of uncertainty analysis and reservoir modeling find, read and cite all the research you need on researchgate. Students of th e following universities can ask for free copies for personal use. This paper discusses the application of this surrogate reservoir model in analysis and quantification of uncertainties. Pdf integrated 3d reservoir interpretation and modeling. The distance volume allows free hand drawing of horizons to be snapped into place in areas with good horizon candidates figure 4. A new procedure to reduce uncertainties in reservoir models. Uncertainty quantification and sensitivity analysis of. That is, uncertainty in the reservoir characterization and modeling is caused by theuncertainty inthe inputdataand uncertaintyinthe inference, as shown in figure 1. Conclusions interactive reservoir geomodeling from uncertainty is a project that attempts to address some of the main issues of reservoir modeling in the appraisal stage. The pursuit of quantification of the uncertainty space can be organized, intuitively plotted, and adjusted to reach the targeted objective more efficiently. The discipline that encompasses these new approaches is called. Constraining uncertainty in static reservoir modeling.
Interactive reservoir geomodeling from uncertainty is a project that attempts to address some of the main issues of reservoir modeling in the appraisal stage. Uncertainty is a function of our state of knowledge. When it comes to sa, local sensitivity analysis lsa, morris, 1991 is widely used in reservoir engineering dubey et al. The aim of geostatistical reservoir characterization is to utilize wide variety of data, in different scales and accuracies, to construct reservoir models which are able to represent geological heterogeneities and also quantifying uncertainties by producing numbers of equiprobable models. Process modelling and model analysis describes the use of models in process engineering. Click download or read online button to get geostatistical reservoir modeling book now. Balanced between case histories and theory, the chapters in this volume equip experienced practitioners. This study focused on the reservoir modeling case of namorado, an oil field located in offshore brazil, the workflow, tolls and benefits of a 3d integrated study with uncertainties. Using geostatistical realizations as spatial maps of different coal reservoir properties is a more realistic approach than assuming uniform properties across the field. Uncertainty analysis in reservoir characterization and. The static reservoir model is usually referred to as the geological model often abbreviated geomodel, and is a digital numerical model describing the initial state of the reservoir before any production of hydrocarbons has taken place, i. Process modelling and model analysis, volume 4 1st edition. Stochastic reservoir simulation for the modeling of uncertainty in coal seam degasification c.
Uncertainty quantification for static reservoir models geovariances. Understanding the impact of those uncertainties on the production performance is. This results in a set of reservoir models which are geologically consistent and honour the dynamic production data, which ultimately leads to improved predictability. The role and need for simulation depends greatly depend on the geological setting, the production environment onshore versus o shore, and eld maturity. For a reservoir modeling point of view,that would mean. Uncertainty analysis and reservoir modeling request pdf. Pdf uncertainty analysis in reservoir characterization. Modeling and analysis of uncertainty at rensselaer polytechnic institute. Uncertainty modeling and analysis in civil engineering. History matching of the punqs3 reservoir model using proxy. Digital reservoir models may serve different purposes, and we typically distinguish between static reservoir models and dynamic reservoir models 22. Recent developments in computational intelligence, in the area of machine learning in particular, have greatly expanded the capabilities of empir ical modeling.
Experimental design method distributes the simulation runs within uncertain ranges of parameters efficiently, thereby minimizes the number of required runs for studying an uncertain system steppan et al. Read online geostatistical reservoir modeling and download geostatistical reservoir modeling book full in pdf formats. This research introduces a so called full approach to. In fact, this methodology provides a quantified decisionbased plan for minimizing risk in oil reservoirs kloosterman et al.
Second if a behavior of reservoir is highly nonlinear, the number of models may not be sufficient. Reservoir simulation is routinely employed in the prediction of reservoir performance under different depletion and operating scenarios. Mathematical models and finite elements for reservoir. Production curve optimization is also necessary to ensure that maximum recovery is achieved for every well and reservoir. Topdown modeling approaches the reservoir simulation and modeling from an opposite angle. Such uncertainty analyses are based on static and dynamic reservoir models. The procedure can be repeated to improve the h sign of. Download pdf uncertainty analysis and reservoir modeling. Lsa computes sensitivities by perturbing each parameter. The production history is complemented by any other field meas. A new procedure to reduce uncertainties in reservoir simulation models using statistical inference and observed data is presented in this paper. Uncertainty analysis of a giant oil field in the middle east using surrogate reservoir model. The model is then used to forecast future production profiles. Uncertainty analysis in reservoir characterization m96.
It is hoped that the seismic imaging route to reservoir fracture model can help to minimise the interwell uncertainty whilst the use of dfn technology helps. Purchase mathematical models and finite elements for reservoir simulation, volume 17 1st edition. How can we manage risk and subsurface uncertainty in. The benefits of using realistic 3d models for reservoir uncertainty quantification. Uncertainty analysis of reservoir models ldi training. History matching of reservoir models by ensemble kalman. Keywords uncertainty, risk analysis, decision analysis, portfolio. Introduction exploration and production of hydrocarbons1 is a highrisk venture. Geostatistical reservoir modeling download ebook pdf.
It attempts to build a realization of the reservoir by starting with well production behavior history. History matching of the punqs3 reservoir model using. Geological uncertainty about the reservoir geometry and petrophysical properties, due to sparse sampling of the reservoir, is one of the uncertainties that could in. Coupling spatial and frequency uncertainty analyses in reservoir modeling. Developing and managing assets in an uncertain world presents a comprehensive survey of cuttingedge approaches used by industry to quantify the. Asnul bahar introduction uncertainty analysis is an integral part of reservoir modeling process to capture various uncertainties that influence the quality and accuracy of a reservoir model. Developing and managing assets in an uncertain world presents a comprehensive survey of cuttingedge.
Uncertainty analysis is an integral part of reservoir modeling process to capture various uncertainties that influence the quality and accuracy of a reservoir model. In this study, one variable at a time design is used. Uncertainty analysis using monte carlo techniques in the hydrologic modeling system hechms william scharffenberg, hechms lead developer, u. Using geostatistical realizations as spatial maps of different coal reservoir properties is a more realistic approach. The stateoftheart skua modeling platform enables the preservation of all identified faults and stratigraphic constraints. Unii t 6 o b jj e c t o r ii e n t e d s o f t w a r. Moreover, a typical characteristic of these models is a very large uncertainty in the.
Geostatistical simulation allows characterizing uncertainty at each intermediate. When dealing with a hydrocarbon reservoir the possibilities for modeling would be a three dimensional sand pack laboratory model or an electrical model consisting of a network of resistivity and electrical capacities. 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. Uncertainty in the true values of the reservoir properties is sometimes. This site is like a library, use search box in the widget to get ebook that you want. Data derived from various sources are integrated by deterministic or. Pdf uncertainty analysis in reservoir characterization and. Spe 102492 quantifying uncertainties associated with. Coal seam reservoir simulation is one of the most effective ways to help with these two main objectives. Jensenperformance analysis for closedloop reservoir management. Methodology the reservoir model, which was built using physical law rvoir parameters. The field that is the subject of this surrogate reservoir model includes 165.
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. These courseware materials are to be used in conjunction with software engineering. The only remaining possibility is numerical modeling. Sharif university of technology, tehran university, iran university of science and. Pdf mathematical models for oil reservoir simulation. Geo expro the quantification of uncertainty in reservoir. Interactive reservoir geomodelling from uncertainty. The understanding of uncertainties involved in reservoir modeling is an essential tool to support decisions in the petroleum industry. As in all modeling and simulation studies, how the reservoir is defined and whether observed productions can be predicted are important considerations. Please practice handwashing and social distancing, and check out our resources for adapting to these times.
This is achieved through the use of doe mbining the proxy models and historical production an btained using optimization algorithms. Process engineering is all about manufacturingof just about anything. Uncertainty modeling and analysis in civil engineering provides a thorough report on the immediate state of uncertainty modeling and analytical methods for civil engineering systems, presenting a toolbox for solving problems in realworld situations. The text also addresses some typical approaches to modelling specific reservoirs through a mix of case. Click download or read online button to uncertainty analysis and reservoir modeling book pdf for free now. The reservoir grid has been converted back in time to compare the reservoir model with the seismic. Both were tried but without or with very limited success. Define the domain to be investigated collect a representative sample of applications in the domain analyze each application in the sample develop an analysis model for the objects. Observed data is used to guide the obtainment of posterior probability density functions pdf.
In the oil and gas industry, reservoir modeling involves the construction of a computer model of. Oleab aniosh, office of mine safety and health research, pittsburgh, pa, united states busgs, eastern energy resources, reston, va, united states abstract coal seam degasification improves coal mine safety by reducing the gas content of coal seams and. Pdf uncertainty analysis of a giant oil field in the. This study focused on the reservoirmodeling case of namorado, an oil field located in offshore brazil, the workflow, tolls and benefits of a. Our approach data integration, risk assessment and quantification of uncertainty are key issues in petroleum exploration and development. Geological model the rst part of the reservoir model is a mathematical description of the reservoir and its.
The presence of inaccuracies, low data coverage, and a high degree of uncertainty requires a new type of modelling tools. Reservoir uncertainty assessment using machine learning. Mar 1, 2017 spreadsheet modeling and decision analysis 7th edition solutions manual ragsdale free download sample pdf solutions manual, answer keys, test bank stay safe and healthy. The overall project was divided into three main categories. The dynamic reservoir modeling solution uses skua to deliver simulationready reservoir models. Methodology and results the above approach is used in a workflow that helps define a fracture network for two different test seismic datasets. Developing and managing assets in an uncertain world presents a comprehensive survey of cuttingedge approaches used by industry to quantify the uncertainty in both conventional and unconventional reservoirs.
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