The intelligent monitoring and evaluation of the psychophysiological state of the workers employed on offshore oil and gas platforms

Oil and gas companies have an urgent need for technologies that provide complete and reliable information about the actual state of health and safety of personnel. To solve this problem, the article proposes a concept solution for the development of a system monitoring of the psychophysiological health of workers employed on offshore oil platforms. The concept is based on a person-centered approach and allows monitoring of health of employees simultaneously linking them to the context of the environment. The urgency of the problem is confirmed by statistical data, according to which workers in the oil and gas industry are 8 times more likely to get injured. The article analyzes the specific features of the professional activity of the workers employed on offshore oil platforms and shows that the deterioration of their health and psychological condition due to the long-term “sea environment” is unavoidable. It offers to develop an intelligent system for monitoring the psychophysiological condition of workers employed on offshore oil platforms and to assess its suitability for their position with the reference to the Cattell test and fuzzy patterns recognition. The development and systematic operation of such a system may timely detect undesirable consequences for the health status of workers employed on offshore oil platforms and prevent wrong decisions due to the “human factor”

Time–Frequency Extraction Model Based on Variational Mode Decomposition and Hilbert–Huang Transform for Offshore Oil Platforms Using MIMU Data

Time–frequency extraction is a key issue to understand structural symmetry of dynamic responses of offshore oil platforms for early warning during drilling operations. Current popular methods for signal characteristics extraction can only obtain the attributes with a single dimension or poor precision. To solve this, a combined Hilbert–Huang transform (HHT) and variational mode decomposition (VMD) method is proposed to extract multidimensional dynamic response characteristics of time, frequency, and energy of offshore oil platforms. Based on the extracted time–frequency–energy information, the frequency-domain integration approach (FDIA) can be applied to calculate the displacement using accelerometer in the micro inertial measurement unit (MIMU). A complementary filtering algorithm was designed to measure the torsion angle of platforms using six degrees of freedom data from the MIMU to obtain the torsion angle information. The performance of the proposed method was validated using a series of simulation shaking-table tests and a field test conducted on an offshore oil platform at Dongying City, Shandong Province, China. During the field test, seven out of eight collisions were detected in the frequency range 5 Hz to 12 Hz. The intensity of the fifth collision was the highest, and the maximum displacement obtained by the accelerometer was 6 mm. In addition, the results show a correlation between the axes of the accelerometer and gyroscope, and their combination can measure a torsion angle up to 1.1°.

Telemedicine applied to offshore medical emergencies: impacts on a Brazilian oil industry

Background The study aims to analyse the impact of the use of advanced telemedicine resources in the management of medical emergencies on offshore oil platforms of a major Brazilian operator during the period 2018–2019. Methods 38 maritime platforms were analysed, totalling a sample of 5992 workers. Exploratory data analysis, adherence test to normal distribution (Ryan-Joiner normality test) and linear correlation test (Spearman’s rho) were used to characterize the data. 5 groups were defined, 1 offshore platform with advanced telemedicine resources (reference group) and 4 platforms without this support. Each group had data on the monthly amount of disembarkation due to health reasons, in 2018 and 2019, through common flights (1087 and 1207) and aeromedical evacuations (68 and 126), respectively. Finally, hypothesis testing was carried out for two independent samples, to compare the average landings of the reference group with the other groups. Results The reference group presented average landings for common flights lower than those of the other groups in 2018. In 2019, presented average landings for common flights lower than those of three groups and statistically equal to that of a group. In 2018 and 2019, the reference group presented statistically equal averages (P-value > α = 0.05) of landings due to aeromedical evacuations. Conclusions Despite the possibility of other contributing factors, such as health management of each group and operation time of the platforms, this study allows us to conclude that, in 2018 and 2019, the group of maritime platforms with advanced telemedicine resources obtained, in general, lower average landings due to health reasons.

Modelling of methane emissions from offshore oil platforms in the Norwegian sea

<p>Methane is a major greenhouse gas that has increased since the pre-industrial era and reducing its emissions is potentially an effective way of mitigating the radiative forcing in the short term. The oil & gas industry has a positive contribution to the global atmospheric methane budget with fugitive emissions from infrastructure installations such as offshore oil platforms. As part of the United Nations Climate and Clean Air Coalition (UN CCAC) objective to quantify global CH4 emissions from oil and gas facilities, a series of aircraft campaigns have been carried out in the Norwegian sea among other areas. We report on the Lagrangian modelling activity of the emissions and transport sensitivities used to support the flux assessment. Source identification has been carried out based on backward modelling and has proved useful to interpret observations form the in situ airborne platforms. In addition, forward modelling of the emission plume in high resolution has been applied to constraining the plume height for mass balance methods assessment. Dependency of the resulting uncertainty of the flux estimates on various factors such as the choice of the meteorology and the of the Lagrangian model parameters is also discussed.</p>

Numerical Trials for the Soil-Spudcan Interface of Self-Elevating Units

This paper describes the development of a numerical model of a jack-up leg supported on the seabed and the study performed in order to analyze the interaction at the interface between the soil and its spudcan. Self-elevating units or jack-ups are widely used for offshore operations and the strength of their whole structure is to be ensured for the environmental conditions encountered during the operations. This is why the determination of the soil-spudcan interface is a major challenge since it depends on a wide range of factors, such as sea conditions, properties of the soil, geometry and material of the structure, etc. In light of the unpredictable and non-linear behavior of the marine environment and the soil, it is necessary to develop further studies on this subject to reduce uncertainties and to ensure the safety of offshore structures, as most of the failures in the offshore oil platforms are related to foundations. To do so, different approaches have been used: • Abaqus/ Standard and Abaqus/Explicit solvers; • Rigid bodies and deformable bodies afterwards; • Three kind of meshes: ○ Lagrangian mesh; ○ Arbitrary Lagrangian - Eulerian mesh; ○ Coupled Eulerian - Lagrangian mesh. To validate the model and the results obtained numerically in the end of the project, a comparison with an analytical calculation of the spudcan penetration has to be performed, based on the geometry of the structure and the properties of the soil.