Optimisation of Offshore Structures Decommissioning – Cost Considerations

2021 ◽  
Author(s):  
Emmanuel Eke ◽  
Ibiye Iyalla ◽  
Jesse Andrawus ◽  
Radhakrishna Prabhu
Keyword(s):  
Petroleum Industry ◽  
Model Performance ◽  
Offshore Structures ◽  
Training Dataset ◽  
Percentage Error ◽  
Offshore Platforms ◽  
Outer Continental Shelf ◽  
The Pacific ◽  
Reduced Gradient ◽  
The Cost

Abstract The petroleum industry is currently being faced with a growing number of ageing offshore platforms that are no longer in use and require to be decommissioned. Offshore decommissioning is a complex venture, and such projects are expected to cost the industry billions of dollars in the next two decades. Early knowledge of decommissioning cost is important to platform owners who bear the asset retirement obligation. However, obtaining the cost estimate for decommissioning an offshore platform is a challenging task that requires extensive structural and economic studies. This is further complicated by the existence of several decommissioning options such as complete and partial removal. In this paper, project costs for decommissioning 23 offshore platforms under three different scenarios are estimated using information from a publicly available source which only specified the costs of completely removing the platforms. A novel mathematical model for predicting the decommissioning cost for a platform based on its features is developed. The development included curve-fitting with the aid of generalised reduced gradient tool in Excel® Solver and a training dataset. The developed model predicted, with a very high degree of accuracy, platform decommissioning costs for four (4) different options under the Pacific Outer Continental Shelf conditions. Model performance was evaluated by calculating the Mean Absolute Percentage Error of predictions using a test dataset. This yielded a value of about 6%, implying a 94% chance of correctly predicting decommissioning cost.

Water Deluge System Design for Fire Fighting

2016 ◽  
Author(s):  
Jin Lee ◽  
Sang Hwan Kim ◽  
Jung Kwan Seo ◽  
Jeom Kee Paik
Keyword(s):  
Fluid Dynamic ◽  
Design Procedure ◽  
Offshore Structures ◽  
Offshore Platforms ◽  
Probabilistic Sampling ◽  
Spray System ◽  
Safety Design ◽  
Fire Scenarios ◽  
Fire And Explosion ◽  
The Cost

The ships and offshore structures are exposed to inherently the risk of fire and explosion. These fire and explosion, accident caused by grave consequences not only to the ships and offshore platforms on the sea but the environment all mankind. The aim of this paper is to focus on an optimization of water deluge and mist spray system locations subjected to jet on the ships and offshore platforms. A trustworthy set of fire scenarios is identified and classified using probabilistic sampling methods calling for Latin Hyper Sampling. These events of fire are numerically calculated for selected scenarios by the computational Fluid Dynamic (CFD) code using a KFX. The Water Deluge Location Index (WLI) is then calculated by using the frequency and consequence of fire scenarios. And then, WLI are utilized to prioritize the optimal locations of water deluge and mist spray systems. The recommended methodology believes that can increase to certainties in the design procedure of unreliability and can regard the cost-effectiveness of safety design.

scholarly journals Analysis of the Lebanese oil and gas exploration in the Mediterranean Sea: An overview and analysis of offshore platforms

2021 ◽  
Vol 2 (1) ◽  
pp. 25-29
Author(s):  
Mohamad khaled Abed El Rahim ◽  
Moath Al Husban
Keyword(s):  
Natural Gas ◽  
Oil And Gas ◽  
Optimal Solution ◽  
Offshore Structures ◽  
Sufficient Information ◽  
Offshore Platforms ◽  
Oil And Gas Exploration ◽  
Oil And Natural Gas ◽  
The Cost ◽  
Oil Gas

Offshore structures are used around the world for many functions, and these structures vary according to the depth of the water, the depth of water and environmental conditions are the main factors that determine the type of platform and method of drilling, appropriate planning, manufacturing, transportation, installation, and start-up. At the beginning of the twentieth century, oil and natural gas were discovered in the Middle East, specifically in the Lebanese basin. This discovery opened the door for Lebanon and entered the club of oil states. This paper is a study and analysis of blocks No. 4 and No. 9 that may contain the largest amount of oil and natural gas in addition to studying and analysing the types of marine installations (fixed and movable) and provide the best suggestions for the type suitable platform for the process of extracting oil and natural gas from the Sea of Lebanon according to the depth of water and factors Natural. The option of a drillship for drilling is the most appropriate option, given the lack of sufficient information about the nature of the soil in the Lebanese Sea. The drillship is considered an optimal solution given for ease of movement and in the absence of oil, the cost is much lower than the installation of fixed platforms. Semisubmersible rig for drilling and Tension Leg Platform or Semisubmersible Platform as well as Subsea System for oil/gas extraction are good alternatives to be employed in the Lebanese oil/gas fields.

A method of technical diagnostics for offshore structures

1994 ◽  
Vol 16 (2) ◽  
pp. 43-48
Author(s):  
Do Son
Keyword(s):  
Diagnostic Method ◽  
Joint Venture ◽  
Oil And Gas ◽  
Residual Life ◽  
Life Time ◽  
Offshore Structures ◽  
Technical Diagnostics ◽  
Offshore Platforms ◽  
South Vietnam ◽  
Local Destruction

This paper describes the results of measurements and analysis of the parameters, characterizing technical state of offshore platforms in Vietnam Sea. Based on decreasing in time material characteristics because of corrosion and local destruction assessment on residual life time of platforms is given and variants for its repair are recommended. The results allowed to confirm advantage of proposed technical diagnostic method in comparison with others and have been used for oil and gas platform of Joint Venture "Vietsovpetro" in South Vietnam.

scholarly journals Effectiveness of transfer learning for enhancing tumor classification with a convolutional neural network on frozen sections

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Young-Gon Kim ◽  
Sungchul Kim ◽  
Cristina Eunbee Cho ◽  
In Hye Song ◽  
Hee Jin Lee ◽  
...  
Keyword(s):  
Neural Network ◽  
Deep Learning ◽  
Convolutional Neural Network ◽  
Transfer Learning ◽  
Frozen Section ◽  
Medical Center ◽  
External Validation ◽  
Model Performance ◽  
Classification Model ◽  
Training Dataset

AbstractFast and accurate confirmation of metastasis on the frozen tissue section of intraoperative sentinel lymph node biopsy is an essential tool for critical surgical decisions. However, accurate diagnosis by pathologists is difficult within the time limitations. Training a robust and accurate deep learning model is also difficult owing to the limited number of frozen datasets with high quality labels. To overcome these issues, we validated the effectiveness of transfer learning from CAMELYON16 to improve performance of the convolutional neural network (CNN)-based classification model on our frozen dataset (N = 297) from Asan Medical Center (AMC). Among the 297 whole slide images (WSIs), 157 and 40 WSIs were used to train deep learning models with different dataset ratios at 2, 4, 8, 20, 40, and 100%. The remaining, i.e., 100 WSIs, were used to validate model performance in terms of patch- and slide-level classification. An additional 228 WSIs from Seoul National University Bundang Hospital (SNUBH) were used as an external validation. Three initial weights, i.e., scratch-based (random initialization), ImageNet-based, and CAMELYON16-based models were used to validate their effectiveness in external validation. In the patch-level classification results on the AMC dataset, CAMELYON16-based models trained with a small dataset (up to 40%, i.e., 62 WSIs) showed a significantly higher area under the curve (AUC) of 0.929 than those of the scratch- and ImageNet-based models at 0.897 and 0.919, respectively, while CAMELYON16-based and ImageNet-based models trained with 100% of the training dataset showed comparable AUCs at 0.944 and 0.943, respectively. For the external validation, CAMELYON16-based models showed higher AUCs than those of the scratch- and ImageNet-based models. Model performance for slide feasibility of the transfer learning to enhance model performance was validated in the case of frozen section datasets with limited numbers.

scholarly journals An Analysis and Comparison of Multi-Factor Asset Pricing Model Performance during Pandemic Situations in Developed and Emerging Markets

Mathematics ◽  
2022 ◽  
Vol 10 (1) ◽  
pp. 142
Author(s):  
Konstantin B. Kostin ◽  
Philippe Runge ◽  
Michel Charifzadeh
Keyword(s):  
Emerging Markets ◽  
Factor Model ◽  
Five Factor Model ◽  
Emerging Market ◽  
Model Performance ◽  
Research Area ◽  
Emerging Countries ◽  
Developed Markets ◽  
The Cost ◽  
Three Factor

This study empirically analyzes and compares return data from developed and emerging market data based on the Fama French five-factor model and compares it to previous results from the Fama French three-factor model by Kostin, Runge and Adams (2021). It researches whether the addition of the profitability and investment pattern factors show superior results in the assessment of emerging markets during the COVID-19 pandemic compared to developed markets. We use panel data covering eight indices of developed and emerging countries as well as a selection of eight companies from these markets, covering a period from 2000 to 2020. Our findings suggest that emerging markets do not generally outperform developed markets. The results underscore the need to reconsider the assumption that adding more factors to regression models automatically yields results that are more reliable. Our study contributes to the extant literature by broadening this research area. It is the first study to compare the performance of the Fama French three-factor model and the Fama French five-factor model in the cost of equity calculation for developed and emerging countries during the COVID-19 pandemic and other crisis events of the past two decades.

scholarly journals Datasets and Their Influence on the Development of Computer Assisted Synthesis Planning Tools in the Pharmaceutical Domain

2019 ◽  
Author(s):  
Amol Thakkar ◽  
Thierry Kogej ◽  
Jean-Louis Reymond ◽  
Ola Engkvist ◽  
Esben Jannik Bjerrum
Keyword(s):  
Model Performance ◽  
Computer Assisted ◽  
Patent Office ◽  
United States Patent ◽  
Planning Tool ◽  
Virtual Libraries ◽  
Synthesis Planning ◽  
Synthetic Routes ◽  
The Cost ◽  
States Patent

<p>Computer Assisted Synthesis Planning (CASP) has gained considerable interest as of late. Herein we investigate a template-based retrosynthetic planning tool, trained on a variety of datasets consisting of up to 17.5 million reactions. We demonstrate that models trained on datasets such as internal Electronic Laboratory Notebooks (ELN), and the publicly available United States Patent Office (USPTO) extracts, are sufficient for the prediction of full synthetic routes to compounds of interest in medicinal chemistry. As such we have assessed the models on 1,731 compounds from 41 virtual libraries for which experimental results were known. Furthermore, we show that accuracy is a misleading metric for assessment of the ‘filter network’, and propose that the number of successfully applied templates, in conjunction with the overall ability to generate full synthetic routes be examined instead. To this end we found that the specificity of the templates comes at the cost of generalizability, and overall model performance. This is supplemented by a comparison of the underlying datasets and their corresponding models.</p>

An Experimental Study of the Interaction Between Pipe Structure and Internal Flow

2009 ◽  
Author(s):  
Marcio Yamamoto ◽  
Motohiko Murai ◽  
Katsuya Maeda ◽  
Shotaro Uto
Keyword(s):  
Gas Flow ◽  
Petroleum Industry ◽  
Internal Flow ◽  
Scale Model ◽  
Offshore Platforms ◽  
Drilling Mud ◽  
Well Drilling ◽  
Hydrocarbon Production ◽  
Flow Effects ◽  
Reduced Scale

Nowadays pipes are widely deployed in the offshore environment especially in the petroleum industry where rigid and flexible pipes are used for well drilling and hydrocarbon production. Whereas during drilling, a mixture of drilling mud, rock cuttings and sometimes gas flows through the drilling riser, during production mono or multiphase (comprising oil, water and gas) flow takes place within the system. However up till now, most of the studies on offshore pipelines and risers have been focused on the pipe structure and its interaction with hydrodynamic forces and offshore platforms. In particular for numerical computation studies and reduced scale model experiments, the pipe is usually modeled as a tensioned beam and sometimes only the internal pressure is taken into account with other effects due to its internal flow being neglected. This paper deals with the interaction between the pipe structure and its internal flow. In order to verify the internal flow effects, an experimental analysis was carried out not using a reduced scale model. In particular, mono-phase fluid flows into the pipe and a parametric analysis using the flow rate was carried out. Discussion about the experimental results and numerical applications is also included.

Hydrate-Induced Vibration in an Offshore Pipeline

SPE Journal ◽  
2019 ◽  
Vol 25 (02) ◽  
pp. 732-743
Author(s):  
M. M. Jujuly ◽  
Mohammad Azizur Rahman ◽  
Aaron Maynard ◽  
Matthew Adey
Keyword(s):  
Gas Hydrate ◽  
Complex Geometry ◽  
Petroleum Industry ◽  
Offshore Structures ◽  
Flow Induced Vibration ◽  
Ansys Fluent ◽  
Safety Measures ◽  
Breakup Mechanism ◽  
Offshore Pipeline ◽  
Computational Fluid Dynamics Cfd

Summary Gas-hydrate plugging poses an operational challenge to offshore petroleum production and transportation. In this study, a computational-fluid-dynamics (CFD) model that uses ANSYS Fluent (ANSYS 2019) multiphase-flow-modeling techniques to simulate and analyze the effect of gas-hydrate flow in pipelines is proposed. For this purpose, the study attempted to integrate the ANSYS Fluent model with an existing commercial subsea-pipeline-visualization tool. To validate the simulation results, two case studies were conducted. The first study was about a pipeline whose dimensions are based on the specifications in existing literature (Balakin et al. 2010a). The second study was about a pipeline with more-complex geometry (M-shaped jumper with six elbows). The Eulerian/Eulerian method was used to model the multiphase hydrate flow. The population-balance method (PBM) was then used to model hydrate agglomeration and its breakup mechanism in the flow. A parametric study of the stresses in the pipelines resulting from flow-induced vibration (FIV) was conducted to identify the regions that underwent the maximum stresses and deformations under various flow conditions. The tool can be used in the petroleum industry to identify the operational hazards in offshore structures and to take necessary safety measures to avoid any potential catastrophic events.

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