Ana Paula Costa

Vortex-Induced Motion: Model Testing of a Monocolumn Floater

The vortex-induced vibrations - VIV have been studied for several fields of engineering due to its occurrence in different structures, such as electrical cables, industries chimneys and offshore risers. Although available an extensive literature describing its fundamental issues, these vortex-induced phenomena still deserve investigation, particularly in the offshore platforms installed in regions with high current speed. Recently, the Vortex-Induced Motions - VIM, a particular case of vortex-induced vibration with high magnitude of response amplitude, have been observed in SPAR platforms installed in Gulf of Mexico - GoM, opening a new investigation field. For those motions, aspects such as asymmetric mooring restoring stiffness and the probable three-dimensionality of the flow turn the problem even more complex. Since 2003, in partnership with University of Sao Paulo and consultant companies, PETROBRAS has been studying the use of monocolumn floaters for oil production in Campos Basin and GoM. Considering the environmental conditions in these areas and assuming that monocolumn floaters can exhibit similar VIM behavior of SPAR platforms, it was started an experimental investigation focusing on VIM responses of small-scale monocolumn floaters in towing tank. Although based on the state of art procedures used for SPAR platforms, the monocolumn experiments considered the different geometry of this concept and the larger susceptibility to the three-dimensional effects, due to the smaller relation draft/beam. Special attention was given to the ratio roughness/beam in order to guarantee similarity between the experiments and its respective real cases. Additionally, different heading conditions were also tested. Thus, the present work presents a set of preliminary results and discussions concerning VIM of monocolumn floaters and its impact on the mooring line design and riser specification.Copyright

Improving the Performance of Risk Analysis Applied to Petroleum Field Development

The appraisal phase in a petroleum field is characterized by several uncertainties, high investment and critical decisions, which are always strongly related to risk. In the past, it was usual to realize production forecast based on a deterministic simulation model. However, production forecast obtained by a probabilistic approach allows the quantification of uncertainty in the reservoir performance by numeric flow simulation of several possible models. Current hardware permits to incorporate more accurate production prediction in the decision processes. A probabilistic approach requires the definition of a methodology. The objective of this work is to develop a methodology to improve the performance of the risk analysis process, trying to get the best accuracy with the lowest number of simulation runs, using an automated process and parallel computing to accelerate the process. The methodology is based on simulation of several flow models representing possible scenarios of the reservoir, through the combination of the uncertain attributes. As simplification, sensitivity analysis is made to reduce the number of uncertain attributes. The simulation models are built through the derivative tree using only the critical attributes. To reduce the simulation time, parallel computing is also applied. After simulation of the models, a statistic treatment is used to obtain the risk curve of the production forecasts and of the net present value. Representative models are selected to integrate the analysis with economic uncertainties. The methodology is applied in petroleum fields and the advantages of the automated process and the simplified procedure are discussed. Introduction Petroleum field development and management are strongly related to risk due to several uncertainties that have to be considered. The most important uncertainties are related to the geological model, economic conditions and technological developments. Typically, the impact of these uncertainties is quantified in terms of volumes in place, recovery factor and economic indicators (Ligero et al., 2003). Uncertainty on the economic conditions is always present in the petroleum industry. Usually, during the exploration phase, uncertainties related to the volumes in place have great impact. In the Appraisal and Development phases, as more information is obtained, the importance of the uncertainty on recovery factor becomes significant. This paper deals with the quantification on uncertainties in these phases, adding new information to the methodology presented by Loschiavo et al. (2000), Steagall and Schiozer (2001), Ligero et al. (2003), Santos and Schiozer (2003), and other papers described in these references to perform risk analysis applied to petroleum field development using numerical reservoir simulation. The methodology used here is the same methodology presented by Steagall and Schiozer (2001). Depending on the complexity of the problem, size of the reservoir and importance of the project, it is not possible to include all uncertain parameters in the analysis and simplifications are necessary to yield viability of the process. Automation of the process, parallel computing (Ligero and Schiozer, 2002), special treatment of the geological attributes (Costa and Schiozer, 2002), treatment of production strategy (Santos and Schiozer, 2003), and fast simulation models (Ligero et al., 2003) are possible simplifications that are briefly discussed in this paper. Other approaches can be used, as presented by Salomão and Grell (2001). All these authors have performed the risk analysis with a fixed economic model because the objectives were normally to quantify the impact of geological uncertainties in the decision making process related to field development. However, if economic condition changes, some additional considerations have to be included in the risk analysis. In this paper, it is used the concept of representative models to test the importance of this variation and some discussion is presented to propose a methodology to integrate this step with the risk methodology. It is also presented a discussion about data integration among geology, reservoir engineering and economic analysis in order to reduce the amount of information necessary and time of the process. Some results are presented to show the advantages of automation and parallel computing to reduce the total time of the procedure where reservoir simulation is necessary in the reservoir performance prediction. SPE 81162 Improving the Performance of Risk Analysis Applied to Petroleum Field Development Eliana L. Ligero, Ana Paula A. Costa, Denis J. Schiozer, SPE, UNICAMP.

Behavior of a Mono-Column Structure (MonoBr) in Waves

MonoBr is the name of a concept of a mono-column structure with a moon-pool developed by PETROBRAS to operate in deep water. A set of tests has been carried out at LabOceano / COPPE / UFRJ to analyze its behavior in waves. Different configurations of the moon-pool entrance have been tested. The main objective of the measurements carried out is to determine the influence of different restrictions on the behavior of the vertical motion of the structure. Results of these measurements are presented and discussed in the paper.Copyright

Treatment of Geological Attributes in Risk Analysis Applied to the Appraisal Phase of Petroleum Fields

Decision analysis applied to petroleum field development is always strongly related to risk due to uncertainties present in the process. The appraisal phase of a petroleum field is characterized by several uncertainties, high investment and critical decisions. The use of numerical simulation allows a detailed study of the reservoir performance by several possible models obtained through a probabilistic approach. Methodologies to quantify the impact of uncertainties are still not well established due to the amount of variables that have to be considered and due to the computational effort that may be required. To make this process possible, some methodologies were developed to simplify a risk analysis. In this paper shows several details of a methodology that can be applied to complex and simple reservoirs in a reasonable amount of time to quantify the impact of the necessary simplifications, mainly by the selection of the ideal number attributes, discussing especially the influence: (1) attributes treatment, (2) sensitivity study, (3) gradual combination the less critical attributes in sensitivity study, (4) influence of the number of critical attributes. The concept of representative models is selected to integrate the analysis with economic uncertainties. The simulations results in this process are combined to calculate the NPV (Net Present Value). After the statistical treatment of the results, it is possible to define the risk curve. This paper shows the importance of the simplifications and the number of simulation run besting the accuracy of the risk curve.

Use of Uncertainty Analysis to Improve Production History Matching and the Decision Making Process

In the present E&P scenario, decisions have to be taken considering risks. An important part of risk evaluation can be accomplished through the evaluation of the impact of uncertainties in the performance of the petroleum fields, yielding higher possibility of success, quantification of possible losses, minimization of sub-optimal development and identification of opportunities. The objective of this work is to use the quantification of the impact of geological uncertainties to improve the production history matching in a Brazilian onshore field located at Potiguar Basin with 17 years of production history. The main advantage of this process is to provide alternatives for possible adjusted models related to the global rate of liquids, oil and water, allowing the selection of the best model to the be latter refined and adjusted on a well to well basis. The key point of the applied methodology in the project is the use of the concept of geological representative models (GRM) which are selected based on the integration of objective functions previously defined to the context. These GRM models are selected to represent all combined models which compose the distribution curve (risk curve) of the process. The distribution curve is obtained through the concept of derivative tree technique which combines the possible scenarios using the numerical simulation to predict reservoir behavior. The numerical simulation is used to increase the reliability of the results allowing one more detailed analysis for each model. An automated tool and parallel computing are used to speed up the process. The utilization of the automated tool as well as a defined methodology to quantify the impact of uncertainties improved the viability of the history matching procedure with a significant reduction of time and effort in the repetitive tasks, improving its results and yielding a more reliable production forecast. Introduction Decision analysis applied to petroleum field development is always strongly related to risk due the uncertainties present in the process. There are many uncertainties that can influence the success of an E&P project. The most common are related to (1) geological aspects (volume in place, faults, oil properties, etc. (2) recovery factor (function of the reservoir properties and production strategy), (3) economic model (mainly prices), (4) technology and political situation. One of the challenges in this area is to integrate the effect of these uncertainties and to select the uncertainties that have significant impact on the decision making process. The geological uncertainty term is related to the knowledge level of the reservoir petrophisical properties. To achieve a more reliable decision analysis, geological uncertainties must be integrated with other types of uncertainties, mainly related to economic scenarios, flexibility in the production strategy definition and technological aspects. Depending on the complexity of the problem, size of the reservoir and importance of the project, it is not possible to include all uncertain parameters and in order to speed up the process, some auxiliary tools and simplifications are necessary. The methodology to quantify the impact of geological uncertainties used in this paper was development by Costa and Schiozer (2003). Some aspects of this process such as gradual combination to define the critical attributes, reduction of levels of discretization for each attribute were used in this paper to improve the production history matching by the concept and the selection of geological representative models (GRM). The objective of this work is to use the quantification of the impact of geological uncertainties to improve the production history matching in a Brazilian onshore field located at Potiguar Basin with 17 years of production history. The main advantage of this process is to provide alternatives for possible adjusted models related to the global rate of liquids, oil and water, allowing the selection of the best model to the be latter refined and adjusted on a well to well basis. Methodology The risk analysis process applied can be described as: (1) definition of uncertainties attributes, (2) sensitivity analysis, (3) numerical simulation, (4) statistical treatment, (5) risk analysis curve and (6) selection of the geological representative models (GRM) to compare with the production history. SPE 99324 Use of Uncertainty Analysis To Improve Production History Matching and the Decision-Making Process A.P.A. Costa, SPE, Petrobras; D.J. Schiozer, SPE, Unicamp; and C.A. Poletto, SPE, Petrobras

Estimation of Damping Coefficients of Moonpools for Monocolumn Type Units

The use of moonpools in offshore technology are normally related to the hull opening in drilling units with the objective to have easy installation process and protect drilling equipment from environmental forces, and it is desirable the minimum motion of the water inside the moonpool, avoiding water impacts when lowering an equipment. Several studies, refs. /7,10,11,12,13/, have been carried out to predict the water dynamics inside the moonpool using analytical and experimental tools, this last due to the high viscous influence in the responses, and the study of coupled dynamics of floating units with moonpools have been presented in previous works (refs. /1,2,3,8,9,17/), with especial focus on FPSO’s and Monocolumn type units. In the present study, the objective is to verify the reliability of numerical approach in heave dynamic evaluation of monocolumns. With this approach the objective is to tune the natural period the floater and moonpool. Two monocolumn example units were numerically calculated using WAMIT software, making possible to verify the 6 degree of freedom of the unit and the 3 of the moonpool. As the software does not evaluate viscous forces, decay tests were performed in order to verify the external viscous damping to be considered in the numerical calculations. The calibrated numerical model transfer functions (RAO) were compared with regular and transient wave tests, where heave and moonpool heave amplitudes could be compared.© 2005 ASME

Impact of Simplifications in Risk Assessment and Decision-Making Process

Decision analysis applied to the development of petroleum fields must take into account the risk associated to several types of uncertainties. In this phase, the importance of risk associated to the recovery factor may increase significantly and numerical simulation is usually required to model the reservoir yielding high computation effort. The process is complex due to (1) high investments (2) large number of uncertain variables (3) strong dependence of the results with the production strategy definition. Therefore, simplifications are usually required to quantify the impact of uncertainties. In previous works, it was shown the impact of several simplifications in the process to be used in the decision making process after the risk assessment. The risk due to geological uncertainty is then separated from the selection of production strategy and other types of uncertainties. In this work, some results are presented and a discussion is made to show the impact of some simplifications in the selection criteria of the geological representative models before and after the integration of the production strategy optimization. The process is applied in an offshore field in Brazil and the results shows that it is possible to improve the performance and reliability of the risk analysis process with less computational effort. Indroduction In petroleum exploration and production, a decision has to be taken considering the risk involved in the process. The first step of the process is to quantify the impact of uncertainties on the performance of petroleum fields. The combination of the uncertainties can be used to quantify the risk related to the decision process. During the exploration phase, uncertainties related to the volumes in place have great impact. In the appraisal and development phases, as more information is obtained, the importance of the uncertainty on recovery factor becomes significant. The process is even more critical because most of the investments are realized during these phases. The most important uncertainties are due to the geological model, economic conditions and technological developments. To achieve a more reliable and general methodology, geological uncertainties must be integrated with other types of uncertainties, mainly related to economic scenarios, flexibility in the production strategy definition and technological aspects. Depending on the complexity of the problem, size of the reservoir and importance of the project, it is not possible to include all uncertain parameters and in order to speed up the process, some auxiliary tools and simplifications are necessary. The key point is then to define with simplifications and assumptions can be made to improve performance without sacrifiyng precision. The methodology to quantify the impact of simplifications criteria in risk analysis process used in this paper was development by Costa and Schiozer (2003). Some aspects of these simplifications such as gradual combination to define the critical attributes, reduction of levels of discretization for each attribute were used in this paper to quantify the impact of geological uncertainties represented by the concept and the selection of geological representative models (GRM). Other authors such as Ligero et al (2003), Santos and Schiozer (2003), perform risk analysis using numerical simulation, automated tools and simplifications procedure to yield viability of the process. The o objective of this paper is to present a discussion to show the impact of some simplifications in selection criteria of the GRM before and after the integration of the production strategy optimization. Uncertainty and Risk Analysis Decision analysis applied to petroleum field development is always strongly related to risk due the uncertainties present in the process. There are many uncertainties that can influence the success of an E&P project. The most common are related to (1) geological aspects (volume in place, faults, oil properties, etc. (2) recovery factor (function of the reservoir properties and production strategy), (3) economic model (mainly prices), (4) technology and political situation. One of the challenges in this area is to integrate the effect of these uncertainties and to select the uncertainties that have significant impact on the decision making process. During the filed development phase, the use of reservoir simulation is important because it increases the reliability, improves the quality of the results, and provides the output of other