Arrangement Method of Offshore Topside Based on an Expert System and Optimization Technique

2017 ◽  
Vol 139 (2) ◽  
Author(s):  
Sung-Kyoon Kim ◽  
Myung-Il Roh ◽  
Ki-Su Kim
Keyword(s):  
Expert System ◽  
Design Problem ◽  
Oil And Gas ◽  
Optimization Technique ◽  
Optimization Method ◽  
Gas Production ◽  
Offshore Platform ◽  
Optimal Arrangement ◽  
Oil And Gas Production ◽  
Two Stages

An offshore platform has several modules that contain much of the equipment needed for oil and gas production, and these are placed on the limited space of the topside. Furthermore, the equipment layout should leave sufficient space in between to ensure operability, maintainability, and safety. Thus, the design problem to arrange the topside of an offshore platform can be difficult to solve due to the number of modules and equipment placed on the topside. This study proposes a method to arrange the offshore topside based on an expert system and multistage optimization in order to obtain the optimal arrangement that addresses various considerations and satisfies the given requirements. The proposed method consists of four components. First, an expert system is proposed to systematically computerize experts' knowledge and experience and to evaluate the feasibility of alternatives for the arrangement of the offshore topside. Second, a multistage optimization method is proposed to yield a better arrangement design by formulating the arrangement design problem as an optimization problem with two stages. Third, an arrangement template model (ATM) was proposed to store the arrangement data of the offshore topside. Fourth, the user interface was developed to run the expert system and for optimization. A prototype program was then developed to solve an floating, production, storage, and offloading (FPSO) topside problem in order to evaluate the applicability of the proposed method. The results showed that the proposed method can be used to obtain the optimal arrangement of an offshore topside.

Structural Health Monitoring of An Offshore Platform Trend of Corrosion and Marine Growth With Predictive Maintenance

2020 ◽  
Author(s):  
K. S. Suharto
Keyword(s):  
Structural Health Monitoring ◽  
Data Processing ◽  
Production Process ◽  
Health Monitoring ◽  
Oil And Gas ◽  
Gas Production ◽  
Offshore Platform ◽  
Offshore Platforms ◽  
Oil And Gas Production ◽  
Potential Failure

Nowadays, there are a lot of oil and gas exploration activities all over the world, especially offshore. Oil and gas production itself has many supporting factors in the production process, of which one of them is the offshore platform. Over time, the offshore platform will experience a degradation in strength from the initial design, therefore offshore platforms need to carry out appropriate inspection, maintenance and repair (IMR) programs so that the offshore platform does not reach critical conditions and disrupt the oil and gas production process, resulting in significant losses and not achieving the planned production rates. The offshore platform design is a combination of steel structure and other materials, methods, and loads that are initially worked at the port, such as wave loads, currents, and several other parameters such as gravity, wind, and earthquake. Most of the offshore platforms that currently exist (worldwide) were made in the period of oil investment that developed between 1970 and 1980, thus, the platform's age has now reached 40 to 50 years (El-Reedy, 2012). This research data based on a platform in the Makassar strait between the islands of Kalimantan and Sulawesi. The method used in this research is the platform's design, data observation, data analysis, data processing, and statistical multilinear regression analysis. This research is investigating the degradation trend of the offshore platform and predicting the future of potential failure because of corrosion and marine growth. After the platform encounters degradation over several years, it will decrease the service life before the degradation starts to matter. The results show after data processing that, offshore platforms encounter degradation over several years, and it is presented by a graph containing the condition trend over a multi-year condition because of corrosion and marine growth, and its effect towards unity check (UC) that define structure health. Unity check value produced from allowable stress versus capacity. In this research, structural health monitoring is predicting the potential failure of the platform towards its UC effect of corrosion and marine growth, with a max of the UC value is 0.8 because its a critical value. The failure of the structure possibly would have an affect on the cost-effectiveness. Therefore it is necessary to predict when the structure will fail so that the costs used are effective. Unfortunately, there is no core data for the environmental changes every year at the platform, so the model's equation does not include environmental conditions.

scholarly journals Causes and Consequences of Fire Emergencies on Oil and Gas Platforms

2021 ◽  
Vol 11 (2) ◽  
pp. 1253-1258
Author(s):  
Elkhan Jafarov
Keyword(s):  
Risk Assessment ◽  
Fire Safety ◽  
Oil And Gas ◽  
Gas Production ◽  
Offshore Platform ◽  
Operating Conditions ◽  
Oil And Gas Production ◽  
Offshore Oil And Gas ◽  
Offshore Oil

This study presents an analysis of the causes and consequences of the largest offshore platform accidents associated with oil and gas production. The research on this problem allows improving the reliability of risk assessment associated with offshore oil and gas production, as well as developing methods for improving the fire safety of oil and gas platforms under various operating conditions.

scholarly journals Expert solution for effects of input parameters on multiphase flow correlations

2021 ◽  
Vol 9 (2) ◽  
Author(s):  
Mohamed A. Abd El-Moniem ◽  
◽  
Ahmed H. El-Banbi ◽  
Keyword(s):  
Expert System ◽  
Pressure Drop ◽  
Oil And Gas ◽  
Gas Production ◽  
Oil Wells ◽  
Gas Wells ◽  
Oil And Gas Production ◽  
Input Parameters ◽  
Bottomhole Pressure ◽  
Selection Of

Oil and gas production represents an essential source of energy. Optimization of oil and gas production systems requires accurate calculation of pressure drop in tubing and flowlines. Many empirical correlations and mechanistic models exist to calculate pressure drop in tubing and flowlines. Previous work has shown that some correlations provide more accurate results under certain flow conditions, PVT data, and well configurations than others. However, the effects of errors in input data on the selection of which correlations to use have not been investigated. This paper studies different multiphase flow correlations to determine the effects of their input parameters on (1) the accuracy of calculated pressure drop and (2) the selection of best correlation. A database consisting of 33 oil wells and 32 gas wells was selected, and a commercial software was used to build different well models. A total of 715 well models were constructed and used to investigate the effects of errors in correlations inputs on both the calculated bottomhole pressure and the selection of best correlation(s). The methodology was based on perturbing the values of the selected input parameters and calculating the new predicted bottomhole flowing pressure. Then, the effects of error in input parameters on how the calculated bottomhole pressure was different from observed data were quantified. The effect of this error in input parameters was also checked against the algorithm that selects the best correlation(s). It was found that errors in input GOR have the greatest effects for oil wells, while gas specific gravity and the tubing roughness are the most effective parameters for gas wells. The results were integrated into a rule-based expert system. A new set of data, consisting of 220 cases from 10 new oil wells and 10 new gas wells, was used to validate the expert system. The expert system was found to predict the best correlation(s) with a success rate of 80%, and it also identifies the input parameters whose error would affect the value of calculated bottomhole pressure significantly. Finally, the rules of the expert system were programmed into a VBA-Code to ease its use.

scholarly journals Investigating the Techno-economic Utility of Integrating an Optimized PV/diesel Hybrid System in an Entire Oil Field in the Western-dessert in Egypt

2021 ◽  
Vol 16 ◽  
pp. 104-120
Author(s):  
Mohammad M. El-Yamany ◽  
Sameh O. Abdullatif ◽  
Hani A. Ghali
Keyword(s):  
Oil And Gas ◽  
Water Cycle ◽  
Optimization Technique ◽  
Electrical Energy ◽  
Gas Production ◽  
Oil Field ◽  
Renewable Energy Resources ◽  
Diesel Generator ◽  
Oil And Gas Production ◽  
Cost Of Energy

Artificial lifting is considered as the most common technique in oil and gas production industry. However, from the electrical energy consumption prospective, artificial lifting is a heavy consumer. In the absence of a grid, oil and gas stack holders are forced to utilize diesel generator for energy production. Herein, an added cost of operation and maintenance is included in the oil production cost. The purpose of this work is to develop a systematic optimization methodology for utilizing renewable energy resources, specifically Photovoltaic (PV), in Oil & Gas Industry. The study has been applied on an entire oil field in the Egyptian western dessert. The load is operated with an integrated solar-assisted system and stand-alone diesel generator. The annual energy requirements using the Levelized cost of energy (LCOE) for ten sucker rod pumping units have been evaluated. A metaheuristic optimizer (Water Cycle Optimization Technique WCOT) has been utilized to optimize the PV contribution in the hybrid PV/diesel system proposed. Moreover, centralized, and distributed generation systems have been investigated technically and economically. The results have shown that the hybrid centralized system can provide up to 62% reduction in the LCOE with respect to the running diesel generator 24/7 system.

scholarly journals A Genetic Algorithm Integrated with Monte Carlo Simulation for the Field Layout Design Problem

2018 ◽  
Vol 73 ◽  
pp. 24 ◽  
Author(s):  
Leonardo de Pádua Agripa Sales ◽  
Anselmo Ramalho Pitombeira-Neto ◽  
Bruno de Athayde Prata
Keyword(s):  
Genetic Algorithm ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Design Problem ◽  
Oil And Gas ◽  
Probabilistic Approach ◽  
Layout Design ◽  
Gas Production ◽  
Oil And Gas Production ◽  
Field Development

Oil and gas production is moving deeper and further offshore as energy companies seek new sources, making the field layout design problem even more important. Although many optimization models are presented in the revised literature, they do not properly consider the uncertainties in well deliverability. This paper aims at presenting a Monte Carlo simulation integrated with a genetic algorithm that addresses this stochastic nature of the problem. Based on the results obtained, we conclude that the probabilistic approach brings new important perspectives to the field development engineering.

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