998 resultados para Reservoir model
Resumo:
Uncertainty quantification of petroleum reservoir models is one of the present challenges, which is usually approached with a wide range of geostatistical tools linked with statistical optimisation or/and inference algorithms. Recent advances in machine learning offer a novel approach to model spatial distribution of petrophysical properties in complex reservoirs alternative to geostatistics. The approach is based of semisupervised learning, which handles both ?labelled? observed data and ?unlabelled? data, which have no measured value but describe prior knowledge and other relevant data in forms of manifolds in the input space where the modelled property is continuous. Proposed semi-supervised Support Vector Regression (SVR) model has demonstrated its capability to represent realistic geological features and describe stochastic variability and non-uniqueness of spatial properties. On the other hand, it is able to capture and preserve key spatial dependencies such as connectivity of high permeability geo-bodies, which is often difficult in contemporary petroleum reservoir studies. Semi-supervised SVR as a data driven algorithm is designed to integrate various kind of conditioning information and learn dependences from it. The semi-supervised SVR model is able to balance signal/noise levels and control the prior belief in available data. In this work, stochastic semi-supervised SVR geomodel is integrated into Bayesian framework to quantify uncertainty of reservoir production with multiple models fitted to past dynamic observations (production history). Multiple history matched models are obtained using stochastic sampling and/or MCMC-based inference algorithms, which evaluate posterior probability distribution. Uncertainty of the model is described by posterior probability of the model parameters that represent key geological properties: spatial correlation size, continuity strength, smoothness/variability of spatial property distribution. The developed approach is illustrated with a fluvial reservoir case. The resulting probabilistic production forecasts are described by uncertainty envelopes. The paper compares the performance of the models with different combinations of unknown parameters and discusses sensitivity issues.
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Due to the increase in water demand and hydropower energy, it is getting more important to operate hydraulic structures in an efficient manner while sustaining multiple demands. Especially, companies, governmental agencies, consultant offices require effective, practical integrated tools and decision support frameworks to operate reservoirs, cascades of run-of-river plants and related elements such as canals by merging hydrological and reservoir simulation/optimization models with various numerical weather predictions, radar and satellite data. The model performance is highly related with the streamflow forecast, related uncertainty and its consideration in the decision making. While deterministic weather predictions and its corresponding streamflow forecasts directly restrict the manager to single deterministic trajectories, probabilistic forecasts can be a key solution by including uncertainty in flow forecast scenarios for dam operation. The objective of this study is to compare deterministic and probabilistic streamflow forecasts on an earlier developed basin/reservoir model for short term reservoir management. The study is applied to the Yuvacık Reservoir and its upstream basin which is the main water supply of Kocaeli City located in the northwestern part of Turkey. The reservoir represents a typical example by its limited capacity, downstream channel restrictions and high snowmelt potential. Mesoscale Model 5 and Ensemble Prediction System data are used as a main input and the flow forecasts are done for 2012 year using HEC-HMS. Hydrometeorological rule-based reservoir simulation model is accomplished with HEC-ResSim and integrated with forecasts. Since EPS based hydrological model produce a large number of equal probable scenarios, it will indicate how uncertainty spreads in the future. Thus, it will provide risk ranges in terms of spillway discharges and reservoir level for operator when it is compared with deterministic approach. The framework is fully data driven, applicable, useful to the profession and the knowledge can be transferred to other similar reservoir systems.
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This presentation describes research at Montana Tech to improve oil recovery rates in the Elm Coulee Oil Field in the Bakken Reservoir, Richmond County, Montana. The slides display current recovery rate predictions, enhanced oil recovery methods, reservoir model building and history matching strategies. Recommended development strategies include implementing hydrocarbon gas injection operations to improve current oil recovery rates by more than 75%. The impact of increased production on Production Engineers is also described. The Principal Investigators include John Evans, Leo Heath, David Reichhardt and Burt Todd in the Petroleum Engineering Department.
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Numerous studies have proven an effect of a probable climate change on the hydrosphere’s different subsystems. In the 21st century global and regional redistribution of water has to be expected and it is very likely that extreme weather phenomenon will occur more frequently. From a global view the flood situation will exacerbate. In contrast to these discoveries the classical approach of flood frequency analysis provides terms like “mean flood recurrence interval”. But for this analysis to be valid there is a need for the precondition of stationary distribution parameters which implies that the flood frequencies are constant in time. Newer approaches take into account extreme value distributions with time-dependent parameters. But the latter implies a discard of the mentioned old terminology that has been used up-to-date in engineering hydrology. On the regional scale climate change affects the hydrosphere in various ways. So, the question appears to be whether in central Europe the classical approach of flood frequency analysis is not usable anymore and whether the traditional terminology should be renewed. In the present case study hydro-meteorological time series of the Fulda catchment area (6930 km²), upstream of the gauging station Bonaforth, are analyzed for the time period 1960 to 2100. At first a distributed catchment area model (SWAT2005) is build up, calibrated and finally validated. The Edertal reservoir is regulated as well by a feedback control of the catchments output in case of low water. Due to this intricacy a special modeling strategy has been necessary: The study area is divided into three SWAT basin models and an additional physically-based reservoir model is developed. To further improve the streamflow predictions of the SWAT model, a correction by an artificial neural network (ANN) has been tested successfully which opens a new way to improve hydrological models. With this extension the calibration and validation of the SWAT model for the Fulda catchment area is improved significantly. After calibration of the model for the past 20th century observed streamflow, the SWAT model is driven by high resolution climate data of the regional model REMO using the IPCC scenarios A1B, A2, and B1, to generate future runoff time series for the 21th century for the various sub-basins in the study area. In a second step flood time series HQ(a) are derived from the 21st century runoff time series (scenarios A1B, A2, and B1). Then these flood projections are extensively tested with regard to stationarity, homogeneity and statistical independence. All these tests indicate that the SWAT-predicted 21st-century trends in the flood regime are not significant. Within the projected time the members of the flood time series are proven to be stationary and independent events. Hence, the classical stationary approach of flood frequency analysis can still be used within the Fulda catchment area, notwithstanding the fact that some regional climate change has been predicted using the IPCC scenarios. It should be noted, however, that the present results are not transferable to other catchment areas. Finally a new method is presented that enables the calculation of extreme flood statistics, even if the flood time series is non-stationary and also if the latter exhibits short- and longterm persistence. This method, which is called Flood Series Maximum Analysis here, enables the calculation of maximum design floods for a given risk- or safety level and time period.
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The Delaware River provides half of New York City's drinking water, is a habitat for wild trout, American shad and the federally endangered dwarf wedge mussel. It has suffered four 100‐year floods in the last seven years. A drought during the 1960s stands as a warning of the potential vulnerability of the New York City area to severe water shortages if a similar drought were to recur. The water releases from three New York City dams on the Delaware River's headwaters impact not only the reliability of the city’s water supply, but also the potential impact of floods, and the quality of the aquatic habitat in the upper river. The goal of this work is to influence the Delaware River water release policies (FFMP/OST) to further benefit river habitat and fisheries without increasing New York City's drought risk, or the flood risk to down basin residents. The Delaware water release policies are constrained by the dictates of two US Supreme Court Decrees (1931 and 1954) and the need for unanimity among four states: New York, New Jersey, Pennsylvania, and Delaware ‐‐ and New York City. Coordination of their activities and the operation under the existing decrees is provided by the Delaware River Basin Commission (DRBC). Questions such as the probability of the system approaching drought state based on the current FFMP plan and the severity of the 1960s drought are addressed using long record paleo‐reconstructions of flows. For this study, we developed reconstructed total annual flows (water year) for 3 reservoir inflows using regional tree rings going back upto 1754 (a total of 246 years). The reconstructed flows are used with a simple reservoir model to quantify droughts. We observe that the 1960s drought is by far the worst drought based on 246 years of simulations (since 1754).
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The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found
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Steam injection is a method usually applied to very viscous oils and consists of injecting heat to reduce the viscosity and, therefore, increase the oil mobility, improving the oil production. For designing a steam injection project it is necessary to have a reservoir simulation in order to define the various parameters necessary for an efficient heat reservoir management, and with this, improve the recovery factor of the reservoir. The purpose of this work is to show the influence of the coupled wellbore/reservoir on the thermal simulation of reservoirs under cyclic steam stimulation. In this study, the methodology used in the solution of the problem involved the development of a wellbore model for the integration of steam flow model in injection wellbores, VapMec, and a blackoil reservoir model for the injection of cyclic steam in oil reservoirs. Thus, case studies were developed for shallow and deep reservoirs, whereas the usual configurations of injector well existing in the oil industry, i.e., conventional tubing without packer, conventional tubing with packer and insulated tubing with packer. A comparative study of the injection and production parameters was performed, always considering the same operational conditions, for the two simulation models, non-coupled and a coupled model. It was observed that the results are very similar for the specified well injection rate, whereas significant differences for the specified well pressure. Finally, on the basis of computational experiments, it was concluded that the influence of the coupled wellbore/reservoir in thermal simulations using cyclic steam injection as an enhanced oil recovery method is greater for the specified well pressure, while for the specified well injection rate, the steam flow model for the injector well and the reservoir may be simulated in a non- coupled way
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Thermal methods made heavy oil production possible in fields where primary recovery failed. Throughout the years steam injection became one of the most important alternatives to increase heavy oil recovery. There are many types of steam injection, and one of them is the cyclic steam injection, which has been used with success in several countries, including Brazil. The process involves three phases: firstly, steam is injected, inside of the producing well; secondly, the well is closed (soak period); and finally, the well is put back into production. These steps constitute one cycle. The cycle is repeated several times until economical production limit is reached. Usually, independent of reservoir type, as the number of cycles increases the cyclic injection turns less efficient. This work aims to analyze rock and reservoir property influence in the cyclic steam injection. The objective was to study the ideal number of cycles and, consequently, process optimization. Simulations were realized using the STARS simulator from the CMG group based in a proposed reservoir model. It was observed that the reservoir thickness was the most important parameter in the process performance, whilst soaking time influence was not significant
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The history match procedure in an oil reservoir is of paramount importance in order to obtain a characterization of the reservoir parameters (statics and dynamics) that implicates in a predict production more perfected. Throughout this process one can find reservoir model parameters which are able to reproduce the behaviour of a real reservoir.Thus, this reservoir model may be used to predict production and can aid the oil file management. During the history match procedure the reservoir model parameters are modified and for every new set of reservoir model parameters found, a fluid flow simulation is performed so that it is possible to evaluate weather or not this new set of parameters reproduces the observations in the actual reservoir. The reservoir is said to be matched when the discrepancies between the model predictions and the observations of the real reservoir are below a certain tolerance. The determination of the model parameters via history matching requires the minimisation of an objective function (difference between the observed and simulated productions according to a chosen norm) in a parameter space populated by many local minima. In other words, more than one set of reservoir model parameters fits the observation. With respect to the non-uniqueness of the solution, the inverse problem associated to history match is ill-posed. In order to reduce this ambiguity, it is necessary to incorporate a priori information and constraints in the model reservoir parameters to be determined. In this dissertation, the regularization of the inverse problem associated to the history match was performed via the introduction of a smoothness constraint in the following parameter: permeability and porosity. This constraint has geological bias of asserting that these two properties smoothly vary in space. In this sense, it is necessary to find the right relative weight of this constrain in the objective function that stabilizes the inversion and yet, introduces minimum bias. A sequential search method called COMPLEX was used to find the reservoir model parameters that best reproduce the observations of a semi-synthetic model. This method does not require the usage of derivatives when searching for the minimum of the objective function. Here, it is shown that the judicious introduction of the smoothness constraint in the objective function formulation reduces the associated ambiguity and introduces minimum bias in the estimates of permeability and porosity of the semi-synthetic reservoir model
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Pós-graduação em Engenharia Mecânica - FEG
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BTES (borehole thermal energy storage)systems exchange thermal energy by conduction with the surrounding ground through borehole materials. The spatial variability of the geological properties and the space-time variability of hydrogeological conditions affect the real power rate of heat exchangers and, consequently, the amount of energy extracted from / injected into the ground. For this reason, it is not an easy task to identify the underground thermal properties to use when designing. At the current state of technology, Thermal Response Test (TRT) is the in situ test for the characterization of ground thermal properties with the higher degree of accuracy, but it doesn’t fully solve the problem of characterizing the thermal properties of a shallow geothermal reservoir, simply because it characterizes only the neighborhood of the heat exchanger at hand and only for the test duration. Different analytical and numerical models exist for the characterization of shallow geothermal reservoir, but they are still inadequate and not exhaustive: more sophisticated models must be taken into account and a geostatistical approach is needed to tackle natural variability and estimates uncertainty. The approach adopted for reservoir characterization is the “inverse problem”, typical of oil&gas field analysis. Similarly, we create different realizations of thermal properties by direct sequential simulation and we find the best one fitting real production data (fluid temperature along time). The software used to develop heat production simulation is FEFLOW 5.4 (Finite Element subsurface FLOW system). A geostatistical reservoir model has been set up based on literature thermal properties data and spatial variability hypotheses, and a real TRT has been tested. Then we analyzed and used as well two other codes (SA-Geotherm and FV-Geotherm) which are two implementation of the same numerical model of FEFLOW (Al-Khoury model).
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The success achieved by thermal methods of recovery, in heavy oils, prompted the emergence of studies on the use of electromagnetic waves as heat generating sources in oil reservoirs. Thus, this generation is achieved by three types of different processes according to the frequency range used. They are: the electromagnetic induction heating, the resistive and the dielectric, also known as radiation. This study was based on computer simulations in oil reservoirs with characteristics similar to those found in the sedimentary basins of the Brazilian Northeast. All cases studied were simulated using the software STARS, CMG (Computer Group, version 2012.10 Modeling). Some simulations took into account the inclusion of electrically sensitive particles in certain sectors of the reservoir model studied by fracturing. The purpose of this work is the use of the electromagnetic induction heating as a recovery method of heavy oil, to check the influence of these aforementioned particles on the reservoir model used. Comparative analyses were made involving electromagnetic induction heating, the operation of hydraulic fracturing and the injection of water to the different situations of the reservoir model studied. It was found that fracturing the injection well in order that the electromagnetic heating occurs in the same well where there is water injection, there was a considerable increase in the recovery factor and in the cumulative oil production in relation to the models in which hydraulic fracturing occurred in the production well and water injection in the injection well. This is due to the generation of steam in situ in the reservoir.
Resumo:
The pre-salt province is composed by large amounts of light oil and with good quality, a reality that puts Brazil in a strategic position facing the great demand for energy worldwide. In this province are the largest discoveries in the world in the last ten years; areas as Libra, Franco and Lula field, everyone containing volumes greater than 8 billion recoverable oil barrels. To develop and optimize the production of these fields, a study was done for choosing the improved oil recovery methods. The main motivations were the presence of carbon dioxide (CO2) as a contaminant and the strategic decision of do not discard it, combined with high GOR (gas-oil ratio) of the reservoir fluid. The method should take advantage of the unique abundant resources: seawater and produced gas. This way, the process of matching these resources in the water alterning gas injection (WAG) became a good option. In this master’s dissertation, it was developed a reservoir model with average characteristics of the Brazilian pre-salt, where was applied the improved oil recovery method of water alternating gas. The production of this reservoir was analyzed by parameters as: the first fluid injected in the injection process, position of the injection wells completion, injection water and gas rate and cycle time. The results showed a good performance of the method, with up to 26% of gains in the recovery factor regarding the primary recovery, since the application of water injection and gas, individually, was not able to overcome 10 % of gain. The most influential parameter found in the results was the cycle time, with higher recovery factor values obtained with the use of shorter times.
Resumo:
The objective of the thermal recovery is to heat the resevoir and the oil in it to increase its recovery. In the Potiguar river basin there are located several heavy oil reservoirs whose primary recovery energy provides us with a little oil flow, which makes these reservoirs great candidates for application of a method of recovery advanced of the oil, especially the thermal. The steam injection can occur on a cyclical or continuous manner. The continuous steam injection occurs through injection wells, which in its vicinity form a zone of steam that expands itself, having as a consequence the displace of the oil with viscosity and mobility improved towards the producing wells. Another possible mechanism of displacement of oil in reservoirs subjected to continuous injection of steam is the distillation of oil by steam, which at high temperatures; their lighter fractions can be vaporized by changing the composition of the oil produced, of the oil residual or to shatter in the amount of oil produced. In this context, this paper aims to study the influence of compositional models in the continuous injection of steam through in the analysis of some parameters such as flow injection steam and temperature of injection. Were made various leading comparative analysis taking the various models of fluid, varying from a good elementary, with 03 pseudocomponents to a modeling of fluids with increasing numbers of pseudocomponents. A commercial numerical simulator was used for the study from a homogeneous reservoir model with similar features to those found in northeastern Brazil. Some conclusions as the increasing of the simulation time with increasing number of pseudocomponents, the significant influence of flow injection on cumulative production of oil and little influence of the number of pseudocomponents in the flows and cumulative production of oil were found
Resumo:
Steam injection is a method usually applied to very viscous oils and consists of injecting heat to reduce the viscosity and, therefore, increase the oil mobility, improving the oil production. For designing a steam injection project it is necessary to have a reservoir simulation in order to define the various parameters necessary for an efficient heat reservoir management, and with this, improve the recovery factor of the reservoir. The purpose of this work is to show the influence of the coupled wellbore/reservoir on the thermal simulation of reservoirs under cyclic steam stimulation. In this study, the methodology used in the solution of the problem involved the development of a wellbore model for the integration of steam flow model in injection wellbores, VapMec, and a blackoil reservoir model for the injection of cyclic steam in oil reservoirs. Thus, case studies were developed for shallow and deep reservoirs, whereas the usual configurations of injector well existing in the oil industry, i.e., conventional tubing without packer, conventional tubing with packer and insulated tubing with packer. A comparative study of the injection and production parameters was performed, always considering the same operational conditions, for the two simulation models, non-coupled and a coupled model. It was observed that the results are very similar for the specified well injection rate, whereas significant differences for the specified well pressure. Finally, on the basis of computational experiments, it was concluded that the influence of the coupled wellbore/reservoir in thermal simulations using cyclic steam injection as an enhanced oil recovery method is greater for the specified well pressure, while for the specified well injection rate, the steam flow model for the injector well and the reservoir may be simulated in a non- coupled way