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ABSTRACT Production DBN and optimization is one of the highest-ranking topics in the current Oil and Gas market scenario, along with one of the most complex and multi-disciplinary from an operational point of view. Compared to traditional industrial standards, multiphase CFD analysis has already shown its high potential in simulating production system processes, increasing the accuracy and the understanding of involved phenomena. In this paper, an innovative multiphase CFD procedure based on the Eulerian-Eulerian approach has been successfully implemented in an offshore gas/condensate field. The CFD analysis was performed with OpenFOAM, a completely customizable C++ toolbox. The procedure is based on different solvers programmed ad hoc and applied in series, starting from the first one, which introduces a simplified new approach to Navier-Stokes equations for multiphase flow, and proceeding with more accurate tools after some iterations. This allows to get high quality solutions, decreasing significantly the computational efforts. In the application of the developed tool to a real case study, the attention has been focused on two main operating issues:the optimization of the reservoir exploitation through the production system DBN and the maximization of condensate recovery, respecting the contractual limitations. The CFD workflow has been applied on the most critical node of the network, i.e. the slug catcher. The analysis started from the generation of an accurate CAD model, which represents the real geometry, simplified considering symmetry effect. Then, a high quality mesh was created and tuned in order to both ensure accuracy and reduce computational effort. Finally, a sensitivity analysis on main working parameters was carried out in order to get the optimum operating conditions for the slug catcher, maximizing the gas and condensate production. The work revealed the strategic significance of CFD analyses for assets optimization and DBN, allowing the tuning of the operating conditions in nodal analysis and most importantly increasing the gas and condensate recovery without any additional cost. INTRODUCTION During the past decade the depletion of the traditional reserves along with the increasing demand have exposed the Oil and Gas Major to invest a lot of money in the exploration and exploitation of fields in harsh environment and complicated conditions. This research was previously sustained by the high price of the oil that grant to repay the undertaken investments. The oil price crisis started in 2015 has completely changed the strategic "game" of field exploitation. To overcome the instability derived from this context, the top Oil companies are focusing their attention on advanced optimization techniques to enhance the performance of their production facilities.
ABSTRACT The current industrial standards adopted to simulate the liquid particle erosion phenomena are based on 1-D equations prescribed by the API114E, which computes the erosion limit velocity related to different materials considered. Therefore, this method relies on simplified models and empirical correlations, validated by experimental data, but characterized by the requirements of an over-design margin factor, to face the large uncertainty intrinsic with the physical phenomenon. In this paper, two CFD multiphase procedures able to simulate the liquid erosion effect in continuous gas phase are presented and applied to support the start-up operations of a new gas/condensate field located offshore in Central America. Indeed, the insurgence of dangerous liquid/gas erosions phenomena, can affect significantly the platform production manifold before the sea line. The procedures are based on two different approaches and tools: the Eulerian/Eulerian implemented on OpenFOAM and the Lagrangian/Eulerian investigated with Fluent. In both cases, the flux is considered fully dispersed, and a new algorithm that evaluates and sets the liquid droplet diameter as a function of Webber number, flow regime and geometry variations has been included. In the first case both liquid and gas are modelled using the Eulerian framework, applying an innovative application devolved in OpenFOAM for two-phase dynamics. The critical erosion velocity is computed along with the superficial pressure and consequently the shear stress on the wall. This allows to apply an experimental model (from literature) able to estimate the rate of erosion to the Eulerian solver. On the other hand, the second approach implements a coupled Lagrangian (liquid) Eulerian (gas) framework. In this case the dispersed phase is not able to penetrate the continuous one, but it is absorbed by the wall after the erosive impact. The same reference model for erosion rate evaluation has been adopted to tune the tools already offered by Fluent. The comparison of the results obtained by both CFD analyseis and industrial standards is reported and within this work. Final recommendations to be applied on field for start-up operations have been summarized. The CFD procedures developed seems to offer the possibility to gain a deeper understanding of erosional physical phenomenon effects: erosion rate, critical velocity, shear stress and phases distribution. This gives the capability to reduce the uncertainty related to the industrial standards, maintaining the computational efforts for the Oil and Gas time scale competitive and optimizing the operating conditions during the entire life of the asset.
ABSTRACT The current oil price scenario is strengthening industry's attention towards more efficient exploitation of resources. Low return rates and marginal new field economics enhance the need for existing assets production performances. This paper presents a set of process Key Performance Indicators, applied to an existing onshore treatment plant and implemented into a real-time monitoring system. The defined KPI's use real-time data to identify possible process upsets and support their root cause identification. Moreover, they have been proven to be a valuable aid in forecasting the equipment's performance degradation. A set of KPIs has been defined for some critical section of an onshore oil plant: separation, stabilization column, sweetening unit and heat exchangers. An optimum value along with a maximum and minimum value has been defined for each KPI, in order to monitor the performance of the aforementioned plant sections. The defined KPI's has been validated against real upsets on separators and sweetening unit occurred in the plant due to inlet flow rate perturbations. Finally, the defined KPI's have been implemented into a "Digital Oilfield" system. Upstream process plants need to face continuous fluctuation of process parameters due to variations coming from wells. As a result of KPIs' validation against real upsets occurred in the plant, these indices has been proved valid to be used for process upset identification and forecasting, as well as equipment performance degradation monitoring. Data filtering and post-processing has been studied in order to allow the implementation of this set of KPI's in "Digital Oilfields" by eliminating abnormal values coming from real-time data monitoring systems. Definition of KPI's for process treatment units and their implementation into "Digital Oilfields" is a very valuable support for field operation. This study provides a set of process KPI's relative to some treatment unit, that can also be extended to similar units in other plants. The capability of immediate intervention on process variables and production improvement was deemed possible thanks to KPIs' implementation into "Digital Oilfields".
ABSTRACT Faster simulation time continues to be a major industry priority for real-time application of integrated optimization asset modeling. Simultaneously, model sizes are rapidly becoming computationally more expensive. A new parallel simulation solution has been developed to quickly solve the largest and most complex modeling studies. This paper shows the benefits of the new parallel technique applied to a real case optimization. The described production optimization tool has the ability to integrate in a unique environment a whole production system, from wellbore to export and storage. A powerful evolutionary algorithm searches for the optimum field configuration that maximizes production. The tool computes the "fitness" of each solution, combines their properties in order to obtain new candidate solutions, and then selects the best individuals to allow the evolution of the population and detect the optimum. A master machine creates the individuals to be tested and multi-thread computation on a large number of simulation nodes allows to drastically reduce run times. The parallelism has been developed and applied to a complex integrated production optimization case study in order to prove the benefits of the novel architecture in terms of computational efforts. The tool was applied to the largest onshore oil field in Europe, with a very complex gathering network, and a large process plant composed of five treatment trains comprising acid gas removal and sulphur recovery unit. Comparison between the traditional and the parallel simulation architecture applied to the integrated production model of this asset shows a significant reduction in run times, decreasing from days to hours. These drastically reduced computational efforts have allowed the new simulator to include heavy computational methods to build more accurate models. Furthermore, the integrated production optimization tool has been developed to become an enterprise solution with an end-user friendly graphic interface linked to a common database for data handling and storage. This paper describes an innovative parallel simulation approach for an integrated production optimization tool. Reduced computational efforts and the possibility to build more accurate models are the main advantages of this tool, together with a newly developed friendly user interface. The benefits introduced by the novel parallel computational method developed for the tool guarantee real-time support to field production optimization even for the largest and most complex models.
Take on Challenges in Deep-Water Production Optimization: A Real Successful Application of an Innovative Integrated Modelling Tool
Brioschi, S. (Eni Upstream & Technical Services) | Montini, M. (Eni Upstream & Technical Services) | Cerri, P. (Eni Upstream & Technical Services) | Scaramellini, S. (Eni Upstream & Technical Services) | Bianco, A. (Eni Upstream & Technical Services) | Masi, S. (Eni Upstream & Technical Services)
ABSTRACT The current oil price scenario is strengthening industry's attention towards a more efficient exploitation of resources. Low rates of return and marginal new field economics enhance the need for existing assets production optimization, especially for deep-water applications. This paper shows the results obtained from a real application on a deep-water asset of an innovative tool for the integrated production optimization of surface facilities based on a genetic algorithm. The described tool, coupled with its fluid-dynamic check workflow, has been applied to investigate the optimum configuration of the asset. The presented tool integrates well performances, gathering system calculation, and process plant simulation in order to optimize the field configuration with a global perspective. Conflicts and interactions between variables, constraints, and operational limitations are balanced and solved holistically by the optimization tool. The tool computes the "fitness" of each solution, combines the properties of them in order to obtain new candidate solutions, and then selects the best individuals to allow the evolution of the population and detect the optimum. The optimum configuration identified by the tool has been tested with a fluid-dynamic simulator in order to check its stability and identify the best operating procedure to reach the optimized configuration. The integrated production optimization tool has been applied on a FPSO with the aim to increase the production of the assets respecting all the operative and flow-assurance constraints typical of a deepwater application. The subsea network consists of seven oil wells connected to an FPSO with two identical parallel flowlines. Subsea manifolds allow to produce each well either through a flowline or the other. Furthermore, additional four wells are connected through a separate flowline to the same FPSO. Wells re-routing is treated by the tool as an optimization variable, allowing to explore all the possible available network configurations simultaneously. Additionally, a fluid-dynamic check workflow was implemented, in order to define the best procedure to switch from the current configuration to the optimized one, respecting all system constraints also during transient conditions. Finally, the optimization actions identified by the tool has been implemented successfully in the field. The paper describes an innovative approach for production optimization on a deep-water application. The integrated production optimization tool was able to explore all the possible network configuration simultaneously, thanks to the limited computational efforts required by the tool. Field application showed its benefits in terms of production enhancement, respecting all system constraints without running into any flow-assurance issue typical for deep-water. The first deepwater application of the tool confirms its robustness for production optimization purposes.
ABSTRACT The current oil price scenario is strengthening the industry's attention towards a more efficient energy usage. This paper shows the energy saving results obtained from field application of an innovative tool for the integrated production optimization of surface facilities based on a genetic algorithm. The objective function of the tool is tailored for each of the described case studies in order to increase field production and reduce energy consumption. The presented tool integrates well performances, gathering system calculation, and process plant simulation in order to optimize the field configuration with a global perspective. Conflicts and interactions between variables, constraints, and operational limitations are balanced and solved holistically by the optimization tool. For each of the field application case studies presented a tailored energy efficiency objective function is defined to optimize production and energy consumption. A powerful evolutionary algorithm searches for the optimum field configuration that represents the best trade-off between efficient usage of energy resources and production maximization. The integrated production optimization tool has been applied on different fields with the aim of simultaneously increasing the energy efficiency of the assets and optimizing production. The benefits of the integrated optimization tool to boost energy efficiency have been proved on an offshore field application. The action suggested from the optimization tool permitted production increase, reducing the global energy losses of the system. A second application is presented, where a significant energy saving has been achieved by the optimized configuration suggested from the tool to recover production after a process upset. All the described applications show a relevant energy saving in terms of primary energy consumption, associated with the increase of field production. This paper describes an innovative approach to increased energy efficiency in oil and gas industry operations. The application of the integrated production optimization tool showed its benefits by improving process and equipment operations and reducing associated operating costs without capital expenditures on energy efficiency.
ABSTRACT This paper presents a novel CFD analysis of an Oil& Gas separator, based on a multi-fluid Eulerian-Eulerian model of the Navier-Stokes equations, implemented in OpenFOAM®. The simulation of a three-phase separator poses a particular challenge to the numerical modeling of transport phenomena since the three-phase flow can span across multiple flow regimes from disperse to separate. To handle such complex behavior, a new three-phase Eulerian-Eulerian solver has been implemented in OpenFOAM with a fully implicit treatment of drag terms and with the capability to describe both disperse and separate flow at high, fully coupled phase fractions. Furthermore, the mixture turbulence model implemented in OpenFOAM for bubble flows has been improved. Firstly, the source term of the turbulent kinetic energy has been modified with a more regime-independent formulation derived from the literature. Then, the derivation of the same model has been extended in order to manage the three phases. The work represents an improvement both from an academic and industrial perspective: it provides a consistent numerical framework for a multiphase flow involving a number of phases higher than two; it replaces the traditional Eulerian-Lagrangian approach with the more appropriate Eulerian-Eulerian one for the analysis of industrial production facilities. These two aspects allow to describe more accurately the flow pattern transitions and to numerically capture the separation and phase inversion phenomena inherent to the system. INTRODUCTION Nowadays, multiphase flows can be considered as the standard condition for the majority of the Oil&Gas production fields. The reasons for this peculiarity are numerous and can be related to different parts of the hydrocarbons production chain. As an example, injection of fluids to sustain production as well as the presence of an active gas cap or an aquifer determine the existence of at least two different phases in the upcoming flow streams. Moreover, the difference in pressure between the wellbore and the production tubing determines the production of a certain (and in many cases non negligible) amount of gas (if the bubble point condition is reached) and the possible arising of non-ideal volumetric behaviors (e.g., retrograde condensation).
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