Análise de modelos geológicos utilizando percolação dinâmica

In the present study we elaborated algorithms by using concepts from percolation theory which analyze the connectivity conditions in geological models of petroleum reservoirs. From the petrophysical parameters such as permeability, porosity, transmittivity and others, which may be generated by any statistical process, it is possible to determine the portion of the model with more connected cells, what the interconnected wells are, and the critical path between injector and source wells. This allows to classify the reservoir according to the modeled petrophysical parameters. This also make it possible to determine the percentage of the reservoir to which each well is connected. Generally, the connected regions and the respective minima and/or maxima in the occurrence of the petrophysical parameters studied constitute a good manner to characterize a reservoir volumetrically. Therefore, the algorithms allow to optimize the positioning of wells, offering a preview of the general conditions of the given model s connectivity. The intent is not to evaluate geological models, but to show how to interpret the deposits, how their petrophysical characteristics are spatially distributed, and how the connections between the several parts of the system are resolved, showing their critical paths and backbones. The execution of these algorithms allows us to know the properties of the model s connectivity before the work on reservoir flux simulation is started

Estudo paramétrico da recuperação de óleo no processo de drenagem gravitacional com injeção de CO2

The gas injection has become the most important IOR process in the United States. Furthermore, the year 2006 marks the first time the gas injection IOR production has surpassed that of steam injection. In Brazil, the installation of a petrochemical complex in the Northeast of Brazil (Bahia State) offers opportunities for the injection of gases in the fields located in the Recôncavo Basin. Field-scale gas injection applications have almost always been associated with design and operational difficulties. The mobility ratio, which controls the volumetric sweep, between the injected gas and displaced oil bank in gas processes, is typically unfavorable due to the relatively low viscosity of the injected gas. Furthermore, the difference between their densities results in severe gravity segregation of fluids in the reservoirs, consequently leading to poor control in the volumetric sweep. Nowadays, from the above applications of gas injection, the WAG process is most popular. However, in attempting to solve the mobility problems, the WAG process gives rise to other problems associated with increased water saturation in the reservoir including diminished gas injectivity and increased competition to the flow of oil. The low field performance of WAG floods with oil recoveries in the range of 5-10% is a clear indication of these problems. In order to find na effective alternative to WAG, the Gas Assisted Gravity Drainage (GAGD) was developed. This process is designed to take advantage of gravity force to allow vertical segregation between the injected CO2 and reservoir crude oil due to their density difference. This process consists of placing horizontal producers near the bottom of the pay zone and injecting gás through existing vertical wells in field. Homogeneous models were used in this work which can be extrapolated to commercial application for fields located in the Northeast of Brazil. The simulations were performed in a CMG simulator, the STARS 2007.11, where some parameters and their interactions were analyzed. The results have shown that the CO2 injection in GAGD process increased significantly the rate and the final recovery of oil

Desenvolvimento de um sistema Inteligente para a análise de cartas dinamométricas no método de elevação por bombeio mecânico

The artificial lifting of oil is needed when the pressure of the reservoir is not high enough so that the fluid contained in it can reach the surface spontaneously. Thus the increase in energy supplies artificial or additional fluid integral to the well to come to the surface. The rod pump is the artificial lift method most used in the world and the dynamometer card (surface and down-hole) is the best tool for the analysis of a well equipped with such method. A computational method using Artificial Neural Networks MLP was and developed using pre-established patterns, based on its geometry, the downhole card are used for training the network and then the network provides the knowledge for classification of new cards, allows the fails diagnose in the system and operation conditions of the lifting system. These routines could be integrated to a supervisory system that collects the cards to be analyzed

Estudo paramétrico da injeção de vapor em reservatórios delgados

Exploration of heavy oil reservoirs is increasing every year in worldwide, because the discovery of light oil reservoirs is becoming increasingly rare. This fact has stimulated the research with the purpose of becoming viable, technically and economically, the exploration of such oil reserves. In Brazil, in special in the Northeast region, there is a large amount of heavy oil reservoir, where the recovery by the so called secondary methods Water injection or gas injection is inefficient or even impracticable in some reservoirs with high viscosity oils (heavy oils). In this scenario, steam injection appears as an interesting alternative for recover of these kinds of oil reservoirs. Its main mechanism consists of oil viscosity reduction through steam injection, increasing reservoir temperature. This work presents a parametric simulation study of some operational and reservoir variables that had influence on oil recovery in thin reservoirs typically found in Brazilian Northeast Basins, that use the steam injection as improved oil recovery method. To carry out simulations, it was used the commercial software STARS (Steam, Thermal, and Advanced Processes Reservoir Simulator) from CMG (Computer Modeling Group) version 2007.11. Reservoirs variables studied were horizontal permeability, vertical and horizontal permeability ratio, water zone and pay zone thickness ratio, pay zone thickness and thermal conductivity of the rock. Whereas, operational parameters studied were distance between wells and steam injection rate. Results showed that reservoir variables that had more influence on oil recovery were horizontal permeability and water zone and pay zone thickness ratio. In relation to operational variables, results showed that short distances between wells and low steam injection rates improved oil recovery

Estudo comparativo da utilização do nitrogênio como fluido alternativo após a injeção de vapor

Currently, due to part of world is focalized to petroleum, many researches with this theme have been advanced to make possible the production into reservoirs which were classified as unviable. Because of geological and operational challenges presented to oil recovery, more and more efficient methods which are economically successful have been searched. In this background, steam flood is in evidence mainly when it is combined with other procedures to purpose low costs and high recovery factors. This work utilized nitrogen as an alternative fluid after steam flood to adjust the best combination of alternation between these fluids in terms of time and rate injection. To describe the simplified economic profile, many analysis based on liquid cumulative production were performed. The completion interval and injection fluid rates were fixed and the oil viscosity was ranged at 300 cP, 1.000 cP and 3.000 cP. The results defined, for each viscosity, one specific model indicating the best period to stop the introduction of steam and insertion of nitrogen, when the first injected fluid reached its economic limit. Simulations in physics model defined from one-eighth nine-spot inverted were realized using the commercial simulator Steam, Thermal and Advanced Processes Reservoir Simulator STARS of Computer Modelling Group CMG

Estudo da segregação gravitacional do processo de injeção de vapor em reservátórios heterogêneos

Due to reservoirs complexity and significantly large reserves, heavy oil recovery has become one of the major oil industry challenges. Thus, thermal methods have been widely used as a strategic method to improve heavy oil recovery. These methods improve oil displacement through viscosity reduction, enabling oil production in fields which are not considered commercial by conventional recovery methods. Among the thermal processes, steam flooding is the most used today. One consequence in this process is gravity segregation, given by difference between reservoir and injected fluids density. This phenomenon may be influenced by the presence of reservoir heterogeneities. Since most of the studies are carried out in homogeneous reservoirs, more detailed studies of heterogeneities effects in the reservoirs during steam flooding are necessary, since most oil reservoirs are heterogeneous. This paper presents a study of reservoir heterogeneities and their influence in gravity segregation during steam flooding process. In this study some heterogeneous reservoirs with physical characteristics similar those found in the Brazilian Northeast Basin were analyzed. To carry out the simulations, it was used the commercial simulator STARS by CMG (Computer Modeling Group) - version 2007.11. Heterogeneities were modeled with lower permeability layers. Results showed that the presence of low permeability barriers can improve the oil recovery, and reduce the effects of gravity segregation, depending on the location of heterogeneities. The presence of these barriers have also increased the recovered fraction even with the reduction of injected steam rate

Uma aplicação da apredizagem por reforço na otimização da produção em um campo de petróleo

The objective of reservoir engineering is to manage fields of oil production in order to maximize the production of hydrocarbons according to economic and physical restrictions. The deciding of a production strategy is a complex activity involving several variables in the process. Thus, a smart system, which assists in the optimization of the options for developing of the field, is very useful in day-to-day of reservoir engineers. This paper proposes the development of an intelligent system to aid decision making, regarding the optimization of strategies of production in oil fields. The intelligence of this system will be implemented through the use of the technique of reinforcement learning, which is presented as a powerful tool in problems of multi-stage decision. The proposed system will allow the specialist to obtain, in time, a great alternative (or near-optimal) for the development of an oil field known

Predição não-linear de curvas de produção de petróleo via redes neurais recursivas

One of the main activities in the petroleum engineering is to estimate the oil production in the existing oil reserves. The calculation of these reserves is crucial to determine the economical feasibility of your explotation. Currently, the petroleum industry is facing problems to analyze production due to the exponentially increasing amount of data provided by the production facilities. Conventional reservoir modeling techniques like numerical reservoir simulation and visualization were well developed and are available. This work proposes intelligent methods, like artificial neural networks, to predict the oil production and compare the results with the ones obtained by the numerical simulation, method quite a lot used in the practice to realization of the oil production prediction behavior. The artificial neural networks will be used due your learning, adaptation and interpolation capabilities