Offshore Oil Production Platforms Research Articles

Reactive power capacity allocation technology of shore‐based power supply system of offshore oil production platform under different network topology reliability measures

AbstractTo improve the economy of offshore oil production platform shore‐based power transmission mode, the reactive power capacity allocation technology of offshore oil production platform shore‐based power supply system based on different network topology reliability measures was proposed. The optimization model of power supply system network topology and the structure model of voltage source converter high voltage direct current transmission system were established, the start and stop control scheme of flexible direct current (DC) transmission system was designed, and the operation parameters of converter station and DC line were monitored in real time. The topological structure of offshore oil production platform shore‐based power supply system is constructed, the mathematical model of flexible DC transmission system is established when the alternating current side voltage is balanced, the reactive power capacity configuration of offshore oil production platform shore‐based power supply system is optimized, and the life cycle cost results are calculated. The experimental results show that the algorithm proposed in this paper can obtain the optimal solution only after 26 calculations, with high optimization efficiency and good convergence effect. Reactive capacity configuration of shore‐based power supply system for offshore production platform can reduce failure rate and life cycle cost.

Analysis of Critical Knowledge for Strengthening Resilience and Operational Safety

Resilience, viewed from an engineering perspective, refers to a system's inherent ability to regulate its operation before, during, and after disruptions. Knowledge is a critical resource that enables resilient responses, as it is essential for responding, monitoring, anticipating unforeseen events, and learning from their occurrences. However, despite the importance of knowledge in promoting resilience in operational safety, there is a lack of tools in the literature that provide evidence and explanation of knowledge resources. To address this gap, this article presents the development stages of an instrument based on the Critical Decision Method to elicit critical knowledge in Operational Safety Events (OSEs). The instrument includes a set of questions that guide the identification of decision-making points and the exploration of knowledge resources mobilized at each stage, founded on situational awareness, resilience engineering, and knowledge engineering. Prospective analysis sessions and retrospective OSE analyses were conducted with teams of workers from offshore oil and gas production and exploration platforms to assess the instrument's feasibility. The instrument enabled the identification of critical knowledge in both scenarios, which served as valuable input for promoting security and resilience. The instrument also facilitated the identification of opportunities to promote organizational learning and the development of effective actions to strengthen intangible resources that influence resilient responses, thereby enabling a thorough exploration of knowledge resources in retrospective analyses or prospective sessions of accidents and severe operational safety events.

SAR ship localization method with denoising and feature refinement

Synthetic Aperture Radar (SAR) ship detection is greatly important to marine transportation monitoring and fishery resource management. To improve the detection accuracy of small ships, an SAR ship localization method with Denoising and Feature Refinement (DFR) is proposed in this paper. It consists of three parts. The first part is the denoising module, which uses non-local mean to suppress the speckle noise of the SAR image. The second part is Hierarchical Feature Fusion (HFF) module. It can integrate more low-level features by adding skip connections. This prevents the low-level spatial position information of the fused features from being diluted by high-level semantic information, therefore it is beneficial to the detection of small ships. The third part is a center-based ship predictor with Feature Refinement (FR). The FR module is proposed to refine the features and reduce the background interference, which is conducive to locate ships more accurately. Extensive experiments are conducted. The experimental results show that after adding the denoising and FR modules, the value of AP0.5 is increased by 1.7% and 2.3%, respectively, which proves the effectiveness of these two modules. In inshore and offshore scenarios, the AP0.5 values of DFR are 0.884 and 0.966, respectively, achieving the best results. The proposed method can also be generalized to mark lesion locations in medical images and detect offshore oil production platforms.

Analysis of Flow-induced Vibration Based on Discharge Pipeline on Offshore Platform

Objective: Because of the widespread use of offshore oil production platforms, there is a large amount of pipeline equipment on them. The excitation generated by fluid flow in the pipeline will cause flow-induced vibration of the pipeline and damage the pipeline structure. As a result, researching the flow-induced vibration of the pipeline is critical. Methods: In this paper, the pipeline on an offshore oil production platform in the South China Sea is taken as the research object, and the calculation and analysis of the pipeline section on the platform are focused on. The fluid-structure coupling method is used to calculate and analyze the pipeline section, and the flow-induced vibration of the pipeline is simulated. Results: Through calculation and analysis, the results show that the vibration speed of the pipeline in its original state exceeds the specified range. To reduce the degree of vibration, the pipeline constraint is redesigned and flow-induced vibration analysis is conducted. The results show that the vibration level meets the requirements. Conclusion: The flow-induced vibration of offshore pipelines is mainly caused by the uneven distribution of pressure in the pipelines caused by gas-liquid two-phase flow in the pipelines, and the reasonable setting of pipeline constraints can effectively reduce the degree of pipeline vibration.

Separation performance of hydrocyclone oil removal device influenced by oil droplet trajectory and oil drop characteristics.

Cyclone separation is an effective method for the treatment of oily wastewater from offshore oil production platforms. There is a lack of research on the impact of dispersion on the separation efficiency of current liquid-liquid separation hydrocyclones. A numerical simulation method was used to study the effect of the oil droplet characteristic parameters on the separation efficiency of a hydrocyclone oil removal device. An analysis of the trajectory of oil droplets revealed the oil removal mechanism of the hydrocyclone oil removal device: under the guidance of tangential velocity, the oil-water mixed fluid in the equipment generates different centrifugal forces due to the density difference, so oil and water adopt different flow paths to flow out. The effects of the particle diameter, velocity, and concentration of the inlet oil droplet on the separation efficiency were investigated. The droplet size had a positive effect on the separation efficiency, the oil concentration had a negative effect on the separation efficiency, and the speed of the oil drop was directly proportional to the separation efficiency within a certain range. These studies improved the basis for the efficient application of hydrocyclone oil removal devices.

Optimizing Operations Sequencing and Demulsifier Injection in Offshore Oil Production Platforms

Short-term production optimization of oil assets concerns routing decisions and equipment control settings that induce optimal steady-state operations. Typically, the decisions are made on the scale of hours to days with the aim of maximizing short-term economic and oil gains. Still an evolving field, this paper contributes by presenting a model and solution strategy for sequencing operations over time to drive the system towards an optimal state, while accounting for constraints that ensure smooth transitions until settling at the terminal steady-state. The constraints include the maximum number of wells that undergo a change in the control settings, maximum number and variation on the input signals for each well, and maximum number of changes in each time period, among others. Additionally, the proposed strategy can optimize the rate of injection of demulsifiers into wells considering the limits and impacts on fluid processing capacity. The paper reports simulated results for a real-world offshore production platform, demonstrating the effectiveness of the optimization strategy to cope with the failure and recovery of compression capacity, and manage the injection of demulsifiers.

Detection of damage in offshore jacket structure using artificial neural network

With industrial growth over the years, geologists have begun to search for offshore sources of oil and natural gas. Most offshore oil-production platforms are jacket type. Offshore jacket structures consist of welded steel space frame. Tubular pipes are opted as they reduce hydrodynamic loads making them highly durable structures. However due to natural phenomenon like cyclones, earthquakes, etc. these structures can get adversely damaged. Apart from that the structure also degrades due to corrosion and fatigue due to the severe conditions it is always exposed to. In many cases physical inspection of the structure for checking damages is not possible due to unfavourable onsite conditions or lack of trained professionals. Hence there is a need to develop alternatives solutions. In recent years much research has been done in the application of Artificial Neural Networks (ANN) in Civil Engineering. ANN are computation systems that are inspired by biological neural systems. This paper aims at creating an ANN to identify damage in an offshore jacket structure using the modal parameters. The training set for the ANN is obtained by using a finite element software. The ANN is then tested using a test set and then it will be used to predict the structural damage in an offshore jacket structure.

Assessment of Geo-Environmental Consequences of Oil and Gas Complex Enterprises’ Extraction Activities on the Shelf

One of the causes of rising seismic tension in a territory is the production activity of mining enterprises, including those in the oil and gas industry. The paper reports the results of modeling and analysis of the tensions of geological structures, which include the contact areas of the continental and oceanic crust, making a slow horizontal movement. The technogenic impact of the production process of an offshore oil and gas production platform and the pressure of the ocean water column are taken into consideration. The differential factorization method is used to investigate the posed boundary value problems. The study assesses the occurring contact stresses and draws conclusions about their dependence on the distance between the plates, the thickness of the water layer, and the frequency of the external load, modeling the intensity of the production process. The results obtained can be used by oil and gas companies to work out scenarios of the production process in a risk-free mode.

Reconciling Methane Emission Measurements for Offshore Oil and Gas Platforms with Detailed Emission Inventories: Accounting for Emission Intermittency.

Comparisons of observation-based emission estimates with emission inventories for oil and gas production operations have demonstrated that intermittency in emissions is an important factor to be accounted for in reconciling inventories with observations. Most emission inventories do not directly report data on durations of active emissions, and the variability in emissions over time must be inferred from other measurements or engineering calculations. This work examines a unique emission inventory, assembled for offshore oil and gas production platforms in federal waters of the Outer Continental Shelf (OCS) of the United States, which reports production-related sources on individual platforms, along with estimates of emission duration for individual sources. Platform specific emission rates, derived from the inventory, were compared to shipboard measurements made at 72 platforms. The reconciliation demonstrates that emission duration reporting, by source, can lead to predicted ranges in emissions that are much broader than those based on annual average emission rates. For platforms in federal waters, total emissions reported in the inventory for the matched platforms were within ∼10% of emissions estimated based on observations, depending on emission rates assumed for nondetects in the observational data set. The distributions of emissions were similar, with 75% of platform total emission rates falling between 0 and 49 kg/h for the observations and between 0.59 and 54 kg/h for the inventory.

Improving the quality of produced water discharged in open waters by incorporating a microbiological treatment on operating offshore platforms

Produced water is the water that comes along with oil during the reservoir extraction and is the main subproduct of the petroleum industry, accounting for 3 to 5 times the global production of oil. The produced water separated from the oil still contains some oily fractions in its composition, making it necessary for some treatment before its discard (most common practice adopted on offshore platforms) or reuse. The traditional method of treatment is based on the physical separation of oil and water, driven by their density difference. This type of treatment is unable to remove dissolved or small diameter particles dispersed, which turned out to be an issue in face of some new legislation worldwide that lowered the maximum amount of total oil and grease (TOG) the water can have for its discharge. Biological treatment is a widespread method for treating wastewater in several different industries due to its relative simplicity and low operational costs. Nevertheless, as it is a treatment that normally requires large-volume vessels, it is not used on offshore platforms due to a lack of space for such high dimension equipment. The objective of this research was to carry out a literature review using the article and patent search bases to find technical options that allow the use of biological treatment for water produced on offshore oil production platforms. Next, propose a model to incorporate biological treatment and estimate the performance of this produced water treatment model. An arrangement was proposed to convert a cargo tank of an operating offshore oil platform into a microbiological reactor. The conversion could be useful to treat the produced water that has a concentration of oil above the maximum limit allowed to discharge or to promote the additional extraction of a fraction of oil that could not be removed by the conventional treatment plants. The objective of this research was to perform a literature review to find technical options that could allow the use of biological treatment for the produced water in offshore oil-producing platforms, to propose a model to incorporate the biological treatment, and to estimate the performance of this model treating produced water. After researching articles and patents in the literature, it was seen that the Upflow Anaerobic Sludge Blanket (UASB) was the best type of reactor to be incorporated into an offshore platform. The reactor was chosen since it had good performance in treating produced water anaerobically and low sludge production. The UASB reactor most resembled the arrangement of a cargo tank, which was a paramount factor for the feasibility of the process's success. It is expected that the cargo tank converted to an UASB could remove at least an extra 30% of the total oil and grease (TOG) when compared to the traditional physical removal process existent for the produced water. However, it is still necessary to perform some laboratory tests to better predict the removal rate that would be observed in using this microbiological treatment with the high salinity-produced water from pre-salt Brazilian fields.

Satellites Detect a Methane Ultra-emission Event from an Offshore Platform in the Gulf of Mexico

Mitigation of methane emissions from fossil fuel extraction, processing, and transport is one of the most effective ways to slow global warming. Satellite-based methods are instrumental for the detection, characterization, and quantification of this type of emissions. However, despite the rapid development of satellite-based methane plume detection methods for terrestrial surfaces, there is still an important observational gap with respect to offshore oil and gas infrastructure, which accounts for roughly 30% of global production. In this work, we have used observations from the WorldView-3 and Landsat 8 satellite missions in a particular observation-illumination geometry to image offshore methane plumes from space. The study site is an offshore oil and gas production platform in the Gulf of Mexico, near the coast of Campeche, in one of Mexico’s major oil producing fields. Our data suggest that the platform vented high volumes of methane during a 17-day ultra-emission event, amounting to 0.04 ± 0.01 Tg of methane (equivalent to 3.36 million tons of carbon dioxide) released to the atmosphere if integrated over time. Our results illustrate how satellites can detect methane plumes from offshore infrastructure, which represents a significant breakthrough in the monitoring of industrial methane emissions from space.

Improving periodic maintenance performance: a grouping and heuristic approach

PurposeThis paper proposes a heuristic, data-driven approach to the rapid performance evaluation of periodic maintenance on complex production plants. Through grouping, maintenance interval (MI)-based evaluation and performance assessment, potential nonvalue-adding maintenance elements can be identified in the current maintenance structure. The framework reduces management complexity and supports the decision-making process for further maintenance improvement.Design/methodology/approachThe evaluation framework follows a prescriptive research approach. The framework is structured in three steps, which are further illustrated in the case study. The case study utilizes real-life data to verify the feasibility and effectiveness of the proposed framework.FindingsThrough a case study conducted on 9,538 pieces of equipment from eight offshore oil and gas production platforms, the results show considerable potential for maintenance performance improvement, including up to a 23% reduction in periodic maintenance hours.Research limitations/implicationsThe problem of performance evaluation under limited data availability has barely been addressed in the literature on the plant level. The proposed framework aims to provide a quantitative approach to reducing the structural complexity of the periodic maintenance evaluation process and can help maintenance professionals prioritize the focus on maintenance improvement among current strategies.Originality/valueThe proposed framework is especially suitable for initial performance assessment in systems with a complex structure, limited maintenance records and imperfect data, as it reduces management complexity and supports the decision-making process for further maintenance improvement. A similar application has not been identified in the literature.

Integration of deep learning and Bayesian networks for condition and operation risk monitoring of complex engineering systems

A challenging problem in risk and reliability analysis of Complex Engineering Systems (CES) is performing and updating risk and reliability assessments on the whole system with sufficiently high frequency. The challenge stems from both operational data complexity and systems’ complexity. The data complexity calls for novel and advanced data-driven methods, e.g., Deep Learning (DL). However, the systems’ complexity cannot be addressed only using black-box models; engineering knowledge and systems modeling methods must also be considered. In this paper, a novel mathematical architecture for operation condition and risk monitoring of CES is presented. In this architecture, a Bayesian Network (BN) is used to model the system, subsystems’ relations, scenarios leading to adverse events, and to fuse subsystem-level information. Further, Bayesian DL models are trained for subsystems’ diagnostics based on condition monitoring data, and their outputs are integrated into the root nodes of the designed BN. This integration enables addressing both the data and systems complexity in a single architecture that provides system-level insight. The proposed architecture also has the capacity to incorporate human inputs and qualitative information. We demonstrate the effectiveness of our proposed approach by performing a case study on a real-world Vapor Recovery Unit at an offshore oil production platform.

Cybersecurity of Offshore Oil and Gas Production Assets Under Trending Asset Digitalization Contexts: A Specific Review of Issues and Challenges in Safety Instrumented Systems

Due to the rapid digitalization of offshore oil fields and production platforms, diverse technological solutions, products, and application software have begun to appear both in upstream and midstream processes raising new organizational and operational challenges. The potential effects of these digital technologies driven developments have also been generating concerns, particularly in safety, security, and regulatory terms. Both hardware and software related changes and challenges in sensitive systems such as safety instrumented systems (SIS) can expose a production asset to new forms of risks. Hence, diverse aspects of cybersecurity have gained serious attention from authorities, operators, and service providers, particularly due to increasing general tendencies of major cyber-attacks on high-risk industrial assets, as well as their significant impact on safety, production, and asset economics terms. A SIS in an offshore oil and gas production asset has a critical role towards its safety integrity level (SIL). In general, a SIS consists of specific safety assurance instruments and pre-defined safety functions that are tightly coupled to detect, prevent, or mitigate hazardous situations ensuring process safety. Under the current industrial contexts of major changes within the offshore oil and gas production sector, partly due to unavoidable commercial changes and partly due to rapid technological developments, a better understanding of the cybersecurity exposure potentials of SIS is quite important to mitigate unwanted events and incidents. Under such circumstances, this paper explores critical issues and challenges related to cybersecurity of SIS as an extended step of a research study done in collaboration with industrial partners. It assesses the current actual status, requirements in governing standards and guidelines, and identifies some dangerous failure modes of SISs that need due security-oriented attention in a continuous asset digitalisation process. Towards the end, the paper defines and elaborates in-depth on specific issues and challenges relating to cybersecurity of SIS. Moreover, it identifies and reflects on generic initial steps that can be taken for assurance of cybersecurity of SIS within offshore oil and gas production assets to ensure necessary safety and security integrity levels under rapidly changing industrial contexts.

Field application of a modular multiple thermal fluid generator for heavy oil recovery

A modular multiple thermal fluid generator is introduced to enhance heavy oil production, which consists of water treatment system, fuel injection system, air compressor, central burning and heat exchanging system, and measuring and controlling system. All the components are mounted in three separated light shelters, which are easy to be lifted and installed, especially on the offshore production platform. It could be operated under 350 ℃ and 20 MPa, and the temperature and GWR (ratio of the volume of gas to the equivalent water volume of steam under standard conditions) could be adjusted by the water injection rate under the given heating capability of the central burning chamber. The temperature of the generated fluid is usually 200–300 ℃ with GWR of 200–300 m3/m3. Compared to conventional steam generator, such compact multiple thermal fluid generator is easy to be installed on the offshore oil production platform, and the generated multiple thermal fluid is potential to enhance heavy oil production in mechanisms of reducing heavy oil viscosity by both heating and injected gas, enlarging the heating reservoir chamber, and pressure by injected gas. In the past 10 years, the multiple thermal fluid generator has been applied to more than 40 wells in Bohai Offshore Oilfield and Xinjiang Oilfield in cyclic multiple thermal fluid stimulation (CMTFS in short) process. As a result, the multiple thermal fluid generators were operated soundly, and the heavy oil production of these wells was enhanced remarkably. (The oil production rate was 2–3 times more than cold production.)

Development of a method for maintaining the performance of drilling fluids during transportation by Platform Supply Vessel

The object of research is the process of transportation of drilling fluid used for lubrication and cooling of drilling equipment of offshore oil production platforms. The subject of the study is the stratification of the density of the drilling fluid along the height of the cargo tank in which it is transported. The technology of transportation of drilling fluid on the Platform Supply Vessel is considered. A problematic point in ensuring this process is that during the transportation of drilling fluids, due to the action of gravitational forces on organic and inorganic compounds in their volume, there is a latent change in their dispersion over the volume of the fluid. This leads to the stratification and stratification of the fluid density along the height, as well as to the formation of sediments at the bottom of the cargo tanks, in which the drilling fluid is transported. The study is aimed at developing a technology that maintains a constant value of the density of the drilling fluid along the depth of the tank in which it is transported. The studies were carried out in the vessel system for transporting drilling fluid of a specialized marine vessel of the Platform Supply Vessel type with a deadweight of 5850 tons. It is experimentally established that for a transportation time of 6–36 hours, the density stratification of the drilling fluid is 3.04–32.04 %. As a method that ensures the minimum stratification of the density of the drilling fluid during its transportation, it is proposed to use an additional X-shaped circulation of the drilling fluid in the volume of adjacent cargo tanks. Studies have confirmed that the density stratification over a time period of 6–36 hours decreases to a range of 2.30–9.01 %. The complex use of additional X-shaped circulation and simultaneous air supply to the bottom of the cargo tank provides a density stratification value of 0.73–2.93 %. The proposed technology was tested on a specialized seagoing vessel of the Platform Supply Vessel type with a deadweight of 5850 tons and can be used on offshore vessels that ensure the operation of offshore oil production platforms.

Optimal reliability-based design of complex structural systems

The reliability-based design of structures as a system remains an issue that has not been adequately addressed. Properly, this issue requires the assessment of the system reliability of a complete structure, considering the effects of both thealeatory and epistemic types of uncertainty. The recently developed probability densityevolutionmethod (PDEM) is effective for assessing the effects of the aleatory uncertainty, resulting in the PDF of the critical state of a system. The effects of the epistemic uncertainty maybe included in the system reliability as the potential error of the calculated mean critical stateof thesystem.The result of the PDEM, including the effect of the epistemic uncertainty, is the probability density function (PDF) of the system response. The application of the proposed method is illustrated with the optimal design of three major engineering systems; namely, an offshore oil production platform; a cable-stayed bridge; and a high-rise building under a strong motion earthquake.

Research on Structural Design and Selection of Minimal Jacket Platform

Minimal jacket platform refers to the offshore oil and gas production platform with simple structure, light weight and less topside facilities. In order to design and select platform structure better, a minimal jacket platform with a single-leg three-post structure type was designed in this paper. Option one uses the independent leg type, and option two uses the main column as the leg type. The structural design, comparison and selection research were carried out from three aspects: static force, fatigue and collapse analysis. The analysis results show that the mechanical performance of the jacket with independent leg type is better, which provides reference for the design of this kind of minimal platform in the future.

Treatment of real oilfield produced water by liquid-liquid extraction and efficient phase separation in a mixer-settler based on phase inversion

Produced water treatment has become a challenge for the oil industry to meet environmental legislation requirements, due to several dissolved organic compounds, which are barely removed under conventional treatments. In this work, oil and grease removal from real offshore produced water samples was evaluated by a novel liquid-liquid extraction process, followed by efficient phase separation in a mixer-settler based on phase inversion. In this novel approach, a condensate–average stream composition collected from offshore oil production platforms was used as an extraction solvent to remove mainly dissolved compounds. This strategy treatment, which is considered unprecedented in the industry, may allow oil producers to overcome many logistic challenges, also reducing inputs consumption and costs. The synthetic condensate potential was also compared to n-hexane and n-heptane in batch tests. According to the results, solvent concentration and pH exerted a significant influence on the extraction efficiency. Only at pH 4 and 1:10 solvent ratio, excellent removal efficiencies were obtained. Another significant result observed in the study was the mixer-settler performance, which allowed instantaneous phase separation with high extraction efficiency. At 10% (v/v) of condensate, the flow rate of 10 L/h and at pH 4, the applied process was able to reach the PW requirements for discharge according to the Brazilian National Environment Council guidelines in a single extraction step, resulting in a final outlet stream containing oil and grease under 29 mg/L, measured according Standard Method 5520 – B (Partition Gravimetric Method). This work offers an alternative to overcome the main produced water management challenges faced by the oil industry, using more efficient and compact equipment and reduced operating costs since the inputs are available on the offshore oil production platforms.

Treatment of produced water from polymer flooding in oil production by ceramic membranes

Polymeric additives are widely used in the oil and gas industry to increase the viscosity of the water injected into the reservoirs for enhancing oil recovery. This technique, also known as polymer flooding (PF), promotes the cogeneration of polymeric residues in the produced water stream. These residues cause an important efficiency reduction on the removal of oil and greases, by commonly used systems installed on offshore oil production platforms. Since ultrafiltration ceramic membranes have been considered as an improvement for designing more efficient treatment processes for new offshore installation units, the authors decided to conduct this work. The study aimed to assess the impact promoted by the presence of a polymer frequently used for PF on the performance of produced water treatment by an ultrafiltration ceramic membrane. For all the experimental conditions, it was observed that the selected membrane, with an average 0.1 μm pore size of, was able to generate a permeate stream with oil and greases concentration (CO) less than 5 mg/L. However, the polymer caused a significant impact on the membrane permeation flux, even when present in the saline samples at the concentration of 0.1 g/L. Under this condition, a reduction of 84% from the initial permeation flux (430 L/h.m2) was observed after 40 min of operation. Increasing the polymer concentration to 1.0 g/L resulted in an additional cutback of 9% from this value. When this sheared sample was prepared without salt, the permeation flux decrease was less intense, but still very significant. In this case, the final flux was 70 L/h.m2, representing a reduction of 83% from the initial value.