V. E. Botechia

Use of Well Indicators in the Production Strategy Optimization Process

The selection of an adequate strategy for oil production is a complex process due to the several parameters that must be taken into account: type, number and position of wells, production and injection capacities of platforms, which must be defined and optimized in order to achieve an exploitation strategy which provides the best possible economic return. Most works presented production strategy optimization methodologies based on production or Net Present Value (NPV). In general, well information is not used in the optimization processes. However, information on well behavior and performance is very important to improve the production strategy and to make the process more robust. The aim of this paper is to present a comparative analysis of the use of different indicators in order to assist the selection/optimization of a production strategy based on well information, using numerical simulation and economic analysis. Changes in the configurations of the production system can be made according to the behavior of the wells and evaluation of the indicators aiming to maximize the NPV of the field. The development of the equations of the well indicators is shown and the methodology is applied to two different geological models: an offshore sandstone reservoir, representing a gas solution drive model and a carbonate reservoir with typical characteristics of the pre-salt areas of Brazil. Introduction The optimization of the production strategy consists of alterations in several parameters on the configuration of the project. A production strategy presenting a low performance can be indicative of an unfavorable schedule, inadequate number, position and/or type of wells, high water production, low well productivity etc. There is a high number of possible combinations for solving the problem of production strategy optimization, consuming a high computation time. According to Wences et al. (2001), while performing an integrated reservoir study, statistics show that 93% of the time is consumed in defining reservoir description and performing calibration of the simulation model and only 7% of that total time is used for forecasting purposes. For this reason, the authors suggest a technique to guide the post calibration work of a reservoir simulation model to determine the best exploitation strategy. The technique is based on a graph in which the NPV is plotted against the number of infill wells showing a maximum value, followed by a step by step methodology, which includes: determination of the fluid saturation distribution at the end of the forecast; choice of an aggressive exploitation plan, positioning the largest number of infill drilling wells based on the remaining fluid distribution; economic evaluation of the forecast considering only the incremental production over the base case; plotting the net present value obtained versus the number of additional infill wells used in the case etc. Usually, the optimization process is made considering an objective-function of the whole field, not taking into account indicators of individual wells in the process. Works such as Nakajima (2003) and Nogueira (2009) show that the performance analysis of wells is very important to make the process more efficient. However, in general, this is not done by the complexity of the process, especially when there are uncertainties involved. Analysis of well indicators can provide important and useful information about the field during the optimization process. This can be carried out as an attempt to automatize and give agility to the process. Considering uncertain scenarios of heterogeneous fields, a same well may behave very differently in each scenario due to the differences among the regions in the simulation models (Botechia, 2012). This kind of analysis provides new alternatives of strategy production or more robustness during the decision-making process. It is emphasized that, although the indicators that will be described here are used to assist the optimization process, this paper does not focus on the general optimization process, but aims to make an analysis and comparison of these well economic indicators, and in which cases they can be used appropriately, using reservoir simulation. Details of the optimization process

Effects Of Control And Revitalization Variables To Improve The Performance Of A Polymer Flooding Strategy

Decisions related to production strategy selection are complex tasks involving large investments and high risk. Even applying in-depth probabilistic procedures to define the number and location of wells, the strategy is likely to be sub-optimal when field information is collected and the geologic model becomes better known. The objective of this work is to improve the performance of sub-optimal strategies through analyzing the effects of control and revitalization variables. The simulation models used to optimize the strategies showed variable levels to be different to those predicted, and so modifications to the strategy are necessary. Control variables relate to field management, and can be altered daily, without fore-planning and without requiring further investment (e.g., well rates). Revitalization variables represent possible future alternatives, which are not usually accounted for in the initial production strategy, and involve additional investment (such as infill drilling). The proposed methodology changes both control and revitalization variables throughout the lifetime of the field, using numerical simulation and economic analysis, to improve performance as measured by Net Present Value (NPV). We apply the procedure to two simulation models representative of an offshore heavy oil field using polymer flooding as the recovery mechanism. These are low flexibility cases (the platform already has the maximum number of wells), thus it is necessary to shut down some wells before opening others (well replacement). These new wells generate extra expenditures that were not accounted for in the original project. The results showed that the economic performance was greatly increased by actions that (1) do not generate extra expenditures (adjustment of well rates and specificities of the recovery mechanism) and (2) by actions that require extra investments (for instance, allocation of wells to substitute the ones that present low performance). In the studied case, the economic performance was increased up to 39%, even with the extra costs caused by the substitution of wells. This great increase in NPV was caused mainly by two reasons: the higher amount of oil produced due to the wells replacement (up to 17%) and the reduction in the amount and cost of the polymer injection (up to 89%). We also showed that higher oil recovery not necessary means better economic performance, since large investments may be required to produce more oil, and this increased production must pay the extra expenditures.

Comparison between Production and Economic Indicators in the Production Strategy Selection for Polymer Flooding

The selection of a production strategy, seeking maximization of field performance according to some indicator, is a complex and important task. Choosing the indicator to be used to complete this task can lead to different results, and this choice must be carefully made to reflect the company objectives. Many companies seek only maximization of the recovery factor, neglecting costs and investments necessary to reach this goal. This may lead to a poor economic performance. Moreover, decisions that require extra investments (for instance, the use of some enhanced recovery technique such as polymer flooding) should be evaluated and taken into account in the analysis, since there are differences in the cash flow of the project options and these additional investments are important to the final decision. The objective of this paper is to compare the use of production and economic indicators in the production strategy selection, considering that there are not budget constraints or platform restrictions. The methodology consists of an optimization process using two different indicators: net present value (NPV) and oil recovery factor (RF). Three different approaches are addressed: (A) using only NPV as objective-function (OF) in the whole process; (B) using only RF as objective-function in the whole process; (C) using NPV as objective-function in the steps that the investments are not fixed (the number of wells and platform capacity are not determined yet) and changing the objective-function to RF when the main investments do not vary (number of wells and platform capacity are already determined). The application of the methodology is made in a model that represents an offshore heavy oil field using polymer flooding as recovery mechanism. The results show that NPV has advantages when considering the whole development of the field in this work conditions (no budget or platform restrictions). In this case, the consideration of the recovery factor as single indicator leads to an overestimated number of wells, resulting in bad economic performance due to high costs, even with higher oil production in relation to the optimization made considering only NPV. The advantage of using NPV is that it considers in its calculation several parameters, such as revenues from oil production, costs from oil and water production, costs from water injection, speed of recovery, and in the case of this work, the cost for polymer injection, which can

Quantification of Simulation Model Grid Size Impact on Polymer Flooding Application in Heavy Oil Heterogeneous Reservoir

Polymer flooding can be a viable alternative to enhance oil recovery of heavy oil fields. The comparison of water and polymer flooding requires a reliable reservoir numerical model to safely ensure the decision analysis including uncertainties and involving a significant amount of simulation runs. Reservoir engineers usually work-around this problem using fast models to reduce computational time; however, it is important to maintain the reliability of heterogeneous reservoir models. Therefore, the proposed work demonstrates how the grid size impacts on accuracy of results and both the time and computational resources. In addition, it is performed an analysis to establish how the typical physical phenomena related to the polymer flooding impact the applicability of the proposed methodology. A highly heterogeneous heavy oil field is used in our proposed studies. The application is conducted to assist pilot test wells. Initially, the definition of the reference strategy (OTM) is presented. In this case study, the OTM strategy is based on the optimization of location and number of wells. Secondly, the effect of grid size on the process is evaluated through two procedures: (1) DA method: a selection of grid size defined by drainage area of the selected wells; and (2) UP method: upscaling is performed in the simulation model. Then, production parameters resulting from models of both procedures (DA and UP) are compared with OTM results. The definition of which procedure is better to represent the wells of interest is performed. Finally, the impact of three polymer flooding physical phenomena (degradation, adsorption and Non-Newtonian effect) on production results is presented, in order to verify the accuracy of the generated fast models in maintained considering these effects. The DA method present good accuracy for reservoir response compared to the reference OTM results. Differently, UP models are not as accurate as DA models for production results indicators. In conclusion, the application of the methodology allows choosing the DA over the UP technique to support our decision in the investigated recovery methods, showing a reliable and fast procedure. Finally, this procedure shows excellent applicability and robustness when a typical polymer flooding study is carried out: the evaluation of physical phenomena impact on production results based on wells of interest. Introduction The oil industry has experienced a gradual decrease on the discovery of new oil deposits on the last decades (Alvarado and Manrique, 2010) and, the reserves that have been found lately are located in

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