Reference Class Forecasting and Machine Learning for Improved Offshore Oil and Gas Megaproject Planning: Methods and Application

This article develops and describes rigorous oil and gas project forecasting methods. First, it builds a theoretical foundation by mapping megaproject performance literature to these projects. Second, it draws on heuristics and biases literature, using a questionnaire to demonstrate forecasting-related biases and principal-agent issues among industry project professionals. Third, it uses methodically collected project performance data to demonstrate that overrun distributions are non-normal and fat-tailed. Fourth, reference-class forecasting is demonstrated for cost and schedule uplifts. Finally, a predictive approach using machine learning (ML) considers project-specific factors to forecast the most likely cost and schedule overruns in a project.

Incorporating Sustainability and Maintenance for Performance Assessment of Offshore Oil and Gas Platforms: A Perspective

The existence of external two-fold pressure regarding competitiveness and sustainable development in a capital-intensive industry supports the need for sustainable performance. However, endeavors to create a sustainable framework to measure the performance of the oil and gas (O&G) industry are mostly devoted to the production and supply chain of petrochemical products and rarely focus on a maintenance perspective. Motivated by such scarcity, the goal of this research was to discuss and articulate the performance assessment framework by integrating concepts of maintenance and sustainability in the O&G industry. This study proposed the use of a range of performance measures for assessing sustainability on offshore production and drilling platforms. The conceptual framework consists of four aspects of sustainability categorized into technical, environmental, social, and economic dimensions. Each measure was assigned according to its relevance at the strategic, tactical, and functional levels of maintenance decision making. The conceptual framework resulted in hierarchical clusters of twelve strategic indicators. These indicators consist of conventional measures as well as new ones relating to the safety and reliability on offshore platforms. The potential contribution of the present study is found in its intention to empower a better understanding of sustainable maintenance and encourage those making decisions about practical implementation within the O&G industry. This paper culminates with directions for future studies.

BRAZILIAN OIL PIONEERS

In the Brazilian popular imagination, the discovery of oil was announced on August 9, 1938, by the Viscount of Corncob. The Donabentense Oil Company drilled Caraminguá’s first well, near the creek that passed through the Yellow Woodpecker Ranch (“Sítio do Picapau Amarelo,” in colloquial Portuguese). The latter was the name of a famous Brazilian children’s book. In fact, the first oil well flowed in Salvador, Bahia, on January 21, 1939, discovered by Manoel Ignácio Bastos (1891 - 1940), a Brazilian geographer engineer, whose business partner, Oscar Salvador Cordeiro (1890 - 1970), was the president of the Bahia Commodities Exchange. A brief analysis of documents, such as reports, Brazilian decrees and executive orders, as well as newspapers, detail the actions of these Brazilian oil pioneers. Statistical data analysis was also performed about onshore and offshore oil production between 1941 and 2019, as a part of Bastos and Cordeiros’ heritage.

Alignment Error Modelling, Analysis and Experiment of the Deep-Water Bolt Flange Automatic Connection Tool

A deep-water bolt flange automatic connection tool plays a very important role in the process of offshore oil exploitation and transportation. In the connection process, the alignment error of bolts and nuts is the key factor to ensure the connection process is successful. Using the kinematics modeling method, this paper created the alignment error model of the deep-water bolt flange automatic connection tool and analyzed the influence of manufacturing accuracy on the alignment error of bolts and nuts through computer simulation software. Based on the error matching design method, the manufacturing accuracy of parts were optimized with a part-size-based priority sequence to ensure the bolt–nut alignment error was within the allowable limits. The land tests, the pool tests and the sea test were carried out. The test results showed that the bolt and nut can be connected in the subsea environment reliably.

Relevance of Marketing Strategies for Gas Stations in China – An Analysis Using SPSS

This study aims to find out the relevance of marketing strategies for gas stations in China. According to IBISWorld, the companies holding the largest market shares in China’s gas station industry include China Petrochemical Corporation, China National Petroleum Corporation, Sinochem Corporation, China National Offshore Oil Corporation, and BP (China) Holdings Limited. Marketing has changed over the past several years. Similarly, gas station marketing is all about more customers, greater sales, and higher profits. Technology provides many different marketing tools to see more fresh faces at the door, increase repeat sales, and improve profits. Word-of-mouth advertising should be encouraged, especially when contests are being held. The prizes from these contests may include car essentials, free coffee, free car wash, or coupons to be used at convenience stores. Customers who have won these contests would surely go around advertising the particular gas station, ultimately bringing in more customers. Other than that, managers can boost the sales volume through radio promotions as well. This study also aims to give future businessmen and women some ideas on how to deal with different kinds of strategies when it comes to marketing, especially in China in hope to cater and prove to the people of China the possibility of promoting businesses, such as the oil industry.

The main directions of sustainable socio-economic development of the Caspian littoral areas of the Republic of Azerbaijan and the existing environmental problems

In Azerbaijan, since the earliest times, the Caspian Sea has contributed to the Received in revised form: 07.10.2021 settlement of population and structure of the economy. The favourable natural geographical conditions of the coasts, exploitation of offshore oil and gas fields and rich tourist-recreational potential favoured the economy of Azerbaijan significantly. However, sea-level fluctuations and environmental damage observed due to exploitation of natural resources served as curbing factor in the development. In modern times, planning of residential areas in the coastal areas, improvement of industrial, agricultural and tourism infrastructure, and successful management of the ecological situation are achievable through effective use of the natural resources and human potential of the Caspian Sea. The coastal region of the Caspian Sea, composed of three zones, is favourable for the development of Azerbaijan’s economy. Theattractiveness of coastal areas is related mainly to preferences of natural conditions and resources and the advantages of their transport- geographical location. As a result, the development level of the economy of the Pre-Caspian region is higher compared to other regions of the country. The region accounts for 88.7 % of the total industrial output in the country. The main part of it, i. e. 95.7 % is shared by the city of Baku. The cause of significant difference in development level between the regions and the capital Baku is associated with the use of oil and gas resources of the Caspian. Thus, offshore oil and gas reserves in the Caspian have played a notable role in the development of coastal areas, and of the country’s whole economy. This has led to inequality in terms of regional development. This factor prompted the need to study the role of the use of resources of the Caspian Sea in the sustainable development of Azerbaijan’s economy. In order to achieve the goal, a comparative analysis of the leading economic branches in the Pre-Caspian regions was carried out from a historical point of view. The obtained information was systematized, and the socio-economic aspects of sustainable development were identified based on statistical-mathematical materials. Aerospace data were used as well.

DSS-OSM: An Integrated Decision Support System for Offshore Oil Spill Management

The marine ecosystem, human health and social economy are always severely impacted once an offshore oil spill event has occurred. Thus, the management of oil spills is of importance but is difficult due to constraints from a number of dynamic and interactive processes under uncertain conditions. An integrated decision support system is significantly helpful for offshore oil spill management, but it is yet to be developed. Therefore, this study aims at developing an integrated decision support system for supporting offshore oil spill management (DSS-OSM). The DSS-OSM was developed with the integration of a Monte Carlo simulation, artificial neural network and simulation-optimization coupling approach to provide timely and effective decision support to offshore oil spill vulnerability analysis, response technology screening and response devices/equipment allocation. In addition, the uncertainties and their interactions were also analyzed throughout the modeling of the DSS-OSM. Finally, an offshore oil spill management case study was conducted on the south coast of Newfoundland, Canada, demonstrating the feasibility of the developed DSS-OSM.