Carlos Eduardo Barreto

Application of Assisted Optimization to Aid Oil Exploitation Strategy Selection for Offshore Fields

Decision-making processes for selecting an oil exploitation strategy can be complex due to the high number of variables to be optimized. Many times, it can be unfeasible to search an optimal solution by evaluating a high quantity of variables simultaneously. In this case, assisted methods that involve engineering analyses and mathematical optimization algorithms are an alternative to obtain a good solution. This paper shows the application of an assisted method to optimize a large number of variables of an oil exploitation strategy. The proposed methodology is to order and combine different optimization procedures with practical engineering analysis. The optimization variables include number and position of wells, platform capacities, wells opening schedule and wells shut-in time. The methodology is applied to a reservoir model based on a Brazilian offshore oil field to discuss the results obtained. Results indicate an efficient procedure for evaluating deterministic scenarios, suggesting optimization procedures for each decision variable and enabling the achievement of good quality solutions with a reasonable number of simulation runs. This is useful in many practical cases, mainly those, which require runs with long simulation time. Introduction Under reservoir engineering point of view, an oil field development and production strategy is the specification of important characteristics of the production system (infrastructure) that significantly and interactively impacts the profit expectation of the whole field. These characteristics involve the design of many details of infrastructure and control that are required for other projects of other areas. In general, the specifications are determined by the use of different optimization processes to assess each element of the strategy, which may demand a multidisciplinary team. The efficiency of the strategy selection is straightly connected with a workflow that rules all evaluations and their interactions. Therefore, an important task for the reservoir engineering area is the organization of all studies required to define relevant aspects of the strategy. The complete infrastructure project designed by reservoir engineers requires the determination of components that can include size, location and arrangement of surface facilities, number, position and completion of wells, injection and production capacities, well opening schedules, use of intelligent wells, among others. In general, these alternatives are selected using different decision-making-processes, treated as variables of different optimization runs and limited by physical and technical constraints. In addition, there is a certain interactive level among the different aspects. As a consequence, the design of the infrastructure of an oil field can be complex and challenging due to the large number of alternatives. The selection of the oil development strategy is sometimes made taking into account just the experience and judgment of the professionals involved. However, this can lead to inadequate solutions due to the possible few evaluations of the problem in the wide solutions space. To deal with this problem, oil companies use several sophisticated methods to evaluate the many aspects of the strategy. Despite they can achieve good solutions for determined specification, the combination of them to solve the more global problem of strategy may result in an unfeasible process. The use of adequate methodologies to combine different methods of optimization for each different aspect of the strategy aids to find better solutions in an efficient way. Therefore, the knowledge of the problem, the choice of appropriate optimization methods and the way to link the methods input and output are part of the reservoir engineer tasks to build more efficient workflows. This work uses an assisted process that combines both reservoir engineering evaluations and mathematic methods to select the oil development and production strategy. In addition, the test example was conceived to be applied in the predevelopment phase. The pre-development phase is here defined as the period before the well development drilling. The

Estimativa da evapotranspiração a partir de variação de nível estático de aquífero

A quantificacao da evapotranspiracao e uma tarefa essencial para o gerenciamento dos recursos hidricos em uma bacia hidrografica, ja que e variavel importante no ciclo hidrologico. Entretanto, estimar a evapotranspiracao real e uma tarefa dificil, e os pesquisadores usam, geralmente, mais de um metodo a fim de validar os resultados. Este trabalho apresenta um metodo para a determinacao da evapotranspiracao real com base na variacao da precipitacao, do escoamento de base e do nivel de agua subterrânea medidas na bacia hidrografica. Usando o metodo proposto em uma bacia hidrografica piloto, a evapotranspiracao real foi estimada em 900 mm por ano. Esse resultado foi comparado com a evapotranspiracao potencial, calculada pelos metodos empiricos e semiempiricos, baseados em dados climatologicos. O metodo de Thornthwaite, com evapotranspiracao potencial de 936 mm por ano, apresentou o valor mais proximo ao metodo de balanco hidrico. O metodo do balanco hidrico, baseado em medidas hidrogeologicas, mostrou-se apropriado para estimar a evapotranspiracao real na bacia hidrografica. Entretanto, e necessario observar as hipoteses e as limitacoes descritas neste estudo para aplicar este metodo a outra bacia hidrografica.

Comparative Analysis of Optimal Oil Production Strategy using Royalty & Tax and Production Sharing Petroleum Fiscal Models

After recent discoveries of large oil reserves in pre-salt areas of Brazil, the government has proposed a change in the current fiscal regime from Royalty & Tax to Production Sharing Contracts. The government wishes to implement the production sharing system to earn higher revenues, believing that this is the best policy to improve State gains to be transferred to society. In this new environment and focusing on the oil production strategy selection process, it is required to know if: 1) the production strategies are the same or different for both models 2) the same technical-economic indicators are suitable to be used to select the optimal production strategy in both systems. Nowadays, there is no clear convergence of points of view to answer these issues, although some debates among professionals and government are taking place. The aim of this paper is to present a comparative analysis of the optimum exploitation strategy for both fiscal models, regarding number of injection and production wells and, their allocation in the reservoir. This objective is accomplished following a production-strategy optimization that combines manual and automatic procedures to maximize the company NPV accounting for the assumption of a known behavior of oil prices. Sensitivity analyses of government take to oil price and cost recovery limits are carried out. The results show that the choice of the optimal-production strategy to maximize NPV depends on the fiscal regime. In addition, the government take is reduced with the increase of oil prices. For any oil price, the government take in the production sharing contract system is higher than in R&T, so that it is one of the reasons why it is more interesting from the government’s point of view. Besides, the increase of cost recovery limit implies in a reduction of the government take up to a stable value. Introduction According to ANP (2011), currently Brazil has approximately 14 billion barrels of oil but, over last decade, the area named Pre-Salt (rocks below salt-rock formation) in Brazil has been the stage of large oil field discoveries. Some information from the media indicates that Brazilian oil reserves may increase from 14 billion to 33 billion barrels with these new reserves expected in the Pre-Salt area.Oil reserves are hosted in rock at a depth between 4000 m and 6000 m. Table 1 shows some features of oil fields discovered over the last decade. Table 1: Some features of large oil discoveries in the area of Brazilian Pre-Salt Oil Field Discovery year Oil reserve (billion barrels) API Participation of Petrobras

Use of Water Cut to Optimize Conventional and Smart Wells

Water-cut prediction by reservoir simulation can be used as the main parameter to determine well shutdown time. In general, analytical formulations are used to determine the maximum water cut that a well can reach and this value is used as a monitoring parameter in reservoir simulation. Moreover, water-cut value can be a good indicator to evaluate field performance and it can be used as a variable in optimization process. This paper presents a methodology to optimize production strategy using water cut as a parameter to shut down wells and smart completions as a variable of the optimization process and as an economic indicator to evaluate strategy efficiency. A discussion on the use of water cut in a reservoir simulation is made, regarding the benefits and limitations of the use. The results show that using only analytical formulation to determine the water cut to shut down wells and completions is not a good approach to maximize production strategy Net Present Value (NPV). On the other hand, the optimization of well and valve operation using water cut significantly improves the NPV. Water cut is successfully used to indicate strategy efficiency and to suggest strategy modification. The results also show that it is necessary to be careful in the use of water cut in an optimization process, because it can present several limitations. This study may help engineers to decide if it is necessary to run an optimization process to determine the parameter used to shut down wells. Furthermore, the results show the importance of a good estimation of the time to shut down wells and completions to reach the optimum potential of a production strategy. Introduction Water cut is a production parameter that is calculated by the ratio between the water production rate and the fluid production rate. In fields in which the gains and costs with gas production is negligible or proportional to the oil production, the water cut is an important economic indicator to determine how profitable a well or completion is. Hence, water cut is widely used to indicate the time limitation to shut down wells and completions, mainly using reservoir simulation, because the usual simulators do not have direct keywords to deal with economic evaluation (Gharbi 2005; Yang et al. 2003; Maschio et al. 2008). Moreover, in cases in which it may be interesting to shut down wells and completions before they reach the economic limit, water cut is also used as a variable to optimize the time of shutting down (Silva and Schiozer 2009). Therefore, water cut is an important indicator in the evaluation of the time limit of operation and as a variable in an optimization process. The focus of this work is the use of water cut in a reservoir simulation in the process of production strategy selection. A strategy-selection process is used to select the exploitation strategy of an oil reserve, including platform, type of wells, well position, surface facilities, well completions, etc. In general, this process is divided into steps to reduce the number of variables (Coopersmith et al. 2003; Schiozer and Mezzomo 2003). An important step to evaluate production strategies is the optimization of operational control of the field, wells and inflow-control devices (ICV), the latter when smart wells are used (Mezzomo 2006). The problem consists of finding an optimum control over a time interval, which maximizes a specific performance indicator of a reservoir, in general, the NPV. Several controls are important in a field optimization. In reservoir simulation, controls can be an operational parameter, controlling flow and pressure, or a monitoring parameter, which monitors a certain parameter and acts when a specified value is reached, water cut, for example. Silva and Schiozer (2009) propose a methodology to optimize production strategy. The methodology includes an optimization of a conventional and smart-well operation using water cut as a variable. The optimization consists of maximizing the NPV by manually changing a single value of water cut to operate all wells and completions. However, no considerations about the efficiency of the use of water cut to optimize well operation are made. Asadollahi et al. (2012) propose an optimization workflow that uses shut-in water cut as a variable of an optimization problem, calculation of the water-cut limit by economic formulation and also use of the water-cut parameter to perform

Impact of the Use of Intelligent Wells on the Evaluation of Oilfield Development and Production Strategy

Intelligent wells are widely used around the world and they have the potential to significantly improve oil production or control water production of wells and fields. However, in many cases, the definition of the number and position of valves is still made considering only the well without evaluating if the decision to use them can change other important aspects of the production strategy. This article presents a study to evaluate some relevant aspects of the inclusion of intelligent wells in a more global study of production strategy selection. Such inclusion is an important step in the precise evaluation of the benefits of intelligent valves. The methodology comprises the economic optimization of a production strategy under different limits of platform flow capacity, the optimization of the number and position of valves (intelligent wells), including and excluding conventional well operation. This study was applied to the UNISIM-I-D benchmark case, starting with a previously optimized production strategy, regarding type, number and position of wells, well-opening sequence and platform flow capacity in 9 different geological scenarios. The optimization methodology uses a complex workflow to test different strategy alternatives using a genetic algorithm and a methodology to optimize the number and position of valves. We showed that the use of intelligent wells can significantly alter the water flow capacity and the operational design of wells. However, for this specific case, the use of intelligent wells was not able to modify oil production and water injection flow capacity. Intelligent well application was viable for 7 out of 9 geological scenarios with the number of valves varying from 1 to 14. The intelligent-well application improved the total NPV from 0% to 1.5%. The platform water flow capacity could be reduced by at least 30% if intelligent valves were implemented. These results are quite different when a less precise optimization methodology is applied, yielding an overestimation of an intelligent well. To conclude, the application of intelligent wells was viable for most of the scenarios. Although intelligent wells present low impact on NPV, they can modify the design of platform capacity significantly. This fact suggests that the optimization of intelligent wells must be combined with the optimization of the platform water flow capacity and the conventional well operation optimization. This work provides important information for reservoir engineers who use reservoir simulation to optimize production strategy. Currently, in many cases, intelligent wells are only evaluated after the selection of the platform design. We have proved that the combined optimization can yield a different production strategy design. In addition, we have also proved that the evaluation of intelligent wells viability without an adequate optimization of conventional well operation overestimated the number and the value of valves.

Evaluation of Different Types of Operation for Inflow-Control-Valves based on Production and Reservoir Data

Intelligent valves provide more flexibility for well operation and different options to improve field production. The number of control alternatives is large and the decision of using inflow-control-valves is not simple, mainly for choking valves. Therefore, it is necessary to quantify economic and technical impacts in order to avoid undesired results. This work uses reservoir simulation to evaluate valves operation as the basis for the decision-making process. The process is based on simulation results to quantify real-time production and reservoir data on the short and long-term effects. Observed data, such as water breakthrough, water front movement and production economic limit are used to make control decisions. A test example is created to represent a fracture region of a reservoir with channel configuration; then, different reservoir size models and different well production constraints are created. The results show that actions to control water front and to shut down regions in which the breakthrough occurs, significantly increase the NPV. Conversely, attempts to control water front and breakthrough in cases in which the production rate is not constrained may lead to a significant NPV reduction without providing any significant increase in oil recovery. It is also shown that it is essential to shut down regions where the production economic limit is reached, even if a higher oil recovery factor can be achieved. As a conclusion, inflow control valves operation based on real-time production and reservoir data may efficiently improve field production when an adequate control is applied. The decisions are complex and must be made carefully, observing the real-time data and associated limiting conditions. This paper provides information that supports the use of water front movement, water saturation and production data to operate inflow-control-valves. It is proved that the use of the production and reservoir data considered in this work can help real-time operation to achieve relevant long-term effects. However, it is important to observe reservoir conditions to make an adequate use of data. Introduction Operation of inflow control valves (ICV) involves the analysis of different information and the use of a wide range of workflows to determine the best configuration of valves aperture along field lifecycle. As field and well technologies step forward to a new monitoring and control scenario, more information has been collected and additional efforts are required to make better interpretation and an effective decision-making. One type of new information is about real-time water saturation, which can be used to determine where the water will be firstly erupted or where the water is more strongly produced. This information can be used to make short-term decisions, including closure of ICV that are nearest to water front and to increase oil production rate based on a more profitable arrangement of well flows. However, it can be difficult to estimate the long-term benefits of short-term actions. This work compares different types of rules to operate ICV, which are used to make short-term decisions based on well flow and water front distance information. The main idea is to show advantages and disadvantages of each set of rules and also to propose a workflow to use water saturation data to better achieve long-term benefits. The rules are constructed taking into account the maximization of oil rate and the retardation and reduction of water production. It is expected that the conclusions aid engineers to better understand the long-term effects of ICV controlling when using simple and objective goals to operate a oilfield. Objectives The objective of this work is to make a long-term evaluation of short-term actions to regulate water and oil production using intelligent wells. The focus is to evaluate the use of information of water front distance to producers and fluid production

Comparison Between Smart and Conventional Wells Optimized Under Economic Uncertainty

Smart completion allows higher operational flexibility for the development of petroleum fields than the conventional completion. However, the real benefits of this technology are not always clear. In order to compare advantages and disadvantages of each type of completion in the exploitation of oil fields, it is necessary to optimize the production strategy for both options. This paper presents a methodology to optimize strategies with reactive and proactive control valves in smart wells; the same methodology is applied to conventional wells in order to compare the different behaviors. This methodology aims to help the manager in the decision of choosing between conventional or smart wells in developing an oil field. An evolutionary algorithm was coupled to a commercial simulator to search for the maximum of the objective function, the Net Present Value (NPV), determining the optimum water cut of producer smart wells for each valve (proactive control), for all valves (reactive control) or for a whole producer conventional well. Then, a fair performance comparison between both types of completions is done. The case studies are simple in order to make clear the difference between the cases. They are classified in reservoir models regarding different heterogeneities, type of oil and under economic uncertainty. Uncertainties in oil prices and in water production cost are considered through three economic scenarios: optimistic, probable and pessimistic. Results show that smart wells are able to increase production time, cumulative oil production and the NPV, also decreasing water production and injection in some cases. The results show higher benefits in using smart wells in high heterogeneity and light oil reservoirs to increase oil production and maximize NPV. Smart wells differ greatly from the conventional ones in pessimistic economic scenarios, where there are operational restrictions due to the unfavorable scenario. Introduction Nowadays, smart wells (SW) can be considered to improve oil recovery in petroleum fields, justifying the necessity of studies to verify the applicability of this type of wells. In SW, completion has parkers that allow partitioning of the wellbore, downhole inflow control valves (ICV) and a variety of sensors, especially those that monitor flow, pressure and temperature, installed on the production tubing. The smart completion allows greater operational flexibility in developing the field, enabling them to take action over time of production, capable of responding to (or preventing) undesired events, avoiding a costly intervention in the well during production. However, many companies today still do not feel fully confident in investing in a more expensive technology, because the real benefits of this technology are still not clear. Part of this lack of confidence is because there is no consolidated methodology that shows the advantages and disadvantages of SW in relation to conventional wells (CW). Moreover, many studies in the literature (1) have unclear results, (2) show only technical results, not considering economic analysis or (3) do not present a fair comparison between both options. This is mainly because of the complexity of the problem, due to the high number of variables involved in the process. The complexity is also due to the dependence among several parameters related to the selection of production strategies. Therefore, the comparison of SW and CW is not easy to do. Another major difficulty is to optimize each valve of several wells in a field, which makes the problem very complex, because the optimization methods cannot solve the problem in feasible computational time. As a result, several studies attempted different methods to solve this problem, among them: simulated annealing (Kharghoria, 2002), conjugate gradient (Kharghoria et al., 2002; Yeten et al., 2002), calculation of gradients (Sarma et al., 2005, Van Essen et al., 2009), direct search (Emerick

An Integrated Methodology for Water Management Under Operational Restrictions

The current concern with the increasing amounts of produced water and the wide variety of operations in which water takes place require considering strategies that, with their further development and implementation, lead to a correct management of the produced and injected water in order to increase the oilfield productivity. Thus, it is possible to determine operation conditions regarding the settings that allow optimizing the oil recovery and the economic incomes of an oil E&P development. It is known that efficient strategies for water management can lead to an effective control of the influence of water on the project development, increasing the economic performance of oil production by means of the reduction of costs and/or the increase of revenues in the cash flow. Examples of this situation are the anticipation of the oil production, the reduction of the treated volumes of water in the field and their respective costs, besides the increase in final oil recovery. Hence, the determination of limits for the water production and injection, the dimensioning of surface facilities and the selection of the proper options for water management shall be based on the economic parameters and production performance, since the handling of an eventual extremely high water production, or an injection not agreed with the necessities of the field and the processing capacity, can affect negatively both, the cash flow and the final oil recovery. Also, it is important to highlight that the strategy selected for water management must consider environmental actions not only to minimize the negative effects of water processes, but also because those actions can be accounted for into the cash flow and in the field operation as intangible goods. This paper presents a brief review on the main aspects of the water management and proposes a methodology which integrates different factors involved in water management to determine the appropriate conditions for its implementation, considering technical and economic factors. The study presents as main benefit the possibility of an integrated solution in order to get a bigger performance of the processes that involve the use of water in oil field operations.