Offshore Oil Production Systems Research Articles

Multi-level predictive maintenance of smart manufacturing systems driven by digital twin: A matheuristics approach

Digital twin technology is gradually being applied to smart manufacturing systems and is providing valuable information for predictive maintenance of swarms of machines, but also raises the need for more accurate and real-time decision making. However, there is still a shortage of research in this area. This paper proposes a general multi-level predictive maintenance decision-making framework driven by digital twin, considering component dependencies, the variable time scale of decisions, and comprehensive maintenance resources, in which an optimal maintenance schedule can be obtained in real time and then fed back to the physical space, so as to realize closed-loop control. A maintenance decision-making optimization model is then formulated based on integer linear programming to minimize total maintenance costs while meeting required production capacity. Further, a novel matheuristics algorithm (i.e., the interoperation of metaheuristics and mathematical programming techniques) is introduced for various maintenance decision scenarios. Finally, a case study of an offshore oil and gas production system consisting of eight subsea Christmas trees is examined, and the effects of changes in production capacity, failure thresholds, and maintenance resources on the multi-level optimization of decision-making solutions are discussed.

INFLUENCE OF THERMOPHYSICAL PROPERTIES ON TRANSFER OF HEAT IN MULTI-LAYER DUCTS AND TEMPERATURE CONTROL USING ELECTRIC HEATING

Ensuring oil production flow in offshore systems is a critical aspect of oil exploration operations. Any interruption in the production process, whether partial or complete, can result in significant financial losses and cause solid deposition in the production line. Such deposition is due to the crystallization of paraffin and hydrates, a common problem caused by low temperatures in deep waters. Among various mitigation strategies, the Pipe-in-Pipe (PIP) system with active heating is a technological solution to address this issue. This work aimed to perform a numerical simulation of the PIP system using the Finite Volume Method with an implicit formulation, considering the effect of temperature on fluid properties and the system's dynamic response. A control loop using a PI velocity algorithm was developed to maintain the temperature above the critical point. Such simulation studies were performed using the Python programming language in the Anaconda suite. The results showed that the fluid properties greatly influence the dynamic response. The PI control maintained the temperature in the desired condition, demonstrating its operational effectiveness in preventing solid deposition and delivering stable and low-oscillatory behavior. This research emphasizes the significance of taking temperature's impact on fluid properties into account when simulating offshore oil production systems and demonstrates the effectiveness of implementing feedback control.

Robust optimization model of an offshore oil production system for cost and pipeline risk of failure

Robust optimization model of an offshore oil production system for cost and pipeline risk of failure

Research on transient composition tracking in natural gas condensate pipeline networks

Offshore pipelines are hailed as the “lifeline” of an offshore oil and gas production system and are essential for offshore oil and gas development. Component tracing technologies for the oil and gas multiphase transmission pipeline networks need to be urgently developed to predict the fluid composition changes in pipeline networks. Instead of assuming the fluid components are constant, we consider they varied with flow. The component conservation equations and a phase change model are established. The equation of state of the fluid is adopted to determine the equilibrium state of each component in real time. Considering the macroscopic flow calculation, microscopic fluid components, and phase equilibrium, the component tracking algorithm is established for natural gas condensate pipeline networks, which can dynamically track the fluid composition in pipeline networks and calculate the phase exchange amount and related flow parameters in real time. Three case studies are performed to verify the effectiveness of the algorithm. These findings are of great practical significance for understanding the gas–liquid two-phase flow in pipeline networks, promoting further engineering applications of component tracking on pipeline networks.

Time series prediction of hydrate dynamics on flow assurance using PCA and Recurrent neural networks with iterative transfer learning

Preventing gas hydrate formation is critical in offshore gas and oil production systems. Several models can predict hydrate formation, however, these empirical approaches have limitations due to dependency on geometries and fluid characteristics of the systems. The trends of hydrate formation or risk are considered statistical, which means there is no definite model to describe its behavior. Herein, we present a novel framework based on a combination of feature reduction methods and several deep learning models to predict the hydrate formation trend through the multivariate sensor data. Transition and segregation trends during hydrate formation were predicted in real-time using sequential time series data from the last 60 s. We employed various deep learning models (Dense, LSTM, GRU, ARLSTM), layers, and dropout to investigate and enhance the prediction ability of each model. Two groups of experimental data (200 rpm, 600 rpm) were used for training and testing the prediction to examine the universal applicability of the model. Transfer learning in training the model was employed to apply the discrete experimental set into time-series data and enhance the accuracy. The results with higher layer numbers and a dropout rate of 0.2 ∼ 0.6 showed the best performance. ARLSTM showed the smallest error among deep learning models and predicted the good trend of kinetic characteristics (transition and segregation part) during the hydrate formation. This approach based on deep learning can be adopted for risk and issue detection of pipelines in the gas production system.

Numerical quasi-three dimensional modeling of stratified oil-water flow in horizontal circular pipe

The stratified oil-water two-phase flow is commonly encountered in offshore oil production systems, and is considered to be among the fundamental flow configuration in two-phase systems. A numerical quasi-three dimensional model for the calculations of the axial pressure gradient, interface height, water holdup, and the flow field in a fully developed oil-water two-phase stratified pipe flow has been developed. The oil-water curved interface configuration is predicted by using minimum energy model. The model solves the governing equations of the steady axial momentum and mass conservation equations together with a low Reynolds number k～ε model of turbulence for the eddy viscosity, performed in the bipolar coordinate system, for convenient describing the curved interface and mapping of the physical domain. The predicted dynamic parameters, such as interface height of close to the pipe wall and in the middle of the pipe cross-section, water holdup, pressure gradient and flow filed are compared with the experiments. At the same time, this model is utilized to study the variation of these dynamic parameters with increasing superficial oil and water velocities. In addition, the numerical model with concave oil-water interface gives more accurate results than a flat interface. It indicates that the interfacial configuration effects are significant.

Towards the Green Economy: an MCDA approach to decommissioning offshore oil and gas production systems

The objective of this study is to explore and analyze the application of the Exponential TODIM method (ExpTODIM), by taking into consideration the proposition made by Petrobras to the Brazilian National Agency for Petroleum, about the decommissioning of the Marlim and Voador production fields. The exploration takes into consideration different perspectives based on the different perspective of the Proponent institution, as well as on that of the Regulator. The application of the ExpTODIM approach increased robustness by different preference structures created with a choice between alternatives and adopting a sensitivity analysis through variations in the decision significance level.

Upstream-flow-based mechanisms for global flow regime transition of gas/liquid two-phase flow in pipeline-riser systems

In order to develop the transition models for undesirable two-phase flow regimes in a pipeline-riser system in offshore oil and gas production systems, the relation between the upstream flow condition in the pipeline and the global flow regime is analysed. The transition of local flow pattern along the upstream pipeline, especially the slug dissipation behaviour, is found to be related to global flow regime transition. The mechanisms for the transition from stable flow regime to different undesirable flow regimes are proposed separately. A set of hybrid criteria is established and validated by experimental data. The proposed criteria can predict the transition to undesirable conditions which are less severe but more common than the typical cases, compared with existing uniform criteria. The findings can help for better understanding of flow regime transition in a pipeline-riser system with more complex layout of pipeline, and also the possible extension of laboratorial experimental results.

Measurement of thickness and analysis on flow characteristics of upper swirling liquid film in gas-liquid cylindrical cyclone

The gas-liquid cylindrical cyclone (GLCC) is a device used to separate gas from liquid in offshore or subsea oil and gas production systems. The liquid film swirling along the upper cylinder wall in the GLCC is referred to as “upper swirling liquid film” (USLF). The flow patterns of USLF have a great influence on GLCC’s separation performance. However, the dynamics of the gas-liquid flow in a GLCC, especially the USLF characteristics, have not been well understood. In this study, experiments were conducted to investigate flow characteristics of USLF in a GLCC. The range of gas and liquid Reynolds numbers, Reg and Rel, was 27,869 ≤ Reg ≤ 68,120 and 2,881 ≤ Rel ≤ 14,335 respectively. The USLF’s thickness was measured using button electrodes. The results showed that the liquid film became thinner after leaving the inlet and the circumferential fluctuation of the thickness was not significant. The gas-liquid velocities had significant influences on film thickness, which increased almost linearly as liquid velocity increased, while presented a roughly S-shaped distribution as gas velocity increased. The friction factors of GLCC were determined based on the measured liquid film thickness and pressure drop. Additionally, the USLF’s flow patterns include swirling annular flow and swirling churn flow. Finally, a judgment criterion for flow pattern transition was established under the minimum gas-liquid interfacial stress theory. The model could accurately predict the transition condition. This work may provide a basis for comprehensive understanding of USLF characteristics.

A distributed feedback-based online process optimization framework for optimal resource sharing

Distributed real-time optimization (RTO) enables optimal operation of large-scale process systems with common resources shared across several clusters. Typically in distributed RTO, the different subsystems are optimized locally, and a centralized master problem is used to coordinate the different subsystems in order to reach system-wide optimal operation. This is especially beneficial in industrial symbiosis, where only limited information can be shared between the different clusters. However, one of the main challenges with this approach is the need to solve numerical optimization problems online for each subsystem. With the recent surge of interest in feedback optimizing control, where the optimization problem is converted into a feedback control problem, this paper proposes a distributed feedback-based RTO (DFRTO) framework for optimal resource sharing in an industrial symbiotic setting. In this approach, a master coordinator updates the shadow price for the shared resource, and the different subsystems locally optimize their operation using feedback control for the given shadow price. The proposed framework is shown to converge to a stationary point of the system-wide optimization problem, and is demonstrated using an industrial symbiotic offshore oil and gas production system with shared resources.

Multi-target Inherent Safety Indices for the Early Design of Offshore Oil&Gas Facilities

Improved tools are needed to manage major accident hazard of progressively more complex offshore oil&gas systems in environmentally sensitive areas. Inherent safety principles provide a strategic opportunity to reduce major accident hazards since the early design phase, but a suitable metric to orient safer design choices is needed to apply such principles intro practice. This study aims at providing a systematic approach to the assessment of the hazard profile of alternative process designs in offshore oil & gas production facilities. A novel methodology providing a ranking of inherently safer solutions in conceptual design is described. The methodology is able to highlight the different contributors to the safety profile of the offshore oil & gas production system, linking them to the specific features of the design. The proposed approach, based on multi-criteria Key Performance Indicators (KPIs), addresses different targets (people, assets, environment) and provides a quantitative assessment of the safety score, accounting for both the possible accident consequences and their credibility. An application to a case study concerning an offshore facility for gas production is discussed to demonstrate the potential of the methodology.

Availability analysis of an offshore oil and gas production system subjected to age-based preventive maintenance by Petri Nets

The main objective of this paper is to model an offshore oil production system subjected to age-based preventive maintenance strategies by Petri Nets and to evaluate its availability by Monte Carlo Simulation. The oil processing and the separation equipment with their reliability and maintainability characteristics, the corrective and preventive maintenance policies and the operational dependencies that lead to the reconfiguration of the system after the failure are implemented. A special attention is given to the effect of age-based perfect and imperfect preventive maintenance strategies on the system availability. The maintenance actions consider the components’ age thresholds and an age reduction ratio. Moreover, the variation of the oil and gas flows from the well over the years is accounted by the model. As case study, an offshore production installation that operates in a Brazilian oilfield is adopted. An elasticity analysis on the model parameters is conducted to assess influence of the maintenance policy on the system availability and on the oil production.

A finite element model for unbonded flexible pipe under combined axisymmetric and bending loads

Flexible pipes are key equipment for offshore oil and gas production systems, conveying fluids between the platform and subsea wells. The structural arrangement of unbonded flexible pipes is quite complex, encompassing several layers with polymeric, metallic and textile materials. Different topologies and a large amount of intricate nonlinear contact interactions between and within their components, especially because of the relative stick-slip mechanism during bending, makes numerical analysis challenging. This paper presents an alternative three-dimensional nonlinear finite element model that describes the response of flexible pipes subjected to combined axisymmetric and bending loads. To simulate the response of a flexible pipe under axial tension or compression combined with uniform curvature, an equivalent thermal loading is employed on the external sheath, which is modelled as an orthotropic thermal expansion material with temperature-independent mechanical properties. To assess the feasibility of the proposed model, the bending moment versus curvature of the finite element solution is compared with experimental results obtained in literature and good agreements are found between them. Detailed finite element results such as contact pressures, armour wire slip displacements and friction, normal and transverse bending stresses are also shown and compared with available analytical models.

Heat dissipation of the Electrical Submersible Pump (ESP) installed in a subsea skid

The recent development of Electrical Submersible Pump (ESP) in the skid, installed in the seabed downstream of the wellhead in an offshore oil production system, is an alternative to the conventional system with the set installed at the bottom of the producing well, facilitating interventions in case of failure. The pump is driven by an electric motor whose cooling must be efficient to ensure the continuity of its operation. The heat withdrawal is performed by the fluid produced. The purpose of this article is to understand the process of electric motor cooling to the single-phase and turbulent flow with convection heat transfer in an annular geometry, which represents the space formed between a capsule and the ESP in the Skid system motor. With this objective it is employed a Computational Fluid Dynamics (CFD) code to solve the governing equations of the turbulent heat transfer single-phase flow. The standard κ-ε model with improved wall function (Enhanced Wall Treatment) is used to closure turbulence problem. This study considered flow rates range of 2200–4200 m3/d (representing Reynolds numbers range of 27 000–133 000 approximately), Prandtl numbers 7–37, three configurations of different annular geometries, one concentric and two eccentric, together with the condition of the constant temperature on the motor surface (130 °C) and capsule (4 °C). The simulations are validated by comparing the Nusselt number in the developed region with the Gnielinski correlation. It is observed that if the constant heat flux condition were used, the motor temperature would have lower values at the beginning and larger at the end of the geometry. Therefore, the higher the Nusselt number, the greater the heat transfer, thus intensifying the cooling of the electric motor. In the eccentric geometry a momentum transfer from the lower to the upper annular region is observed, causing the Nusselt number present an angular variation. In eccentric geometries the flow develops in greater lengths, observing that the greater the eccentricity, the greater this length. Finally, for the ESP in the Skid system the use of an eccentric geometry is not adequate.

Phase split of oil-water two phase flow at double-layer T-junctions pipes

Offshore oil and gas production systems are in urgent need of a more compact, high-efficient oil-water separator. T-junction pipes are a potential solution to the need. Combining dynamic separation principle of T-junctions pipes with shallow pond theory, this paper presents a novel design of double-layer T-junctions pipes to realize high-efficient oil-water separation. The separation system consisted of upper and lower double-layer pipes that are connected by two vertical pipes. There exists an axially floating oil pipe along the top of the upper outer pipe. This design makes the Reynolds number decrease, which is beneficial to the formation of oil-water stratified flow. The slender seam at the bottom of inner pipe reduces the turbulence intensity, thus avoiding remixing oil with water. The influence of mixture velocity, oil content, water superficial velocity, oil superficial velocity, and inlet flow pattern on the phase split of oil-water two phase flow at double-layer T-junctions pipes has been investigated. Experimental results showed that the separation performance was less affected by the inlet oil content than by the inlet mixture velocity. Additionally, the phase split in the separation system was very sensitive to the inlet flow pattern. For separated flow pattern, oil-water can be well separated. But for dispersed flow pattern, the oil-water separation efficiency was low. Besides, the using of floating oil pipe can increase the system separation efficiency.

Numerical investigation of flow erosion of sand-laden oil flow in a U-bend

U-bend comprised of two 90° elbows is widely used in offshore oil production systems to convey sand-laden oil flow and to adjust the flow direction, and hence one of the easily-worn part. The majority of this work is to investigate the erosion behavior of liquid-solid flow and the particle trajectories in a U-bend. The computational fluid dynamics-discrete phase model (CFD-DPM) based on the Eulerian-Lagrangian approach coupled with an erosion model is employed to solve the liquid-solid flow and to predict the erosion distribution. The numerical model is validated by the experimental data available in previous literature. The results indicate that the erosion mainly occurs in the extrados and the lower surface of the U-bend and the downstream tube. Particularly, two erosion spots along the extrados in sequence are caused by the impingement of particles. Compared to the impingement occurring at the first 90° elbow, more particles with higher velocity take part in the impingement on the second 90° elbow, resulting in severer erosion. The erosion rate is sensitive to the flow velocity and particle size. The growth of either of them results in the enhancement of erosion.

Remaining Useful Life Estimation of Structure Systems Under the Influence of Multiple Causes: Subsea Pipelines as a Case Study

In dynamic complex environments, the degradation of structure systems is generally caused not by a single factor but by multiple ones, and the process is subject to a high level of uncertainty. This article contributes a hybrid physics-model-based and data-driven remaining useful life (RUL) estimation methodology of structure systems considering the influence of multiple causes by using dynamic Bayesian networks (DBNs). The structure model and parameter model of DBNs for the degradation process caused by a single factor are established on the basis of theoretical or empirical physical models, thereby solving the problem of insufficient data. An RUL estimation model is subsequently established by integrating these degradation process models. The RUL value is obtained from the time difference between the detection point and predicted failure point, which is determined using the failure threshold of performance. The sensor data and expert knowledge can be input into the estimation model to update the RUL value whenever necessary. The subsea pipelines in offshore oil and gas subsea production systems are adopted to demonstrate the proposed methodology. The degradation processes with fatigue, corrosion, sand erosion, and internal waves are modeled using DBNs, and the RUL is estimated using a DBN-based RUL methodology.

Numerical evaluation of a subsea equipment installation method designed to avoid resonant responses

Several methods have been employed to install the different types of subsea equipment that are required for offshore oil and gas production systems. More recently, the increasing development of oil fields at remote, ultra-deepwater scenarios has been requiring heavier and more complex subsea equipment. In such scenarios the usual installation methods have been facing increasing challenges, including resonance effects associated to the dynamic behavior of the cable-equipment system. In this context, after presenting a review of the state-of-the-art of installation methods for subsea equipment, this work presents a methodology for the design and evaluation of an installation method based on the combination of steel wire and polyester ropes. The goal is to obtain a feasible and safe installation method that can avoid resonance effects along all phases of the lowering procedure, without the need of specialized devices such as heave compensators, and using only simpler installation vessels such as standard tugboats instead of more expensive and specialized vessels (such as drilling rigs). The method is evaluated by numerical simulations for case studies considering representative metocean data for Brazilian ultra-deepwater scenarios, following a methodology that considers the random characteristic of actual sea states by employing an irregular spectral representation. The results indicate that the method may indeed be feasible for the deepwater installation of heavier equipment, potentially being more cost-effective especially for remote locations where other more complex methods might become inefficient.

Design, Management and Key Success Factors of an Offshore Cathodic Protection System for Corrosion Control

Corrosion is a very prevalent issue for offshore operations in the oil and gas industry. If the corrosion issues are not addressed adequately, these may lead to quality failures, safety incidents, compromise to asset integrity and high inspection costs. This research paper discusses and analyzes corrosion types, corrosion threats, mechanisms to protect against corrosion, design and management of cathodic protection system, and key success factors for a cathodic protection system for an offshore oil and gas production system.

Are complex black-box models for Permanent Downhole Gauge pressure estimation necessary?

The Permanent Downhole Gauge (PDG) is a pressure and temperature sensor located subsea near the perforation point in the offshore oil production system. This sensor is very useful in operation problems detection (fouling, valves, plugging, etc.), multiphasic flow analysis, production tests adjustment, control strategy and model identification. Given its location under hazardous conditions, it may come to failure or imprecisions in measurement. The high costs related to the maintenance make it infeasible to perform. To overcome this issue, a methodology based on digital signal processing (DSP) is proposed in order to design a low pass digital filter aiming the PDG pressure reconstruction. The proposed methodology requires no plant model, low computational cost and only the Christmas-Tree pressure measurement. The proposed methodology is compared with two commonly employed black-box methodologies: Neural Network and Transfer Function Estimation. The results show the success of the designed filter and the advantages over the black-box approaches. The estimation of the PDG pressure from three operating wells using real process data was performed.