Pre-salt Fields Research Articles

3D unrestricted fluid-driven fracture propagation based on coupled hydromechanical interface elements

Exploring unconventional reservoirs has raised several engineering challenges to improve oil/gas recovery. In the Brazilian pre-salt fields, highly heterogeneous carbonate formations compose these reservoirs containing fractures in multiple scales. The extracted carbon dioxide is reinjected in the reservoirs to increase oil recovery and reduce greenhouse gas emissions. For that reason, it is essential to develop robust numerical methods capable of simulating fracture propagation in naturally fractured porous media. This paper presents a new 3D mesh fragmentation technique to simulate non-planar hydraulic fracture propagation, considering its interaction with natural fractures. This method is based on discrete fracture representation through hydromechanical interface elements with a cohesive zone model to simulate fluid-driven fracture propagation. The proposed 3D mesh fragmentation algorithm inserts triple noded-interface elements into the continuum finite element faces, ensuring continuity of the fluid pressure field. The approach is successfully validated against experimental fracturing tests and analytical models. Also, by applying the proposed fragmentation technique, we study the influence of pre-existing oriented fractures on hydraulic fracture propagation in different scenarios. The results provide insight into the complex hydraulic fracturing process in naturally fractured formations. Finally, this approach is an attractive alternative to simulate multi-staged fracturing into 3D multilayered fractured rock formations.

Model-based life cycle control of ICVs in injectors in a benchmark analogous to a pre-salt field

Some fields in the Brazilian pre-salt feature light oil and high gas/CO2 content, which is a bottleneck to oil production due to gas processing restrictions in the facilities. To deal with this, Water-alternate-gas (WAG) is used as a recovery mechanism while the use of Interval Control Valves (ICVs) is also recommended, since these enable controlling the production or injection through segments in the wells.In this context of high gas production and WAG, a good injection management is crucial and the use of ICVs in the injection wells can help to improve the oil production and the field's economic return. In this work, we propose and compare four approaches (A, B, C, and D) to control the ICVs of the injectors considering numerical simulation and Net present value (NPV) as objective function. Approaches A and B use streamlines to correlate producers and injectors, and they also use the Gas-oil ratio (GOR) of the producers as a monitoring variable to close the valves of the injectors. The difference between them is that, in Approach A, the valves remain closed during the entire field's life cycle, while there is an alternation of each opened or closed valve for every WAG cycle in Approach B. In Approach C, the alternation between each valve is made since the beginning of the WAG cycles, instead of waiting for a trigger to start closing the valves. These three approaches are sub-divided into other (minor) approaches, depending on whether the valve remains closed, or not, during the water injection cycles. Finally, in Approach D, we attempt to control the cumulative fluid injection between the zones of the injectors. The study is applied to the SEC1_2022 benchmark case, a synthetic model analogous to a pre-salt field. Finally, we apply the best approach found to a reference case (“true response”) to assess how the proposed strategy would behave in real cases.The results indicate that closing the valves in earlier stages of the field's life cycle is better than using GOR as a trigger. Furthermore, the alternation between opened and closed valves proved to be the best way to control the valves in this case. Approach D was the best among those evaluated, with the highest increase in oil production and greatest decrease in water production, providing highest NPV. Although the platform remained constrained by gas production, this approach provided a better fluid distribution in the field and among wells, improving both oil recovery and economic returns.

Evaluation of CO2 as an Acid Catalyst Precursor for Promoting a Nitrogen-Generating System

Summary Nitrogen-generating systems (NGSs) are mainly used in the oil industry to fluidize low melting point organic deposits and gas hydrate buildups. They are exothermic reactions between two nitrogenous salts in acidic catalytic media. This work investigates the use of CO2 to promote NGS reactions instead of commonly used acids such as acetic and citric acids, which can be problematic for corrosion control. Sodium nitrite and ammonium chloride were the reactants, and CO2 performance was evaluated for up to 4 hours at 5 and 25°C, and either under autogenous pressure at 10, 25, and 50 bar of CO2 or pressurized at 10 bar of CO2 by adding 40 bar of nitrogen (totaling 50 bar). The nitrite conversion was determined by measuring the concentration of residual nitrite using titration. Thus, it was verified that the CO2 effectively promoted the NGS at various experimental conditions. The nitrite conversion increased with increasing CO2 pressure and increasing temperature. Moreover, the nitrite conversion was enhanced in the pressurized system (PS) because the high pressure enabled the dissolution of CO2 in the aqueous medium, and therefore, the constant formation of carbonic acid, favoring the acidic catalytic medium at the reaction. This advantage was confirmed by carrying out an NGS catalyzed by acetic acid, in which the pH increases as reagents are consumed, and therefore, a lower nitrite conversion is achieved. The use of CO2 also converts the NGS in a process more suitable for flow assurance applications in offshore oil production, particularly in the Brazilian presalt fields where the coproduced CO2 can be used.

Data-driven deep-learning forecasting for oil production and pressure

Production forecasting plays an important role in oil and gas production, aiding engineers to perform field management. However, this can be challenging for complex reservoirs such as the highly heterogeneous carbonate reservoirs from Brazilian Pre-salt fields. We propose a new setup for forecasting multiple outputs using machine-learning algorithms and evaluate a set of deep-learning architectures suitable for time-series forecasting. The setup proposed is called N-th Day and it provides a coherent solution for the problem of forecasting multiple data points in which a sliding window mechanism guarantees there is no data leakage during training. We also devise four deep-learning architectures for forecasting, stacking the layers to focus on different timescales, and compare them with different existing off-the-shelf methods. The obtained results confirm that specific architectures, as those we propose, are crucial for oil and gas production forecasting. Although LSTM and GRU layers are designed to capture temporal sequences, the experiments also indicate that the investigated scenario of production forecasting requires additional and specific structures.

Full waveform inversion based on the non-parametric estimate of the probability distribution of the residuals

SUMMARY In an attempt to overcome the difficulties of the full waveform inversion (FWI), several alternative objective functions have been proposed over the last few years. Many of them are based on the assumption that the residuals (differences between modelled and observed seismic data) follow specific probability distributions when, in fact, the true probability distribution is unknown. This leads FWI to converge to an incorrect probability distribution if the assumed probability distribution is different from the real one and, consequently it may lead the FWI to achieve biased models of the subsurface. In this work, we propose an objective function which does not force the residuals to follow a specific probability distribution. Instead, we propose to use the non-parametric kernel density estimation technique (KDE) (which imposes the least possible assumptions about the residuals) to explore the probability distribution that may be more suitable. As evidenced by the results obtained in a synthetic model and in a typical P-wave velocity model of the Brazilian pre-salt fields, the proposed FWI reveals a greater potential to overcome more adverse situations (such as cycle-skipping) and also a lower sensitivity to noise in the observed data than conventional L2- and L1-norm objective functions and thus making it possible to obtain more accurate models of the subsurface. This greater potential is also illustrated by the smoother and less sinuous shape of the proposed objective function with fewer local minima compared with the conventional objective functions.

Virtual flow metering of oil wells for a pre-salt field

The flow rate values reported in real time, for an oil and gas production unit, refer to the total amount produced by that unit. On the other hand, data referring to the flow rate of each producing well in real time are usually not available, due to the difficulty in implementing flow measurement devices. These individual flows are determined by production tests that are generally performed every two months and are important for production planning and optimization. Therefore, there is a need to generate models capable of predicting the flow of each well in the period between tests, in order to identify possible issues during the production. In this context, we propose in this paper a method to predict the liquid and gas flow rates of each well as function of measured variables available in plant data collected in real time. Choke valve specifications and fluid properties are also required as model input data. Since there is no flow measurement device, it is not possible to directly validate the model results against plant data. In this case, the model validation is performed using the total liquid and gas flow rates presented in the Daily Operation Report (DOR) and those provided by fiscal meters. Relative errors below 3.5% were observed, showing good agreement between the calculated flow rates and the provided by fiscal meters. The proposed method was implemented in the computational environment EMSO, which presents as advantages the low simulation time and robustness over a wide range of input data. These advantages become important as the model is used for monitoring platforms in real time. The range of applicability of this model can be attributed to the Gas-Oil Rate (GOR). In this work, the lowest and highest values of GOR considering all the wells are 207.58 and 393.97, respectively.

Strontium-based low salinity water as an IOR/EOR method: Oil-brine interaction

Strontium-based injection water for enhanced oil recovery has been neglected due to the low solubility of the cation in water. However, challenging reservoirs like those in the Brazilian pre-salt region demand non-conventional solutions to improve oil production. This work shows for the first time that the strontium cation in low salinity water solutions shall be henceforth considered as a potential component in the development of enhanced/improved oil recovery (EOR/IOR) studies. Acidic and non-acidic model oils and real crude oils from Brazilian post-salt and pre-salt fields were used for this study. The oil/brine interfacial tension and viscoelastic properties of the interfacial films were measured by an ascendant drop tensiometer. The results showed that strontium presents the highest interfacial activity among the other alkaline-earth metals. Also, the strontium-based low salinity water produced the most elastic interfacial film, which is desired for the improvement of oil volumetric sweeping promoted by water flooding. Nonetheless, it is worth highlighting that further studies including core flooding experiments must be performed to assess the strontium effect on the crude oil outflow through reservoir pores as well as the influence of water/oil/rock interactions upon it.

Fault current limiters: a case study of protection and operational continuity for FPSOs

The Floating Production Storage Offloading offshore (FPSO) has been employed in the oil and gas exploration at the Brazilian pre-salt fields. Due to the increasing production capacity of process plants and consequently its power demands, FPSO power systems are experiencing higher fault current levels, which can present peak values of almost 200 kA in the medium voltage circuit. One solution to keep fault currents within safe values for the new electrical installations is to split the main switchgear busbar in two parts interconnecting them with a pyrotechnic device (PD). However, this typical fault current limiter (FCL) imposes operational restrictions to the FPSO; when the PD is triggered, the production of barrels is severely reduced. This work proposes two alternative FCLs to mitigate this problem: a Pyrotechnic Device (PD) associated with a parallel Air-Core Reactor (ACR) and a resistive Superconducting Fault Current Limiter (r-SFCL). As described in this manuscript, both alternatives allow full operation of the FPSO even after its actuation. The simulation model used to reproduce the transient behavior of two FCLs and the power system of typical FPSO was developed in the software Alternative Transients Program. The results show that the alternatives can limit the fault current below the main switchgear supportability limit, improving the reliability of FPSO’s production.

Geoscience platform for reservoir property modeling automation using AI: a case study in a pre-salt field in the Santos basin

Geoscience platform for reservoir property modeling automation using AI: a case study in a pre-salt field in the Santos basin

Simulating, Testing and Validating Thermoplastic Composite Pipes Resistance to Rapid Gas Decompression Effects for Pre-salt Fields

Simulating, Testing and Validating Thermoplastic Composite Pipes Resistance to Rapid Gas Decompression Effects for Pre-salt Fields

Scale inhibitor development for Brazilian Pre-salt fields applications

Scale inhibitor development for Brazilian Pre-salt fields applications

Guest Editorial: The South American Deepwater Sector

2020 set the stage for a profound transformation in the oil and gas industry. The oil and gas industry was already facing a challenging transition process as economies move toward a low-carbon future; however, surviving and prospering in a low-oil-price and high-risk environment is an even greater and more urgent challenge. Producers with relatively high-cost production will bear the brunt of production curtailments, since none are able to sustain uneconomic production for very long. In the years leading to 2019, shale plays stole the show, increasing production as long as prices sustained the frantic pace of drilling required for the production increases observed in the US. On the other hand, the intrinsic characteristics of deepwater plays - highly front-loaded investments and long project cycles - worked against them. Relatively low prices that were just as challenging for shale plays were considered a reason to delay deepwater projects (Rigzone 2016). Portfolio diversification is an important risk-mitigation strategy, whether by region, country, environment, or play type. However, for the majors of the industry, it is increasingly difficult and risky to rely on many relatively small projects to keep their portfolio pipeline full. Given the size of large companies, large projects are required to guarantee high levels of production over long periods and to keep their project portfolio manageable. Larger plays, and those that are less subject to environmental restrictions, tend to be found in large offshore basins, where deepwater plays dominate. At the same time, the world offers fewer opportunities with acceptable country risk. Thus, larger plays in safer regions have become essential elements of the core business of large oil and gas players. Besides offering the potential for large production, deepwater plays often can provide low Opex because of their scale and productivities, such as in the Brazilian pre-salt trend (the “pre-salt”), where many wells have consistently delivered sustained average production above 40 thousand BOPD (ANP 2020). Furthermore, deepwater plays involve large, complex projects that are well suited to the megaproject management capabilities of large players of the industry. Those projects are also amenable to technological innovations that have delivered impressive performance improvements and cost reductions. As an example, Petrobras claims that in 2020 its lifting costs for deepwater pre-salt fields have come down to below $3.00/bbl, and under $5.00/bbl including rig-leasing costs (Petrobras 2020a). As to innovation-related gains, two Petrobras programs represent unprecedented achievements in deep waters. Prod1000 expects to reach first oil within 1,000 days of a discovery, and Exp100 seeks to achieve a 100% discovery rate in exploratory wells, a feat that breaks the paradigm that has assigned high exploratory risks to deepwater exploration everywhere in the world (Petrobras 2020b). Existing infrastructure in deepwater plays has also become key in locating exploration and production (E&P) activities, since it can lower Capex and aid the viability of projects that would otherwise be uneconomical.

Prediction of design loads for deep water subsea lifting operations based on non-stationary time response

Two methodologies for the prediction of the design loads of deep water subsea lifting operations crossing resonance zones are presented. These methodologies are applicable to models that consider the influence of the payout speed on the dynamics of the operation, leading to a non-stationary time series for the dynamic forces on the system. The first model is based on running several random simulations of the same scenario and using these simulations as a sample in which statistical parameters are inferred. The second model uses a weighted least squares approach to predict a normalizing function that is used to evaluate the statistical parameters of the response. Both models are tested by considering the installation of a typical manifold in the Pre-Salt fields, in Brazil, and are able to predict the general form of the envelope of forces on the cable for various sea states and payout speeds. The models also provided similar results for the availability of the vessel after evaluating the weather window for this operation. Finally, the advantages of using the weighted least squares approach in comparison to the direct method are discussed, since it may considerably reduce the total number of simulations required to perform a real operation assessment, especially during preliminary design phases.

Regulating the electro-energetic use of natural gas by gas-to-wire offshore technology: Case study from Brazil

This work aims to analyse, from the point of view of long-term electrical power sector planning, the regulatory aspects for the implementation of offshore gas-to-wire (GtW) technology, focusing on a Brazilian case study and pre-salt fields. The main results show that in terms of implementation, offshore GtW must be auctioned as a structuring project and offshore transmission for the GtW power plant could adopt the same model used for Itaipú transmission or be attached to the Basic Network, GtW also requires a practice of priority dispatch, by a contract of quantity (and not availability). Policy changes are urgently needed to coordinate regulation of the electricity and gas sectors.

Probabilistic Neural Network with Bayesian-based, spectral torque imaging and Deep Convolutional Autoencoder for PDC bit wear monitoring

Drill bit wear monitoring plays an important role during drilling operations, particularly in drilling challenging environments, such as ultradeep water and hard rock formations. The machine learning algorithms, applied to real-time analysis, has occupied an important role in the oil well industry. We here propose a machine learning system to aid drill bit wear assessment for real-time operations, using a Probabilistic Neural Network (PNN) and Bayes Theorem, combined with Power Spectral Density (PSD) of surface torque image and feature extraction by Deep Convolutional Autoencoder (DCAE). A case study was performed with wells from Brazilian ultradeep water pre-salt fields. The analysis shows that a feature extraction DCAE is more efficient to discriminate the bit wear state when compared with PSD torque image and torque raw data. After that, several numerical experiments were performed to investigate the best machine learning classification model, considering DCAE feature extraction. The cross-validation results considering all the dataset shows the PNN evaluation metrics: 87% accuracy, 83% precision, 91% recall and 86% for F1-score. The field tests validation was performed in real-time simulation, with 3 wells from the original dataset plus 2 offset wells. The simulations show that the proposed system can capture the best moment for the tripping pipe to replace a worn-out drill bit. The field tests experimental results indicate that the system proposed can aid drilling engineers in monitoring Polycrystalline Diamond Compact (PDC) drill bit wear in real-time operations.

Technology Focus: Intelligent Operations (May 2020)

Intelligent operations have been a focus for many parts of our industry for close to 2 decades. Our understanding of what this means, how it can be realized, and the boundaries of what is possible have advanced significantly in this period. Initial industry focus was around acquiring more real-time data (e.g., pressures and temperatures) along the flow path from reservoir to the point of sale and optimizing overall field performance. From the initial, simpler integrated-asset models, we have advanced to integrated work flows that enable optimal management of very large and complex fields and their equally complex surface facilities (papers SPE 196564 and SPE 197361). Another area of focus was using smart well completions to optimize production and injection reactively and proactively. Downhole technology and capabilities have matured significantly since the original installations in the late 1990s. The first paper highlighted here, SPE 195935, describes learnings from more than 100 intelligent well completions in presalt fields located in the ultradeepwater Santos Basin offshore Brazil. The industry continues to push the boundary on how this technology can be applied further (papers SPE 195850 and SPE 195361). The future of intelligent operations in our industry is being driven by advances from other sectors that have been embraced for petroleum applications. Foundational changes already taking place include advances in the type and volume of data being acquired (e.g., distributed-temperature- and distributed-acoustic-sensor data through fiber) and how the data are used. Paper SPE 194127 describes how smarter gauges with microelectromechanical-system inertial measurement sensors can enable more-accurate wellbore-trajectory estimation. We are leveraging the Internet of things, artificial intelligence, and machine-learning technologies capable of handling large volumes of data to analyze and optimize all aspects of upstream operations in real time, as seen in the next two papers highlighted in this section. In paper SPE 194084, electrical engineers, computer scientists, and drillers collaborate to use deep-learning techniques for real-time classification of cutting volumes at the shale shakers using a video feed from the rig. All of the technology advances also come together in paper OTC 29531, where live data streams from multiple sources, including wave states, motion sensors, and pressure and temperature gauges, are used with machine learning to develop a live fatigue counter for the risers on a floating production, storage, and offloading vessel and establish that facility life extension is possible. However, especially in these uncertain times, frequent hand washing with soap might indeed be the most intelligent operation of all. Stay safe!

Effect of CO2 on the dynamic and equilibrium interfacial tension between crude oil and formation brine for a deepwater Pre-salt field

Interfacial tension (IFT) between oil and brine is key to determine the Capillary Number, which governs capillary forces in the porous medium. As a result, changes in IFT affect the displacement efficiency and the residual oil saturation having direct impact on the Recovery Factor. Fluids in Pre-salt fields (offshore Brazil) have particular characteristics, such as high salinity in the brines, elevated content of asphaltenes and resins in the oils and high CO2 content in the produced gas for some fields. The effect of CO2 on the IFT depends on complex electrostatic and acid-base equilibria, and cannot be predicted by a single fluid property. This work presents the experimental study of the effect of CO2 dissolution on the IFT between a Pre-salt oil with a high total base number (TBN) and non-negligible total acid number (TAN) and a high salinity brine using the pendant drop technique. The oil and its asphaltenic fraction were characterized by Fourier-transform infrared spectroscopy, nuclear magnetic resonance spectroscopy, and elemental analysis identifying characteristic functional groups and indicating both acidic and basic polar functional groups. CO2 dissolution resulted in an IFT increase of 56% evidencing that, despite the high TBN of this oil, basic groups have low surface-activity. Moreover, a study of IFT as a function of pH showed that the maximum IFT was found in strongly acidic environments, but constant IFT values were obtained at neutral and basic pH values. Thus, the interfacial activity is governed by asphaltenes and resins with polar groups of varying acid/base behavior. The presence of CO2 also accelerated the dynamic behavior of IFT reducing the equilibrium time by 70%. This is caused by the reduction of oil viscosity, which impacts the relaxation time and enhances the diffusion of surface-active species towards the interface. The results in this work evidence that the CO2 content should be considered when modeling fluid properties for this type of reservoirs, as it affects the oil-brine IFT. In addition, for this oil with high content of surface-active compounds and non-negligible TAN and TBN, CO2 flooding does not contribute to reduce the IFT. Therefore, the efficiency of this Enhanced Oil Recovery technique in this type of field relies on viscosity reduction, miscible displacement and wettability alteration rather than IFT reduction.

Multiscale Integration for Karst-Reservoir Flow-Simulation Models

Summary The significant oil reserves related to karst reservoirs in a Brazilian presalt field add new frontiers to the development of upscaling procedures to reduce time for numerical simulations. This work aims to represent karst reservoirs in reservoir simulators using special connections between matrix medium and karst medium, each modeled in different grid domains of a single-porosity flow model. This representation intends to provide a good relationship between accuracy and simulation time. The concept follows the embedded discrete-fracture model (EDFM) developed by Li and Lee (2008) and later extended by Moinfar et al. (2014); however, this work extends the approach for karst reservoirs [embedded discrete-karst model (EDKM)] by adding a representative volume through gridblocks to represent karst geometries and porosity. For the extension of the EDFM approach in a karst reservoir, we adapt the methodology to four stages: construction of a single-porosity model with two grid domains; geomodeling of karst and matrix properties, each for the corresponding grid domain; application of special connections through the conventional reservoir simulator to represent the transmissibility between the matrix and the karst medium; and calculation of transmissibility between the matrix and the karst medium. For a proper verification, we applied the EDKM methodology in a carbonate reservoir with megakarst structures, which consists of nonwell-connected enlarged conduits and greater than 300 mm of aperture. The reference model was a refined grid with karst features explicitly combined with matrix facies, including coquinas interbedded with mudstones and shales. The gridblock of the reference model measures approximately 10 × 10 × 1 m. For the simulation model, the matrix-grid domain has a gridblock size of approximately 100 × 100 × 5 m. The karst-grid domain had the same block size as the refined grid. Flow in the individual karst-grid domain or matrix-grid domain is governed by Darcy's equation, implicitly solved by a simulator. However, the transmissibility for the special connections between karst and matrix blocks is calculated as a function of open area to flow, matrix permeability, and block-center distance. The matrix properties were scaled up through conventional analytical methods. The results show that EDKM had a considerable performance regarding a dynamic matching response with the reference model, within a reduced simulation time, while maintaining a higher dynamic resolution in the karst-grid domain without using an unconstructed grid. This work aims to contribute to the extension of the EDFM approach for karst reservoirs, which can be applied to commercial finite-difference reservoir simulators. This could be a solution to reduce simulation time without disregarding the explicit representation of karst features in structured grids.

Colombia’s New Ambitions Include Caribbean and Shale Development, But Are They Achievable?

At some point during the first half of this year, Colombia replaced politically and economically crippled Venezuela as Latin America’s third-largest oil-producing country. That put Colombia behind only Brazil and Mexico in the hydrocarbons-rich region, two nations on divergent paths in terms of oil flow. Since Brazil ended state-owned Petrobras’ monopoly and opened up its industry to international companies in the late 1990s, the country’s oil output has almost tripled as it found and tapped into its giant offshore presalt fields. Output from Mexico’s state-owned Pemex, meanwhile, has fallen to its lowest level since at least 1990, and President Andrés Manuel López Obrador is working to stymie energy reforms implemented in 2013 to rejuvenate industry in the country. With the lessons of its resource-rich neighbors in mind, Colombia finds itself in a similar position where it must carefully choose a path forward for its industry or risk squandering great potential, or worse, losing what took years to build. The Andean country in the early 2000s overhauled its regulatory framework, reduced government take, and held licensing rounds with the intent of attracting foreign investment. Oil production subsequently rose to more than 1 million B/D before dropping amid the global industry downturn. Output in May averaged just short of 900,000 B/D. The Colombian government is trying to build on the foundation established by those reforms by implementing a novel permanent, continuously open bidding process and exploring unconventional development. The aim is to replenish depleted oil and gas reserves and increase production. Based on its 2018 output, the country’s crude reserves are good for just 6.2 years, while its natural gas reserves would last 9.8 years, falling below the 10-year mark for the first time in decades, according to statistics from Colombia’s National Hydrocarbons Agency (ANH). But Colombia has long been seen by the global industry as a petroleum province with upside that surpasses just incremental reserves and production gains. All of its liquids and nearly all of its gas production is extracted conventionally onshore, meaning its offshore and unconventional sectors are nascent. Colombia, which shares a more than 2000-km border with Venezuela, has proven petroleum systems that have produced oil and gas for a century, and the application of horizontal drilling and hydraulic fracturing offers huge promise.• Maria Fernanda SuÁrez, Colombia’s minister of mines and energy, has said that unconventional development could triple the country’s oil and gas reserves. Standing in the way, however, has been public resistance to hydraulic fracturing, and pilot projects that would demonstrate its benefits are yet to get environmental approval. There is “game-changing potential—if the industry can get going with development,” said Ruaraidh Montgomery, research director at oil and gas research firm•Welligence Energy Analytics.

Lifetime sensitivity analysis of FPSO operating parameters on energy consumption and overall oil production in a pre-salt oil field

Floating production storage and offloading (FPSO) platforms are great energy consumers. Reservoir fluid composition and operating parameters of FPSOs are known to be important parameters for the total energy demand, and also for enhancing overall oil production. In the current research paper, the contribution of eight thermodynamic input parameters of a typical Brazilian FPSO operating on a pre-salt field is quantified by the Smoothing Spline ANOVA method for two responses: (i) energy consumption of the plant and; (ii) overall oil production. Three operation modes are considered in the analysis: Mode 1 (maximum oil/gas content), Mode 2 (50% BS&W) and Mode 3 (maximum water/CO2 content). The input parameters considered in the present research are: output pressure of the first control valve (P1), output pressure of the second stage of separation train (P2), input pressure of the third stage of separation train (P3), output pressure of dilution water pump (P4), output pressure of the main gas compressor (Pc), petroleum temperature of the first heat exchanger (T1), petroleum temperature of the second heat exchanger (T2), and dilution water temperature of heat exchanger (T3) are considered as input parameters. In terms of energy consumption, parameters P3 and Pc are always relevant for all operation modes. Furthermore, P3, P2, and T2 are the most important parameters for overall oil production for all operation modes.